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What is type 1 diabetes? A Mayo Clinic expert explains

Learn more about type 1 diabetes from endocrinologist Yogish Kudva, M.B.B.S.

I'm Dr. Yogish C. Kudva an endocrinologist at Mayo Clinic. In this video, we'll cover the basics of type 1 diabetes. What is it? Who gets it? The symptoms, diagnosis, and treatment. Whether you're looking for answers for yourself or someone you love. We are here to give you the best information available. Type 1 diabetes is a chronic condition that affects the insulin making cells of the pancreas. It's estimated that about 1.25 million Americans live with it. People with type 1 diabetes don't make enough insulin. An important hormone produced by the pancreas. Insulin allows your cells to store sugar or glucose and fat and produce energy. Unfortunately, there is no known cure. But treatment can prevent complications and also improve everyday life for patients with type 1 diabetes. Lots of people with type 1 diabetes live a full life. And the more we learn and develop treatment for the disorder, the better the outcome.

We don't know what exactly causes type 1 diabetes. We believe that it is an auto-immune disorder where the body mistakenly destroys insulin producing cells in the pancreas. Typically, the pancreas secretes insulin into the bloodstream. The insulin circulates, letting sugar enter your cells. This sugar or glucose, is the main source of energy for cells in the brain, muscle cells, and other tissues. However, once most insulin producing cells are destroyed, the pancreas can't produce enough insulin, meaning the glucose can't enter the cells, resulting in an excess of blood sugar floating in the bloodstream. This can cause life-threatening complications. And this condition is called diabetic ketoacidosis. Although we don't know what causes it, we do know certain factors can contribute to the onset of type 1 diabetes. Family history. Anyone with a parent or sibling with type 1 diabetes has a slightly increased risk of developing it. Genetics. The presence of certain genes can also indicate an increased risk. Geography. Type 1 diabetes becomes more common as you travel away from the equator. Age, although it can occur at any age there are two noticeable peaks. The first occurs in children between four and seven years of age and the second is between 10 and 14 years old.

Signs and symptoms of type 1 diabetes can appear rather suddenly, especially in children. They may include increased thirst, frequent urination, bed wetting in children who previously didn't wet the bed. Extreme hunger, unintended weight loss, fatigue and weakness, blurred vision, irritability, and other mood changes. If you or your child are experiencing any of these symptoms, you should talk to your doctor.

The best way to determine if you have type 1 diabetes is a blood test. There are different methods such as an A1C test, a random blood sugar test, or a fasting blood sugar test. They are all effective and your doctor can help determine what's appropriate for you. If you are diagnosed with diabetes, your doctor may order additional tests to check for antibodies that are common in type 1 diabetes in the test called C-peptide, which measures the amount of insulin produced when checked simultaneously with a fasting glucose. These tests can help distinguish between type 1 and type 2 diabetes when a diagnosis is uncertain.

If you have been diagnosed with type 1 diabetes, you may be wondering what treatment looks like. It could mean taking insulin, counting carbohydrates, fat protein, and monitoring your glucose frequently, eating healthy foods, and exercising regularly to maintain a healthy weight. Generally, those with type 1 diabetes will need lifelong insulin therapy. There are many different types of insulin and more are being developed that are more efficient. And what you may take may change. Again, your doctor will help you navigate what's right for you. A significant advance in treatment from the last several years has been the development and availability of continuous glucose monitoring and insulin pumps that automatically adjust insulin working with the continuous glucose monitor. This type of treatment is the best treatment at this time for type 1 diabetes. This is an exciting time for patients and for physicians that are keen to develop, prescribe such therapies. Surgery is another option. A successful pancreas transplant can erase the need for additional insulin. However, transplants aren't always available, not successful and the procedure can pose serious risks. Sometimes it may outweigh the dangers of diabetes itself. So transplants are often reserved for those with very difficult to manage conditions. A successful transplant can bring life transforming results. However, surgery is always a serious endeavor and requires ample research and concentration from you, your family, and your medical team.

The fact that we don't know what causes type 1 diabetes can be alarming. The fact that we don't have a cure for it even more so. But with the right doctor, medical team and treatment, type 1 diabetes can be managed. So those who live with it can get on living. If you would like to learn even more about type 1 diabetes, watch our other related videos or visit mayoclinic.org. We wish you well.

Type 1 diabetes, once known as juvenile diabetes or insulin-dependent diabetes, is a chronic condition. In this condition, the pancreas makes little or no insulin. Insulin is a hormone the body uses to allow sugar (glucose) to enter cells to produce energy.

Different factors, such as genetics and some viruses, may cause type 1 diabetes. Although type 1 diabetes usually appears during childhood or adolescence, it can develop in adults.

Even after a lot of research, type 1 diabetes has no cure. Treatment is directed toward managing the amount of sugar in the blood using insulin, diet and lifestyle to prevent complications.

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Type 1 diabetes symptoms can appear suddenly and may include:

• Feeling more thirsty than usual
• Urinating a lot
• Bed-wetting in children who have never wet the bed during the night
• Feeling very hungry
• Losing weight without trying
• Feeling irritable or having other mood changes
• Feeling tired and weak
• Having blurry vision

When to see a doctor

Talk to your health care provider if you notice any of the above symptoms in you or your child.

The exact cause of type 1 diabetes is unknown. Usually, the body's own immune system — which normally fights harmful bacteria and viruses — destroys the insulin-producing (islet) cells in the pancreas. Other possible causes include:

• Exposure to viruses and other environmental factors

The role of insulin

Once a large number of islet cells are destroyed, the body will produce little or no insulin. Insulin is a hormone that comes from a gland behind and below the stomach (pancreas).

• The pancreas puts insulin into the bloodstream.
• Insulin travels through the body, allowing sugar to enter the cells.
• Insulin lowers the amount of sugar in the bloodstream.
• As the blood sugar level drops, the pancreas puts less insulin into the bloodstream.

The role of glucose

Glucose — a sugar — is a main source of energy for the cells that make up muscles and other tissues.

• Glucose comes from two major sources: food and the liver.
• Sugar is absorbed into the bloodstream, where it enters cells with the help of insulin.
• The liver stores glucose in the form of glycogen.
• When glucose levels are low, such as when you haven't eaten in a while, the liver breaks down the stored glycogen into glucose. This keeps glucose levels within a typical range.

In type 1 diabetes, there's no insulin to let glucose into the cells. Because of this, sugar builds up in the bloodstream. This can cause life-threatening complications.

Risk factors

Some factors that can raise your risk for type 1 diabetes include:

• Family history. Anyone with a parent or sibling with type 1 diabetes has a slightly higher risk of developing the condition.
• Genetics. Having certain genes increases the risk of developing type 1 diabetes.
• Geography. The number of people who have type 1 diabetes tends to be higher as you travel away from the equator.
• Age. Type 1 diabetes can appear at any age, but it appears at two noticeable peaks. The first peak occurs in children between 4 and 7 years old. The second is in children between 10 and 14 years old.

Complications

Over time, type 1 diabetes complications can affect major organs in the body. These organs include the heart, blood vessels, nerves, eyes and kidneys. Having a normal blood sugar level can lower the risk of many complications.

Diabetes complications can lead to disabilities or even threaten your life.

• Heart and blood vessel disease. Diabetes increases the risk of some problems with the heart and blood vessels. These include coronary artery disease with chest pain (angina), heart attack, stroke, narrowing of the arteries (atherosclerosis) and high blood pressure.

Nerve damage (neuropathy). Too much sugar in the blood can injure the walls of the tiny blood vessels (capillaries) that feed the nerves. This is especially true in the legs. This can cause tingling, numbness, burning or pain. This usually begins at the tips of the toes or fingers and spreads upward. Poorly controlled blood sugar could cause you to lose all sense of feeling in the affected limbs over time.

Damage to the nerves that affect the digestive system can cause problems with nausea, vomiting, diarrhea or constipation. For men, erectile dysfunction may be an issue.

• Kidney damage (nephropathy). The kidneys have millions of tiny blood vessels that keep waste from entering the blood. Diabetes can damage this system. Severe damage can lead to kidney failure or end-stage kidney disease that can't be reversed. End-stage kidney disease needs to be treated with mechanical filtering of the kidneys (dialysis) or a kidney transplant.
• Eye damage. Diabetes can damage the blood vessels in the retina (part of the eye that senses light) (diabetic retinopathy). This could cause blindness. Diabetes also increases the risk of other serious vision conditions, such as cataracts and glaucoma.
• Foot damage. Nerve damage in the feet or poor blood flow to the feet increases the risk of some foot complications. Left untreated, cuts and blisters can become serious infections. These infections may need to be treated with toe, foot or leg removal (amputation).
• Skin and mouth conditions. Diabetes may leave you more prone to infections of the skin and mouth. These include bacterial and fungal infections. Gum disease and dry mouth also are more likely.
• Pregnancy complications. High blood sugar levels can be dangerous for both the parent and the baby. The risk of miscarriage, stillbirth and birth defects increases when diabetes isn't well-controlled. For the parent, diabetes increases the risk of diabetic ketoacidosis, diabetic eye problems (retinopathy), pregnancy-induced high blood pressure and preeclampsia.

There's no known way to prevent type 1 diabetes. But researchers are working on preventing the disease or further damage of the islet cells in people who are newly diagnosed.

Ask your provider if you might be eligible for one of these clinical trials. It is important to carefully weigh the risks and benefits of any treatment available in a trial.

• Summary of revisions: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-Srev.
• Papadakis MA, et al., eds. Diabetes mellitus. In: Current Medical Diagnosis & Treatment 2022. 61st ed. McGraw Hill; 2022. https://accessmedicine.mhmedical.com. Accessed May 4, 2022.
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• Diabetes mellitus (DM). Merck Manual Professional Version. https://www.merckmanuals.com/professional/endocrine-and-metabolic-disorders/diabetes-mellitus-and-disorders-of-carbohydrate-metabolism/diabetes-mellitus-dm. Accessed May 4, 2022.
• AskMayoExpert. Type 1 diabetes mellitus. Mayo Clinic; 2021.
• Robertson RP. Pancreas and islet transplantation in diabetes mellitus. https://www.uptodate.com/contents/search. Accessed May 4, 2022.
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• Hyperglycemia (high blood glucose). American Diabetes Association. https://www.diabetes.org/healthy-living/medication-treatments/blood-glucose-testing-and-control/hyperglycemia. Accessed May 4, 2022.
• Diabetes and DKA (ketoacidosis). American Diabetes Association. https://www.diabetes.org/diabetes/dka-ketoacidosis-ketones. Accessed May 4, 2022.
• Insulin resistance & prediabetes. National Institute of Diabetes and Digestive and Kidney Diseases. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/prediabetes-insulin-resistance. Accessed May 4, 2022.
• Blood sugar and insulin at work. American Diabetes Association. https://www.diabetes.org/tools-support/diabetes-prevention/high-blood-sugar. Accessed May 4, 2022.
• Inzucchi SE, et al. Glycemic control and vascular complications in type 1 diabetes. https://www.uptodate.com/contents/search. Accessed May 4, 2022.
• Diabetes and oral health. American Diabetes Association. https://www.diabetes.org/diabetes/keeping-your-mouth-healthy. Accessed May 4, 2022.
• Drug treatment of diabetes mellitus. Merck Manual Professional Version. https://www.merckmanuals.com/professional/endocrine-and-metabolic-disorders/diabetes-mellitus-and-disorders-of-carbohydrate-metabolism/drug-treatment-of-diabetes-mellitus. Accessed May 4, 2022.
• Weinstock DK, et al. Management of blood glucose in adults with type 1 diabetes mellitus. https://www.uptodate.com/contents/search. Accessed May 7, 2022.
• FDA proves first automated insulin delivery device for type 1 diabetes. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/fda-approves-first-automated-insulin-delivery-device-type-1-diabetes. Accessed May 4, 2022.
• Boughton CK, et al. Advances in artificial pancreas systems. Science Translational Medicine. 2019; doi:10.1126/scitranslmed.aaw4949.
• Hypoglycemia (low blood sugar). American Diabetes Association. https://www.diabetes.org/healthy-living/medication-treatments/blood-glucose-testing-and-control/hypoglycemia. Accessed May 4, 2022.
• Diabetes in the workplace and the ADA. U.S. Equal Opportunity Employment Commission. https://www.eeoc.gov/laws/guidance/diabetes-workplace-and-ada. Accessed May 4, 2022.
• Cardiovascular disease and risk management: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S010.
• Diabetes technology. Standards of Medical Care in Diabetes — 2022. 2022; doi:10.2337/dc22-S007.
• FDA authorizes a second artificial pancreas system. JDRF. https://www.jdrf.org/blog/2019/12/13/jdrf-reports-fda-authorizes-second-artificial-pancreas-system/. Accessed May 4, 2022.
• Classification and diagnosis of diabetes: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S002.
• Retinopathy, neuropathy, and foot care: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S012.
• Glycemic targets: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S012.
• Pharmacologic approaches to glycemic treatment: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S009.
• Facilitating behavior change and well-being to improve health outcomes: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S005.
• Centers for Disease Control and Prevention. Use of hepatitis B vaccination for adults with diabetes mellitus: Recommendations of the Advisory Committee on Immunization Practices (ACIP). Morbidity and Mortality Weekly Report. 2011;60:1709.
• Management of diabetes in pregnancy: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S015.
• Older adults: Standards of medical care in diabetes — 2022. Diabetes Care. 2022; doi:10.2337/dc22-S013.
• FDA approves first-of-its-kind automated insulin delivery and monitoring system for use in young pediatric patients. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/fda-approves-first-its-kind-automated-insulin-delivery-and-monitoring-system-use-young-pediatric#:~:text=Today, the U.S. Food and,by individuals aged 2 to. Accessed May 8, 2022.
• What you need to know: Getting a COVID-19 vaccine. American Diabetes Association. https://www.diabetes.org/coronavirus-covid-19/vaccination-guide. Accessed June 1, 2022.

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Pathophysiology and Clinical Presentation

Pathophysiology:

Type 1 Diabetes Mellitus is a syndrome characterized by hyperglycemia and insulin deficiency resulting from the loss of beta cells in pancreatic islets (Mapes & Faulds, 2014). Nonimmune (type 1B diabetes), occurs secondary to other diseases and is much less common than autoimmune (type 1A). The destruction of beta cells in Type 1A diabetes results from the interaction of both genetic and environmental factors. Although the genetic susceptibility is not well understood, type 1 diabetes is most strongly associated with major histocompatibility complex (MHC), specifically histocompatibility leukocyte antigen (HLA) class II alleles (HLA-DQ and HLA-DR) (McCance & Heuther, 2014). Type 1 diabetes is less hereditary than type 2 but 7-13% of patients also have a first degree relative with type 1 diabetes (Mapes & Faulds, 2014). Environmental factors include viral infections (especially enteroviruses), exposure to infectious microorganisms (such as  Helicobacter pylori ), exposure to cow’s milk proteins and a lack of vitamin D (McCance & Heuther, 2014).

The destruction of insulin-producing beta cells in the pancreas starts with the formation of autoantigens. These autoantigens are ingested by antigen-presenting cells which activate T helper 1 (Th1) and T helper 2 (Th2) lmphocytes. Activated Th1 lymphocytes secrete interluekin-2 (IL-2) and interferon. IL-2 activates autoantigen-specific T cytotoxic lymphocytes which destroy islet cells through the secretion of toxic perforins and granzymes. Interferon activates macrophages and stimulates the release of inflammatory cytokines (including IL-1 and tumor necrosis factor [TNF]) which further destroy beta cells (McCance & Heuther, 2014). Activated Th2 lymphocytes produce  IL-4 which stimulates B lymphocytes to proliferate and produce islet cell autoantibodies (ICAs) and  anti-glutamic acid decarboxylase (antiGAD65) antibodies. AntiGAD65 is an enzyme that helps control the release of insulin from beta cells and can be used to determine the cause of diabetes (McCance & Heuther, 2014). Insulin autoantibodies [IAAs]) and zinc transporter 8 (Znt8) protein are also associated with type 1 diabetes mellitus. Despite it’s complicated pathophysiology, it is important to understand the destruction of beta cells in type 1 diabetes because it leads to a lack of insulin and amylin. Without insulin or amylin the body cannot promote glucose disappearance or limit glucose appearance from the bloodstream, respectively, resulting in hyperglycemia (Mapes & Faulds, 2014).

Clinical Presentation:

Type 1 diabetes does not present clinically until 80-90% of the beta cells have been destroyed (McCance & Heuther, 2014). Because insulin stimulates glucose uptake into tissues, stores glycose as glycogen, inhibits glucagon secretion and inhibits glucose production from the liver, the destruction of insulin-producing beta cells causes hyperglycemia (Mapes & Faulds, 2014). Type 1 diabetics may present with abrupt onset of diabetic ketoacidosis, polyuria, polyphagia, polydipsia, or rapid weight loss with marked hyperglycemia (Mapes & Faulds, 2014).  To diagnose diabetes, patients must have an A1C level greater than 6.5% percent on two separate tests; the presence of ketones in the urine and/or autoantibodies in the blood can distinguish type 1 from type 2 diabetes (Mayo Clinic, 2014).

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• Type 1 Diabetes Mellitus
• Author: Romesh Khardori, MD, PhD, FACP; Chief Editor: George T Griffing, MD  more...
• Sections Type 1 Diabetes Mellitus
• Practice Essentials
• Pathophysiology
• Epidemiology
• Patient Education
• Physical Examination
• Complications
• Laboratory Studies
• Tests to Differentiate Type 1 from Type 2 Diabetes
• Approach Considerations
• Self-Monitoring of Glucose Levels
• Continuous Glucose Monitoring
• Insulin Therapy
• Management of Hypoglycemia
• Management of Hyperglycemia
• Management of Complications
• Glycemic Control During Serious Medical Illness and Surgery
• Glycemic Control During Pregnancy
• Consultations
• Medication Summary
• Antidiabetics, Insulins
• Antidiabetics, Amylinomimetics
• Hypoglycemia Antidotes
• Monoclonal Antibodies
• Allogeneic Islet Cells
• Questions & Answers

Type 1 diabetes is a chronic illness characterized by the body’s inability to produce insulin due to the autoimmune destruction of the beta cells in the pancreas. Although onset frequently occurs in childhood, the disease can also develop in adults. [ 1 ]

ICD-10 code

The International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) code for type 1 diabetes without complications is E10.9.

Signs and symptoms

The classic symptoms of type 1 diabetes are as follows:

Unexplained weight loss

Other symptoms may include fatigue, nausea, and blurred vision.

The onset of symptomatic disease may be sudden. It is not unusual for patients with type 1 diabetes to present with diabetic ketoacidosis (DKA).

See Clinical Presentation for more detail.

Diagnostic criteria by the American Diabetes Association (ADA) include the following [ 2 ] :

A fasting plasma glucose (FPG) level ≥126 mg/dL (7.0 mmol/L), or

A 2-hour plasma glucose level ≥200 mg/dL (11.1 mmol/L) during a 75-g oral glucose tolerance test (OGTT), or

A random plasma glucose ≥200 mg/dL (11.1 mmol/L) in a patient with classic symptoms of hyperglycemia or hyperglycemic crisis

Lab studies

A fingerstick glucose test is appropriate for virtually all patients with diabetes. All fingerstick capillary glucose levels must be confirmed in serum or plasma to make the diagnosis. All other laboratory studies should be selected or omitted on the basis of the individual clinical situation.

An international expert committee appointed by the ADA, the European Association for the Study of Diabetes (EASD), and the International Diabetes Association recommended the HbA 1c assay for diagnosing type 1 diabetes only when the condition is suspected but the classic symptoms are absent. [ 3 ]

Screening for type 1 diabetes in asymptomatic low-risk individuals is not recommended. [ 2 ] However, in patients at high risk (eg, those who have first-degree relatives with type 1 diabetes), it may be appropriate to perform annual screening for anti-islet antibodies before the age of 10 years, along with 1 additional screening during adolescence. [ 4 ]

See Workup for more detail.

Glycemic control

The ADA recommends using patient age as one consideration in the establishment of glycemic goals, with different targets for preprandial, bedtime/overnight, and hemoglobin A 1c (HbA 1c ) levels in patients aged 0-6, 6-12, and 13-19 years. [ 5 ] Benefits of tight glycemic control include not only continued reductions in the rates of microvascular complications but also significant differences in cardiovascular events and overall mortality.

Self-monitoring

Optimal diabetic control requires frequent self-monitoring of blood glucose levels, which allows rational adjustments in insulin doses. All patients with type 1 diabetes should learn how to self-monitor and record their blood glucose levels with home analyzers and adjust their insulin doses accordingly.

Real-time continuous monitoring of glucose—using continuous glucose monitors (CGMs)—can help patients improve glycemic control. [ 6 , 7 ] CGMs contain subcutaneous sensors that measure interstitial glucose levels every 1-5 minutes, providing alarms when glucose levels are too high or too low or are rapidly rising or falling.

Insulin therapy

Patients with type 1 diabetes require lifelong insulin therapy. Most require 2 or more injections of insulin daily, with doses adjusted on the basis of self-monitoring of blood glucose levels. Insulin replacement is accomplished by giving a basal insulin and a preprandial (premeal) insulin. The basal insulin is either long-acting (glargine or detemir) or intermediate-acting (NPH). The preprandial insulin is either rapid-acting (lispro, aspart, insulin inhaled, or glulisine) or short-acting (regular).

Common insulin regimens include the following:

Split or mixed: NPH with rapid-acting (eg, lispro, aspart, or glulisine) or regular insulin before breakfast and supper

Split or mixed variant: NPH with rapid-acting or regular insulin before breakfast, rapid-acting or regular insulin before supper, and NPH before bedtime (the idea is to reduce fasting hypoglycemia by giving the NPH later in the evening)

Multiple daily injections (MDI): A long-acting insulin (eg, glargine or detemir) once a day in the morning or evening (or twice a day in about 20% of patients) and a rapid-acting insulin before meals or snacks (with the dose adjusted according to the carbohydrate intake and the blood glucose level)

Continuous subcutaneous insulin infusion (CSII): Rapid-acting insulin infused continuously 24 hours a day through an insulin pump at 1 or more basal rates, with additional boluses given before each meal and correction doses administered if blood glucose levels exceed target levels

Diet and activity

All patients on insulin should have a comprehensive diet plan, created with the help of a professional dietitian, that includes the following:

A daily caloric intake prescription

Recommendations for amounts of dietary carbohydrate, fat, and protein

Instructions on how to divide calories between meals and snacks

Exercise is also an important aspect of diabetes management. Patients should be encouraged to exercise regularly.

See Treatment and Medication for more detail.

Type 1 diabetes mellitus (DM) is a multisystem disease with both biochemical and anatomic/structural consequences. It is a chronic disease of carbohydrate, fat, and protein metabolism caused by the lack of insulin, which results from the marked and progressive inability of the pancreas to secrete insulin because of autoimmune destruction of the beta cells. [ 1 ] (See Pathophysiology.) (See also Glucose Intolerance .)

Type 1 DM can occur at any age. Although it frequently arises in juveniles, it can also develop in adults. (See Epidemiology.)

Unlike people with type 2 DM , those with type 1 DM usually are not obese and usually present initially with diabetic ketoacidosis (DKA). The distinguishing characteristic of a patient with type 1 DM is that if his or her insulin is withdrawn, ketosis and eventually ketoacidosis develop. Therefore, these patients are dependent on exogenous insulin. (See Presentation.)

Treatment of type 1 DM requires lifelong insulin therapy. A multidisciplinary approach by the physician, nurse, and dietitian, with regular specialist consultation, is needed to control glycemia, as well as to limit the development of its devastating complications and manage such complications when they do occur. (See Treatmentand Medication.)

Despite the differences between type 1 and type 2 DM, the costs of the 2 conditions are often combined. In a study that focused on type 1 alone, Tao et al estimated that in the United States, type 1 DM is responsible for $14.4 billion in medical costs and lost income each year. [ 8 ]

Type 1 DM is the culmination of lymphocytic infiltration and destruction of insulin-secreting beta cells of the islets of Langerhans in the pancreas. As beta-cell mass declines, insulin secretion decreases until the available insulin no longer is adequate to maintain normal blood glucose levels. After 80-90% of the beta cells are destroyed, hyperglycemia develops and diabetes may be diagnosed. Patients need exogenous insulin to reverse this catabolic condition, prevent ketosis, decrease hyperglucagonemia, and normalize lipid and protein metabolism.

Currently, autoimmunity is considered the major factor in the pathophysiology of type 1 DM. In a genetically susceptible individual, viral infection may stimulate the production of antibodies against a viral protein that trigger an autoimmune response against antigenically similar beta cell molecules.

Approximately 85% of type 1 DM patients have circulating islet cell antibodies, and the majority also have detectable anti-insulin antibodies before receiving insulin therapy. The most commonly found islet cell antibodies are those directed against glutamic acid decarboxylase (GAD), an enzyme found within pancreatic beta cells.

The prevalence of type 1 DM is increased in patients with other autoimmune diseases, such as Graves disease, Hashimoto thyroiditis, and Addison disease. Pilia et al found a higher prevalence of islet cell antibodies (IA2) and anti-GAD antibodies in patients with autoimmune thyroiditis. [ 9 ]

A study by Philippe et al used computed tomography (CT) scans, glucagon stimulation test results, and fecal elastase-1 measurements to confirm reduced pancreatic volume in individuals with DM. [ 10 ] This finding, which was equally present in both type 1 and type 2 DM, may also explain the associated exocrine dysfunction that occurs in DM.

Polymorphisms of the class II human leukocyte antigen (HLA) genes that encode DR and DQ are the major genetic determinants of type 1 DM. Approximately 95% of patients with type 1 DM have either HLA-DR3 or HLA-DR4. Heterozygotes for those haplotypes are at significantly greater risk for DM than homozygotes. HLA-DQs are also considered specific markers of type 1 DM susceptibility. In contrast, some haplotypes (eg, HLA-DR2) confer strong protection against type 1 DM. [ 11 ]

Sensory and autonomic neuropathy

Sensory and autonomic neuropathy in people with diabetes are caused by axonal degeneration and segmental demyelination. Many factors are involved, including the accumulation of sorbitol in peripheral sensory nerves from sustained hyperglycemia. Motor neuropathy and cranial mononeuropathy result from vascular disease in blood vessels supplying nerves.

Using nailfold video capillaroscopy, Barchetta et al detected a high prevalence of capillary changes in patients with diabetes, particularly those with retinal damage. This reflects a generalized microvessel involvement in both type 1 and type 2 DM. [ 12 ]

Microvascular disease causes multiple pathologic complications in people with diabetes. Hyaline arteriosclerosis, a characteristic pattern of wall thickening of small arterioles and capillaries, is widespread and is responsible for ischemic changes in the kidney, retina, brain, and peripheral nerves.

Atherosclerosis of the main renal arteries and their intrarenal branches causes chronic nephron ischemia. It is a significant component of multiple renal lesions in diabetes.

Vitamin D deficiency is an important independent predictor of development of coronary artery calcification in individuals with type 1 DM. [ 13 ] Joergensen et al determined that vitamin D deficiency in type 1 diabetes may predict all causes of mortality but not development of microvascular complications. [ 14 ]

Nephropathy

In the kidneys, the characteristic wall thickening of small arterioles and capillaries leads to diabetic nephropathy, which is characterized by proteinuria, glomerular hyalinization (Kimmelstiel-Wilson), and chronic renal failure. Exacerbated expression of cytokines such as tumor growth factor beta 1 is part of the pathophysiology of glomerulosclerosis, which begins early in the course of diabetic nephropathy.

Genetic factors influence the development of diabetic nephropathy. Single-nucleotide polymorphisms affecting the factors involved in its pathogenesis appear to influence the risk for diabetic nephropathy in different people with type 1 DM. [ 15 ]

Double diabetes

In areas where rates of type 2 DM and obesity are high, individuals with type 1 DM may share genetic and environmental factors that lead to their exhibiting type 2 features such as reduced insulin sensitivity. This condition is termed double diabetes.

In a study that included 207 patients with type 1 DM, Epstein et al used the estimated glucose disposal rate (eGDR) to assess insulin resistance and found that mean eGDR was significantly lower (and, thus, insulin resistance was higher) in black patients (5.66 mg/kg/min) than in either Hispanic patients (6.70 mg/kg/min) or white patients (7.20 mg/kg/min). In addition, low eGDR was associated with an increased risk of vascular complications of diabetes (eg, cardiovascular disease, diabetic retinopathy, or severe chronic kidney disease). [ 16 , 17 ]

Type 1A DM results from autoimmune destruction of the beta cells of the pancreas and involves both genetic predisposition and an environmental component.

Genetic factors

Although the genetic aspect of type 1 DM is complex, with multiple genes involved, there is a high sibling relative risk. [ 18 ] Whereas dizygotic twins have a 5-6% concordance rate for type 1 DM, [ 19 ] monozygotic twins will share the diagnosis more than 50% of the time by the age of 40 years. [ 20 ]

For the child of a parent with type 1 DM, the risk varies according to whether the mother or the father has diabetes. Children whose mother has type 1 DM have a 2-3% risk of developing the disease, whereas those whose father has the disease have a 5-6% risk. When both parents are diabetic, the risk rises to almost 30%. In addition, the risk for children of parents with type 1 DM is slightly higher if onset of the disease occurred before age 11 years and slightly lower if the onset occurred after the parent’s 11th birthday.

The genetic contribution to type 1 DM is also reflected in the significant variance in the frequency of the disease among different ethnic populations. Type 1 DM is most prevalent in European populations, with people from northern Europe more often affected than those from Mediterranean regions. [ 21 ] The disease is least prevalent in East Asians. [ 22 ]

Genome-wide association studies have identified several loci that are associated with type 1 DM, but few causal relations have been established. The genomic region most strongly associated with other autoimmune diseases, the major histocompatibility complex (MHC), is the location of several susceptibility loci for type 1 DM—in particular, class II HLA DR and DQ haplotypes. [ 23 , 24 , 25 ]

A hierarchy of DR-DQ haplotypes associated with increased risk for type 1 DM has been established. The most susceptible haplotypes are as follows [ 26 ] :

DRB1*0301 - DQA1*0501 - DQB1*0201 (odds ratio [OR] 3.64)

DRB1*0405 - DQA1*0301 - DQB1*0302 (OR 11.37)

DRB1*0401 - DQA1*0301 - DQB*0302 (OR 8.39)

DRB1*0402 - DQA1*0301 - DQB1*0302 (OR 3.63)

DRB1*0404 - DQA1*0301 - DQB1*0302 (OR 1.59)

DRB1*0801 - DQB1*0401 - DQB1*0402 (OR 1.25)

Other haplotypes appear to offer protection against type 1 DM. These include the following [ 26 ] :

DRB1*1501 - DQA1*0102 - DQB1*0602 (OR 0.03)

DRB1*1401 - DQA1*0101 - DQB1*0503 (OR 0.02)

DRB1*0701 - DQA1*0201 - DQB1*0303 (OR 0.02)

From 90% to 95% of young children with type 1 DM carry HLA-DR3 DQB1*0201, HLA-DR4 DQB1*0302, or both. Carriage of both haplotypes (ie, DR3/4 heterozygotes) confers the highest susceptibility.

These high-risk haplotypes are found primarily in people of European descent; other ethnic groups are less well studied. In African Americans, the DRB1*07:01 - DQA1*03:01 -DQB1*02:01g haplotype is associated with increased risk (OR 3.96), whereas the DRB1*07:01-DQA1*02:01 - DQB1*02:01g haplotype appears to be protective (OR 0.34). [ 27 ]

The insulin gene ( INS ), which encodes for the pre-proinsulin peptide, is adjacent to a variable number of tandem repeats (VNTR) polymorphism at chromosome 11p15.5. [ 28 ] Different VNTR alleles may promote either resistance or susceptibility to type 1 DM through their effect on INS transcription in the thymus; for example, protective VNTRs are associated with higher INS expression, which may promote deletion of insulin-specific T cells. [ 29 ]

Other genes that have been reported to be involved in the mechanism of type 1 DM include CTLA4 (important in T-cell activation), PTPN22 (produces LYP, a negative regulator of T-cell kinase signaling), and IL2RA (encodes for CD25 which is involved with regulating T-cell function). UBASH3A (also known as STS2 ), may be involved in the increased risk not only of type 1 DM but also of other autoimmune disease and Down syndrome; it is located on locus chromosome 21q22.3. [ 30 ]

In addition, genome-wide association studies have implicated numerous other genes, including the following [ 31 ] :

Environmental factors

Extragenetic factors also may contribute. Potential triggers for immunologically mediated destruction of the beta cells include viruses (eg, enterovirus, [ 32 ] mumps, rubella, and coxsackievirus B4), toxic chemicals, exposure to cow’s milk in infancy, [ 33 ] and cytotoxins.

Combinations of factors may be involved. Lempainen et al found that signs of an enterovirus infection by 12 months of age were associated with the appearance of type 1 DM–related autoimmunity among children who were exposed to cow's milk before 3 months of age. These results suggest an interaction between the 2 factors and provide a possible explanation for the contradictory findings obtained in studies that examined these factors in isolation. [ 34 ]

One meta-analysis found a weak but significant linear increase in the risk of childhood type 1 DM with increasing maternal age. [ 35 ] However, little evidence supports any substantial increase in childhood type 1 DM risk after pregnancy complicated by preeclampsia. [ 36 ]

A study by Simpson et al found that neither vitamin D intake nor 25-hydroxyvitamin D levels throughout childhood were associated with islet autoimmunity or progression to type 1 DM. [ 37 ] This study was based in Denver, Colorado, and has been following children at increased risk of diabetes since 1993.

Early upper respiratory infection may also be a risk factor for type 1 diabetes. In an analysis of data on 148 children considered genetically at risk for diabetes, upper respiratory infections in the first year of life were associated with an increased risk for type 1 diabetes . [ 38 , 39 ] All children in the study who developed islet autoimmunity had at least 2 upper respiratory infections in the first year of life and at least 1 infection within 6 months before islet autoantibody seroconversion.

Children with respiratory infections in the first 6 months of life had the greatest increased hazard ratio (HR) for islet autoantibody seroconversion (HR = 2.27), and the risk was also increased in those with respiratory infections at ages 6 to almost 12 months (HR = 1.32). [ 38 , 39 ] The rate of islet autoantibody seroconversion was highest among children with more than 5 respiratory infections in the first year of year of life. Respiratory infections in the second year of life were not related to increased risk. [ 38 , 39 ]

Evidence exists that coronavirus disease 2019 (COVID-19) may actually lead to the development of type 1 and type 2 diabetes. One theory is that diabetes arises when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, binds “to angiotensin-converting enzyme 2 (ACE2) receptors in key metabolic organs and tissues, including pancreatic beta cells and kidneys.” The CoviDiab registry was established by an international group of diabetes researchers to gather data on COVID-19–related diabetes. [ 40 ]

A report by Xie and Al-Aly found that among study patients who had survived the first 30 days of COVID-19, the risk for diabetes at 1 year was increased by about 40%. More specifically, the hazard ratios (HRs) for diabetes at 1 year among patients who, during the acute infection, were not hospitalized, were hospitalized, or were admitted to intensive care were 1.25, 2.73, and 3.76, respectively. The investigators stated that diabetes "should be considered as a facet of the multifaceted long COVID syndrome." [ 41 , 42 ]

A study by Tang et al detected SARS-CoV-2 antigen in pancreatic beta cells, as taken from autopsy samples from individuals who had had COVID-19. The research indicated that insulin expression decreases in SARS-CoV-2–infected beta cells, with these cells possibly undergoing transdifferentiation. [ 43 ] A study by Wu et al also indicated that infected beta cells secrete less insulin, with the investigators finding evidence that SARS-CoV-2 can induce beta-cell apoptosis. [ 44 ]

A study from the US Centers for Disease Control and Prevention (CDC) indicates that SARS-CoV-2 infection increases the likelihood of diabetes developing in children under age 18 years, more than 30 days post infection. The investigators, using two US health claims databases, reported that pediatric patients with COVID-19 in the HealthVerity database were 31% percent more likely than other youth to receive a new diabetes diagnosis, while those in the IQVIA database were 166% more likely. The study could not specify the type or types of diabetes specifically related to COVID-19, with the report saying that the disease could be causing both type 1 and type 2 diabetes but through differing mechanisms. The researchers suggested, however, that COVID-19 may induce diabetes by directly attacking pancreatic cells that express ACE2 receptors, that it may give rise to diabetes “through stress hyperglycemia resulting from the cytokine storm and alterations in glucose metabolism caused by infection,” or that COVID-19 may cause diabetes via the conversion of prediabetes to diabetes. Whether the diabetes is transient or chronic was also unknown. [ 45 , 46 ]

A study by Kendall et al found that compared with pediatric subjects with a non–SARS-CoV-2 respiratory infection, the proportion of children who were diagnosed with new-onset type 1 DM within 6 months after a SARS-CoV-2 infection was 72% greater. According to the investigators, who looked at patients aged 18 years or younger, the rate of new-onset type 1 DM among the two groups was 0.025% and 0.043%, respectively, at 6 months. [ 47 ]

However, a study by Cromer et al looked at adult patients with newly diagnosed diabetes mellitus at the time of hospital admission for COVID-19, finding that a number of them subsequently regressed to a state of normoglycemia or prediabetes. The investigators reported that out of 64 survivors in the study with newly diagnosed diabetes (62 of whom had type 2 diabetes), 26 (40.6%) were known to undergo such regression (median 323-day follow-up). [ 48 ]

United States statistics

A 2011 report from the US Centers for Disease Control and Prevention (CDC) estimated that approximately 1 million Americans have type 1 DM. [ 49 ] The CDC estimated that each year from 2002 to 2005, type 1 DM was newly diagnosed in 15,600 young people. Among children younger than 10 years, the annual rate of new cases was 19.7 per 100,000 population; among those 10 years or older, the rate was 18.6 per 100,000 population. [ 49 ]

Type 1 DM is the most common metabolic disease of childhood. About 1 in every 400-600 children and adolescents has type 1 DM. In adults, type 1 DM constitutes approximately 5% of all diagnosed cases of diabetes. [ 49 ]

A study by Mayer-Davis et al indicated that between 2002 and 2012, the incidence of type 1 and type 2 DM saw a significant rise among youths in the United States. According to the report, after the figures were adjusted for age, sex, and race or ethnic group, the incidence of type 1 (in patients aged 0-19 years) and type 2 DM (in patients aged 10-19 years) during this period underwent a relative annual increase of 1.8% and 4.8%, respectively. The greatest increases occurred among minority youths. [ 50 ]

International statistics

Internationally, rates of type 1 DM are increasing. In Europe, the Middle East, and Australia, rates of type 1 DM are increasing by 2-5% per year. [ 51 ] The prevalence of type 1 DM is highest in Scandinavia (ie, approximately 20% of the total number of people with DM) and lowest in China and Japan (ie, fewer than 1% of all people with diabetes). Some of these differences may relate to definitional issues and the completeness of reporting.

The 10th edition of the International Diabetes Federation Diabetes Atlas, published in December 2021, reported that worldwide, 1 in 10 adults has diabetes. The data predicted that there would be a global increase in the number of adults with diabetes from 537 million in 2021 to 786 million by 2045, a 46% rise. Although increases are expected throughout the world, Africa, the Middle East, and Southeast Asia are predicted to have the greatest expansion. [ 52 ]

Age-related demographics

Previously referred to as juvenile-onset diabetes, type 1 DM is typically diagnosed in childhood, adolescence, or early adulthood. Although the onset of type 1 DM often occurs early in life, 50% of patients with new-onset type 1 DM are older than 20 years of age.

Type 1 DM usually starts in children aged 4 years or older, appearing fairly abruptly, with the peak incidence of onset at age 11-13 years (ie, in early adolescence and puberty). There is also a relatively high incidence in people in their late 30s and early 40s, in whom the disease tends to present less aggressively (ie, with early hyperglycemia without ketoacidosis and gradual onset of ketosis). This slower-onset adult form of type 1 DM is referred to as latent autoimmune diabetes of the adult (LADA). [ 49 ]

A study by Thomas et al, using data from the UK Biobank, determined that in 42% of type 1 DM cases reviewed, disease onset occurred in patients aged 31 to 60 years. The report also found that because type 2 DM is far more common than type 1 in individuals in the 31- to 60-year age group, with type 1 DM making up only 4% of all diabetes cases in this population, identification of type 1 DM is difficult in patients over age 30 years. The presence of type 1 DM was identified in the study using a genetic risk score that employed 29 common genetic variants. [ 53 , 54 ]

The risk of development of antibodies (anti-islet) in relatives of patients with type 1 DM decreases with increasing age. This finding supports annual screening for antibodies in relatives younger than 10 years and 1 additional screening during adolescence. [ 4 ]

Sex- and race-related demographics

Type 1 DM is more common in males than in females. In populations of European origin, the male-to-female ratio is greater than 1.5:1.

Type 1 DM is most common among non-Hispanic whites, followed by African Americans and Hispanic Americans. It is comparatively uncommon among Asians.

Type 1 DM is associated with a high morbidity and premature mortality. More than 60% of patients with type 1 DM do not develop serious complications over the long term, but many of the rest experience blindness, end-stage renal disease (ESRD), and, in some cases, early death. The risk of ESRD and proliferative retinopathy is twice as high in men as in women when the onset of diabetes occurred before age 15 years. [ 55 ]

Patients with type 1 DM who survive the period 10-20 years after disease onset without fulminant complications have a high probability of maintaining reasonably good health. Other factors affecting long-term outcomes are the patient’s education, awareness, motivation, and intelligence level. The 2012 American Diabetes Association (ADA) standard of care emphasizes the importance of long-term, coordinated care management for improved outcomes and suggests structural changes to existing systems of long-term care delivery. [ 5 ]

The morbidity and mortality associated with diabetes are related to the short- and long-term complications. Such complications include the following:

Hypoglycemia from management errors

Increased risk of infections

Microvascular complications (eg, retinopathy and nephropathy)

Neuropathic complications

Macrovascular disease

These complications result in increased risk for ischemic heart disease, cerebral vascular disease, peripheral vascular disease with gangrene of lower limbs, chronic renal disease, reduced visual acuity and blindness, and autonomic and peripheral neuropathy. Diabetes is the major cause of blindness in adults aged 20-74 years, as well as the leading cause of nontraumatic lower-extremity amputation and ESRD.

In both diabetic and non-diabetic patients, coronary vasodilator dysfunction is a strong independent predictor of cardiac mortality. In diabetic patients without coronary artery disease, those with impaired coronary flow reserve have event rates similar to those with prior coronary artery disease, while patients with preserved coronary flow reserve have event rates similar to non-diabetic patients. [ 56 ]

A study by Bode et al indicated that among patients with coronavirus disease 2019 (COVID-19), the US in-hospital death rate for individuals living with diabetes, patients with an HbA 1c of 6.5% or higher, and those with hyperglycemia throughout their stay is 29%, a figure over four times greater than that for patients without diabetes or hyperglycemia. Moreover, the in-hospital death rate for patients with no evidence of preadmission diabetes who develop hyperglycemia while admitted was found to be seven times higher (42%). [ 57 , 58 ]

A whole-population study from the United Kingdom (UK) reported that the risk of in-hospital death for patients with COVID-19 was 2.0 times greater for those with type 2 diabetes and 3.5 times higher for individuals with type 1 diabetes. However, patients under age 40 years with either type of diabetes were at extremely low risk for death. [ 59 , 60 ]

A French study, by Wargny et al, indicated that among patients with diabetes who are hospitalized with COVID-19, approximately 20% will die within 28 days. Individuals particularly at risk for mortality over this 4-week period include patients of advanced age, as well as those with a history of microvascular complications (especially those who have had kidney or eye damage), who have dyspnea on admission or inflammatory markers (increased white blood cell [WBC] count, raised C-reactive protein, elevated aspartate transaminase), or who have undergone routine insulin and statin treatment. It should be kept in mind, however, that the data was gathered between March 10 and April 10, 2020, with a statement from Diabetes UK explaining that in people with diabetes, COVID-19–associated mortality has decreased over time as treatment has improved. [ 61 , 62 ]

Another study, by Barrera et al, looking at 65 observational reports (15,794 participants), found that among COVID-19 patients with diabetes, the unadjusted relative risk for admission to an intensive care unit (ICU) was 1.96, and for mortality, 2.78. [ 63 , 64 ]

Another study from the United Kingdom found that risk factors for mortality in COVID-19 patients with type 1 or type 2 diabetes include male sex, older age, renal impairment, non-White ethnicity, socioeconomic deprivation, and previous stroke and heart failure. Moreover, patients with type 1 or type 2 diabetes had a significantly greater mortality risk with an HbA 1c level of 86 mmol/mol or above, compared with persons with an HbA 1c level of 48-53 mmol/mol. In addition, an HbA 1c of 59 mmol/mol or higher in patients with type 2 diabetes increased the risk as well. The study also found that in both types of diabetes, body mass index (BMI) had a U-shaped relationship with death, the mortality risk being increased in lower BMI and higher BMI but being reduced between these (25.0-29.9 kg/m 2 ). [ 65 , 60 ]

A literature review by Schlesinger et al strengthened the association between severe diabetes and COVID-19–related mortality, finding that among study patients with diabetes, the likelihood of death from COVID-19 was 75% greater in chronic insulin users. The study also indicated that the chance of death from COVID-19 is 50% less in individuals undergoing metformin therapy than in other patients with diabetes. The investigators suggested that the medications themselves did not impact survival but were indicators of the severity of diabetes in each group, with the prognosis being poorer among those with more severe diabetes. [ 66 , 67 ]

However, a Belgian study, by Vangoitsenhoven et al, indicated that in most people, the presence of type 1 diabetes mellitus is not associated with a greater risk of hospitalization for COVID-19. The investigators found that during the first 3 months of the pandemic in Belgium, the COVID-19 hospitalization rate was similar between individuals with type 1 diabetes and those without (0.21% vs 0.17%, respectively). Among the patients with type 1 diabetes, older persons had a greater tendency toward COVID-19–related hospitalization, although glucose control, comorbidity profile, and angiotensin-converting enzyme (ACE) inhibitor/angiotensin II receptor blocker (ARB) therapy did not significantly differ between the hospitalized and non-hospitalized groups. This and other research suggest that in persons with type 1 diabetes, an increased risk of death from COVID-19 is found primarily in particularly vulnerable individuals instead of in such patients overall. [ 68 , 69 ]

A retrospective, multicenter study by Carrasco-Sánchez et al indicated that among noncritical patients with COVID-19, the presence of hyperglycemia on hospital admission independently predicts progression to critical status, as well as death, whether or not the patient has diabetes. The in-hospital mortality rate in persons with a blood glucose level of higher than 180 mg/dL was 41.1%, compared with 15.7% for those with a level below 140 mg/dL. Moreover, the need for ventilation and intensive care unit admission were also greater in the presence of hyperglycemia. The report involved over 11,000 patients with confirmed COVID-19, only about 19% of whom had diabetes. [ 70 , 71 ]

In contrast to the above study, a report by Klonoff et al on over 1500 US patients with COVID-19 found no association between hyperglycemia on hospital admission and mortality, in non-ICU patients. However, the in-hospital mortality rate was significantly greater in such patients if they had a blood glucose level above 13.88 mmol/L on the second or third hospital day, compared with those with a level below 7.77 mmol/L. Findings for patients admitted directly to the ICU differed from these, with the investigators determining that mortality was associated with the presence of hyperglycemia on admission but was not significantly linked with a high glucose level on the second hospital day. [ 72 , 73 ]

Type 1 diabetic patients also have a high prevalence of small-fiber neuropathy. [ 74 , 75 ] In a prospective study of 27 patients who had type 1 diabetes with a mean disease duration of 40 years, almost 60% of the subjects showed signs or symptoms of neuropathy, including sensory neuropathy symptoms (9 patients), pain (3 patients), and carpal-tunnel symptoms (5 patients). [ 74 , 75 ] Of the 27 patients, 22 were diagnosed with small-fiber dysfunction by means of quantitative sensory testing.

Abnormal results on intraepidermal nerve-fiber density measurement (IENFD) were seen in 19 patients. [ 75 ] IENFD was negatively correlated with HbA 1c , but this relation was no longer significant after adjustment for age, body mass index, and height. N-ε-(carboxymethyl) lysine (CML), which is linked to painful diabetic neuropathy, remained independently associated with IENFD even after adjustment for these variables. Large-fiber neuropathy was also common, being found in 16 patients.

Although ESRD is one of the most severe complications of type 1 DM, its incidence is relatively low: 2.2% at 20 years after diagnosis and 7.8% at 30 years after diagnosis. [ 76 ] A greater risk is that mild diabetic nephropathy in type 1 diabetic persons appears to be associated with an increased likelihood of cardiovascular disease. [ 77 ] Moreover, the long-term risk of an impaired glomerular filtration rate (GFR) is lower in persons treated with intense insulin therapy early in the course of disease than in those given conventional therapy. [ 78 ]

Although mortality from early-onset type 1 DM (onset age, 0-14 y) has declined, the same may not be true for late-onset type 1 DM (onset age, 15-29 y). One study suggest that women tend to fare worse in both cohorts and that alcohol and drug use account for more than one third of deaths. [ 79 ]

Control of blood glucose, hemoglobin A 1c (HbA 1c ), lipids, blood pressure, and weight significantly affects prognosis. Excess weight gain with intensified diabetes treatment is associated with hypertension, insulin resistance, dyslipidemia and extensive atherosclerotic cardiovascular disease. [ 80 ]

Patients with diabetes face a lifelong challenge to achieve and maintain blood glucose levels as close to the normal range as possible. With appropriate glycemic control, the risk of both microvascular and neuropathic complications is decreased markedly. In addition, aggressive treatment of hypertension and hyperlipidemia decreases the risk of macrovascular complications.

A study by Zheng et al indicated that HbA 1c levels in persons with diabetes are longitudinally associated with long-term cognitive decline, as found using a mean 4.9 cognitive assessments of diabetes patients over a mean 8.1-year follow-up period. The investigators saw a significant link between each 1 mmol/mol rise in HbA 1c and an increased rate of decline in z scores for global cognition, memory, and executive function. Patients in the study had a mean age of 65.6 years. The report cited a need for research into whether optimal glucose control in people with diabetes can affect their cognitive decline rate. [ 81 , 82 ]

A study indicated that children with type 1 DM who have an HbA 1c level of 9% or above are at greater risk of mortality, intubation, and sepsis due to COVID-19 than are children without type 1 DM. However, the report also found evidence that such risk is not greater in children with an HbA 1c level at or below 7%. The investigators found the COVID-19 mortality rates in children without type 1 DM, those with type 1 DM, and those with type 1 DM with an HbA 1c of 7% or lower to be 0.047%, 0.328%, and 0%, respectively. [ 83 ]

The benefits of glycemic control and control of comorbidities in type 1 DM must be weighed against the risk of hypoglycemia and the short-term costs of providing high-quality preventive care. However, studies have shown cost savings due to a reduction in acute diabetes-related complications within 1-3 years of starting effective preventive care.

Education is a vital aspect of diabetes management. Patients with new-onset type 1 DM require extensive education if they are to manage their disease safely and effectively and to minimize long-term complications. Such education is best coordinated by the patient’s long-term care providers.

At every encounter, the clinician should educate the patient—and, in the case of children, the parents—about the disease process, management, goals, and long-term complications. In particular, clinicians should do the following:

Make patients aware of the signs and symptoms of hypoglycemia and knowledgeable about ways to manage it

Help patients understand and acknowledge the course of diabetes (eg, by teaching patients that they have a chronic condition that requires lifestyle modification and that they are likely to have chronic complications if they do not take control of their disease)

Reassure patients about the prognosis in properly managed type 1 DM

ADA guidelines urge that attention be paid to older adolescent patients who may be leaving their home and their current health care providers. At the transition between pediatric and adult health care, older teens can become detached from the health care system, putting their medical care and their glycemic control at risk. [ 5 ] The guidelines identify the National Diabetes Education Program (NDEP) as a source of materials that can help smooth the transition to adult health care.

Education about an appropriate treatment plan and encouragement to follow the plan are especially important in patients with diabetes. Physicians must ensure that the care for each patient with diabetes includes all necessary laboratory tests, examinations (eg, foot and neurologic examinations), and referrals to specialists (eg, an ophthalmologist or podiatrist).

A dietitian should provide specific diet control education to the patient and family. A nurse should educate the patient about self–insulin injection and performing fingerstick tests for blood glucose level monitoring.

For patient education information, see the Diabetes Center , as well as Diabetes .

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Contributor Information and Disclosures

Romesh Khardori, MD, PhD, FACP (Retired) Professor, Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, Eastern Virginia Medical School Romesh Khardori, MD, PhD, FACP is a member of the following medical societies: American Association of Clinical Endocrinology , American College of Physicians , American Diabetes Association , Endocrine Society Disclosure: Nothing to disclose.

George T Griffing, MD Professor Emeritus of Medicine, St Louis University School of Medicine George T Griffing, MD is a member of the following medical societies: American Association for Physician Leadership , American Association for the Advancement of Science , American College of Medical Practice Executives , American College of Physicians , American Diabetes Association , American Federation for Medical Research , American Heart Association , Central Society for Clinical and Translational Research , Endocrine Society , International Society for Clinical Densitometry , Southern Society for Clinical Investigation Disclosure: Nothing to disclose.

Howard A Bessen, MD Professor of Medicine, Department of Emergency Medicine, University of California, Los Angeles, David Geffen School of Medicine; Program Director, Harbor-UCLA Medical Center

Howard A Bessen, MD is a member of the following medical societies: American College of Emergency Physicians

Disclosure: Nothing to disclose.

Barry E Brenner, MD, PhD, FACEP Professor of Emergency Medicine, Professor of Internal Medicine, Program Director, Emergency Medicine, Case Medical Center, University Hospitals, Case Western Reserve University School of Medicine

Barry E Brenner, MD, PhD, FACEP is a member of the following medical societies: Alpha Omega Alpha , American Academy of Emergency Medicine , American College of Chest Physicians , American College of Emergency Physicians , American College of Physicians , American Heart Association , American Thoracic Society , Arkansas Medical Society , New York Academy of Medicine , New York Academy ofSciences ,and Society for Academic Emergency Medicine

Aneela Naureen Hussain, MD, FAAFM Assistant Professor, Department of Family Medicine, State University of New York Downstate Medical Center; Consulting Staff, Department of Family Medicine, University Hospital of Brooklyn

Aneela Naureen Hussain, MD, FAAFM is a member of the following medical societies: American Academy of Family Physicians , American Medical Association , American Medical Women's Association , Medical Society of the State of New York , and Society of Teachers of Family Medicine

Anne L Peters, MD, CDE Director of Clinical Diabetes Programs, Professor, Department of Medicine, University of Southern California, Keck School of Medicine, Los Angeles, California, Los Angeles County/University of Southern California Medical Center

Anne L Peters, MD, CDE is a member of the following medical societies: American College of Physicians and American Diabetes Association

Disclosure: Amylin Honoraria Speaking and teaching; AstraZeneca Consulting fee Consulting; Lilly Consulting fee Consulting; Takeda Consulting fee Consulting; Bristol Myers Squibb Honoraria Speaking and teaching; NovoNordisk Consulting fee Consulting; Medtronic Minimed Consulting fee Consulting; Dexcom Honoraria Speaking and teaching; Roche Honoraria Speaking and teaching

Don S Schalch, MD Professor Emeritus, Department of Internal Medicine, Division of Endocrinology, University of Wisconsin Hospitals and Clinics

Don S Schalch, MD is a member of the following medical societies: American Diabetes Association , American Federation for Medical Research , Central Society for Clinical Research , and Endocrine Society

Erik D Schraga, MD Staff Physician, Department of Emergency Medicine, Mills-Peninsula Emergency Medical Associates

Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference

Disclosure: Medscape Salary Employment

Miriam T Vincent, MD, PhD Professor and Chair, Department of Family Practice, State University of New York Downstate Medical Center

Miriam T Vincent, MD, PhD is a member of the following medical societies: Alpha Omega Alpha , American Academy of Family Physicians , American Association for the Advancement of Science , Medical Society of the State of New York , North American Primary Care Research Group , Sigma Xi , and Society of Teachers of Family Medicine

Disclosure: Joslin Diabetes Group, Harvard Honoraria Speaking and teaching

Scott R Votey, MD Director of Emergency Medicine Residency, Ronald Reagan UCLA Medical Center; Professor of Medicine/Emergency Medicine, University of California, Los Angeles, David Geffen School of Medicine

Scott R Votey, MD is a member of the following medical societies: Society for Academic Emergency Medicine

Frederick H Ziel, MD Associate Professor of Medicine, University of California, Los Angeles, David Geffen School of Medicine; Physician-In-Charge, Endocrinology/Diabetes Center, Director of Medical Education, Kaiser Permanente Woodland Hills; Chair of Endocrinology, Co-Chair of Diabetes Complete Care Program, Southern California Permanente Medical Group

Frederick H Ziel, MD is a member of the following medical societies: American Association of Clinical Endocrinologists , American College of Endocrinology , American College of Physicians , American College of Physicians-American Society of Internal Medicine , American Diabetes Association , American Federation for Medical Research , American Medical Association , American Society for Bone and Mineral Research , California Medical Association , Endocrine Society , andInternational Society for Clinical Densitometry

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Diagnostic tests for diabetes, type 1 diabetes, prediabetes and type 2 diabetes, cystic fibrosis–related diabetes, posttransplantation diabetes mellitus, monogenic diabetes syndromes, pancreatic diabetes or diabetes in the context of disease of the exocrine pancreas, gestational diabetes mellitus, 2. classification and diagnosis of diabetes: standards of medical care in diabetes—2021.

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American Diabetes Association; 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2021 . Diabetes Care 1 January 2021; 44 (Supplement_1): S15–S33. https://doi.org/10.2337/dc21-S002

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The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee ( https://doi.org/10.2337/dc21-SPPC ), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction ( https://doi.org/10.2337/dc21-SINT ). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC .

Diabetes can be classified into the following general categories:

Type 1 diabetes (due to autoimmune β-cell destruction, usually leading to absolute insulin deficiency, including latent autoimmune diabetes of adulthood)

Type 2 diabetes (due to a progressive loss of adequate β-cell insulin secretion frequently on the background of insulin resistance)

Specific types of diabetes due to other causes, e.g., monogenic diabetes syndromes (such as neonatal diabetes and maturity-onset diabetes of the young), diseases of the exocrine pancreas (such as cystic fibrosis and pancreatitis), and drug- or chemical-induced diabetes (such as with glucocorticoid use, in the treatment of HIV/AIDS, or after organ transplantation)

Gestational diabetes mellitus (diabetes diagnosed in the second or third trimester of pregnancy that was not clearly overt diabetes prior to gestation)

This section reviews most common forms of diabetes but is not comprehensive. For additional information, see the American Diabetes Association (ADA) position statement “Diagnosis and Classification of Diabetes Mellitus” ( 1 ).

Type 1 diabetes and type 2 diabetes are heterogeneous diseases in which clinical presentation and disease progression may vary considerably. Classification is important for determining therapy, but some individuals cannot be clearly classified as having type 1 or type 2 diabetes at the time of diagnosis. The traditional paradigms of type 2 diabetes occurring only in adults and type 1 diabetes only in children are no longer accurate, as both diseases occur in both age-groups. Children with type 1 diabetes typically present with the hallmark symptoms of polyuria/polydipsia, and approximately one-third present with diabetic ketoacidosis (DKA) ( 2 ). The onset of type 1 diabetes may be more variable in adults; they may not present with the classic symptoms seen in children and may experience temporary remission from the need for insulin ( 3 – 5 ). Occasionally, patients with type 2 diabetes may present with DKA ( 6 ), particularly ethnic and racial minorities ( 7 ). It is important for the provider to realize that classification of diabetes type is not always straightforward at presentation and that misdiagnosis is common (e.g., adults with type 1 diabetes misdiagnosed as having type 2 diabetes; individuals with maturity-onset diabetes of the young [MODY] misdiagnosed as having type 1 diabetes, etc.). Although difficulties in distinguishing diabetes type may occur in all age-groups at onset, the diagnosis becomes more obvious over time in people with β-cell deficiency.

In both type 1 and type 2 diabetes, various genetic and environmental factors can result in the progressive loss of β-cell mass and/or function that manifests clinically as hyperglycemia. Once hyperglycemia occurs, patients with all forms of diabetes are at risk for developing the same chronic complications, although rates of progression may differ. The identification of individualized therapies for diabetes in the future will require better characterization of the many paths to β-cell demise or dysfunction ( 8 ). Across the globe many groups are working on combining clinical, pathophysiological, and genetic characteristics to more precisely define the subsets of diabetes currently clustered into the type 1 diabetes versus type 2 diabetes nomenclature with the goal of optimizing treatment approaches. Many of these studies show great promise and may soon be incorporated into the diabetes classification system ( 9 ).

Characterization of the underlying pathophysiology is more precisely developed in type 1 diabetes than in type 2 diabetes. It is now clear from studies of first-degree relatives of patients with type 1 diabetes that the persistent presence of two or more islet autoantibodies is a near certain predictor of clinical hyperglycemia and diabetes. The rate of progression is dependent on the age at first detection of autoantibody, number of autoantibodies, autoantibody specificity, and autoantibody titer. Glucose and A1C levels rise well before the clinical onset of diabetes, making diagnosis feasible well before the onset of DKA. Three distinct stages of type 1 diabetes can be identified ( Table 2.1 ) and serve as a framework for future research and regulatory decision-making ( 8 , 10 ). There is debate as to whether slowly progressive autoimmune diabetes with an adult onset should be termed latent autoimmune diabetes in adults (LADA) or type 1 diabetes. The clinical priority is awareness that slow autoimmune β-cell destruction can occur in adults leading to a long duration of marginal insulin secretory capacity. For the purpose of this classification, all forms of diabetes mediated by autoimmune β-cell destruction are included under the rubric of type 1 diabetes. Use of the term LADA is common and acceptable in clinical practice and has the practical impact of heightening awareness of a population of adults likely to develop overt autoimmune β-cell destruction ( 11 ), thus accelerating insulin initiation prior to deterioration of glucose control or development of DKA ( 4 , 12 ).

Staging of type 1 diabetes ( 8 , 10 )

FPG, fasting plasma glucose; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; 2-h PG, 2-h plasma glucose.

The paths to β-cell demise and dysfunction are less well defined in type 2 diabetes, but deficient β-cell insulin secretion, frequently in the setting of insulin resistance, appears to be the common denominator. Type 2 diabetes is associated with insulin secretory defects related to inflammation and metabolic stress among other contributors, including genetic factors. Future classification schemes for diabetes will likely focus on the pathophysiology of the underlying β-cell dysfunction ( 8 , 9 , 13 – 15 ).

Diabetes may be diagnosed based on plasma glucose criteria, either the fasting plasma glucose (FPG) value or the 2-h plasma glucose (2-h PG) value during a 75-g oral glucose tolerance test (OGTT), or A1C criteria ( 16 ) ( Table 2.2 ).

Criteria for the diagnosis of diabetes

DCCT, Diabetes Control and Complications Trial; FPG, fasting plasma glucose; OGTT, oral glucose tolerance test; WHO, World Health Organization; 2-h PG, 2-h plasma glucose.

In the absence of unequivocal hyperglycemia, diagnosis requires two abnormal test results from the same sample or in two separate test samples.

Generally, FPG, 2-h PG during 75-g OGTT, and A1C are equally appropriate for diagnostic screening. It should be noted that the tests do not necessarily detect diabetes in the same individuals. The efficacy of interventions for primary prevention of type 2 diabetes ( 17 , 18 ) has mainly been demonstrated among individuals who have impaired glucose tolerance (IGT) with or without elevated fasting glucose, not for individuals with isolated impaired fasting glucose (IFG) or for those with prediabetes defined by A1C criteria.

The same tests may be used to screen for and diagnose diabetes and to detect individuals with prediabetes ( Table 2.2 and Table 2.5 ) ( 19 ). Diabetes may be identified anywhere along the spectrum of clinical scenarios—in seemingly low-risk individuals who happen to have glucose testing, in individuals tested based on diabetes risk assessment, and in symptomatic patients.

Fasting and 2-Hour Plasma Glucose

The FPG and 2-h PG may be used to diagnose diabetes ( Table 2.2 ). The concordance between the FPG and 2-h PG tests is imperfect, as is the concordance between A1C and either glucose-based test. Compared with FPG and A1C cut points, the 2-h PG value diagnoses more people with prediabetes and diabetes ( 20 ). In people in whom there is discordance between A1C values and glucose values, FPG and 2-h PG are more accurate ( 21 ).

Recommendations

2.1 To avoid misdiagnosis or missed diagnosis, the A1C test should be performed using a method that is certified by the NGSP and standardized to the Diabetes Control and Complications Trial (DCCT) assay. B

2.2 Marked discordance between measured A1C and plasma glucose levels should raise the possibility of A1C assay interference and consideration of using an assay without interference or plasma blood glucose criteria to diagnose diabetes. B

2.3 In conditions associated with an altered relationship between A1C and glycemia, such as hemoglobinopathies including sickle cell disease, pregnancy (second and third trimesters and the postpartum period), glucose-6-phosphate dehydrogenase deficiency, HIV, hemodialysis, recent blood loss or transfusion, or erythropoietin therapy, only plasma blood glucose criteria should be used to diagnose diabetes. (See other   conditions   altering   the   relationship   of   a1c   and   glycemia below for more information.) B

The A1C test should be performed using a method that is certified by the NGSP ( www.ngsp.org ) and standardized or traceable to the Diabetes Control and Complications Trial (DCCT) reference assay. Although point-of-care A1C assays may be NGSP certified and cleared by the U.S. Food and Drug Administration (FDA) for use in monitoring glycemic control in people with diabetes in both Clinical Laboratory Improvement Amendments (CLIA)-regulated and CLIA-waived settings, only those point-of-care A1C assays that are also cleared by the FDA for use in the diagnosis of diabetes should be used for this purpose, and only in the clinical settings for which they are cleared. As discussed in Section 6 “Glycemic Targets” ( https://doi.org/10.2337/dc21-S006 ), point-of-care A1C assays may be more generally applied for assessment of glycemic control in the clinic.

A1C has several advantages compared with FPG and OGTT, including greater convenience (fasting not required), greater preanalytical stability, and less day-to-day perturbations during stress, changes in diet, or illness. However, these advantages may be offset by the lower sensitivity of A1C at the designated cut point, greater cost, limited availability of A1C testing in certain regions of the developing world, and the imperfect correlation between A1C and average glucose in certain individuals. The A1C test, with a diagnostic threshold of ≥6.5% (48 mmol/mol), diagnoses only 30% of the diabetes cases identified collectively using A1C, FPG, or 2-h PG, according to National Health and Nutrition Examination Survey (NHANES) data ( 22 ).

When using A1C to diagnose diabetes, it is important to recognize that A1C is an indirect measure of average blood glucose levels and to take other factors into consideration that may impact hemoglobin glycation independently of glycemia, such as hemodialysis, pregnancy, HIV treatment ( 23 , 24 ), age, race/ethnicity, pregnancy status, genetic background, and anemia/hemoglobinopathies. (See other   conditions   altering   the   relationship   of   a1c   and   glycemia below for more information.)

The epidemiologic studies that formed the basis for recommending A1C to diagnose diabetes included only adult populations ( 22 ). However, recent ADA clinical guidance concluded that A1C, FPG, or 2-h PG can be used to test for prediabetes or type 2 diabetes in children and adolescents (see screening   and   testing   for   prediabetes   and   type   2 diabetes   in   children   and   adolescents below for additional information) ( 25 ).

Race/Ethnicity/Hemoglobinopathies

Hemoglobin variants can interfere with the measurement of A1C, although most assays in use in the U.S. are unaffected by the most common variants. Marked discrepancies between measured A1C and plasma glucose levels should prompt consideration that the A1C assay may not be reliable for that individual. For patients with a hemoglobin variant but normal red blood cell turnover, such as those with the sickle cell trait, an A1C assay without interference from hemoglobin variants should be used. An updated list of A1C assays with interferences is available at www.ngsp.org/interf.asp .

African Americans heterozygous for the common hemoglobin variant HbS may have, for any given level of mean glycemia, lower A1C by about 0.3% compared with those without the trait ( 26 ). Another genetic variant, X-linked glucose-6-phosphate dehydrogenase G202A, carried by 11% of African Americans, was associated with a decrease in A1C of about 0.8% in homozygous men and 0.7% in homozygous women compared with those without the variant ( 27 ).

Even in the absence of hemoglobin variants, A1C levels may vary with race/ethnicity independently of glycemia ( 28 – 30 ). For example, African Americans may have higher A1C levels than non-Hispanic Whites with similar fasting and postglucose load glucose levels ( 31 ). Though conflicting data exists, African Americans may also have higher levels of fructosamine and glycated albumin and lower levels of 1,5-anhydroglucitol, suggesting that their glycemic burden (particularly postprandially) may be higher ( 32 , 33 ). Similarly, A1C levels may be higher for a given mean glucose concentration when measured with continuous glucose monitoring ( 34 ). Despite these and other reported differences, the association of A1C with risk for complications appears to be similar in African Americans and non-Hispanic Whites ( 35 , 36 ).

Other Conditions Altering the Relationship of A1C and Glycemia

In conditions associated with increased red blood cell turnover, such as sickle cell disease, pregnancy (second and third trimesters), glucose-6-phosphate dehydrogenase deficiency ( 37 , 38 ), hemodialysis, recent blood loss or transfusion, or erythropoietin therapy, only plasma blood glucose criteria should be used to diagnose diabetes ( 39 ). A1C is less reliable than blood glucose measurement in other conditions such as the postpartum state ( 40 – 42 ), HIV treated with certain protease inhibitors (PIs) and nucleoside reverse transcriptase inhibitors (NRTIs) ( 23 ), and iron-deficient anemia ( 43 ).

Confirming the Diagnosis

Unless there is a clear clinical diagnosis (e.g., patient in a hyperglycemic crisis or with classic symptoms of hyperglycemia and a random plasma glucose ≥200 mg/dL [11.1 mmol/L]), diagnosis requires two abnormal test results, either from the same sample ( 44 ) or in two separate test samples. If using two separate test samples, it is recommended that the second test, which may either be a repeat of the initial test or a different test, be performed without delay. For example, if the A1C is 7.0% (53 mmol/mol) and a repeat result is 6.8% (51 mmol/mol), the diagnosis of diabetes is confirmed. If two different tests (such as A1C and FPG) are both above the diagnostic threshold when analyzed from the same sample or in two different test samples, this also confirms the diagnosis. On the other hand, if a patient has discordant results from two different tests, then the test result that is above the diagnostic cut point should be repeated, with careful consideration of the possibility of A1C assay interference. The diagnosis is made on the basis of the confirmed test. For example, if a patient meets the diabetes criterion of the A1C (two results ≥6.5% [48 mmol/mol]) but not FPG (<126 mg/dL [7.0 mmol/L]), that person should nevertheless be considered to have diabetes.

Each of the tests has preanalytic and analytic variability, so it is possible that a test yielding an abnormal result (i.e., above the diagnostic threshold), when repeated, will produce a value below the diagnostic cut point. This scenario is likely for FPG and 2-h PG if the glucose samples remain at room temperature and are not centrifuged promptly. Because of the potential for preanalytic variability, it is critical that samples for plasma glucose be spun and separated immediately after they are drawn. If patients have test results near the margins of the diagnostic threshold, the health care professional should discuss signs and symptoms with the patient and repeat the test in 3 – 6 months.

In a patient with classic symptoms, measurement of plasma glucose is sufficient to diagnose diabetes (symptoms of hyperglycemia or hyperglycemic crisis plus a random plasma glucose ≥200 mg/dL [11.1 mmol/L]). In these cases, knowing the plasma glucose level is critical because, in addition to confirming that symptoms are due to diabetes, it will inform management decisions. Some providers may also want to know the A1C to determine the chronicity of the hyperglycemia. The criteria to diagnose diabetes are listed in Table 2.2 .

2.4 Screening for type 1 diabetes risk with a panel of islet autoantibodies is currently recommended in the setting of a research trial or can be offered as an option for first-degree family members of a proband with type 1 diabetes. B

2.5 Persistence of autoantibodies is a risk factor for clinical diabetes and may serve as an indication for intervention in the setting of a clinical trial. B

Immune-Mediated Diabetes

This form, previously called “insulin-dependent diabetes” or “juvenile-onset diabetes,” accounts for 5 – 10% of diabetes and is due to cellular-mediated autoimmune destruction of the pancreatic β-cells. Autoimmune markers include islet cell autoantibodies and autoantibodies to GAD (GAD65), insulin, the tyrosine phosphatases IA-2 and IA-2β, and zinc transporter 8 (ZnT8). Numerous clinical studies are being conducted to test various methods of preventing type 1 diabetes in those with evidence of islet autoimmunity ( www.clinicaltrials.gov and www.trialnet.org/our-research/prevention-studies ) ( 12 , 45 – 49 ). Stage 1 of type 1 diabetes is defined by the presence of two or more of these autoimmune markers. The disease has strong HLA associations, with linkage to the DQA and DQB genes. These HLA-DR/DQ alleles can be either predisposing or protective ( Table 2.1 ). There are important genetic considerations, as most of the mutations that cause diabetes are dominantly inherited. The importance of genetic testing is in the genetic counseling that follows. Some mutations are associated with other conditions, which then may prompt additional screenings.

The rate of β-cell destruction is quite variable, being rapid in some individuals (mainly infants and children) and slow in others (mainly adults) ( 50 ). Children and adolescents may present with DKA as the first manifestation of the disease. Others have modest fasting hyperglycemia that can rapidly change to severe hyperglycemia and/or DKA with infection or other stress. Adults may retain sufficient β-cell function to prevent DKA for many years; such individuals may have remission or decreased insulin needs for months or years and eventually become dependent on insulin for survival and are at risk for DKA ( 3 – 5 , 51 , 52 ). At this latter stage of the disease, there is little or no insulin secretion, as manifested by low or undetectable levels of plasma C-peptide. Immune-mediated diabetes is the most common form of diabetes in childhood and adolescence, but it can occur at any age, even in the 8th and 9th decades of life.

Autoimmune destruction of β-cells has multiple genetic predispositions and is also related to environmental factors that are still poorly defined. Although patients are not typically obese when they present with type 1 diabetes, obesity is increasingly common in the general population, and there is evidence that it may also be a risk factor for type 1 diabetes. As such, obesity should not preclude the diagnosis. People with type 1 diabetes are also prone to other autoimmune disorders such as Hashimoto thyroiditis, Graves disease, celiac disease, Addison disease, vitiligo, autoimmune hepatitis, myasthenia gravis, and pernicious anemia (see Section 4 “Comprehensive Medical Evaluation and Assessment of Comorbidities,” https://doi.org/10.2337/dc21-S004 ).

Idiopathic Type 1 Diabetes

Some forms of type 1 diabetes have no known etiologies. These patients have permanent insulinopenia and are prone to DKA but have no evidence of β-cell autoimmunity. However, only a minority of patients with type 1 diabetes fall into this category. Individuals with autoantibody-negative type 1 diabetes of African or Asian ancestry may suffer from episodic DKA and exhibit varying degrees of insulin deficiency between episodes (possibly ketosis-prone diabetes). This form of diabetes is strongly inherited and is not HLA associated. An absolute requirement for insulin replacement therapy in affected patients may be intermittent. Future research is needed to determine the cause of β-cell destruction in this rare clinical scenario.

Screening for Type 1 Diabetes Risk

The incidence and prevalence of type 1 diabetes is increasing ( 53 ). Patients with type 1 diabetes often present with acute symptoms of diabetes and markedly elevated blood glucose levels, and approximately one-third are diagnosed with life-threatening DKA ( 2 ). Multiple studies indicate that measuring islet autoantibodies in individuals genetically at risk for type 1 diabetes (e.g., relatives of those with type 1 diabetes or individuals from the general population with type 1 diabetes–associated genetic factors) identifies individuals who may develop type 1 diabetes ( 10 ). Such testing, coupled with education about diabetes symptoms and close follow-up, may enable earlier identification of type 1 diabetes onset. A study reported the risk of progression to type 1 diabetes from the time of seroconversion to autoantibody positivity in three pediatric cohorts from Finland, Germany, and the U.S. Of the 585 children who developed more than two autoantibodies, nearly 70% developed type 1 diabetes within 10 years and 84% within 15 years ( 45 ). These findings are highly significant because while the German group was recruited from offspring of parents with type 1 diabetes, the Finnish and American groups were recruited from the general population. Remarkably, the findings in all three groups were the same, suggesting that the same sequence of events led to clinical disease in both “sporadic” and familial cases of type 1 diabetes. Indeed, the risk of type 1 diabetes increases as the number of relevant autoantibodies detected increases ( 48 , 54 , 55 ). In The Environmental Determinants of Diabetes in the Young (TEDDY) study, type 1 diabetes developed in 21% of 363 subjects with at least one autoantibody at 3 years of age ( 56 ).

There is currently a lack of accepted and clinically validated screening programs outside of the research setting; thus, widespread clinical testing of asymptomatic low-risk individuals is not currently recommended due to lack of approved therapeutic interventions. However, one should consider referring relatives of those with type 1 diabetes for islet autoantibody testing for risk assessment in the setting of a clinical research study (see www.trialnet.org ). Individuals who test positive should be counseled about the risk of developing diabetes, diabetes symptoms, and DKA prevention. Numerous clinical studies are being conducted to test various methods of preventing and treating stage 2 type 1 diabetes in those with evidence of autoimmunity with promising results (see www.clinicaltrials.gov and www.trialnet.org ).

2.6 Screening for prediabetes and type 2 diabetes with an informal assessment of risk factors or validated tools should be considered in asymptomatic adults. B

2.7 Testing for prediabetes and/or type 2 diabetes in asymptomatic people should be considered in adults of any age with overweight or obesity (BMI ≥25 kg/m 2 or ≥23 kg/m 2 in Asian Americans) and who have one or more additional risk factors for diabetes ( Table 2.3 ). B

2.8 Testing for prediabetes and/or type 2 diabetes should be considered in women with overweight or obesity planning pregnancy and/or who have one or more additional risk factor for diabetes ( Table 2.3 ). C

2.9 For all people, testing should begin at age 45 years. B

2.10 If tests are normal, repeat testing carried out at a minimum of 3-year intervals is reasonable, sooner with symptoms. C

2.11 To test for prediabetes and type 2 diabetes, fasting plasma glucose, 2-h plasma glucose during 75-g oral glucose tolerance test, and A1C are equally appropriate ( Table 2.2 and Table 2.5 ). B

2.12 In patients with prediabetes and type 2 diabetes, identify and treat other cardiovascular disease risk factors. A

2.13 Risk-based screening for prediabetes and/or type 2 diabetes should be considered after the onset of puberty or after 10 years of age, whichever occurs earlier, in children and adolescents with overweight (BMI ≥85th percentile) or obesity (BMI ≥95th percentile) and who have one or more risk factor for diabetes. (See Table 2.4 for evidence grading of risk factors.) B

2.14 Patients with HIV should be screened for diabetes and prediabetes with a fasting glucose test before starting antiretroviral therapy, at the time of switching antiretroviral therapy, and 3−6 months after starting or switching antiretroviral therapy. If initial screening results are normal, fasting glucose should be checked annually. E

Criteria for testing for diabetes or prediabetes in asymptomatic adults

CVD, cardiovascular disease; GDM, gestational diabetes mellitus; IFG, impaired fasting glucose; IGT, impaired glucose tolerance.

Risk-based screening for type 2 diabetes or prediabetes in asymptomatic children and adolescents in a clinical setting ( 202 )

GDM, gestational diabetes mellitus.

After the onset of puberty or after 10 years of age, whichever occurs earlier. If tests are normal, repeat testing at a minimum of 3-year intervals (or more frequently if BMI is increasing or risk factor profile deteriorating) is recommended. Reports of type 2 diabetes before age 10 years exist, and this can be considered with numerous risk factors.

Prediabetes

“Prediabetes” is the term used for individuals whose glucose levels do not meet the criteria for diabetes but are too high to be considered normal ( 35 , 36 ). Patients with prediabetes are defined by the presence of IFG and/or IGT and/or A1C 5.7 – 6.4% (39 – 47 mmol/mol) ( Table 2.5 ). Prediabetes should not be viewed as a clinical entity in its own right but rather as an increased risk for diabetes and cardiovascular disease (CVD). Criteria for testing for diabetes or prediabetes in asymptomatic adults is outlined in Table 2.3 . Prediabetes is associated with obesity (especially abdominal or visceral obesity), dyslipidemia with high triglycerides and/or low HDL cholesterol, and hypertension.

Criteria defining prediabetes *

FPG, fasting plasma glucose; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; OGTT, oral glucose tolerance test; 2-h PG, 2-h plasma glucose.

For all three tests, risk is continuous, extending below the lower limit of the range and becoming disproportionately greater at the higher end of the range.

IFG is defined as FPG levels from 100 to 125 mg/dL (from 5.6 to 6.9 mmol/L) ( 57 , 58 ) and IGT as 2-h PG during 75-g OGTT levels from 140 to 199 mg/dL (from 7.8 to 11.0 mmol/L) ( 59 ). It should be noted that the World Health Organization (WHO) and numerous other diabetes organizations define the IFG cutoff at 110 mg/dL (6.1 mmol/L).

As with the glucose measures, several prospective studies that used A1C to predict the progression to diabetes as defined by A1C criteria demonstrated a strong, continuous association between A1C and subsequent diabetes. In a systematic review of 44,203 individuals from 16 cohort studies with a follow-up interval averaging 5.6 years (range 2.8 – 12 years), those with A1C between 5.5% and 6.0% (between 37 and 42 mmol/mol) had a substantially increased risk of diabetes (5-year incidence from 9% to 25%). Those with an A1C range of 6.0–6.5% (42 – 48 mmol/mol) had a 5-year risk of developing diabetes between 25% and 50% and a relative risk 20 times higher compared with A1C of 5.0% (31 mmol/mol) ( 60 ). In a community-based study of African American and non-Hispanic White adults without diabetes, baseline A1C was a stronger predictor of subsequent diabetes and cardiovascular events than fasting glucose ( 61 ). Other analyses suggest that A1C of 5.7% (39 mmol/mol) or higher is associated with a diabetes risk similar to that of the high-risk participants in the Diabetes Prevention Program (DPP) ( 62 ), and A1C at baseline was a strong predictor of the development of glucose-defined diabetes during the DPP and its follow-up ( 63 ). Hence, it is reasonable to consider an A1C range of 5.7 – 6.4% (39 – 47 mmol/mol) as identifying individuals with prediabetes. Similar to those with IFG and/or IGT, individuals with A1C of 5.7 – 6.4% (39 – 47 mmol/mol) should be informed of their increased risk for diabetes and CVD and counseled about effective strategies to lower their risks (see Section 3 “Prevention or Delay of Type 2 Diabetes,” https://doi.org/10.2337/dc21-S003 ). Similar to glucose measurements, the continuum of risk is curvilinear, so as A1C rises, the diabetes risk rises disproportionately ( 60 ). Aggressive interventions and vigilant follow-up should be pursued for those considered at very high risk (e.g., those with A1C >6.0% [42 mmol/mol]).

Table 2.5 summarizes the categories of prediabetes and Table 2.3 the criteria for prediabetes testing. The ADA diabetes risk test is an additional option for assessment to determine the appropriateness of testing for diabetes or prediabetes in asymptomatic adults ( Fig. 2.1 ) ( diabetes.org/socrisktest ). For additional background regarding risk factors and screening for prediabetes, see screening   and   testing   for   prediabetes   and   type   2 diabetes   in   asymptomatic   adults and also screening   and   testing   for   prediabetes   and   type   2 diabetes   in   children   and   adolescents below.

ADA risk test ( diabetes.org/socrisktest ).

Type 2 Diabetes

Type 2 diabetes, previously referred to as “noninsulin-dependent diabetes” or “adult-onset diabetes,” accounts for 90 – 95% of all diabetes. This form encompasses individuals who have relative (rather than absolute) insulin deficiency and have peripheral insulin resistance. At least initially, and often throughout their lifetime, these individuals may not need insulin treatment to survive.

There are various causes of type 2 diabetes. Although the specific etiologies are not known, autoimmune destruction of β-cells does not occur, and patients do not have any of the other known causes of diabetes. Most, but not all, patients with type 2 diabetes have overweight or obesity. Excess weight itself causes some degree of insulin resistance. Patients who do not have obesity or overweight by traditional weight criteria may have an increased percentage of body fat distributed predominantly in the abdominal region.

DKA seldom occurs spontaneously in type 2 diabetes; when seen, it usually arises in association with the stress of another illness such as infection, myocardial infarction, or with the use of certain drugs (e.g., corticosteroids, atypical antipsychotics, and sodium–glucose cotransporter 2 inhibitors) ( 64 , 65 ). Type 2 diabetes frequently goes undiagnosed for many years because hyperglycemia develops gradually and, at earlier stages, is often not severe enough for the patient to notice the classic diabetes symptoms caused by hyperglycemia. Nevertheless, even undiagnosed patients are at increased risk of developing macrovascular and microvascular complications.

Patients with type 2 diabetes may have insulin levels that appear normal or elevated, yet the failure to normalize blood glucose reflects a relative defect in glucose-stimulated insulin secretion. Thus, insulin secretion is defective in these patients and insufficient to compensate for insulin resistance. Insulin resistance may improve with weight reduction, exercise, and/or pharmacologic treatment of hyperglycemia but is seldom restored to normal. Recent interventions with intensive diet and exercise or surgical weight loss have led to diabetes remission ( 66 – 72 ) (see Section 8 “Obesity Management for the Treatment of Type 2 Diabetes,” https://doi.org/10.2337/dc21-S008 ).

The risk of developing type 2 diabetes increases with age, obesity, and lack of physical activity. It occurs more frequently in women with prior gestational diabetes mellitus (GDM), with hypertension or dyslipidemia, with polycystic ovary syndrome, and in certain racial/ethnic subgroups (African American, American Indian, Hispanic/Latino, and Asian American). It is often associated with a strong genetic predisposition or family history in first-degree relatives (more so than type 1 diabetes). However, the genetics of type 2 diabetes is poorly understood and under intense investigation in this era of precision medicine ( 13 ). In adults without traditional risk factors for type 2 diabetes and/or younger age, consider islet autoantibody testing (e.g., GAD65 autoantibodies) to exclude the diagnosis of type 1 diabetes.

Screening and Testing for Prediabetes and Type 2 Diabetes in Asymptomatic Adults

Screening for prediabetes and type 2 diabetes risk through an informal assessment of risk factors ( Table 2.3 ) or with an assessment tool, such as the ADA risk test ( Fig. 2.1 ) (online at diabetes.org/socrisktest ), is recommended to guide providers on whether performing a diagnostic test ( Table 2.2 ) is appropriate. Prediabetes and type 2 diabetes meet criteria for conditions in which early detection via screening is appropriate. Both conditions are common and impose significant clinical and public health burdens. There is often a long presymptomatic phase before the diagnosis of type 2 diabetes. Simple tests to detect preclinical disease are readily available. The duration of glycemic burden is a strong predictor of adverse outcomes. There are effective interventions that prevent progression from prediabetes to diabetes (see Section 3 “Prevention or Delay of Type 2 Diabetes,” https://doi.org/10.2337/dc21-S003 ) and reduce the risk of diabetes complications ( 73 ) (see Section 10 “Cardiovascular Disease and Risk Management,” https://doi.org/10.2337/dc21-S010 , and Section 11 “Microvascular Complications and Foot Care,” https://doi.org/10.2337/dc21-S011 ). In the most recent National Institutes of Health (NIH) Diabetes Prevention Program Outcomes Study (DPPOS) report, prevention of progression from prediabetes to diabetes ( 74 ) resulted in lower rates of developing retinopathy and nephropathy ( 75 ). Similar impact on diabetes complications was reported with screening, diagnosis, and comprehensive risk factor management in the U.K. Clinical Practice Research Datalink database ( 73 ). In that report, progression from prediabetes to diabetes augmented risk of complications.

Approximately one-quarter of people with diabetes in the U.S. and nearly half of Asian and Hispanic Americans with diabetes are undiagnosed ( 57 , 58 ). Although screening of asymptomatic individuals to identify those with prediabetes or diabetes might seem reasonable, rigorous clinical trials to prove the effectiveness of such screening have not been conducted and are unlikely to occur. Based on a population estimate, diabetes in women of childbearing age is underdiagnosed ( 76 ). Employing a probabilistic model, Peterson et al. ( 77 ) demonstrated cost and health benefits of preconception screening.

A large European randomized controlled trial compared the impact of screening for diabetes and intensive multifactorial intervention with that of screening and routine care ( 78 ). General practice patients between the ages of 40 and 69 years were screened for diabetes and randomly assigned by practice to intensive treatment of multiple risk factors or routine diabetes care. After 5.3 years of follow-up, CVD risk factors were modestly but significantly improved with intensive treatment compared with routine care, but the incidence of first CVD events or mortality was not significantly different between the groups ( 59 ). The excellent care provided to patients in the routine care group and the lack of an unscreened control arm limited the authors' ability to determine whether screening and early treatment improved outcomes compared with no screening and later treatment after clinical diagnoses. Computer simulation modeling studies suggest that major benefits are likely to accrue from the early diagnosis and treatment of hyperglycemia and cardiovascular risk factors in type 2 diabetes ( 79 ); moreover, screening, beginning at age 30 or 45 years and independent of risk factors, may be cost-effective (<$11,000 per quality-adjusted life year gained—2010 modeling data) ( 80 ). Cost-effectiveness of screening has been reinforced in cohort studies ( 81 , 82 ).

Additional considerations regarding testing for type 2 diabetes and prediabetes in asymptomatic patients include the following.

Age is a major risk factor for diabetes. Testing should begin at no later than age 45 years for all patients. Screening should be considered in adults of any age with overweight or obesity and one or more risk factors for diabetes.

BMI and Ethnicity

In general, BMI ≥25 kg/m 2 is a risk factor for diabetes. However, data suggest that the BMI cut point should be lower for the Asian American population ( 83 , 84 ). The BMI cut points fall consistently between 23 and 24 kg/m 2 (sensitivity of 80%) for nearly all Asian American subgroups (with levels slightly lower for Japanese Americans). This makes a rounded cut point of 23 kg/m 2 practical. An argument can be made to push the BMI cut point to lower than 23 kg/m 2 in favor of increased sensitivity; however, this would lead to an unacceptably low specificity (13.1%). Data from WHO also suggests that a BMI of ≥23 kg/m 2 should be used to define increased risk in Asian Americans ( 85 ). The finding that one-third to one-half of diabetes in Asian Americans is undiagnosed suggests that testing is not occurring at lower BMI thresholds ( 86 , 87 ).

Evidence also suggests that other populations may benefit from lower BMI cut points. For example, in a large multiethnic cohort study, for an equivalent incidence rate of diabetes, a BMI of 30 kg/m 2 in non-Hispanic Whites was equivalent to a BMI of 26 kg/m 2 in African Americans ( 88 ).

Medications

Certain medications, such as glucocorticoids, thiazide diuretics, some HIV medications ( 23 ), and atypical antipsychotics ( 66 ), are known to increase the risk of diabetes and should be considered when deciding whether to screen.

Individuals with HIV are at higher risk for developing prediabetes and diabetes on antiretroviral (ARV) therapies, so a screening protocol is recommended ( 89 ). The A1C test may underestimate glycemia in people with HIV; it is not recommended for diagnosis and may present challenges for monitoring ( 24 ). In those with prediabetes, weight loss through healthy nutrition and physical activity may reduce the progression toward diabetes. Among patients with HIV and diabetes, preventive health care using an approach used in patients without HIV is critical to reduce the risks of microvascular and macrovascular complications. Diabetes risk is increased with certain PIs and NRTIs. New-onset diabetes is estimated to occur in more than 5% of patients infected with HIV on PIs, whereas more than 15% may have prediabetes ( 90 ). PIs are associated with insulin resistance and may also lead to apoptosis of pancreatic β-cells. NRTIs also affect fat distribution (both lipohypertrophy and lipoatrophy), which is associated with insulin resistance. For patients with HIV and ARV-associated hyperglycemia, it may be appropriate to consider discontinuing the problematic ARV agents if safe and effective alternatives are available ( 91 ). Before making ARV substitutions, carefully consider the possible effect on HIV virological control and the potential adverse effects of new ARV agents. In some cases, antihyperglycemic agents may still be necessary.

Testing Interval

The appropriate interval between screening tests is not known ( 92 ). The rationale for the 3-year interval is that with this interval, the number of false-positive tests that require confirmatory testing will be reduced and individuals with false-negative tests will be retested before substantial time elapses and complications develop ( 92 ). In especially high-risk individuals, particularly with weight gain, shorter intervals between screening may be useful.

Community Screening

Ideally, testing should be carried out within a health care setting because of the need for follow-up and treatment. Community screening outside a health care setting is generally not recommended because people with positive tests may not seek, or have access to, appropriate follow-up testing and care. However, in specific situations where an adequate referral system is established beforehand for positive tests, community screening may be considered. Community testing may also be poorly targeted; i.e., it may fail to reach the groups most at risk and inappropriately test those at very low risk or even those who have already been diagnosed ( 93 ).

Screening in Dental Practices

Because periodontal disease is associated with diabetes, the utility of screening in a dental setting and referral to primary care as a means to improve the diagnosis of prediabetes and diabetes has been explored ( 94 – 96 ), with one study estimating that 30% of patients ≥30 years of age seen in general dental practices had dysglycemia ( 96 , 97 ). A similar study in 1,150 dental patients >40 years old in India reported 20.69% and 14.60% meeting criteria for prediabetes and diabetes using random blood glucose. Further research is needed to demonstrate the feasibility, effectiveness, and cost-effectiveness of screening in this setting.

Screening and Testing for Prediabetes and Type 2 Diabetes in Children and Adolescents

In the last decade, the incidence and prevalence of type 2 diabetes in children and adolescents has increased dramatically, especially in racial and ethnic minority populations ( 53 ). See Table 2.4 for recommendations on risk-based screening for type 2 diabetes or prediabetes in asymptomatic children and adolescents in a clinical setting ( 25 ). See Table 2.2 and Table 2.5 for the criteria for the diagnosis of diabetes and prediabetes, respectively, which apply to children, adolescents, and adults. See Section 13 “Children and Adolescents” ( https://doi.org/10.2337/dc21-S013 ) for additional information on type 2 diabetes in children and adolescents.

Some studies question the validity of A1C in the pediatric population, especially among certain ethnicities, and suggest OGTT or FPG as more suitable diagnostic tests ( 98 ). However, many of these studies do not recognize that diabetes diagnostic criteria are based on long-term health outcomes, and validations are not currently available in the pediatric population ( 99 ). The ADA acknowledges the limited data supporting A1C for diagnosing type 2 diabetes in children and adolescents. Although A1C is not recommended for diagnosis of diabetes in children with cystic fibrosis or symptoms suggestive of acute onset of type 1 diabetes and only A1C assays without interference are appropriate for children with hemoglobinopathies, the ADA continues to recommend A1C for diagnosis of type 2 diabetes in this cohort to decrease barriers to screening ( 100 , 101 ).

2.15 Annual screening for cystic fibrosis–related diabetes (CFRD) with an oral glucose tolerance test should begin by age 10 years in all patients with cystic fibrosis not previously diagnosed with CFRD. B

2.16 A1C is not recommended as a screening test for cystic fibrosis–related diabetes. B

2.17 Patients with cystic fibrosis–related diabetes should be treated with insulin to attain individualized glycemic goals. A

2.18 Beginning 5 years after the diagnosis of cystic fibrosis–related diabetes, annual monitoring for complications of diabetes is recommended. E

Cystic fibrosis–related diabetes (CFRD) is the most common comorbidity in people with cystic fibrosis, occurring in about 20% of adolescents and 40 – 50% of adults ( 102 ). Diabetes in this population, compared with individuals with type 1 or type 2 diabetes, is associated with worse nutritional status, more severe inflammatory lung disease, and greater mortality. Insulin insufficiency is the primary defect in CFRD. Genetically determined β-cell function and insulin resistance associated with infection and inflammation may also contribute to the development of CFRD. Milder abnormalities of glucose tolerance are even more common and occur at earlier ages than CFRD. Whether individuals with IGT should be treated with insulin replacement has not currently been determined. Although screening for diabetes before the age of 10 years can identify risk for progression to CFRD in those with abnormal glucose tolerance, no benefit has been established with respect to weight, height, BMI, or lung function. OGTT is the recommended screening test; however, recent publications suggest that an A1C cut point threshold of 5.5% (5.8% in a second study) would detect more than 90% of cases and reduce patient screening burden ( 103 , 104 ). Ongoing studies are underway to validate this approach. Regardless of age, weight loss or failure of expected weight gain is a risk for CFRD and should prompt screening ( 103 , 104 ). The Cystic Fibrosis Foundation Patient Registry ( 105 ) evaluated 3,553 cystic fibrosis patients and diagnosed 445 (13%) with CFRD. Early diagnosis and treatment of CFRD was associated with preservation of lung function. The European Cystic Fibrosis Society Patient Registry reported an increase in CFRD with age (increased 10% per decade), genotype, decreased lung function, and female sex ( 106 , 107 ). Continuous glucose monitoring or HOMA of β-cell function ( 108 ) may be more sensitive than OGTT to detect risk for progression to CFRD; however, evidence linking these results to long-term outcomes is lacking, and these tests are not recommended for screening outside of the research setting ( 109 ).

CFRD mortality has significantly decreased over time, and the gap in mortality between cystic fibrosis patients with and without diabetes has considerably narrowed ( 110 ). There are limited clinical trial data on therapy for CFRD. The largest study compared three regimens: premeal insulin aspart, repaglinide, or oral placebo in cystic fibrosis patients with diabetes or abnormal glucose tolerance. Participants all had weight loss in the year preceding treatment; however, in the insulin-treated group, this pattern was reversed, and patients gained 0.39 (± 0.21) BMI units (P = 0.02). The repaglinide-treated group had initial weight gain, but this was not sustained by 6 months. The placebo group continued to lose weight ( 110 ). Insulin remains the most widely used therapy for CFRD ( 111 ). The primary rationale for the use of insulin in patients with CFRD is to induce an anabolic state while promoting macronutrient retention and weight gain.

Additional resources for the clinical management of CFRD can be found in the position statement “Clinical Care Guidelines for Cystic Fibrosis–Related Diabetes: A Position Statement of the American Diabetes Association and a Clinical Practice Guideline of the Cystic Fibrosis Foundation, Endorsed by the Pediatric Endocrine Society” ( 112 ) and in the International Society for Pediatric and Adolescent Diabetes's 2014 clinical practice consensus guidelines ( 102 ).

2.19 Patients should be screened after organ transplantation for hyperglycemia, with a formal diagnosis of posttransplantation diabetes mellitus being best made once a patient is stable on an immunosuppressive regimen and in the absence of an acute infection. B

2.20 The oral glucose tolerance test is the preferred test to make a diagnosis of posttransplantation diabetes mellitus. B

2.21 Immunosuppressive regimens shown to provide the best outcomes for patient and graft survival should be used, irrespective of posttransplantation diabetes mellitus risk. E

Several terms are used in the literature to describe the presence of diabetes following organ transplantation ( 113 ). “New-onset diabetes after transplantation” (NODAT) is one such designation that describes individuals who develop new-onset diabetes following transplant. NODAT excludes patients with pretransplant diabetes that was undiagnosed as well as posttransplant hyperglycemia that resolves by the time of discharge ( 114 ). Another term, “posttransplantation diabetes mellitus” (PTDM) ( 114 , 115 ), describes the presence of diabetes in the posttransplant setting irrespective of the timing of diabetes onset.

Hyperglycemia is very common during the early posttransplant period, with ∼90% of kidney allograft recipients exhibiting hyperglycemia in the first few weeks following transplant ( 114 – 117 ). In most cases, such stress- or steroid-induced hyperglycemia resolves by the time of discharge ( 117 , 118 ). Although the use of immunosuppressive therapies is a major contributor to the development of PTDM, the risks of transplant rejection outweigh the risks of PTDM and the role of the diabetes care provider is to treat hyperglycemia appropriately regardless of the type of immunosuppression ( 114 ). Risk factors for PTDM include both general diabetes risks (such as age, family history of diabetes, etc.) as well as transplant-specific factors, such as use of immunosuppressant agents ( 119 ). Whereas posttransplantation hyperglycemia is an important risk factor for subsequent PTDM, a formal diagnosis of PTDM is optimally made once the patient is stable on maintenance immunosuppression and in the absence of acute infection ( 117 – 120 ). In a recent study of 152 heart transplant recipients, 38% had PTDM at 1 year. Risk factors for PTDM included elevated BMI, discharge from the hospital on insulin, and glucose values in the 24 h prior to hospital discharge ( 121 ). In an Iranian cohort, 19% had PTDM after heart and lung transplant ( 122 ). The OGTT is considered the gold standard test for the diagnosis of PTDM (1 year posttransplant) ( 114 , 115 , 123 , 124 ). However, screening patients using fasting glucose and/or A1C can identify high-risk patients requiring further assessment and may reduce the number of overall OGTTs required.

Few randomized controlled studies have reported on the short- and long-term use of antihyperglycemic agents in the setting of PTDM ( 119 , 125 , 126 ). Most studies have reported that transplant patients with hyperglycemia and PTDM after transplantation have higher rates of rejection, infection, and rehospitalization ( 117 , 119 , 127 ). Insulin therapy is the agent of choice for the management of hyperglycemia, PTDM, and preexisting diabetes and diabetes in the hospital setting. After discharge, patients with preexisting diabetes could go back on their pretransplant regimen if they were in good control before transplantation. Those with previously poor control or with persistent hyperglycemia should continue insulin with frequent home self-monitoring of blood glucose to determine when insulin dose reductions may be needed and when it may be appropriate to switch to noninsulin agents.

No studies to date have established which noninsulin agents are safest or most efficacious in PTDM. The choice of agent is usually made based on the side effect profile of the medication and possible interactions with the patient's immunosuppression regimen ( 119 ). Drug dose adjustments may be required because of decreases in the glomerular filtration rate, a relatively common complication in transplant patients. A small short-term pilot study reported that metformin was safe to use in renal transplant recipients ( 128 ), but its safety has not been determined in other types of organ transplant. Thiazolidinediones have been used successfully in patients with liver and kidney transplants, but side effects include fluid retention, heart failure, and osteopenia ( 129 , 130 ). Dipeptidyl peptidase 4 inhibitors do not interact with immunosuppressant drugs and have demonstrated safety in small clinical trials ( 131 , 132 ). Well-designed intervention trials examining the efficacy and safety of these and other antihyperglycemic agents in patients with PTDM are needed.

2.22 All children diagnosed with diabetes in the first 6 months of life should have immediate genetic testing for neonatal diabetes. A

2.23 Children and those diagnosed in early adulthood who have diabetes not characteristic of type 1 or type 2 diabetes that occurs in successive generations (suggestive of an autosomal dominant pattern of inheritance) should have genetic testing for maturity-onset diabetes of the young. A

2.24 In both instances, consultation with a center specializing in diabetes genetics is recommended to understand the significance of these mutations and how best to approach further evaluation, treatment, and genetic counseling. E

Monogenic defects that cause β-cell dysfunction, such as neonatal diabetes and MODY, represent a small fraction of patients with diabetes (<5%). Table 2.6 describes the most common causes of monogenic diabetes. For a comprehensive list of causes, see Genetic Diagnosis of Endocrine Disorders ( 133 ).

Most common causes of monogenic diabetes ( 133 )

AD, autosomal dominant; AR, autosomal recessive; IUGR, intrauterine growth restriction; OGTT, oral glucose tolerance test; UPD6, uniparental disomy of chromosome 6; 2-h PG, 2-h plasma glucose.

Neonatal Diabetes

Diabetes occurring under 6 months of age is termed “neonatal” or “congenital” diabetes, and about 80 – 85% of cases can be found to have an underlying monogenic cause ( 134 – 137 ). Neonatal diabetes occurs much less often after 6 months of age, whereas autoimmune type 1 diabetes rarely occurs before 6 months of age. Neonatal diabetes can either be transient or permanent. Transient diabetes is most often due to overexpression of genes on chromosome 6q24, is recurrent in about half of cases, and may be treatable with medications other than insulin. Permanent neonatal diabetes is most commonly due to autosomal dominant mutations in the genes encoding the Kir6.2 subunit ( KCNJ11 ) and SUR1 subunit ( ABCC8 ) of the β-cell K ATP channel. A recent report details a de novo mutation in EIF2B1 affecting eIF2 signaling associated with permanent neonatal diabetes and hepatic dysfunction, similar to Wolcott-Rallison syndrome but with few severe comorbidities ( 138 ). Correct diagnosis has critical implications because most patients with K ATP -related neonatal diabetes will exhibit improved glycemic control when treated with high-dose oral sulfonylureas instead of insulin. Insulin gene ( INS ) mutations are the second most common cause of permanent neonatal diabetes, and, while intensive insulin management is currently the preferred treatment strategy, there are important genetic counseling considerations, as most of the mutations that cause diabetes are dominantly inherited.

Maturity-Onset Diabetes of the Young

MODY is frequently characterized by onset of hyperglycemia at an early age (classically before age 25 years, although diagnosis may occur at older ages). MODY is characterized by impaired insulin secretion with minimal or no defects in insulin action (in the absence of coexistent obesity). It is inherited in an autosomal dominant pattern with abnormalities in at least 13 genes on different chromosomes identified to date. The most commonly reported forms are GCK-MODY (MODY2), HNF1A-MODY (MODY3), and HNF4A-MODY (MODY1).

For individuals with MODY, the treatment implications are considerable and warrant genetic testing ( 139 , 140 ). Clinically, patients with GCK-MODY exhibit mild, stable fasting hyperglycemia and do not require antihyperglycemic therapy except sometimes during pregnancy. Patients with HNF1A- or HNF4A-MODY usually respond well to low doses of sulfonylureas, which are considered first-line therapy. Mutations or deletions in HNF1B are associated with renal cysts and uterine malformations (renal cysts and diabetes [RCAD] syndrome). Other extremely rare forms of MODY have been reported to involve other transcription factor genes including PDX1 ( IPF1 ) and NEUROD1 .

Diagnosis of Monogenic Diabetes

A diagnosis of one of the three most common forms of MODY, including GCK-MODY, HNF1A-MODY, and HNF4A-MODY, allows for more cost-effective therapy (no therapy for GCK-MODY; sulfonylureas as first-line therapy for HNF1A-MODY and HNF4A-MODY). Additionally, diagnosis can lead to identification of other affected family members. Genetic screening is increasingly available and cost-effective ( 138 , 140 ).

A diagnosis of MODY should be considered in individuals who have atypical diabetes and multiple family members with diabetes not characteristic of type 1 or type 2 diabetes, although admittedly “atypical diabetes” is becoming increasingly difficult to precisely define in the absence of a definitive set of tests for either type of diabetes ( 135 – 137 , 139 – 145 ). In most cases, the presence of autoantibodies for type 1 diabetes precludes further testing for monogenic diabetes, but the presence of autoantibodies in patients with monogenic diabetes has been reported ( 146 ). Individuals in whom monogenic diabetes is suspected should be referred to a specialist for further evaluation if available, and consultation is available from several centers. Readily available commercial genetic testing following the criteria listed below now enables a cost-effective ( 147 ), often cost-saving, genetic diagnosis that is increasingly supported by health insurance. A biomarker screening pathway such as the combination of urinary C-peptide/creatinine ratio and antibody screening may aid in determining who should get genetic testing for MODY ( 148 ). It is critical to correctly diagnose one of the monogenic forms of diabetes because these patients may be incorrectly diagnosed with type 1 or type 2 diabetes, leading to suboptimal, even potentially harmful, treatment regimens and delays in diagnosing other family members ( 149 ). The correct diagnosis is especially critical for those with GCK-MODY mutations where multiple studies have shown that no complications ensue in the absence of glucose-lowering therapy ( 150 ). Genetic counseling is recommended to ensure that affected individuals understand the patterns of inheritance and the importance of a correct diagnosis.

The diagnosis of monogenic diabetes should be considered in children and adults diagnosed with diabetes in early adulthood with the following findings:

Diabetes diagnosed within the first 6 months of life (with occasional cases presenting later, mostly INS and ABCC8 mutations) ( 134 , 151 )

Diabetes without typical features of type 1 or type 2 diabetes (negative diabetes-associated autoantibodies, nonobese, lacking other metabolic features, especially with strong family history of diabetes)

Stable, mild fasting hyperglycemia (100 – 150 mg/dL [5.5 – 8.5 mmol/L]), stable A1C between 5.6% and 7.6% (between 38 and 60 mmol/mol), especially if nonobese

Pancreatic diabetes includes both structural and functional loss of glucose-normalizing insulin secretion in the context of exocrine pancreatic dysfunction and is commonly misdiagnosed as type 2 diabetes. Hyperglycemia due to general pancreatic dysfunction has been called “type 3c diabetes” and, more recently, diabetes in the context of disease of the exocrine pancreas has been termed pancreoprivic diabetes ( 1 ). The diverse set of etiologies includes pancreatitis (acute and chronic), trauma or pancreatectomy, neoplasia, cystic fibrosis (addressed elsewhere in this chapter), hemochromatosis, fibrocalculous pancreatopathy, rare genetic disorders ( 152 ), and idiopathic forms ( 1 ), which is the preferred terminology. A distinguishing feature is concurrent pancreatic exocrine insufficiency (according to the monoclonal fecal elastase 1 test or direct function tests), pathological pancreatic imaging (endoscopic ultrasound, MRI, computed tomography), and absence of type 1 diabetes–associated autoimmunity ( 153 – 157 ). There is loss of both insulin and glucagon secretion and often higher-than-expected insulin requirements. Risk for microvascular complications is similar to other forms of diabetes. In the context of pancreatectomy, islet autotransplantation can be done to retain insulin secretion ( 158 , 159 ). In some cases, autotransplant can lead to insulin independence. In others, it may decrease insulin requirements ( 160 ).

2.25 Test for undiagnosed prediabetes and diabetes at the first prenatal visit in those with risk factors using standard diagnostic criteria. B

2.26 Test for gestational diabetes mellitus at 24 – 28 weeks of gestation in pregnant women not previously found to have diabetes. A

2.27 Test women with gestational diabetes mellitus for prediabetes or diabetes at 4 – 12 weeks postpartum, using the 75-g oral glucose tolerance test and clinically appropriate nonpregnancy diagnostic criteria. B

2.28 Women with a history of gestational diabetes mellitus should have lifelong screening for the development of diabetes or prediabetes at least every 3 years. B

2.29 Women with a history of gestational diabetes mellitus found to have prediabetes should receive intensive lifestyle interventions and/or metformin to prevent diabetes. A

For many years, GDM was defined as any degree of glucose intolerance that was first recognized during pregnancy ( 60 ), regardless of the degree of hyperglycemia. This definition facilitated a uniform strategy for detection and classification of GDM, but this definition has serious limitations ( 161 ). First, the best available evidence reveals that many, perhaps most, cases of GDM represent preexisting hyperglycemia that is detected by routine screening in pregnancy, as routine screening is not widely performed in nonpregnant women of reproductive age. It is the severity of hyperglycemia that is clinically important with regard to both short- and long-term maternal and fetal risks. Universal preconception and/or first trimester screening is hampered by lack of data and consensus regarding appropriate diagnostic thresholds and outcomes and cost-effectiveness ( 162 , 163 ). A compelling argument for further work in this area is the fact that hyperglycemia that would be diagnostic of diabetes outside of pregnancy and is present at the time of conception is associated with an increased risk of congenital malformations that is not seen with lower glucose levels ( 164 , 165 ).

The ongoing epidemic of obesity and diabetes has led to more type 2 diabetes in women of reproductive age, with an increase in the number of pregnant women with undiagnosed type 2 diabetes in early pregnancy ( 166 – 169 ). Because of the number of pregnant women with undiagnosed type 2 diabetes, it is reasonable to test women with risk factors for type 2 diabetes ( 170 ) ( Table 2.3 ) at their initial prenatal visit, using standard diagnostic criteria ( Table 2.2 ). Women found to have diabetes by the standard diagnostic criteria used outside of pregnancy should be classified as having diabetes complicating pregnancy (most often type 2 diabetes, rarely type 1 diabetes or monogenic diabetes) and managed accordingly. Women who meet the lower glycemic criteria for GDM should be diagnosed with that condition and managed accordingly. Other women should be rescreened for GDM between 24 and 28 weeks of gestation (see Section 14 “Management of Diabetes in Pregnancy,” https://doi.org/10.2337/dc21-S014 ). The International Association of the Diabetes and Pregnancy Study Groups (IADPSG) GDM diagnostic criteria for the 75-g OGTT as well as the GDM screening and diagnostic criteria used in the two-step approach were not derived from data in the first half of pregnancy, so the diagnosis of GDM in early pregnancy by either FPG or OGTT values is not evidence based ( 171 ) and further work is needed.

GDM is often indicative of underlying β-cell dysfunction ( 172 ), which confers marked increased risk for later development of diabetes, generally but not always type 2 diabetes, in the mother after delivery ( 173 , 174 ). As effective prevention interventions are available ( 175 , 176 ), women diagnosed with GDM should receive lifelong screening for prediabetes to allow interventions to reduce diabetes risk and for type 2 diabetes to allow treatment at the earliest possible time ( 177 ).

GDM carries risks for the mother, fetus, and neonate. The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study ( 178 ), a large-scale multinational cohort study completed by more than 23,000 pregnant women, demonstrated that risk of adverse maternal, fetal, and neonatal outcomes continuously increased as a function of maternal glycemia at 24 – 28 weeks of gestation, even within ranges previously considered normal for pregnancy. For most complications, there was no threshold for risk. These results have led to careful reconsideration of the diagnostic criteria for GDM.

GDM diagnosis ( Table 2.7 ) can be accomplished with either of two strategies:

The “one-step” 75-g OGTT derived from the IADPSG criteria, or

The older “two-step” approach with a 50-g (nonfasting) screen followed by a 100-g OGTT for those who screen positive, based on the work of Carpenter and Coustan's interpretation of the older OʼSullivan ( 179 ) criteria.

Screening for and diagnosis of GDM

GDM, gestational diabetes mellitus; GLT, glucose load test; OGTT, oral glucose tolerance test.

American College of Obstetricians and Gynecologists notes that one elevated value can be used for diagnosis ( 189 ).

Different diagnostic criteria will identify different degrees of maternal hyperglycemia and maternal/fetal risk, leading some experts to debate, and disagree on, optimal strategies for the diagnosis of GDM.

One-Step Strategy

The IADPSG defined diagnostic cut points for GDM as the average fasting, 1-h, and 2-h PG values during a 75-g OGTT in women at 24 – 28 weeks of gestation who participated in the HAPO study at which odds for adverse outcomes reached 1.75 times the estimated odds of these outcomes at the mean fasting, 1-h, and 2-h PG levels of the study population. This one-step strategy was anticipated to significantly increase the incidence of GDM (from 5 – 6% to 15–20%), primarily because only one abnormal value, not two, became sufficient to make the diagnosis ( 180 ). Many regional studies have investigated the impact of adopting the IADPSG criteria on prevalence and have seen a roughly one- to threefold increase ( 181 ). The anticipated increase in the incidence of GDM could have a substantial impact on costs and medical infrastructure needs and has the potential to “medicalize” pregnancies previously categorized as normal. A recent follow-up study of women participating in a blinded study of pregnancy OGTTs found that 11 years after their pregnancies, women who would have been diagnosed with GDM by the one-step approach, as compared with those without, were at 3.4-fold higher risk of developing prediabetes and type 2 diabetes and had children with a higher risk of obesity and increased body fat, suggesting that the larger group of women identified by the one-step approach would benefit from increased screening for diabetes and prediabetes that would accompany a history of GDM ( 182 , 183 ). The ADA recommends the IADPSG diagnostic criteria with the intent of optimizing gestational outcomes because these criteria are the only ones based on pregnancy outcomes rather than end points such as prediction of subsequent maternal diabetes.

The expected benefits of using IADPSG to the offspring are inferred from intervention trials that focused on women with lower levels of hyperglycemia than identified using older GDM diagnostic criteria. Those trials found modest benefits including reduced rates of large-for-gestational-age births and preeclampsia ( 184 , 185 ). It is important to note that 80 – 90% of women being treated for mild GDM in these two randomized controlled trials could be managed with lifestyle therapy alone. The OGTT glucose cutoffs in these two trials overlapped with the thresholds recommended by the IADPSG, and in one trial ( 185 ), the 2-h PG threshold (140 mg/dL [7.8 mmol/L]) was lower than the cutoff recommended by the IADPSG (153 mg/dL [8.5 mmol/L]). No randomized controlled trials of treating versus not treating GDM diagnosed by the IADPSG criteria but not the Carpenter-Coustan criteria have been published to date. Data are also lacking on how the treatment of lower levels of hyperglycemia affects a mother's future risk for the development of type 2 diabetes and her offspring's risk for obesity, diabetes, and other metabolic disorders. Additional well-designed clinical studies are needed to determine the optimal intensity of monitoring and treatment of women with GDM diagnosed by the one-step strategy ( 186 , 187 ).

Two-Step Strategy

In 2013, the NIH convened a consensus development conference to consider diagnostic criteria for diagnosing GDM ( 188 ). The 15-member panel had representatives from obstetrics and gynecology, maternal-fetal medicine, pediatrics, diabetes research, biostatistics, and other related fields. The panel recommended a two-step approach to screening that used a 1-h 50-g glucose load test (GLT) followed by a 3-h 100-g OGTT for those who screened positive. The American College of Obstetricians and Gynecologists (ACOG) recommends any of the commonly used thresholds of 130, 135, or 140 mg/dL for the 1-h 50-g GLT ( 189 ). A systematic review for the U.S. Preventive Services Task Force compared GLT cutoffs of 130 mg/dL (7.2 mmol/L) and 140 mg/dL (7.8 mmol/L) ( 190 ). The higher cutoff yielded sensitivity of 70–88% and specificity of 69 – 89%, while the lower cutoff was 88 – 99% sensitive and 66 – 77% specific. Data regarding a cutoff of 135 mg/dL are limited. As for other screening tests, choice of a cutoff is based upon the trade-off between sensitivity and specificity. The use of A1C at 24–28 weeks of gestation as a screening test for GDM does not function as well as the GLT ( 191 ).

Key factors cited by the NIH panel in their decision-making process were the lack of clinical trial data demonstrating the benefits of the one-step strategy and the potential negative consequences of identifying a large group of women with GDM, including medicalization of pregnancy with increased health care utilization and costs. Moreover, screening with a 50-g GLT does not require fasting and is therefore easier to accomplish for many women. Treatment of higher-threshold maternal hyperglycemia, as identified by the two-step approach, reduces rates of neonatal macrosomia, large-for-gestational-age births ( 192 ), and shoulder dystocia, without increasing small-for-gestational-age births. ACOG currently supports the two-step approach but notes that one elevated value, as opposed to two, may be used for the diagnosis of GDM ( 189 ). If this approach is implemented, the incidence of GDM by the two-step strategy will likely increase markedly. ACOG recommends either of two sets of diagnostic thresholds for the 3-h 100-g OGTT—Carpenter-Coustan or National Diabetes Data Group ( 193 , 194 ). Each is based on different mathematical conversions of the original recommended thresholds by O'Sullivan ( 179 ), which used whole blood and nonenzymatic methods for glucose determination. A secondary analysis of data from a randomized clinical trial of identification and treatment of mild GDM ( 195 ) demonstrated that treatment was similarly beneficial in patients meeting only the lower thresholds per Carpenter-Coustan ( 193 ) and in those meeting only the higher thresholds per National Diabetes Data Group ( 194 ). If the two-step approach is used, it would appear advantageous to use the Carpenter-Coustan lower diagnostic thresholds as shown in step 2 in Table 2.7 .

Future Considerations

The conflicting recommendations from expert groups underscore the fact that there are data to support each strategy. A cost-benefit estimation comparing the two strategies concluded that the one-step approach is cost-effective only if patients with GDM receive postdelivery counseling and care to prevent type 2 diabetes ( 196 ). The decision of which strategy to implement must therefore be made based on the relative values placed on factors that have yet to be measured (e.g., willingness to change practice based on correlation studies rather than intervention trial results, available infrastructure, and importance of cost considerations).

As the IADPSG criteria (“one-step strategy”) have been adopted internationally, further evidence has emerged to support improved pregnancy outcomes with cost savings ( 197 ), and IADPSG may be the preferred approach. Data comparing population-wide outcomes with one-step versus two-step approaches have been inconsistent to date ( 198 , 199 ). In addition, pregnancies complicated by GDM per the IADPSG criteria, but not recognized as such, have outcomes comparable to pregnancies with diagnosed GDM by the more stringent two-step criteria ( 200 , 201 ). There remains strong consensus that establishing a uniform approach to diagnosing GDM will benefit patients, caregivers, and policy makers. Longer-term outcome studies are currently underway.

Suggested citation: American Diabetes Association. 2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes—2021 . Diabetes Care 2021;44(Suppl. 1):S15−S33

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PARITA PATEL, MD, AND ALLISON MACEROLLO, MD

Am Fam Physician. 2010;81(7):863-870

A more recent article on diabetes mellitus is available .

See related editorial on page 843 .

Author disclosure: Nothing to disclose.

Based on etiology, diabetes is classified as type 1 diabetes mellitus, type 2 diabetes mellitus, latent autoimmune diabetes, maturity-onset diabetes of youth, and miscellaneous causes. The diagnosis is based on measurement of A1C level, fasting or random blood glucose level, or oral glucose tolerance testing. Although there are conflicting guidelines, most agree that patients with hypertension or hyperlipidemia should be screened for diabetes. Diabetes risk calculators have a high negative predictive value and help define patients who are unlikely to have diabetes. Tests that may help establish the type of diabetes or the continued need for insulin include those reflective of beta cell function, such as C peptide levels, and markers of immune-mediated beta cell destruction (e.g., autoantibodies to islet cells, insulin, glutamic acid decarboxylase, tyrosine phosphatase [IA-2α and IA-2β]). Antibody testing is limited by availability, cost, and predictive value.

Prevention, timely diagnosis, and treatment are important in patients with diabetes mellitus. Many of the complications associated with diabetes, such as nephropathy, retinopathy, neuropathy, cardiovascular disease, stroke, and death, can be delayed or prevented with appropriate treatment of elevated blood pressure, lipids, and blood glucose. 1 – 4

In 1997, the American Diabetes Association (ADA) introduced an etiologically based classification system and diagnostic criteria for diabetes, 5 which were updated in 2010. 1 Type 2 diabetes accounts for approximately 90 to 95 percent of all persons with diabetes in the United States, and its prevalence is increasing in adults worldwide. 6 With the rise in childhood obesity, type 2 diabetes is increasingly being diagnosed in children and adolescents. 6

The risk of diabetes is increased in close relatives suggesting a genetic predisposition, although no direct genetic link has been identified. 7 Type 1 diabetes accounts for 5 to 10 percent of persons with diabetes 6 and is characterized by insulin deficiency that is typically an autoimmune-mediated condition.

Latent autoimmune diabetes in adults includes a heterogenous group of conditions that are phenotypically similar to type 2 diabetes, but patients have autoantibodies that are common with type 1 diabetes. Diagnostic criteria include age of 30 years or older; no insulin treatment for six months after diagnosis; and presence of autoantibodies to glutamic acid decarboxylase, islet cells, tyrosine phosphatase (IA-2α and IA-2β), or insulin.

Patients with maturity-onset diabetes of youth typically present before 25 years of age, have only impaired insulin secretion, and have a monogenetic defect that leads to an autosomal dominant inheritance pattern. These patients are placed in a subcategory of having genetic defects of beta cell. 8

The old terminology of prediabetes has now been replaced with “categories of increased risk for diabetes.” This includes persons with impaired fasting glucose, impaired glucose tolerance, or an A1C level of 5.7 to 6.4 percent. 1 , 9 , 10

Diagnostic Criteria and Testing

The 1997 ADA consensus guidelines lowered the blood glucose thresholds for the diagnosis of diabetes. 5 This increased the number of patients diagnosed at an earlier stage, although no studies have demonstrated a reduction in long-term complications. Data suggest that as many as 5.7 million persons in the United States have undiagnosed diabetes. 6 Table 1 compares specific diagnostic tests for diabetes. 11 – 14

TESTS TO DIAGNOSE DIABETES

Blood Glucose Measurements . The diagnosis of diabetes is based on one of three methods of blood glucose measurement ( Table 2 ) . 1 Diabetes can be diagnosed if the patient has a fasting blood glucose level of 126 mg per dL (7.0 mmol per L) or greater on two separate occasions. The limitations of this test include the need for an eight-hour fast before the blood draw, a 12 to 15 percent day-to-day variance in fasting blood glucose values, and a slightly lower sensitivity for predicting microvascular complications. 15 , 16

Diabetes can also be diagnosed with a random blood glucose level of 200 mg per dL (11.1 mmol per L) or greater if classic symptoms of diabetes (e.g., polyuria, polydipsia, weight loss, blurred vision, fatigue) are present. Lower random blood glucose values (140 to 180 mg per dL [7.8 to 10.0 mmol per L]) have a fairly high specificity of 92 to 98 percent; therefore, patients with these values should undergo more definitive testing. A low sensitivity of 39 to 55 percent limits the use of random blood glucose testing. 15

The oral glucose tolerance test is considered a first-line diagnostic test. Limitations include poor reproducibility and patient compliance because an eight-hour fast is needed before the 75-g glucose load, which is followed two hours later by a blood draw. 17 The criterion for diabetes is a serum blood glucose level of greater than 199 mg per dL (11.0 mmol per L).

In 2003, the ADA lowered the threshold for diagnosis of impaired fasting glucose to include a fasting glucose level between 100 and 125 mg per dL (5.6 and 6.9 mmol per L). Impaired glucose tolerance continues to be defined as a blood glucose level between 140 and 199 mg per dL (7.8 and 11.0 mmol per L) two hours after a 75-g load. Patients meeting either of these criteria are at significantly higher risk of progression to diabetes and should be counseled on effective strategies to lower their risk, such as weight loss and exercise. 1 , 9

A1C . A1C measurement has recently been endorsed by the ADA as a diagnostic and screening tool for diabetes. 1 One advantage of using A1C measurement is the ease of testing because it does not require fasting. An A1C level of greater than 6.5 percent on two separate occasions is considered diagnostic of diabetes. 18 Lack of standardization has historically deterred its use, but this test is now widely standardized in the United States. 19 A1C measurements for diagnosis of diabetes should be performed by a clinical laboratory because of the lack of standardization of point-of-care testing. Limitations of A1C testing include low sensitivity, possible racial disparities, and interference by anemia and some medications. 15

TESTS TO IDENTIFY TYPE OF DIABETES

Tests that can be used to establish the etiology of diabetes include those reflective of beta cell function (e.g., C peptide) and markers of immune-mediated beta cell destruction (e.g., insulin, islet cell, glutamic acid decarboxylase, IA-2α and IA-2β autoantibodies). Table 3 presents the characteristics of these tests. 20 – 27

C peptide is linked to insulin to form proinsulin and reflects the amount of endogenous insulin. Patients with type 1 diabetes have low C peptide levels because of low levels of endogenous insulin and beta cell function. Patients with type 2 diabetes typically have normal to high levels of C peptide, reflecting higher amounts of insulin but relative insensitivity to it. In a Swedish study of patients with clinically well-defined type 1 or 2 diabetes, 96 percent of patients with type 2 diabetes had random C peptide levels greater than 1.51 ng per mL (0.50 nmol per L), whereas 90 percent of patients with type 1 diabetes had values less than 1.51 ng per mL. 20 In the clinically undefined population, which is the group in which the test is most often used, the predictive value is likely lower.

Antibody testing is limited by availability, cost, and predictive value, especially in black and Asian patients. Prevalence of any antibody in white patients with type 1 diabetes is 85 to 90 percent, 5 whereas the prevalence in similar black or Hispanic patients is lower (19 percent in both groups in one study). 28 In persons with type 2 diabetes, the prevalence of islet cell antibody is 4 to 21 percent; glutamic acid decarboxylase antibody, 7 to 34 percent; IA-2, 1 to 2 percent; and any antibody, 11.6 percent. 24 , 25 , 29 In healthy persons, the prevalence of any antibody marker is 1 to 2 percent 30 ; thus, overlap of the presence of antibodies in various types of diabetes and patients limits the utility of individual tests.

As with any condition, a rationale for screening should first be established. Diabetes is a common disease that is associated with significant morbidity and mortality. It has an asymptomatic stage that may be present for up to seven years before diagnosis. The disease is treatable, and testing is acceptable and accessible to patients. Early treatment of diabetes that was identified primarily by symptoms improves microvascular outcomes. 31 However, it is not clear whether universal screening reduces diabetes-associated morbidity and mortality. Table 4 presents screening guidelines from several organizations. 1 , 8 , 32 – 38

TYPE 1 DIABETES

Screening for type 1 diabetes is not recommended because there is no accepted treatment for patients who are diagnosed in the asymptomatic phase. The Diabetes Prevention Trial identified a group of high-risk patients based on family history and positivity to islet cell antibodies. However, treatment did not prevent progression to type 1 diabetes in these patients. 39

TYPE 2 DIABETES

Medications and lifestyle interventions may reduce the risk of diabetes, although 20 to 30 percent of patients with type 2 diabetes already have complications at the time of presentation. 40 Although a recent analysis suggests that screening for and treating impaired glucose tolerance in persons at risk of diabetes may be cost-effective, the data on screening for type 2 diabetes are less certain. 41 It is unclear whether the early diagnosis of type 2 diabetes through screening programs, with subsequent intensive interventions, provides an incremental benefit in final health outcomes compared with initiating treatment after clinical diagnosis.

Guidelines differ regarding who should be screened for type 2 diabetes. The U.S. Preventive Services Task Force (USPSTF) recommends limiting screening to adults with a sustained blood pressure of greater than 135/80 mm Hg. 34 , 42 The American Academy of Family Physicians concurs, but specifically includes treated and untreated patients. 43 The Canadian Task Force on Preventive Health Care recommends screening all patients with hypertension or hyperlipidemia. 33 The ADA recommends screening a much broader patient population based on risk. 1

There are several questionnaires to predict a patient's risk of diabetes. The Diabetes Risk Calculator was developed using data from the National Health and Nutrition Examination Survey III and incorporates age, height, weight, waist circumference, ethnicity, blood pressure, exercise, history of gestational diabetes, and family history. 13 , 14 For diagnosis of diabetes, it has a positive predictive value (PPV) of 14 percent and a negative predictive value (NPV) of 99.3 percent. The tool is most valuable in helping define which patients are very unlikely to have diabetes. 13

GESTATIONAL DIABETES

Whether patients should be screened for gestational diabetes is unclear. The USPSTF states that there is insufficient evidence to recommend for or against screening. 34 The ADA and the American College of Obstetricians and Gynecologists recommend risk-based testing, although most women require testing based on these inclusive guidelines. 36 The Glucola test is the most commonly used screening test for gestational diabetes and includes glucose testing one hour after a 50-g oral glucose load. An abnormal Glucola test result (i.e., blood glucose level of 140 mg per dL or greater) should be confirmed with a 75-g or 100-g oral glucose tolerance test. Whether screening and subsequent treatment of gestational diabetes alter clinically important perinatal outcomes is unclear. Untreated gestational diabetes is associated with a higher incidence of macrosomia and shoulder dystocia. 44 A randomized controlled trial found that treatment led to a reduction in serious perinatal complications, with a number needed to treat of 34. Treatment did not reduce risk of cesarean delivery or admission to the neonatal intensive care unit, however. 44

New-Onset Symptomatic Hyperglycemia

Patients may initially present with diabetic ketoacidosis or hyperglycemic hyperosmolar state ( Table 5 ) , 45 both of which are initially managed with insulin because they are essentially insulin deficiency states. Both groups of patients may present with polyuria, polydipsia, and signs of dehydration. Diagnostic criteria of diabetic ketoacidosis include a blood glucose level greater than 250 mg per dL (13.9 mmol per L), pH of 7.3 or less, serum bicarbonate level less than 18 mEq per L (18 mmol per L), and moderate ketonemia. However, significant ketosis has also been shown to occur in up to one third of patients with hyperglycemic hyperosmolar state. 46

Although diabetic ketoacidosis typically occurs in persons with type 1 diabetes, more than one half of newly diagnosed black patients with unprovoked diabetic ketoacidosis are obese and many display classic features of type 2 diabetes—most importantly with a measurable insulin reserve. 47 Thus, the presentation does not definitively determine the type of diabetes a patient has. Presence of antibodies, particularly glutamic acid decarboxylase antibody, predicts a higher likelihood of lifelong insulin requirement. There is, however, an overlap of presence of antibodies in type 1 and type 2 diabetes, and among patients with type 2 diabetes who may not require insulin. 48

A Swedish population-based study showed that among the 9.3 percent of young adults with newly diagnosed diabetes that could not be classified as type 1 or type 2, the presence of glutamic acid decarboxylase antibody was associated with a need for insulin within three years (odds ratio = 18.8; 95% confidence interval, 1.8 to 191). 26 The PPV for insulin treatment was 92 percent in those with the antibody. It should be noted that among patients who were negative for antibodies, 51 percent also needed insulin within three years. In contrast, the United Kingdom Prospective Diabetes Study found that only 5.7 percent of patients without glutamic acid decarboxylase antibody eventually needed insulin therapy, giving the test an NPV of 94 percent. 25 With these conflicting data, clinical judgment using a patient's phenotype, history, presentation, and selective laboratory testing is the best way to manage patients with diabetes.

American Diabetes Association. Standards of medical care in diabetes–2010. Diabetes Care. 2010;33(suppl 1):S11-S61.

Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group [published correction appears in Lancet . 1999;354(9178):602]. Lancet. 1998;352(9131):837-853.

The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993;329(14):977-986.

Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359(15):1577-1589.

Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care. 1997;20(7):1183-1197.

Centers for Disease Control and Prevention. 2007 national diabetes fact sheet. http://www.cdc.gov/diabetes/pubs/factsheet07.htm. Accessed July 8, 2009.

Tuomi T. Type 1 and type 2 diabetes: what do they have in common?. Diabetes. 2005;54(suppl 2):S40-S45.

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(suppl 1):S62-S69.

Knowler WC, Barrett-Connor E, Fowler SE, et al.; for the Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393-403.

Tuomilehto J, Lindström J, Eriksson JG, et al.; for the Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001;344(18):1343-1350.

Tabaei BP, Herman WH. A multivariate logistic regression equation to screen for diabetes: development and validation. Diabetes Care. 2002;25(11):1999-2003.

Rohlfing CL, Wiedmeyer HM, Little RR, England JD, Tennill A, Goldstein DE. Defining the relationship between plasma glucose and HbA(1c): analysis of glucose profiles and HbA(1c) in the Diabetes Control and Complications Trial. Diabetes Care. 2002;25(2):275-278.

Heikes KE, Eddy DM, Arondekar B, Schlessinger L. Diabetes Risk Calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes. Diabetes Care. 2008;31(5):1040-1045.

Mochan E, Ebell M. Risk-assessment tools for detecting undiagnosed diabetes. Am Fam Physician. 2009;80(2):175-178.

Saudek CD, Herman WH, Sacks DB, Bergenstal RM, Edelman D, Davidson MB. A new look at screening and diagnosing diabetes mellitus. J Clin Endocrinol Metab. 2008;93(7):2447-2453.

Petersen PH, Jørgensen LG, Brandslund I, De Fine Olivarius N, Stahl M. Consequences of bias and imprecision in measurements of glucose and HbA1C for the diagnosis and prognosis of diabetes mellitus. Scand J Clin Lab Invest Suppl. 2005;240:51-60.

Ko GT, Chan JC, Woo J, et al. The reproducibility and usefulness of the oral glucose tolerance test in screening for diabetes and other cardiovascular risk factors. Ann Clin Biochem. 1998;35(pt 1):62-67.

International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care. 2009;32(7):1327-1334.

Little RR, Rohlfing CL, Wiedmeyer HM, Myers GL, Sacks DB, Goldstein DE for the NGSP Steering Committee. The National Glycohemoglobin Standardization Program: a five-year progress report. Clin Chem. 2001;47(11):1985-1992.

Berger B, Stenström G, Sundkvist G. Random C-peptide in the classification of diabetes. Scand J Clin Lab Invest. 2000;60(8):687-693.

Sacks DB, Bruns DE, Goldstein DE, Maclaren NK, McDonald JM, Parrott M. Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus. Clin Chem. 2002;48(3):436-472.

Sabbah E, Savola K, Kulmala P, et al. Diabetes-associated autoanti-bodies in relation to clinical characteristics and natural course in children with newly diagnosed type 1 diabetes. The Childhood Diabetes in Finland Study Group. J Clin Endocrinol Metab. 1999;84(5):1534-1539.

Tuomi T, Carlsson A, Li H, et al. Clinical and genetic characteristics of type 2 diabetes with and without GAD antibodies. Diabetes. 1999;48(1):150-157.

Turner R, Stratton I, Horton V, et al. UKPDS 25: autoantibodies to islet-cell cytoplasm and glutamic acid decarboxylase for prediction of insulin requirement in type 2 diabetes. UK Prospective Diabetes Study Group [published correction appears in Lancet . 1998;351(9099):376]. Lancet. 1997;350(9087):1288-1293.

Bottazzo GF, Bosi E, Cull CA, et al. IA-2 antibody prevalence and risk assessment of early insulin requirement in subjects presenting with type 2 diabetes (UKPDS 71) [published correction appears in Diabetologia . 2005;48(6):1240]. Diabetologia. 2005;48(4):703-708.

Törn C, Landin-Olsson M, Ostman J, et al. Glutamic acid decarboxylase antibodies (GADA) is the most important factor for prediction of insulin therapy within 3 years in young adult diabetic patients not classified as type 1 diabetes on clinical grounds. Diabetes Metab Res Rev. 2000;16(6):442-447.

Savola K, Bonifacio E, Sabbah E, et al. IA-2 antibodies—a sensitive marker of IDDM with clinical onset in childhood and adolescence. Childhood Diabetes in Finland Study Group. Diabetologia. 1998;41(4):424-429.

Avilés-Santa L, Maclaren N, Raskin P. The relationship between immune-mediated type 1 diabetes mellitus and ethnicity. J Diabetes Complications. 2004;18(1):1-9.

Davis TM, Wright AD, Mehta ZM, et al. Islet autoantibodies in clinically diagnosed type 2 diabetes: prevalence and relationship with metabolic control (UKPDS 70). Diabetologia. 2005;48(4):695-702.

Maclaren N, Lan M, Coutant R, et al. Only multiple autoantibodies to islet cells (ICA), insulin, GAD65, IA-2 and IA-2beta predict immune-mediated (type 1) diabetes in relatives. J Autoimmun. 1999;12(4):279-287.

Harris MI, Klein R, Welborn TA, Knuiman MW. Onset of NIDDM occurs at least 4–7 yr before clinical diagnosis. Diabetes Care. 1992;15(7):815-819.

American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for the management of diabetes mellitus. http://www.aace.com/pub/pdf/guidelines/DMGuidelines2007.pdf .Accessed July 8, 2009.

Feig DS, Palda VA, Lipscombe L. Screening for type 2 diabetes mellitus to prevent vascular complications: updated recommendations from the Canadian Task Force on Preventive Health Care. CMAJ. 2005;172(2):177-180.

U.S. Preventive Services Task Force. Screening for type 2 diabetes mellitus in adults. Recommendation statement. June 2008. http://www.ahrq.gov/clinic/uspstf08/type2/type2rs.htm#clinical . Accessed July 8, 2009.

Committee on Obstetric Practice. ACOG Committee Opinion No. 435: postpartum screening for abnormal glucose tolerance in women who had gestational diabetes mellitus. Obstet Gynecol. 2009;113(6):1419-1421.

American College of Obstetricians and Gynecologists Committee on Practice Bulletins—Obstetrics. ACOG practice bulletin. Clinical management guidelines for obstetrician-gynecologists. Number 30, September 2001 (replaces technical bulletin number 200, December 1994). Gestational diabetes. Obstet Gynecol. 2001;98(3):525-538.

Canadian Task Force on Preventive Health Care. Summary table of recommendations. Sreening for gestational diabetes mellitus. http://www.ctfphc.org/Tables/Ch02tab.htm . Accessed January 18, 2010.

U.S. Preventive Services Task Force. Screening for gestational diabetes mellitus. Recommendation statement. May 2008. http://www.ahrq.gov/clinic/uspstf08/gestdiab/gdrs.htm . Accessed January 18, 2010.

Diabetes Prevention Trial—Type 1 Diabetes Study Group. Effects of insulin in relatives of patients with type 1 diabetes mellitus. N Engl J Med. 2002;346:1685-1691.

Glucose tolerance and mortality: comparison of WHO American Diabetes Association diagnostic criteria. The DECODE study group. European Diabetes Epidemiology Group. Diabetes Epidemiology: Collaborative analysis Of Diagnostic criteria in Europe. Lancet. 1999;354(9179):617-621.

Gillies CL, Lambert PC, Abrams KR, et al. Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis. BMJ. 2008;336(7654):1180-1185.

Screening for type 2 diabetes mellitus in adults: U.S. Preventive Services Task Force recommendation statement [published correction appears in Ann Intern Med . 2008;149(2):147]. Ann Intern Med. 2008;148(11):846-854.

American Academy of Family Physicians. Recommendations for clinical preventive services. https://www.aafp.org/patient-care/clinical-recommendations/a-z.html . Accessed July 8, 2009.

Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, Robinson JS for the Australian Carbohydrate Intolerance Study in Pregnant Women (ACHOIS) Trial Group. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med. 2005;352(24):2477-2486.

Umpierrez GE, Murphy MB, Kitabchi AE. Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome. Diabetes Spectrum. 2002;15(1):28-36.

Kitabchi AE, Umpierrez GE, Murphy MB, et al. Management of hyperglycemic crises in patients with diabetes. Diabetes Care. 2001;24(1):131-153.

Umpierrez GE, Casals MM, Gebhart SP, Mixon PS, Clark WS, Phillips LS. Diabetic ketoacidosis in obese African-Americans. Diabetes. 1995;44(7):790-795.

Palmer JP, Hampe CS, Chiu H, Goel A, Brooks-Worrell BM. Is latent auto-immune diabetes in adults distinct from type 1 diabetes or just type 1 diabetes at an older age?. Diabetes. 2005;54(suppl 2):S62-S67.

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Type 1 diabetes mellitus: etiology, presentation, and management

Affiliation.

• 1 Division of Pediatric Endocrinology, University of Florida College of Medicine, PO Box 100296, Gainesville, FL 32610, USA.
• PMID: 16301083
• DOI: 10.1016/j.pcl.2005.07.006

This article reviews our current understanding of the etiology, presentation, and management of type 1 diabetes. The discussion includes a review of the natural history of diabetes, the complex relationship between genetic and environmental risk for type 1 diabetes, and current methods for prediction of type 1 diabetes. The article also reviews the current management of children who have new-onset type 1 diabetes, age-appropriate management goals, and diabetes complications. Finally, the article discusses the future of diabetes screening programs and the progress toward the ultimate goal of curing type 1 diabetes.

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Chapter 1 - Primer: Immunology and Autoimmunity Stephanie C. Eisenbarth and Dirk Homann

Updated 8/08, slides updated 8/07 Click to download Powerpoint slide set

Normal Immune Response In many respects, the modern age of immunology began with the independent descriptions by Talmage and Burnet in 1957 of the clonal selection theory (11). “The basic concept was of the immunologically competent cell; that is a cell which is susceptible to specific stimulation by contact with the appropriate antigenic determinant. The main possibilities of reaction are: (a) destruction, especially if physiologically immature; (b) proliferation without essential change of character – to what we would now call memory cells; and (c) proliferation and antibody production as a clone of plasma cells.” In 1957 the mechanism underlying the huge diversity (which is fundamental to the clonal selection theory) of immunological reactivity of single lymphocytes was unknown. It is now understood that B andT cells bear on their surface unique antigen receptors created by genetic recombinatorial processes. The receptor of B cells is the immunoglobulin molecule(antibody), which can recognize soluble protein antigens. For each B cell its antibody receptor has the same specificity as the antibodies that will eventually be secreted by the mature plasma cell, the final fate of the B cell. Antibody genes are created by a combinatorial process in which any of a family of multiple variable-region gene segments (V) combine with short joining (J) and diversity (D) gene segments and then with the constant-region gene segments of immunoglobulin. A similar process in T cells, results in the pairing of rearranged alpha and beta (or gamma and delta) chains and produces an estimated 107 -108 different TCRs (T cell receptors) in adult humans (12). A number of DNA cleavage and repair enzymes are responsible for VDJ recombination of both the immunoglobulin and T cell receptor genes, including recombination-activating genes (RAG-1 and RAG-2). These enzymes are essential in recombination and therefore lymphocyte development. Indeed in RAG deficient mice and patients with Omenn Syndrome, lymphocyte development does not occur resulting in severe immunodeficiency (13). Following gene rearrangement in B cells, heavy and light chains of immunoglobulin are joined resulting in billions of different antibodies/B cell receptors (differing by their amino acid sequence). Antibody genes (but not T cell receptor genes) also undergo somatic hypermutation once B cell development is complete- a process of V region gene mutation in the secondary lymphoid organs that increases the affinity with which antigens are recognized by clones of B lymphocytes (called “affinity maturation”).  Lastly, antibodies can also undergo class switching to modify and specify an immune response.  Class switching involves gene rearrangement in the constant Fc region of the antibody/B cell receptor, which switches the default mu locus (IgM) antibody isotype for either the alpha, gamma or epsilon loci (IgA, IgG or IgE, respectively).  The recently described enzyme, activation-induced deaminase (AID) is responsible for the last two important steps of antibody diversification (14), (15), however, how AID directs somatic hypermutation and class switching is an important area of ongoing research (16). Antigen Presenting Cells and MHC Exogenous antigens are taken into a cell by specific receptors (e.g., binding of antigen to surface immunoglobulin of B cells, immunoglobulin Fc receptor-mediated uptake of immune complexes) or non-antigen-specific mechanisms (e.g., endocytosis). Such antigens are then cleaved into peptides and coupled to class II MHC molecules for presentation on the cell surface of antigen presenting cells forrecognition by T cells (CD4-positive T cells). Endogenous antigens synthesized by the cell (e.g., self proteins or viral proteins), are cleaved by peptidases in a proteosome complex, transported into the endoplasmic reticulum by specific peptide transporters (TAP1& TAP2) (17), coupled to class I MHC molecules and then presented on the cell surface for recognition by T cells bearing CD8 accessory molecules.

An important difference exists in the way in which B and T cells recognize their cognate antigen. Whereas the B cell receptor can recognize whole proteins in solution, typical (alpha/beta) T cells respond only to peptide antigen bound to class I or class II molecules of the major histocompatibility complex (MHC) on antigen presenting cells (APCs). Although APCs (e.g. macrophages, B cells, and dendritic cells) play a role in clearance of pathogens and other particles, a crucial element of APCs is the ability to endocytose proteins, process these antigens into smaller peptides and then present peptides in the groove of MHC molecules.  MHC molecules were initially called “transplantation antigens” as they determine the ability of a donor to accept a transplanted graft. HLA/MHC molecules function by binding short peptides, usually 9-10 amino acids in length, and presenting these peptides to the T cell receptor. T cells expressing a T cell receptor complex that includes the co-receptor CD4 interact with class II molecules (DR, DP, and DQ of man, H2-A and H2-E of the mouse [see Table 1.2]). The CD8 co-receptor performs a similar function for T cells that interact with class I molecules (HLA A, B, and C of man; K and D molecules of the mouse). Figure 1.1 illustrates the uptake, cleavage, and presentation of an external antigen to a CD4-positive T cell.

HLAclass II genes are also calledimmune response genes; these molecules are highly polymorphic, differing between individuals in their amino acid sequence (18). Each different sequence is given a number for man and letters+/-numbers for mice.  For instance DQB1*0302 is a DR4 associated diabetogenic allele of man and I-A g7 an analogous diabetogenic allele of the NOD mouse.  Allelic HLA differences are inherited in a Mendelian fashion. The sequence differences determine which peptides can be bound and presented. Thus, such inherited differences in HLA molecules between individuals can determine which antigen an individual can respond to, and importantly, which autoimmune disorder they are likely to develop. As modeled above, the developing immune system has the potential to respond to essentially every foreign antigen, but also to every self-antigen.

T Cell Activation and the Innate Immune System In addition to the requirement of peptide presentation in the context of MHC molecules (“signal one”), a T cell requires an activation signal from the antigen-presenting cell (see Figure 1.2). This “second signal” can be provided by cell surface molecules CD80 or CD86 (B7.1 and B7.2, respectively). Additional B7 family members (such as B7.h) and other co-stimulatory molecules are also capable of providing this second signal (19). Thus, recognizing its cognate peptide in the groove of the MHC molecule is not enough to activate a naive T cell and therefore is also not enough to break tolerance to self-peptides. On the contrary, if a T cell recognizes its cognate peptide on the surface of an antigen-presenting cell (APC) without appropriate co-stimulation, tolerance or anergy is induced. The requirement for a second signal is a potent mechanism of preventing non-specific or self-specific T cell inflammatory reactions. However, this leads to the question of how the APC knows when to activate a T cell with a second signal in order to initiate an appropriateimmune response (20).  Work over the past ten years has started to answer this question. One T cell can recognize up to a million different peptides with its receptor (see section on “Target Antigens”) but it would obviously be disadvantageous for the immune system to activate a T cell in the absence of a real threat (e.g. infection) (21). This puzzle was recently solved with the discovery of pattern recognition receptors (PRR) and in particular, Toll-like receptors (TLRs) first in Drosophila and then in mammals(19). PRRs are considered a part of the Innate Immune system (as opposed to the Adaptive Immune System); Innate Immunity reacts faster to infections and is comprised of phagocytic cells, the complement system and a number of soluble inflammatory mediators such as antibacterial peptides and cytokines (see Table 1.3). PRRs are located on APCs, T cells (22) and some epithelium (23) and recognize highly conserved sequences within pathogen structures or PAMPs (pathogen-associated molecular patterns). For example, lipopolysaccharide (LPS), a cell wall component of Gram-negative bacteria, signals through TLR4. The eleven TLRs that have been identified provide for a broad spectrum of responsiveness to pathogens, including bacteria, viruses and fungi. Therefore, when an APC encounters an invading pathogen, it not only engulfs it for antigen presentation, but also is stimulated via PRRs to upregulate MHC and co-stimulatory molecule expression and to produce a host of pro-inflammatory cytokines (e.g., IL-1, IL-6 and IL-12) (24). The combination of these changes in the APC enables effective stimulation of naive T cells and is the link between the Innate and Adaptive Immune systems (see Figure 1.3)(25), (26).  Molecules such as LPS can be crucially important not only for induction classical Th1 mediated disease (e.g., anti-tuberculosis response), but depending upon the dose administered, Th2 disorders as well (e.g., asthma) (27).

LPS (Lipopolysaccharide); NOD (Nucleotide-binding and Oligomerization domain-containing) PGN (Peptidoglycan), DC (Dendritic Cell), LTA (Lipoteichoic Acid); LBP (LPS Binding Protein); Phagocytes (Monocytes, Macrophages & Neutrophils); MBP (Mannan-binding Protein) = MBL (Mannose-binding Lectin). The NALPs represent a large family of intracellular molecules related to NOD (nucleotide-binding oligomerisation domain molecules that are able to sense multiple Pathogen Associated Molecular Patterns that gain access to the intracellular compartment as well as signals of cell stress (e.g. extracellular ATP, uric acid) often resulting in the secretion of potent inflammatory molecules such as IL-1(28).  Mutations of these molecules result in a series of autoinflammatory diseases (28) but are implicated in multiple inflammatory responses (e.g. uric acid crystals and gout(29); silicosis (30), asbestosis (31) and even adaptive immune responses enhanced by the adjuvant Alum (32). For further readings on the information in Table 1.3 see (33-36). B Cell Activation Once an antigen-specific T cell has been appropriately activated, it in turn helps activate the humoral arm - the B cell. Helper CD4+ T cells initiate the majority of humoral responses, although there are a few exceptions with certain classes of pathogens, but we will focus on the former here. T cell help is initiated within the lymph nodes or spleen when an antigen-specific armed T cell recognizes its antigen peptide in MHC II on the surface of the B cell (whose Ig receptor recognized the same pathogen, internalized it and presented fragments of the pathogen on class II). This is termed Linked Recognition because it ensures that the T and B cells recognize the same pathogen although not necessarily the same epitope. Engagement of the TCR induces upregulation of CD40 Ligand on the surface of the T cell and the secretion of Bcell activators, such as IL-4, IL-5 and IL-6. The combination of these cytokines stimulates the B cell to proliferate, secrete antibody and, depending on the cytokines produced by the effector T cell, isotype switch from producing IgM to IgA, IgG or IgE antibodies. Therefore, this is another stage at which tolerance to self-peptides is censured or can be broken. If an autoreactive B cell does not encounter an activated T cell specific for the same self-protein, then no autoantibodies can be produced (unless the antigen is a large repeating molecule and T cell independent). This control step could be circumvented in autoimmunity, however, through the chance meeting of an armed T cell specific for a foreign peptide which recognizes a B cell that has phagocytosed and presented that T cell’s antigen on MHC, but has antibodies specific for a self antigen. Activation of that B cell would lead to the production of autoantibodies(see Table 1.4). Chemokines The immune system is a distributed network of organs, tissues, cells and extracellular factors. Functional integration of these components faces a particular challenge as the principal sentinels, regulators and effectors of immune function are often highly mobile single cells. The regulated spatio-temporal positioning of these cells is achieved by adhesion molecules such as integrins and selectins as well as chemo-attractant cytokines (chemokines) and their receptors that function as a “molecular address system” to regulate trafficking of specific cells into, out of and within defined anatomic microenvironments (37-41). Accordingly, chemokines have been implicated in a wide variety of pathological states including infectious disease, cancer, allergy, autoimmunity, and transplant rejection (42-47). The family of chemokines consists of a large number of structurally related and mainly secreted molecules that share a defining tetracysteine motif. According to a recent systematic classification (48), chemokines are divided into four distinct subfamilies based on the configuration of their aminoterminal cysteine residues (Table 1.4). CC chemokines (CCL1-28) harbor two adjacent cysteines whereas these residues are separated by a single, non-conserved amino acid among the CXC chemokines (CXCL1-16). The sole CX3C chemokine (CX3CL1) contains three amino acids between the corresponding cysteine residues and C chemokines (XCL1 and 2) lack one of the first two cysteines present in the other subfamilies. Overall, chemokines distinguished according to these structural criteria interact with specific members of corresponding chemokine receptor subgroups. Nevertheless, due to promiscuity among certain members of the CXC and CC subfamilies, some chemokines are capable of binding more then one chemokine receptor and vice versa. Furthermore, small alterations in the amino termini of many chemokines can lead to pronounced changes in bioactivity and are the basis for aspects of protease-mediated regulation of chemokine function (37;41). It should be noted that an older and complementary classification distinguishes inducible (inflammatory) and constitutive (homeostatic) chemokines. However, this distinction is not without problems since the constitutive expression patterns of many chemokines under conditions of immune homeostasis have not been precisely defined. Indeed, “constitutive chemokines” can be upregulated during inflammation while some “inducible chemokines” are apparently expressed in the absence of injury, infection or other inflammatory stimuli (37). The defining function of chemokines, demonstrated in numerous in vitro experiments, is their capacity to induce the directed migration of locomotive cells by establishing a spatial gradient. While the existence of comparable chemokine gradients in vivo remains a matter of debate, chemokines exhibit a host of additional functions including control of lymphopoiesis and lymphoid organogenesis, alterations of leukocyte adhesive properties by modulation of integrins as well as regulation of lymphocyte differentiation, proliferation, apoptosis, cytokine release and degranulation (40-42;49;50). Chemokines and Type 1 Diabetes Work conducted over the past decade has implicated as many as half of all known chemokines in the pathogenesis of T1D (51). Published observations range from correlative data obtained by molecular profiling of islet cells, or infiltrating T cells to successful therapeutic intervention by means of experimental chemokine/chemokine receptor blockade (Table 1.4). For example, early work by Bradley et al. has shown that pancreas-infiltrating CD4+T cells produce a wide range of chemokines including CCL2, CCL3, CCL4, CCL5, CCL7, CCL12, CXCL10 and XCL1 (52). and specified that a high CCL3:CCL4 ratio in the pancreata of NOD mice is associated with destructive insulitis while a lower CCL3:CCL4 ratio was observed in diabetes-resistant NOR mice (53). A possible pathogenic role for CCL17 and CCL22 was deduced from the CCR4+ phenotype of islet-infiltrating CD4+T cells as well as corresponding chemokine neutralization studies (54). More recently, the importance of CXCR3-binding chemokines CXCL9 and CXCL10 has been documented by the absence of T1D induction in CXCR3-/- mice or mice treated with a neutralizing antibody specific for CXCL10 (55;56). In addition, transgenic expression of CXCL10 in beta-cells, although not associated with spontaneous diabetes development, leads to accelerated virus-induced T1D onset (57), a process that may be amplified through CXCL10 production by islet-specific T cells. Nevertheless, CXCL10-blockade alone may not be sufficient under experimental conditions associated with enhanced inflammatory alterations (U. Christen, personal communication) and may thus require the therapeutic targeting of additional chemokines. For example, CCL5 is upregulated in the pancreata and islets of prediabetic mice(55;56) and neutralization of the CCL5 receptor CCR5 can reduce beta-cell destruction and T1D incidence (58). Taken together, the wide-ranging observations derived from experimental model systems and clinical studies emphasize the complex regulation of T1D pathogenesis by different chemokines and suggest a multiplicity of potential targets for prevention and amelioration of disease. Yet an integration of these observations into a coherent perspective on T1D pathogenesis has been hampered by the fact that the relevant cellular sources of these chemokines have for the most part not been identified. Furthermore, the majority of published chemokine expression analyses are limited to quantitation of chemokine transcripts and corresponding data on chemokine protein expression is often scarce. Consequently, proposed pathogenetic mechanisms are at times somewhat speculative and the precise contribution of individual chemokines as well as chemokines at large to T1D development remains at present incompletely defined.

Programmed Cell Death and Central Tolerance Because the immune effector mechanisms that have evolved are capable of rapidly killing cells, the potential for response to self is a consequence of having a potent immune system (analogous to having firearms in a house to protect oneself from burglars - weapons that may nevertheless accidentally kill family members). As stated by Burnet, “Autoimmune disease can be defined as a condition in which structural or functional damage is produced by the reaction of immunocytes or antibodies with normal components of the body . . . the central theme is the emergence of ‘forbidden clones’ of pathogenic immunocytes and the various ways by which these can arise and find ways of escaping the normal controls”. Such a pathogenic mechanism underlies the disease of mice with mutations or knockouts of the AIRE (Autoimmune Regulator) gene (see below). At a functional level, the breaking of “tolerance” is fundamental to concepts of autoimmunity. The first and perhaps most vital stage of tolerance induction to self-antigens occurs in the thymus during T cell development. It was previously believed, that certain peripheral tissue-restricted proteins or certain proteins that are exclusively expressed only after a particular developmental stage could not be expressed in the thymus. Self-reactive T cells are deleted in the thymus by reacting strongly to self-antigens presented by thymic APCs. Therefore, if certain antigens could not be expressed in the thymus, the process of selection would be “blind” to such self-reactive T cell clones, which could therefore escape negative selection. These clones would then have to be controlled or deactivated in the periphery (see next section). However, the thymus and other lymphoid organs actually contain “self-antigen-presenting cells” (59). For example, insulin message and protein are present in the thymus, lymph node, and spleen. Functional studies suggest that minute quantities of such self-antigens are important for the maintenance of central tolerance (60). More recent work has identified a gene responsible for this ectopic expression of self-antigens in the thymus - AIRE or Autoimmune Regulatory gene (59). Mutations of the AIRE gene on chromosome 21 in fact cause APS-I (Autoimmune Polyendocrine Syndrome), which presents with a spectrum of autoimmune diseases such as Addison’s disease, hypoparathyroidism, mucocutaneous candidiasis, hepatitis, and type 1 diabetes (61;62). Anderson and colleagues went on to show that many of the target self-antigens in APS-1 are not expressed in the thymus of mice lacking AIRE. It is likely that the AIRE gene has a number of different effects on central tolerance in addition to influence on expression of “peripheral” antigens in the thymus.  These important discoveries emphasize the critical role central tolerance plays in preventing autoimmune disease by removing potentially self-reactive lymphocytes from the T cell repertoire (63). Peripheral Tolerance and Regulatory T Cells In addition to the concept of “forbidden” clones arising because of mutations that bypass normal regulatory events, it has become clear that, given the appropriate context of antigen presentation, autoimmune responses can be generated to essentially all proteins. For example, subcutaneous injection of human insulin (the current therapy for type 1A diabetes) almost invariably leads to low levels of anti-insulin autoantibodies. For most destructive autoimmune disorders, a characteristic group of autoantibodies arise (see Table 1.5). These antibodies frequently react with a series of molecules derived from the same subcellular localization. For lupus erythematous, it is the ribonucleoprotein complex; for type 1 diabetes, insulin secretory granules and islet synaptic-like microvesicles. This suggests that once tissue destruction commences, in the context of an inflammatory lesion (e.g., insulitis), tolerance is broken to a series of autoantigens. This highlights the importance of another form of tolerance that controls the expansion of autoreactive lymphocytes after T cell development and selection are concluded - peripheral tolerance.

Whereas central tolerance occurs in the thymus during T cell development, peripheral tolerance occurs in secondary lymphoid organs (e.g., lymph nodes and spleen) after T cell development is concluded. This form of tolerance regulates the activation of naïve T cells via two mechanisms: anergy and regulatory T cells. Anergy involves the clonal inactivation of T cells with the potential to respond to self-antigens, resulting in cells that are resistant to activation upon antigen encounter. The second form of immune regulation can occur by T regulatory cells (Tregs). This is an emerging field within immunology and many different types of Tregs have been described with only a few over-arching principles (see Table 1.6). In general, “natural Tregs” can be identified by the surface expression of CD25 (the IL-2 receptor), CTLA-4, GITR, CD62L and OX40(64) and lack of the IL7(CD127 receptor)(36) and intracellular expression of FoxP3. Foxp3, unlike these other markers, is primarily (?exlusively for mouse) found in regulatory T cells and is required fort the development of CD25+ Tregs in the thymus (65), but for human T cells can also be acquired. Scurfy mice lack a functional Foxp3, which results in a deficiency of the protein scurfin. These mice succumb to a lethal autoimmune syndrome that mimics the IPEX (immune dysregulation, polyendocrinopathy, enteropathy, X-linked) syndrome in man (also termed XPID syndrome). In the human disease infants die of overwhelming autoimmunity and can have neonatal diabetes. Autoimmunity in both man and the murine model results from a deficiency in CD4+CD25+ regulatory T cells. Studies using the scurfy mice have identified IL-10 as one mechanism by which Foxp3+ Tregs may control wasting diseases such as IBD (Inflammatory Bowel Disease). How they limit aberrant T cell proliferation is not yet clear. Interestingly, during normal immune responses to pathogens, Tregs may be held in check by the triggering of pattern recognition receptors on APCs, resulting in the production of IL-6 and possibly other molecules capable of inhibiting suppressor T cell activity (66). Much work is currently underway to elucidate the development and effector mechanisms utilized by Tregs and these studies should shed light on important pathways used by the immune system to regulate itself and prevent autoimmunity. Indoleamine 2,3-dioxygenase (IDO) has been a recent focus of numerous studies due to its role in the suppression of T cell responses. IDO is an enzyme that degrades tryptophan possibly resulting in either T cell depletion of an essential amino acid or the production of downstream metabolites that enhance APC suppressor function.  IDO has been implicated as a negative regulator of autoimmune disease in animal models such as systemic lupus erythematosus, multiple sclerosis and diabetes mellitus (67). In addition, this enzyme may be one mechanism used by Tregs to exert their suppressor effects. The suppressive cytokine TGFbeta, is also used by Tregs to inhibit peripheral T cells. In fact creation of a transgenic mouse with a T cell receptor that recognizes an islet insulin peptide (insulin B:9-23) suppresses type 1 diabetes of the NOD mouse led to T cells of the transgenic that suppress diabetes through a TGFbeta depedent mechanism via T cell production of TGFbeta which acted in both an autocrine and paracrine manner (40).  T cell receptors from a clone recognizing the same peptide, but which were pathogenic, when used to produce transgenic mice resulted in diabetes (41). Thus for these T cell receptors it appears their phenotype in terms of pathogenicity is determined by the receptor sequence with fidelity when transgenic mice are created.

The Genetics of Autoimmunity The general concept that autoimmunity develops in the setting of genetic susceptibility, and in particular in association with a series of specific HLA alleles, applies to most human autoimmune disorders. It is important to note, however, that the same HLA allele may protect from one and yet be associated with another disorder (e.g., the HLA DR2 associated DQ allele, DQA1*0102, DQB1*0602 is rare in patients with type 1 diabetes but is associated with multiple sclerosis (70;71)). It appears that susceptibility encoded by alleles within the HLA region do not globally influence the development of autoimmunity but rather influence the likelihood of specific disorders. An alternative manner by which HLA alleles may determine susceptibility to autoimmune disease is by altering the developing T cell repertoire. This may be particularly important for diseases associated with what have been termed “superantigens” such as Kawasaki’s disease. Superantigens are molecules that bind outside of the peptide binding “groove” of class I and class II molecules and trigger whole families of T cells by binding to common sequences of T cell receptors (bearing specific Vbeta chains). Superantigens thereby activate large numbers of T cells (more than a usual antigen which interacts only with clones of T cells with a specific complementary binding site).  Thus, for T cell responses to superantigens, it is predicted that responding cells will bear T cell receptors of whole families (e.g. Vbeta8.2), but the T cell receptor antigen-binding region (“complementarity determining region”) will differ in amino acid sequence. Recent experiments with transgenic mice have provided convincing evidence that the predilection of T cells for self-antigens is due to the way the T cell receptor repertoire is derived. Developing thymocytes express a multitude of T cell receptors, and only the infrequent thymocyte that expresses a receptor with low affinity for MHC antigens presented in the thymus matures further; the selection signal is supplied via engagement of the T cell receptor complex. This selection on self-MHC with self peptides (termed positive selection) is potentially dangerous in that T cells with an autoreactive nature can be selected. However, those developing autoreactive thymocytes with a very strong affinity for self MHC transduce a signal via their T cell receptor that leads to cell death rather than further differentiation, termed negative selection. The MHC repertoire seems to play an important role in this process of TCR selection. For example, Santamaria and coworkers have produced a transgenic mouse with a T cell receptor that targets islets and causes diabetes. However, multiple class II alleles, when crossed onto this transgenic mouse background, delete the autoreactive T cells and prevent disease (72;73). In autoimmune diseases studied to date, concordance of identical twins is usually between 30% to 70%(74;75). Concordance of non-identical twins is often in the range of 5% and similar to the risk of siblings. Furthermore, data strongly suggests that alleles of genes outside the major histocompatibility complex contribute to disease susceptibility, in that monozygotic twins have a higher disease concordance for many autoimmune disorders (e.g., multiple sclerosis and type 1 diabetes) than HLA (MHC) identical siblings. For type 1 diabetes however, extreme risk can be identified for siblings who have the highest risk HLA DR/DQ genotype (DR3/4;DQ2/DQ8) and have inherited both HLA haplotypes identical by descent with their proband sibling. A risk as high as 80% for activating islet autoimmunity can be identified(76) with diabetes following several years after the appearance of islet autoantibodies.  Alleles of a number of genes influencing multiple autoimmune disorders are now well established including PTPN22, CTLA-4, IL2 receptor.  A single amino acid change to PTPN22 (R620W) that codes for a lymphocyte specific phosphatase, results in increased suppression of T cell receptor signaling, and is associated with diabetes, rheumatoid arthritis, Graves’ disease and other autoimmune disorders (77;78).  In animal models, a number of alleles influencing disease susceptibility have been defined (79). In humans, for example, autoimmunity is associated with complement deficiency in the case of lupus erythematosus (80), with alleles of insulin in type 1 diabetes (81;82) and nucleoside phosphorylase deficiency in hemolytic anemia. It is likely that complement deficiencies contribute to autoimmunity by altering processing of antigen-antibody complexes and/or activation of Fc receptors. Insulin gene polymorphisms influence insulin synthesis in the thymus and therefore may influence “tolerance” to insulin (83). T cells are particularly sensitive to nucleotide metabolites and it is thought that nucleoside phosphorylase deficiency may be associated with autoimmunity secondary to T cell toxicity in hemolytic anemia. The genes underlying two remarkable syndromes of autoimmunity APS-I (Autoimmune Polyendocrine Syndrome Type 1) and XPID (X-linked Polyendocrinopathy, Immune dysregulation and Diarrhea) are now cloned. For both syndromes mutations of transcription factors lead to multiple autoimmune disorders including type 1 diabetes (see section on “Programmed Cell Death and Tolerance”). With refined techniques for genetic mapping and the knowledge provided by the genome project it is likely that in the next decade progress will be made in the definition of alleles underlying genetic susceptibility for common autoimmune disorders. However, even as genes causing autoimmunity are discovered their mechanism of action will not be immediately clear. Triggering of Autoimmunity A large group of experimental autoimmune disorders can be induced by immunization with self-proteins. To induce disease, and even to generate an immune response, such molecules are usually injected in a depot form with adjuvants that activate antigen-presenting cells.

For example, a model of multiple sclerosis follows immunization with myelin basic protein (84). There are conceptually similar models for experimental autoimmune thyroiditis (immunization with thyroglobulin), experimental myocarditis (immunization with myosin peptides), and experimental autoimmune oophoritis (immunization with the oocyte sperm cell receptor) (85). Once disease is induced in these animal models, T cell clones reacting with immunizing antigens are sufficient to transfer disease. In that disease can be induced by simple immunization with self-molecules, it is clear that T cells and B cells reactive to self exist in normal animals. Thus, the context of immunization determines whether pathogenic clones are expanded.  Recent crystal structure analysis of MHC with a bound autoantigen also suggests that the TCR may bind in an unusal configuration in autoimmune disease in which only part of the autoantignen is actually recognized (see Figure 1.4) (58). In part, the ease of inducing autoimmunity raises the question as to what mechanismspreventexpansion of autoimmune clones.

In animal models, both genetic (e.g., T cell immunodeficiency gene on chromosome 4 of the BB rat) and environmental manipulations of the immune system (neonatal thymectomy, injection of anti-RT6 antibodies in nonlymphopenic BB rats, and neonatal therapy with cyclosporine A or injection of poly-IC into RT1-U rats) lead to autoimmunity (86). It appears that neonatal thymectomy induces autoimmunity by decreasing a specific subset of “regulatory” T lymphocytes (see “Programmed Cell Death & Tolerance” section) (87). Table 1.7 presents an “etiologic” classification of human autoimmunity based upon identified triggering factors. Infectious agents (88), neoplasms, and drugs have all been found to induce specific autoimmune diseases. Tumors that induce autoimmunity are characterized by the expression of specific autoantigens. One of the best-characterized oncogenic autoimmune syndromes results in cerebellar degeneration. Oncogenic cerebellar degeneration is associated with specific anti-Purkinje cell antibodies. It is induced by ovarian carcinomas expressing what have been termed CDR (cerebellar degeneration related) antigens (89). Additional oncogenic autoimmune disorders include pemphigus associated with lymphoma, myasthenia gravis and pure red cell aplasia associated with thymomas, and retinopathy associated with small-cell carcinoma. It is thought that, similar to the induced autoimmune disorders of animals described above, presentation to the immune system by tumor cells of self-peptides induces “remote” autoimmunity. The drug penicillamine (dimethylcysteine) is associated with a large number of different autoimmune disorders, including myasthenia gravis, bullous pemphigoid, lupus erythematosus, polymyositis, and dermatomyositis. In addition to overt disease, penicillamine induces antibodies such as anti-insulin autoantibodies in the absence of overt pathology. It is hypothesized that penicillamine may induce autoimmunity by haptenation of multiple proteins. One of the best examples of autoimmunity induced by food antigens is celiac disease, or gluten sensitive enteropathy (90). Celiac disease is characterized by marked lymphocytic infiltrates of the small bowel associated with villous atrophy. Ingestion of the wheat protein gliadin leads to the production of anti-transglutaminase autoantibodies and destruction of the villi. The disease is “cured” by elimination of wheat gluten from the diet. Like most autoimmune disorders, celiac disease occurs only in the presence of specific HLA alleles; in particular, with DQ alpha and beta sequences (DQA1*0501 and DQB1*0201) which occur in individuals with either a DR5 (DQA1*0501) and DR7 (DQB1*0201) HLA haplotypes in trans or in individuals with DR3 haplotypes (DQA1*0501/DQB*0201). There is now considerable evidence that the enzyme transglutaminase that is a very important target of autoimmunity in celiac disease acts on gliadin peptides to deamidate glutamine residues and this is “essential” for the generation of pathogenic peptides stimulating T cell responses (91).  It is also hypothesized that gliadin peptides may form covalent bonds with transglutaminase, thus acting as a hapten for immune activation. Autoimmunity associated with mononucleosis is related to the unique ability of the virus to directly infect B cells (92). The Epstein-Barr virus (EBV) stimulates B cell proliferation and polyclonal antibody production. These polyclonal antibodies reacting with self -antigens can lead to disease. The proliferation of B cells is self-limited in the presence of an effective T cell response. Although pathogens may trigger autoimmune processes, infections can also suppress autoimmunity. For example, multiple viral infections in NOD mice prevent diabetes, as does a single injection of complete Freund’s adjuvant. Therefore the nature and timing of infection is likely to be critical in the triggering of autoimmune processes. Target Antigens The antibody and T cell responses characteristic of autoimmune disorders appear to be “antigen-driven.” The amino acid sequences of autoantibodies are mutated relative to immunoglobulin germ-line sequences and autoantibodies are usually of high affinity. In addition, the large number of different autoantibodies to different autoantigens for even a single autoimmune disease suggests that whatever the initial lesion leading to autoimmunity, the immune response “spreads” to a series of antigenic epitopes and molecules of the involved tissue. For example, large families of antibodies react with islet autoantigens during the beta cell destruction associated with type 1 diabetes. To date, these autoantibodies target molecules within two islet secretory organelles: insulin secretory granules (e.g., insulin, proinsulin, ICA512 (IA-2), ZnT8, carboxypeptidase H, GM2-1 ganglioside) and synaptic-like microvesicles where gamma amino butyric acid (GABA) is stored (e.g. glutamic acid decarboxylase). The detection of a family of autoantibodies for each autoimmune disease complicates the elucidation of which autoantigen (if any) is central to disease pathogenesis. In the past, the major criteria for defining such autoantigens rested primarily on the ability to immunize with the given antigen and create disease. This is probably an inadequate criterion to define pathogenic autoantigens of spontaneous autoimmune disorders of man and animal models. It is known that for many tissues, immunization with several different autoantigens can induce disease (e.g., myelin basic protein and proteolipid protein for experimental autoimmune encephalitis). With the development of molecular genetic techniques, more definitive tests of an antigen’s disease relevance are now possible. For example, genes for specific autoantigens can be introduced into ectopic tissues by creating transgenic mice with the gene coding for the autoantigen coupled to a promoter directing ectopic expression. If, for example, destruction of the ectopic tissue is induced, the single autoantigen is sufficient to target autoimmunity. In a similar manner, induction of thymic expression of an autoantigen may be sufficient to induce tolerance to the antigen (see section on “Central Tolerance”). If all autoimmunity is blocked in such transgenic mice, then the given autoantigen is essential for disease pathogenesis. Introduction of autoantigen synthesis by transplanted tissues (e.g., adenovirus gene transfer systems) may allow a series of autoantigens to be rapidly tested to determine whether they are “sufficient” for tissue destruction. Just as important, gene knockouts can be used to directly test the relevance of specific antigens. Baekkeskov and coworkers have found that NOD mice lacking GAD65 develop diabetes. Thus, GAD65 is not essential, though GAD67 may play a role. Of note a knockout of the insulin 2 gene accelerates and a knockout of insulin 1 gene prevents most diabetes of the NOD mouse (93) while knocking out both insulin genes, and replacing insulin with a mutated insulin in the key insulin B chain 9-23 sequence, prevents almost all anti-islet autoimmunity (68). Autoantibodies usually react with conformational epitopes of their target antigen, and for many autoimmune disorders autoantibodies to multiple different epitopes of even single antigens are targets. In contrast, T lymphocytes target relatively short peptides (8-12 amino acids in length). Peptides that have only one or two similar amino acids have been shown to activate the same T cell receptor. Thus there is enormous potential for a given T cell receptor to react with peptides from multiple different molecules and some of these molecules will have no “obvious” sequence homology (21).  This suggests that many molecules may be “molecular mimics” (peptide mimotopes) and may be one mechanism of initiation autoimmune responses. In that most individuals do not have autoimmune disease, the immune system usually deletes or appropriately regulates autoreactive T cells. Effector Mechanisms In most immune disorders, both humoral and cellular arms of the immune system contribute to disease pathogenesis. Autoantibody-mediated disorders include autoimmune hemolytic anemia, immune-mediated thrombocytopenia (ITP), myasthenia gravis, Lambert-Eaton myasthenic syndrome, pemphigus, and Graves’ disease. For each of these disorders, if the mother has autoantibodies, a transient neonatal disease may follow transplacental passage of antibodies.  Autoantibodies can induce pathology by blocking the function of specific receptors (e.g., hypothyroidism (94) or “geriatric” hypoparathyroidism (95)), by stimulating receptors (Grave’s disease, hypoglycemia associated with anti-insulin receptor autoantibodies), by direct cytotoxicity (hemolytic anemia), by opsonizing cells (hemolytic anemia and ITP), or by deposition of immune complexes (lupus nephritis).  There is also evidence that autoantibodies and B lymphocytes can enhance T cell mediated disorders and thus anti-B lymphocyte therapties (e.g. anti-CD20) are being studied or used in a series of presumably T cell mediated disorders (72). Cell-mediated immunity is usually associated with tissue destruction (e.g., type 1 diabetes or thyroiditis) either through direct cellular cytotoxicity or by indirect cytotoxic mechanisms (e.g., delayed-type hypersensitivity). The classic pathway of allogeneic tissue rejection is mediated by direct recognition of antigenic peptides complexed with MHC class I molecules by CD8-positive cytotoxic T cells; killing by cytotoxic T cells involves direct cellular contact between T cells and the target cell. The function and expansion of clones of such cytotoxic T cells are dependent upon “help” provided by CD4-positive T cells that respond to antigenic stimulation by releasing a series of lymphokines, including IL-2 . CD4-positive T cells have been subdivided based on the cytokines they produce (96) into multiple groups of “helper cells”: Th0, Th1, and Th2 and Th17. Th0 cells constitute a small subset of cells in the thymus postulated to react to autoantigens resulting in the production of IL-2 but also low levels of interferon gamma (IFN-g). Th1 cells mediate delayed type hypersensitivity reactions and produce IL-2 and IFN-gamma. Th2 cells produce IL-4, IL-5 and IL-13 and are associated with allergic diseases. Th17 cells secrete IL17 and are strongly associated with multiple autoimmune and inflammatory diseases(10). An additional mechanism of cell-mediated destruction of target cells involves indirect cytotoxicity mediated by CD4-positive (Th1) lymphocytes. Such CD4-positive lymphocytes, following recognition of their target antigen presented in the context of a class II MHC molecule, secrete a group of cytokines (e.g., interferon gamma), which in turn activates cells such as macrophages to release IL-1, nitric oxide, and free radicals. Each of these molecules can directly kill selected target tissues (97). This second mechanism may be primarily responsible for the autoimmune beta cell destruction of type 1 diabetes and for destruction of xenogeneic tissue transplants. For example, islet specific CD4-positive clones (as will be discussed in later chapters) are sufficient to transfer diabetes (98). Therapy of Autoimmunity A series of novel therapies for the prevention and treatment of autoimmunity are being studied. One can broadly divide these into therapies which are antigen-specific and those which are antigen-nonspecific. Examples of antigen-specific therapies include prevention of diabetes in NOD mice by parenteral or oral administration of insulin (99;100), MHC-binding peptide therapies for prevention of experimental autoimmune encephalitis (101) and T cell or peptide vaccination strategies (102). Another form of antigen-specific therapy includes the removal of a disease-inciting antigen (if it is identified). For example, celiac disease is successfully treated by the removal of the wheat protein gliadin from the diet. Studies of the effects of eliminating bovine milk products in neonates are underway for infants at high genetic risk of type 1 diabetes, though recent epidemiologic studies have implicated early introduction of cereals to infants may also increase the risk of developing autoimmune diabetes (103;104). For endocrine glands it is possible to suppress cellular activity through feedback inhibitory circuits (e.g., administration of thyroxine or insulin inhibits thyroid or beta cells, respectively). Therapy with insulin not only prevents development of diabetes in BB rats and NOD mice (105), but also prevents lymphocytic infiltrates into the islets and beta cell destruction. Protection by insulin in the BB rat requires metabolically active insulin and induction of hypoglycemia with concomitant inhibition of insulin secretion by beta cells. In contrast, non-metabolically active peptides of insulin prevent diabetes in NOD mice. A single report suggests that glucocorticoid therapy in patients with anti-adrenal autoantibodies leads to loss of autoantibodies and prevention of Addison’s disease (106). Antigen nonspecific therapies include drugs such as rapamycin, cyclosporine A, glucocorticoids, some anti-T cell monoclonal antibodies, IL-2-diptheria toxin conjugates (107;108), and FK506 (tacrolimus). A recent trial of a single course of anti-IL2 receptor antibody followed by chronic mycophenolate mofetil therapy failed to slow loss of C-peptide secretion in patients with new onset diabetes (ADA 2008 oral presentation Trialnet).  This suggests that potentially acceptable “moderate” broad immunosuppression will not be sufficient in type 1 diabetes.  The disadvantage of non-antigen specific therapies is the likely suppression of important immune functions with increased risk of infection and malignancy. In addition, non-selective drugs have unique toxicity unrelated to immunosuppression, such as osteoporosis and diabetes with glucocorticoids and renal toxicity, which is associated with cyclosporine A. Nevertheless, it is clear that potent immunosuppressive drugs such as cyclosporine A, which act by blocking cytokine production by T cells, can prevent certain forms of autoimmunity. When it is possible to use such drugs at low doses with marked therapeutic effect (e.g., cyclosporine A for psoriasis), they become important therapeutic agents. It is also hoped that certain strategies of short-term immunosuppression may lead to a state of long-term tolerance, thereby minimizing the deleterious effects of immunosuppression. For example, treatment with specific monoclonal antibodies directed against the T cell co-receptor CD4 can lead to long-term engraftment of both heart and islet transplants; non-activating anti-CD3 antibodies can cause long-term remission of diabetes in NOD mice and multiple studies now document preservation of islet beta cell function in man for approximately 2 years (109;110). Another proposed antigen-specific therapy of autoimmunity involves immune deviation, which is thought to induce tolerance following oral administration of antigen. It is hypothesized that the feeding of autoantigens induces T cell production of suppressive cytokines such as TGF-beta upon subsequent encounters with antigen (111). Studies on the mechanism underlying oral tolerance are most advanced for experimental autoimmune encephalitis, where in vivo antibodies to TGF-beta block induction of ‘oral tolerance’ (112). For the most part however, studies of oral tolerance in man have failed to achieve clinical benefit. The trimolecular complex (MHC molecule, peptide antigen, and T cell receptor) underlying the specificity of T cell responses is an obvious target for therapy of autoimmunity. In experimental disorders with a very limited T cell receptor response, such as experimental autoimmune encephalitis (almost exclusive use of T cells bearing Vbeta8.2 T cell receptor chain), targeting of a specific family of T cell receptors is efficacious in preventing disease. Another approach being pursued is the production of peptides that bind to MHC alleles associated with disease. For example, a peptide binding to a high-risk allele for type 1 diabetes, DQA1*0301/DQB1*0302, might prevent diabetes by preventing the binding of “diabetogenic” peptides. One of the most exciting pathways for the prevention of autoimmunity in animal models goes under the rubric of “immunologic vaccination.” It has been found that a series of spontaneous and experimental autoimmune disorders can be prevented by administering target autoantigens or peptides of given autoantigens. A single injection of the insulin B chain peptide, amino acids B:9-23, can prevent type 1 diabetes for the life of an NOD mouse (113). Multiple routes of antigen administration have been used successfully to prevent disease in animal models including subcutaneous injection with or without adjuvant, oral or nasal mucosal administration and administration of DNA constructs coding for the autoantigen. Direct production and infusion of regulatory T cells targeting islet antigens has shown promise in animal models (114). Unfortunately “ Immunologic vaccination” for type 1 diabetes to date has not been effective. For example an altered peptide ligand of insulin peptide B:9-23 in new onset patients failed to slow loss of C-peptide. In addition there is a risk that the peptide will actually exacerbate disease. Large trials of oral insulin and low dose parenteral insulin injections did not delay progression to diabetes overall (115),although the majority of patients in the oral insulin trial who expressed insulin autoantibodies above 80nU/ml (initial trial entry criteria) did have a significant delay in the development of diabetes.  This significant effect (delay of several years in progression) requires confirmation as it is a “subgroup” analysis (93) and a repeat Trialnet study of oral insulin is underway.  Development of improved assays to measure T cell function and autoreactive T cell frequencies will be important in improving the risk benefit ratio for such therapies. Two general assay formats, namely ELISPOT assays (116) and “tetramer” (also termed “multimer”) (117) assays have already greatly impacted studies of T cell responses to infections and are likely to be important for autoimmunity. The ELISPOT assays rely upon culturing lymphocytes and then detecting individual cells and the cytokines they produce. One form of tetramer assay utilizes avidin to couple together four biotin labeled MHC molecules containing a relevant peptide. By having four MHC molecules the affinity for reaction with the receptors of T cells is greatly increased. Such molecular complexes are labeled with fluorescent dyes and are able to bind to the T cell receptors specific for the restricting MHC element and the peptide. Using tetramers and a fluorescent cell sorter, autoreactive T lymphocytes can be identified. It would be a major advance if one could rapidly evaluate therapies for autoimmune disorders in terms of effects upon the pathogenic autoimmune T cells with ELISPOT and/or tetramer analysis (118).

Conclusion Autoimmunity is a result of the failure of a number of immunological processes, from genetically associated HLA risk factors to environmentally derived signals that may overcome tolerance and regulatory control mechanisms. Dissecting the numerous components leading to overt disease is necessary before effective and specific therapies can be developed. Many recent advances, such as the discovery of Toll-like receptors, and the “re-discovery” of regulatory T cells, will greatly aid in our understanding and therefore in our ability to treat the underlying causes of autoimmune disorders.

For comments, corrections or to contribute teaching slides, please contact Dr. Eisenbarth at: [email protected]

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• v.31(3); May-Jun 2011

Pattern of presentation in type 1 diabetic patients at the diabetes center of a university hospital

Abdulaziz m. al rashed.

From the Department of Pediatrics, King Abdulaziz University Hospital, College of Medicine, King Saud University, Riyadh, Saudi Arabia

BACKGROUND AND OBJECTIVES:

Diabetes mellitus (DM) is a major health problem worldwide. This study aimed to investigate the pattern of presentation and complications of pediatric diabetes.

DESIGN AND SETTING:

Retrospective study of children treated at a diabetes clinic at a university hospitalfor diabetes over 12-year period.

PATIENTS AND METHODS:

We collected data on the age at onset, sex, clinical presentation, duration of symptoms before diagnosis, and partial remission rate that were obtained from the hospital medical records, the National Diabetes Registry, and the statistics department.

Of 369 diabetic children, most (n=321) children had polyuria (92%) 321/369=87% as the presenting symptom; other symptoms included polydipsia (310 patients, 88.8% 310/369=84%), weight loss (292 patients, 83.9%), nocturia (240 patients, 68.8% 240/369=65%), diabetic ketoacidosis (DKA) (174 patients, 49.9% 174/369=47.20%), and abdominal pain (172 patients, 49.3% 174/369=46.6%). Presenting symptoms were missing in 20 files, so the percentages were calculated among 349 patients. Most patients had acute diabetic complications such as hypoglycemia (222 patients, 62%) and DKA (88 patients, 38.1%, but none had severe complications such as coma and cerebral edema. Chronic complications included retinopathy (4 patients, 1.3%), neuropathy (2 patients, 0.6%), coronary heart disease (2 patients, 0.6%), and nephropathy (1 patient, 0.4%).

CONCLUSION:

The pattern of presentation of type 1 diabetes has changed as the incidence of DKA has decreased; unlike in previous studies, DKA was not the most common presenting symptom in this study. Chronic complications of diabetes, such as retinopathy, neuropathy, coronary heart disease, and nephropathy are mostly rare but still present. These complications might be prevented by achieving better awareness of the need for glycemic control.

Diabetes mellitus (DM) is a major health problem worldwide. Current studies have revealed a definite global increase in the incidence and prevalence of diabetes, with the World Health Organization (WHO) projecting that there will be almost 221 million cases in the year 2010 and up to 285 million cases in the year 2025. 1 It is the fourth or fifth leading cause of death in most developed countries. 1 , 2 Although this increase is mainly expected in type 2 diabetes, a parallel increase in childhood diabetes, including type 1 and 2 diabetes, has been reported. 3 DM in children has previously been considered rare in African and Asian populations. 4 – 8 The WHO Diabetes Mondiale (WHO DIAMOND) project group has reported a worldwide increase in the incidence and variation (over 400-fold) of type 1 diabetes, with the highest occurring in Finland (over 45 per 100 000 children under the age of 15 years) and the lowest in parts of China and Fiji. 9

DM in children in Saudi Arabia has not been studied well and further studies are needed. 10 Little local information on the disease is available, and most cases reported have been of type 2 DM. 11 The epidemiology and characteristics of DM, particularly insulin-dependent DM, are not known in the Saudi community, and only a small amount of data is available. 11 Moreover, the data confirm the need to develop a national registry and the need for further epidemiological research. 12 Furthermore, adolescents are not examined in pediatric clinics, and they do not receive adequate attention in adult clinics. 13

Saudi Arabia is a unique country among developing nations in view of its excellent economic status and relatively low literacy rate, particularly among mothers, in addition to the cultural and religious background, which might influence the management of diabetes. 14 The presentation of type 1 diabetes in Saudi children seems to differ from that in children from Western countries. 15 The most common clinical sign is diabetic ketoacidosis (DKA), which is observed in 67.2% of the patients. 11 DKA is the most serious presenting symptom of type 1 DM. The frequency and severity of DKA at presentation vary significantly worldwide. 16 In Saudi Arabia, studies have revealed that DKA is present in 55% to 77% of the DM cases. 15 , 17 Ketoacidosis is the most common presenting symptom of childhood DM in this region. 18

This study presents some of the epidemiological and clinical features and complications of childhood DM as recorded in the Diabetes Center at King Abdulaziz University Hospital, Riyadh, Saudi Arabia. The Diabetes Center receives patients from Riyadh District and suburban areas; in addition, it is a tertiary care center that receives referred patients from different cities in the country. The objective of this study was to investigate the pattern of presentation of pediatric diabetes in patients enrolled in the diabetes center of a university hospital and to review the complications of diabetes in the study group.

PATIENTS AND METHODS

All diabetic children who were enrolled in the study from among those treated at the King Abdulaziz University Hospital over a 12-year period from 1993 to 2005. Vital data for the study were extracted from several sources, including hospital medical records, the National Diabetes Registry, and the statistics department. The data were extracted by an experienced physician under the strict supervision of the author, who also checked for the consistency and completeness of the extracted data. The recorded information included the age at onset, sex, nationality, consanguinity, clinical presentation, duration of symptoms before diagnosis, and partial remission rate (which was defined according to the criteria of the International Study Group of Diabetes in Children and Adolescents as a period of freedom from clinical symptoms of diabetes with insulin requirements of <0.5 units/kg/day and absent or minimal glycosuria for more than 4 weeks). During this study, type 1 diabetes was predominantly diagnosed on the basis of the clinical and biological features. Polyuria, polydipsia, weight loss and fatigability were the principal clinical features for diagnosis. Significant hyperglycemia was taken into account as a biological feature according to the National Diabetes Data Group criteria of fasting blood glucose of >140 mg/dL (>7.7 mmol/L), 2-hour postprandial blood glucose level of >200 mg/dL (>11.1 mmol/L), and glycosuria with or without ketonuria.

Both clinical and biological features were included in the diagnosis of DKA. Clinical features such as vomiting, abdominal pain, moderate-to-severe dehydration, and stupor, in addition to hyperglycemia with blood glucose levels exceeding 15 mmol/L, ketonuria and metabolic acidosis with a bicarbonate level of <15 mmol/L, played significant roles in determining DKA. The chronic complications such as retinopathy, nephropathy and neuropathy were identified by ophthalmic findings indicative of retinopathy, persistent microalbuminuria, and abnormal nerve conductions, respectively. Data analyses (chi square tests, Fischer exact test) were performed using the statistical packages STATA, R, and Minitab.

Of the 369 diabetic patients, 159 (43.1%) patients were between 11 and 15 years of age. The age groups 6-10 years and >15 years consisted of a similar number of patients—100 (27.1%) and 97 (26.3%) patients, respectively. Only 13 (3.5%) patients were less than 5 years old. The mean (standard deviation) age was 12.3 (4.0) years with a range of 2-18 years ( Table 1 ). Of the enrolled patients, 175 (47.4%) were male and 194 (52.6%) were female. The study group included 324 (87.8%) Saudi patients and 45 (12.2%) patients of different Arab nationalities. A positive family history of DM was recorded in 260 (73.7%) patients, including both type 1 and type 2 diabetes patients. The overall mean (SD) duration of diabetes was 4.6 (3.7) years. There were two major peaks of age at diagnosis, one at the age of 7 years and the other at 11 years, with a sharp drop after the age of 11 years; the curve almost reached a plateau at the age of 18 years ( Figure 1 ). Most patients (134 patients, 58.5%) had a less than 15 days duration of symptoms before diagnosis. The duration of symptoms before diagnosis ranged from 1 to 365 days, with a median of 14 days ( Table 1 ). The mean total insulin intake was 36.0 units/d, with a range of 2-106 units/d and a median of 37 units/d. Partial remission was observed in 21 (9.1%) patients ( Table 1 ). Numbers of patients by age group, duration of diabetes, family history, diabetic complications, and were above 17 years of age at the time of diagnosis, and these were the oldest patients in this study. Two peaks [peaks of age at time of diagnosis?] were observed, one as early as at 12 days of age in a case that was diagnosed in another hospital and referred to the Diabetes Center of King Abdulaziz University Hospital. Three patients duration of partial remission by the other variables are presented in Tables ​ Tables2a, 2a , ​ ,2b, 2b , and ​ and2c 2c .

Characteristics of pediatric diabetic patients attending the diabetes center at a university hospital (1993-2005) (n=369).

Distribution curve of age of diagnosis pediatric patients attending the diabetes center at a university hospital (1993-2005).

Sex of pediatric diabetic patients by age group

Sex and and age group by duration of diabetes

Sex, age group and duration by family history of diabetes, diabetic complications and duration of partial remission

The most frequent presenting symptoms were polyuria, polydipsia, weight loss, nocturia ( Table 3 ) while DKA was present in about half ( Table 3 ). Because of missing data, not all information on all parients was available. The data on fatigability was available for 231 patients; fatigability was observed in 179 of these 231 patients. The less frequent symptoms included fever, obesity, delayed wound healing, vomiting, loss of consciousness, and diarrhea; a history of preceding illness was also less frequent. Ten (4.3%) patients of the studied cohort were asymptomatic. Most patients had acute diabetic complications such as hypoglycemia, and DKA ( Table 4 ). None of the patients had severe complications such as coma and cerebral edema. Chronic complications included retinopathy, neuropathy, coronary heart disease and nephropathy.

Symptoms of pediatric diabetic patients on presentation at the diabetes center according sex, age group, and duration of symptoms

Diabetic complications (acute and chronic)

Among the patients in the study, diabetes was diagnosed as early as at 12 days of age in a case that was diagnosed in another hospital and referred to the Diabetes Center of King Abdulaziz University Hospital. Three patients were above 17 years of age at the time of diagnosis, and these were the oldest patients in this study. Two peaks in age at time of diagnosis were observed, one at 7 and the other at 11 years of age. In a study by Salman et al, the age at onset ranged from 7.5 months to 12 years, with a peak at around 5-7 years and 11-14 years, respectively. The second peak in this study was observed to occur in the age range similar to that reported by Abdullah (10-13 years), while the first peak was observed to occur slightly earlier (4-6 years). 19 , 20 In the study by Abdullah, the youngest patient was 6 months old at diagnosis.

The present study showed a female preponderance, with 194 (52.6%) females versus 175 (47.4%) males; such a female preponderance was also observed in the series conducted by Salman et al, wherein 53.6% of patients were female. On the contrary, the series conducted by Abdullah showed a male preponderance, with a male-to-female ratio of 1.3:1; this ratio is similar to the ratios observed in the UK, Denmark and India. 19 , 20 In this study, the duration of symptoms before diagnosis was 1-35 days with a median of 14 days as compared to a duration of 2-60 days with a mean of 18.2 days in the series conducted by Salman et al.

The most common clinical presentations in the present study were polyuria (92%) and polydipsia (88.8%). In the study by Salman et al, DKA was the most common clinical presentation and was observed in 74 (67.3%) patients; while in the present study, DKA was observed in 49.9% of the patients. In the study by Abdullah, 55% of the patients presented with DKA. Studies in Malaysia revealed a figure (48%) similar to that in the present study, while studies in Philippines and India revealed figures of 63% and 20%-40%, respectively. 6 , 21 , 22 DKA is considered uncommon in Japan and Indonesia. 23 , 24 DKA was observed in 49.9% of the patients in this series; thus DKA was less common in this study than in other local studies, such as those by Salman et al (DKA was observed in 67.2% of the patients) and Abdullah (DKA observed in 55% of the patients). This difference may be explained by a higher level of awareness among parents and improvement in health services with early diagnosis.

The partial remission rate in this study was only 9.1%, which is lower than the rates observed in the studies by Abdullah (32%) and Salman et al. (30.9%). It correlates to those studies in relation to age group; none of the patients below 5 years of age had any episode. Partial remission is considered more common when diabetes is diagnosed in older children and teenagers, and most patients in the present study were diagnosed when they were less than 11 years of age ( Figure 1 ); this might explain the low rate of partial remission observed in this study. The lower incidence of DKA may further explain the low rate of partial remission.

A positive family history of both types (1 and 2) of diabetes was observed in 73.7% of the patients in this study; this figure is higher than that reported in the study by Abdullah (56.7%). DM occurs significantly more frequently in the parents and siblings of diabetics than in those of the control population. 25 , 26 In the study by Salman et al,, both the consanguinity rate and family history of type 1 and 2 diabetes were higher than those reported in the literature and also in a similar local study. 25 – 29

The treatment of DM in children requires the provision of a comprehensive, well-coordinated and continuous service. This is best achieved by teamwork. Adolescents or “young adults” in Saudi Arabia and in some other non-Western countries are not examined at pediatric clinics and do not receive adequate attention at adult clinics. Studies of the microvascular complications in non-insulin-dependent DM patients suggest that the onset of these complications occurs at least 4-6 years before clinical diagnosis. Evidence shows that strict glycemic control prevents microvascular complications. 30

In summary, the incidence of DKA was lower than that reported in previous studies; in addition, unlike in previous studies, DKA was not the most common clinical presentation. This difference is due to better awareness and early diagnosis. Additionally, the partial remission rate was lower, which indicates early diagnosis. Although chronic complications are uncommon in children, retinopathy, neuropathy, coronary heart disease and nephropathy have been observed; this necessitates an awareness among physicians, caretakers and patients about the importance of early diagnosis and strict control of DM. The incidence of family history was higher than that reported previously, which can be explained by the higher rate of consanguinity in the Saudi community. This observation indicates the need for further genetic studies of DM in the Saudi population.

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Genetics of type-1 diabetes

• Mini-Review
• Published: 02 September 2024

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• Hiroshi Ikegami   ORCID: orcid.org/0000-0001-8808-4605 1 , 2 &
• Shinsuke Noso 3  

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Type-1 diabetes is a multifactorial disease characterized by genetic and environmental factors that contribute to its development and progression. Despite progress in the management of type-1 diabetes, the final goal of curing the disease is yet to be achieved. To establish effective methods for the prevention, intervention, and cure of the disease, the molecular mechanisms and pathways involved in its development and progression should be clarified. One effective approach is to identify genes responsible for disease susceptibility and apply information obtained from the function of genes in disease etiology for the protection, intervention, and cure of type-1 diabetes. In this review, we discuss the genetic basis of type-1 diabetes, along with prospects for its prevention, intervention, and cure for type-1 diabetes.

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Professor Emeritus, Kindai University, Osaka-sayama, Japan

Hiroshi Ikegami

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Ikegami, H., Noso, S. Genetics of type-1 diabetes. Diabetol Int (2024). https://doi.org/10.1007/s13340-024-00754-1

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Received : 13 March 2024

Accepted : 06 August 2024

Published : 02 September 2024

DOI : https://doi.org/10.1007/s13340-024-00754-1

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