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Diagnosis and problem identification, planning and intervention, case presentation, case study: a patient with type 1 diabetes who transitions to insulin pump therapy by working with an advanced practice dietitian.

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Claudia Shwide-Slavin; Case Study: A Patient With Type 1 Diabetes Who Transitions to Insulin Pump Therapy by Working With an Advanced Practice Dietitian. Diabetes Spectr 1 January 2003; 16 (1): 37–40. https://doi.org/10.2337/diaspect.16.1.37

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Registered dietitians (RDs) who have earned the Board Certified–Advanced Diabetes Manager (BC-ADM) credential hold a master’s or doctorate degree in a clinically relevant area and have at least 500 hours of recent experience helping with the clinical management of people with diabetes. 1 They work in both inpatient and outpatient settings, including diabetes or endocrine-based specialty clinics, primary care offices, hospitals, and private practices. Advanced practice dietitians provide all components of diabetes care, including advanced assessment (medical history and physical examination), diagnosis, medical management, education, counseling, and overall case management.

The role of RDs in case and disease management was explored in a recent article 2 that included interviews with three dietitians who work as case managers or disease managers. All three reported experiencing challenges in practice and noted that the meaning of “case management” varies from one health care setting to another. This is also true for RD, BC-ADMs. Advanced practice dietitians specializing in diabetes require case management expertise that stresses communication skills, knowing the limits of your own discipline, knowing how to interact with other health care professionals, and knowing when to seek the expertise of other members of the diabetes care team.

Clinical practice includes assessment and data collection, diagnosis and problem identification, planning, and intervention. In many cases, diabetes educators who are dietitians and those who are nurses are cross-trained to perform the same roles. The first one to meet with a client handles that client’s assessment, and cases are discussed and interventions planned at weekly team meetings.

For advanced practice dietitians, the first session with a client often involves a complete physical assessment, not just a nutrition history. This includes a comprehensive medical history of all body systems. The diabetes-focused physical examination, just as performed by clinicians from other disciplines, includes height and weight measurement, body mass index (BMI) calculation, examination of injection sites, assessment of injection technique, and foot assessment.

Assessment also includes reviewing which medications the client is taking, evaluating their effectiveness and side effects, and determining the need for adjustment based on lifestyle, dietary intake, and blood glucose goals.

When carbohydrate counting is added to therapy, dietitians calculate carbohydrate-to-insulin ratios and teach clients how to use carbohydrate counting instead of a sliding-scale approach to insulin. Medications are adjusted based on clients’ lifestyles until blood glucose goals are achieved.

The therapeutic problem solving, regimen management, case management, and self-management training performed by advanced practice dietitians exceeds the traditional role of most dietetics professionals. 3  

A role delineation study for clinical nurse specialists, nurse practitioners, RDs, and registered pharmacists, 4 conducted in 2000 by the American Nurses Credentialing Center, reported equal findings among all four groups for the skills used to identify pathophysiology, analyze diagnostic tests, and list problems. Assessment for medical nutrition therapy typically includes evaluation of food intake, metabolic status, lifestyle, and readiness to change. For people with diabetes, monitoring glucose and measuring hemoglobin A 1c (A1C), lipids, blood pressure, and renal status are essential to evaluating nutrition-related outcomes.

The U.S. Air Force health care system conducted a pilot test giving RDs clinical privileges and evaluating their clinical judgment in patient nutritional care. A protocol was approved, and dietitians were allowed to order and interpret selected outpatient laboratory tests independently. The higher-level clinical judgments and laboratory privileges were linked to additional certifications. 5  

The Diabetes Prevention Program (DPP) also provided a unique opportunity for dietitians to demonstrate advance practice roles. 6 Dietitians served as lifestyle coaches, contacting participants at least once a month to address intervention goals. As case managers, they interviewed potential volunteers, assessed past experience with weight loss, and scheduled quarterly outcome assessments and weekly reviews of each participant’s progress at team meetings. Within the DPP’s central management, dietitians served as program coordinators and served on national study committees related to participant recruitment and retention, quality control, the use of protocols, and lifestyle advisory groups. 7  

Dietitians now play key roles in translating DPP findings and serving as community advocates to reduce the incidence of obesity and the health care burden of type 2 diabetes. This includes serving in a consultative role to other health care team members on issues regarding weight loss and risk factor reduction.

Advanced practice RDs offer comprehensive diabetes patient care services, including identifying patient goals and expected outcomes, selecting nonpharmacological and pharmacological treatments, and developing integrated plans of care. Problems discussed with patients range from acute and chronic diabetes complications to comorbid conditions, other conditions, preventive interventions, and self-management education. Advanced practice RDs also review patients’ health care resources and order laboratory tests if information is not available from referral sources. They provide supportive counseling and referral to specialists, as needed. And, they provide a full report of their findings and any regimen changes and recommendations they make to referring clinicians after each visit.

These activities and responsibilities go beyond the scope and standards of practice for the RDs and for RD, CDEs. 8 They will be included in the scope of practice document for RD, BC-ADMs that is now being developed by the Diabetes Care and Education Practice Group of The American Dietetic Association.

The following case study illustrates the clinical role of advanced practice dietitians in the field of diabetes.

B.C. is a 51-year-old white man who was diagnosed with type 1 diabetes 21 years ago. He believes that his diabetes has been fairly well controlled during the past 20 years and that his insulin needs have increased. He was recently remarried, and his wife is now helping him care for his diabetes.

His endocrinologist referred him to the RD for an urgent visit because 4 days ago he had a hypoglycemic event requiring treatment in the emergency room (ER). He has come to see the dietitian because his doctor and his wife insisted that he do so.

B.C. has had chronic problems with asymptomatic hypoglycemia. His last doctor’s visit was 3–4 weeks ago, when areas of hypertrophy were found. His endocrinologist asked him to change his injection sites from his thigh to his abdomen after the ER incident.

He does not think he needs any diabetes education but would like help in losing 10 lb. His body mass index is 25 kg/m 2 .

His medications include pravastatin (Pravacol), 10 mg daily; NPH insulin, 34 units in the morning and 13 units at bedtime; and regular insulin at breakfast and dinner following a sliding-scale algorithm. He also takes lispro (Humalog) insulin as needed to correct high blood glucose.

Before his ER visit, B.C. monitored his blood glucose only minimally, testing fasting and sometimes before dinner but not keeping records. Since his severe hypoglycemia 4 days ago, he has begun checking his blood glucose four times a day, before meals and bedtime.

Lab Results

B.C.’s most recent laboratory testing results were as follows:

A1C: 8.3% (normal 4.2–5.9%)

Lipid panel

    • Total cholesterol: 207 mg/dl (normal: 100–200 mg/dl)

    • HDL cholesterol: 46 mg/dl (normal: 35–65 mg/dl)

    • LDL cholesterol: 132 mg/dl (normal: <100 mg/dl)

    • Triglycerides: 144 mg/dl (normal: <150 mg/dl)

Creatinine: 0.9 mg/dl (normal: 0.5–1.4 mg/dl)

Microalbumin: 4 μg (normal: 0–29 μg)

At his initial visit with the RD for crisis management of asymptomatic hypoglycemia, she examined his injection sites and asked if he had made the changes recommended by his clinician. She reviewed his injection technique, diet history, incidence of hypoglycemia, and hypoglycemia treatment methods. She discussed with B.C. ways to reduce his risks of hypoglycemia, including food choices, insulin timing, and absorption variations at different injection sites.

The RD reinforced his clinician’s instruction to avoid old injection sites and added a new recommendation to lower insulin doses because of improved absorption at the new sites.

B.C. was now checking his blood glucose and recording results in a handheld electronic device in a form that could be downloaded, e-mailed, or faxed, but he was not recording his food choices. The dietitian asked him to keep food records and started his carbohydrate-counting education. A follow-up visit was scheduled for 1 week later.

At the second visit, B.C.’s mid-afternoon blood glucose was <70 mg/dl. He did not respond to treatment with 15 g carbohydrate from 4 oz. of regular soda. His blood glucose continued to drop, measuring 47 mg/dl 15 minutes later. He drank another 8 oz. of soda, and his blood glucose increased to 63 mg/dl 1 hour later. He then drank another 8 oz. of soda and ate a sandwich before leaving the dietitian’s office. He called in 1 hour later to report that his blood glucose was finally up to 96 mg/dl.

B.C.’s records showed a pattern of mid-afternoon hypoglycemia. He was willing to add a shot of lispro at lunch to his regimen, so the RD recommended reducing his morning NPH to prevent lows later in the day.

The RD also calculated insulin and carbohydrate ratios for blood glucose correction and meal-related insulin coverage using the “1500 rule” and the “500 rule.”

The 1500 rule is a commonly accepted formula for estimating the drop in a person’s blood glucose per unit of fast-acting insulin. This value is referred to as an “insulin sensitivity factor” (ISF) or “correction factor.” To use the 1500 rule, first determine the total daily dose (TDD) of all rapid- and long-acting insulin. Then divide 1500 by the TDD to find the ISF (the number of mg/dl that 1 unit of rapid-acting insulin will lower the blood glucose level). B.C.’s average TDD was 41 units. Therefore, his estimated ISF was 37 mg/dl per 1 unit of insulin. The RD rounded this up to 40 mg/dl to be prudent, given his history of hypoglycemia.

The 500 rule is a formula for calculating the insulin-to-carbohydrate ratio. To use the 500 rule, divide 500 by the TDD. For B.C., the insulin-to-carbohydrate ratio was calculated at 1:12 (1 unit of insulin to cover every 12 g of carbohydrate), but again this was rounded up to 1:14 for safety. Later, his carbohydrate ratio was adjusted down to 1:10 based on blood glucose monitoring results before and 2 hours after meals.

The RD taught B.C. how to use the insulin-to-carbohydrate ratio instead of his sliding scale to adjust his insulin and asked him to try to follow the new recommendations. With his endocrinologist’s approval, she reduced his NPH doses to 34 units and added a shot of lispro at lunchtime, the dose to be based on the amount of carbohydrate in the meal and his before-meal blood glucose level.

The RD asked B.C. to return in 1 week for evaluation and review of his new regimen. However, 3 days later, he returned after having had another severe episode of hypoglycemia.

In the course of these early visits, a good rapport developed between B.C. and the dietitian. B.C. learned that his judgment on how hypo- and hyperglycemia felt was often inaccurate and led him to make insulin adjustments that contributed to his hypoglycemia problems. By improving B.C.’s understanding of insulin doses and blood glucose responses, the RD hoped to help him become more skilled at making insulin dose adjustments. For the time being, however, he was still at risk for asymptomatic hypoglycemia. He had recently filled a prescription for glucagon, but the RD needed to review and encourage its proper use. She also provided literature to support his wife in case she needed to administer glucagon for him.

At this third visit, the RD reduced B.C.’s morning NPH dose to 22 units because of his rapid drop in blood glucose between noon and 1:00 p.m. This reduction finally eliminated his mid-afternoon lows.

B.C. had started using carbohydrate counting to make his decisions about lunchtime insulin doses. He liked carbohydrate counting because it gave him a more viable reason for testing his blood glucose frequently. Over the years, B.C.’s glycemia had become increasingly difficult to control. He had stopped checking his blood glucose because he felt unable to improve the situation once he had the information. In the early 1990s, his endocrinologist had started him self-adjusting insulin doses using the exchange system, but he found that he was always “chasing his blood sugars.” Carbohydrate counting changed everything. He now knew what to do to improve his blood glucose levels, and that made him feel more in charge of his diabetes.

Still, although carbohydrate counting led to more frequent testing and better blood glucose control than his old sliding scale, it was not perfect. At home, he had mastered this technique, but he ate many of his meals in restaurants, where carbohydrate counting was more challenging.

B.C. found it difficult to carry different types of insulin. This and his lifestyle suggested the need to change his multiple daily injections from regular to lispro insulin. He continued checking his blood glucose before and 2 hours after meals. His insulin-to-carbohydrate ratio of 1:10 g and his ISF of 1:40 mg/dl allowed him to stay within his goal of no more than a 30-mg/dl increase in blood glucose 2 hours after meals. He continued to be asymptomatic of hypoglycemia, but lows occurred less frequently. The new goal of therapy was to recover his hypoglycemia symptoms at a more normal level of about 70 mg/dl. He was scheduled for another visit 2 weeks later.

Between visits to the RD, BC-ADM, his clinician identified problems with the timing of his long-acting insulin peak, resulting in early nocturnal lows. Based on the clinician’s clinical experience of lente demonstrating a slightly smoother peak, she changed B.C.’s long-acting insulin unit-for-unit from NPH to lente.

At B.C.’s next visit, he and the RD reviewed his insulin doses of 22 units of lente in the morning and 11 units of lente at night. His TDD including premeal lispro now averaged 49 units. His average blood glucose levels were 130 mg/dl fasting, 100 mg/dl mid-afternoon, 127 mg/dl before dinner, and 200 mg/dl at bedtime.

The bedtime levels were higher because of late meals, the fat content of restaurant meals, his meat food choices, and his inexperience at counting carbohydrates for prepared foods. The dietitian suggested mixing regular and lispro insulin to try and get the average bedtime blood glucose level to 140 mg/dl. Mixing his calculated dose to be one-third regular and two-third lispro would provide coverage lasting a little longer than that of just lispro to cover higher-fat foods that took longer to digest. At the same time, the dietitian encouraged B.C. to choose lower-fat foods to help reduce his LDL cholesterol and assist with weight loss. B.C. now had an incentive to keep accurate food records to help evaluate his accuracy at calculating insulin doses.

B.C. and the RD also reviewed his decisions for treating lows. At his first meeting, B.C. ate anything and everything when he experienced hypoglycemia, which often resulted in blood glucose levels >400 mg/dl. Now, he was appropriately using 15–30 g of quick-acting glucose—usually 4–8 oz. of orange juice. He based this amount on his blood glucose level, expecting about a 40-mg/dl rise over 30 minutes from 10 g of carbohydrate. He checked his glucose level before treating when possible and always checked 15–30 minutes after treating to evaluate the results. Once his glucose reached 80 mg/dl or above, he either ate a meal or ate 15 g of carbohydrate per hour to prevent a recurrence of hypoglycemia until his next meal.

In completing her assessment during the next few meetings with B.C., the RD identified a problem with erectile dysfunction. She notifed his clinician and referred him to a urologist. Eventually, the urologist diagnosed reduced blood flow and started B.C. on sildenafil (Viagra).

B.C. wanted to resume exercise to help his weight loss efforts. Because exercise improves insulin sensitivity and can acutely lower blood glucose, the dietitian taught B.C. how to reduce his insulin doses by 25–50% for planned physical activity to further reduce his risks of hypoglycemia. He learned to carry his blood glucose meter, fluids, and carbohydrate foods during and after exercise. His pre-exercise blood glucose goal was set at 150 mg/dl. The dietitian instructed B.C. to test his blood glucose again after exercise and to eat carbohydrate foods if it was <100 mg/dl.

She also gave instructions for unplanned exercise. He would require additional carbohydrate depending on his blood glucose level before exercise, his previous experience with similar exercise, and the timing of the exercise. Education follow-ups were scheduled with the dietitian for 1 month later and every 3 months thereafter.

At his next annual eye exam, B.C. discovered that he had background retinopathy. He also reported feeling that his daily injection regimen had become too complicated. Still feeling limited in his ability to control his diabetes and looking for an alternative to insulin injections, he wanted to discuss continuous subcutaneous insulin infusion therapy (insulin pump therapy).

He, his endocrinologist, and his dietitian discussed the pros and cons of pump therapy and how it might affect his current situation. They reviewed available insulin pumps and sets and agreed on which ones would best meet his needs. The equipment was ordered, and a training session was scheduled with the dietitian (a certified pump trainer) in 1 month.

B.C. started using an insulin pump 2 years after his first visit with the dietitian. His insulin-to-carbohydrate ratio was adjusted for his new therapy regimen, and a new ISF was calculated to help him reduce high blood glucose levels. His endocrinologist set basal insulin rates at 0.3 units/hour to start at midnight and 0.5 units/hour to start at 3:00 a.m. This more natural delivery of insulin based on B.C.’s body rhythms and lifestyle further improved his diabetes control.

One week after starting pump therapy, B.C. called the dietitian to report large urine ketones and a blood glucose level of 317 mg/dl. His endocrinologist had changed his basal rates, but he wanted to meet with the dietitian to review his sites, set insertion, troubleshooting skills, and related issues. Working together, they eventually discovered that problems with his pump sites required using a bent-needle set to resolve absorption issues.

B.C’s relationship with his endocrinologist and dietitian was seamless. He met with the dietitian when his clinician was unavailable or when he needed more time to work through problems.

B.C. has met with the RD 15 times over 3 years. Eventually, he recovered symptoms of hypoglycemia when his blood glucose levels were 70 mg/dl. After 6 months of education meetings, his lab values had reached target ranges. Most recently, his LDL cholesterol was <100 mg/dl, his A1C results were <7%, his hypoglycemia symptoms were maintained at a blood glucose level of 70 mg/dl, and his blood glucose had been stabilized using the square-wave and dual-wave features on his insulin pump.

B.C. learned how to achieve recommended goals and to self-manage his diabetes with the help of his care team: endocrinologist, cardiologist, ophthalmologist, podiatrist, urologist, and advanced practice dietitian.

Advanced practice dietitians in diabetes work in many settings and see clients referred from many different types of medical professionals. They may see clients either before or after their appointments with other members of the health care team, depending on appointment availability and their need for nutrition therapy and diabetes education. Referring clinicians rely on their evaluations and findings. When necessary, clinician approval can be obtained for immediate interventions, enhancing the timeliness of care.

Why would an RD want to obtain the skills and certification necessary to earn the BC-ADM credential? The answer, as illustrated in the case study above, lies in their routine use of two sets of skills and performance of two roles: patient education and clinical management.

Dietitians who specialize in diabetes often find that their role expands beyond provider of nutrition counseling. As part of a multidisciplinary team, they become increasingly involved with patient care. As they move patients toward self-management of their disease, they necessarily participate actively in assessment and diagnosis of patients; planning, implementation, and coordination of their diabetes care regimens; and monitoring and evaluation of their treatment options and strategies. They find that their daily professional activities go beyond diabetes education, crossing over into identifying problems, providing or coordinating clinical care, adjusting therapy, and referring to other medical professionals. They often work independently, providing consultation both to people with diabetes and to other diabetes care team members.

The BC-ADM credential acknowledges this professional autonomy while promoting team collaboration and thus improving the quality of care for people with diabetes. The new certification formally recognizes advanced practice dietitians as they move beyond their traditional roles and into clinical problem solving and case management.

Claudia Shwide-Slavin, MS, RD, BC-ADM, CDE, is a private practice dietitian in New York, N.Y.

Note of disclosure: Ms. Shwide-Slavin has received honoraria for speaking engagements from Medtronic Minimed, which manufactures insulin pumps, and Eli Lilly and Co., which manufactures insulin products for the treatment of diabetes.

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Case report article, case report: insulin-dependent diabetes mellitus and diabetic keto-acidosis in a child with covid-19.

• 1 Division of Pediatric Infectious Diseases, Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
• 2 Division of Critical Care Medicine, Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
• 3 Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States

During the COVID pandemic, a surge in pediatric Type 1 Diabetes Mellitus (T1DM) cases appears to be occurring, potentially due to the presence of autoantibody-induced immune dysregulation triggered by COVID-19. We describe one such case in a previously healthy 7-year-old with asymptomatic COVID-19 presenting with a high nasopharyngeal SARS CoV-2 virus load, detectable COVID-19 IgG antibodies, diabetic keto-acidosis and islet cell autoantibodies. COVID-19 is not a trivial disease in children and adolescents and can lead to lifelong sequelae such as T1DM. Raising awareness about a possible association between COVID-19 and T1DM in children is critical.

Introduction

During the COVID-19 pandemic, the number of cases of T1DM in youth spiked, with evidence suggesting an association between both conditions ( 1 , 2 ). Studies have long implicated viruses, particularly respiratory infections, as potential triggers of T1DM in children and young adults ( 3 ). In a large prospective pediatric study, a temporal association was noted between respiratory infections and development of autoantibodies against insulin-producing pancreatic beta islet cells ( 3 ). Following a surge in COVID-19 cases, a prospective registry demonstrated a significant increase in pediatric diabetic ketoacidosis (DKA) diagnoses ( 1 ). Between March to May 2020, 532 children in Germany were diagnosed with T1DM, with 45% presenting with DKA. The incidence of DKA in children was nearly double of that reported in the prior year (24.5%) with the risk of DKA in 2020 being 1.85 times higher than in the 2 prior years (2.75 times higher in children <6 years of age as compared to 2019) ( 1 ). In the U.K., investigators reported an 80% increase in the number of cases of T1DM in children as compared to prior years ( 2 ). The reason for higher rates of DKA in youth could be multi-factorial and related to delayed medical care ( 4 ). Findings, however, parallel what was observed in adults with COVID-19 ( 5 ).

Patient Information

A 7-year-old previously healthy Hispanic male with no pre-existing co-morbidities presented to the UCLA emergency department with progressive anorexia and a 10-pound weight loss over 3 weeks in August 2020. Three days prior to presentation, the patient complained of acutely worsened anorexia with polydipsia, abdominal pain, nausea, and headache ( Table 1 ). Both the patient and his mother denied any prior or concurrent presence of fever, cough, nasal congestion, shortness of breath, diarrhea, or dysuria. There was no history of recent illnesses or sick contacts. The child lived in a multigenerational family household in south Los Angeles, including both grandparents who worked as school janitors, his mother who was studying for her degree remotely, a young adolescent cousin and a 13-year-old healthy sister. No one in the household reported recent illnesses and the family history was overall unremarkable.

Table 1 . Timeline.

Clinical Findings

In the emergency department, the patient's initial vital signs were a temperature of 36.8°C, heart rate of 131 beats per minute (BPM), blood pressure of 114/75 mmHg, respiratory rate of 37 breaths per minute and an oxygen saturation of 99% on room air. His weight was 25 kg, height 121.9 cm, and BMI was at the 75% percentile for age. On initial examination, he was drowsy but arousable. His exam was notable for dry mucous membranes, reduced skin turgor, tachypnea, clear lungs clear to auscultation, and soft, non-distended, non-tender abdomen. While he appeared fatigued, he had a non-focal neurological exam and responded appropriately to questions.

Diagnostic Assessment

An initial point-of-care blood glucose was 470 mg/dL. A complete blood count (CBC) showed a normal white blood cell (WBC) count of 6.69 × 10 E 3 /uL, with an absolute neutrophil count (ANC) of 4,650 cells/uL, as well as a mild lymphopenia (1,420 lymphocytes/μL) ( Table 2 ). The urinalysis was significant for a specific gravity of 1.024, 2+ ketones, 3+ glucose, 2+ protein. Chest X-ray did not show any pulmonary pathology. Clinical and laboratory findings were consistent with diabetic ketoacidosis (DKA). In the emergency department, the patient received a 10 mL/kg normal saline bolus and started on continuous insulin infusion. He was then transferred to the pediatric intensive care unit (PICU) for further care.

Table 2 . Laboratory values on and during admission with abnormal results highlighted.

On arrival to the PICU, the patient was persistently tachycardic, with heart rates ranging from 100–140 BPM. He required a total of 40 mL/kg of normal saline fluid boluses over 24 h. An electrocardiogram was obtained, which revealed sinus tachycardia with incomplete right bundle branch block. His heart rate improved to 90–100 beats per minute over the next 2 days. A repeat CBC following hydration 24 h later showed a WBC count of 15.27 × 10 E 3 /μL with an ANC of 12,740 cells/μL, persistent lymphopenia (1,430 lymphocytes/μL) and 70 immature granulocytes/μL, hemoglobin of 16.1 g/dL, hematocrit of 46%, platelet count of 362 × 10 E 3 /μL. As the DKA was resolving on the two-bag system, the patient's hypokalemia, hypomagnesemia, hypocalcemia, and hypophosphatemia were repleted as appropriate.

On admission to the hospital, as per current hospital policy, a nasopharyngeal swab was tested for the presence of SARS-CoV-2 RNA using the Thermo Fisher TaqPath assay (Thermo Fisher Scientific, Waltham, MA). This returned positive the next morning, with cycle threshold (Ct) values of 23.25 for ORF1ab target, 23.12 for the N target, and 22.73 for the S target. A repeat upper respiratory specimen obtained 3 days later and evaluated using the BDMax assay (Beckon Dickinson and Company, Franklin Lakes, NJ) also returned positive, with Ct values of 26.7 for the N1 target and 27.5 for the N2 target. LIAISON ® SARS-CoV-2 IgG assay targeting the spike protein (S1/S2) (Diasorin S.p.A., Saluggia (VC)—Italy) was also positive on admission (optical density of 29.0; positive ≥ 15.0, range 400 units/mL. The patient never had any fever, diarrhea, nor any respiratory symptoms during the admission. Additional laboratory evaluations for inflammatory markers potentially associated with COVID-19 Multi-Inflammatory Syndrome in Children (MIS-C) are shown in Table 2 . Except for very mildly elevated procalcitonin, C-reactive protein, D-Dimer and ferritin levels, inflammatory markers were normal. Markers of type 1 diabetes, however, were grossly abnormal, with an islet antigen 2 (IA-2) autoantibody of >120.0 U/ml and the glutamic acid decarboxylase antibody >250.0 IU/ml. Hemoglobin A1C was elevated at 14.8%.

The patient remained on a continuous insulin infusion and the two-bag system for 2 days and then was switched to a subcutaneous insulin regimen once the acidosis resolved. Adequate glucose control on the new subcutaneous insulin regimen was achieved and he was discharged after a 4-day admission.

Therapeutic Intervention (Plan of Treatment)

The patient responded well to usual DKA protocol, with somewhat interesting features of high insulin requirements and low potassium. After stabilization of the metabolic acidosis, a subcutaneous insulin regimen was started per endocrinology with the patient transferred to the pediatric ward. He continued on a Lantus insulin regimen for basal coverage with carb correction. A sliding scale with Humolog was initiated. Additional laboratory studies including IgA, IA-2 Ab, insulin Ab, transglutaminase Ab panel, ICA-512-HgbA1c, transglutaminase abs panel GAD 65, anti-insulin antibodies, c-peptide, and Zinc Transporter 8 were ordered ( Table 2 ).

Both the patient and his mother received diabetes education for home regimens. He required electrolyte correction and was discharged home with oral potassium supplementation and 2,000 IU vit D per dietary recommendations. A repeat Covid PCR test was stil positive on 8/24. The patient was discharged home to quarantine with mother for 14 days from the first positive SARS CoV-2 PCR test.

Follow-up, Expected, and Actual Outcomes

The child was seen in the endocrine clinic 1 day after discharge and again 1 and 3 weeks after discharge, being found to have acceptable blood glucose levels. He was following a carbohydrate-controlled diet fairly well and thus no changes were made during the diabetic nutrition follow-up visits. The expected outcome for new onset T1DM is well-controlled DM care and dietary modification, however, we do not have enough information regarding the long term outcomes of simultaneous T1DM and Covid-19 infection in children.

Our pediatric patient illustrates the typical pattern of T1DM in children during the COVID-19 pandemic and differs from that of a published report in a 19 year old with new onset DKA following COVID-19 ( 6 ) as our patient had a classic presentation of autoantibody-mediated T1DM. The timing of SARS-CoV-2 infection in our patient coincided with development of indolent symptoms of diabetes, particularly anorexia and weight loss. Although T1DM is most commonly diagnosed in childhood, it is a relatively rare disease, occurring in about 1.5 in 1,000 children ( 7 ). COVID-19 is also infrequently identified in children as compared to adults, with pediatric cases mainly diagnosed during pandemic surges ( 7 ). For this reason, the magnitude of the association between T1DM, DKA, and COVID-19 in youth is difficult to quantify, but is, nonetheless, apparent. In a report of U.S. children hospitalized with COVID-19, 2.7% had a history of chronic diabetes, and 2.9% developed DKA during their hospital stay ( 8 ). Whether SARS CoV-2 itself or deferred medical care are responsible for a higher presentation of DKA cases in younger populations has been a matter of debate ( 4 , 9 ).

ACE2 is expressed in multiple organs, including exocrine and endocrine tissues of the pancreas. SARS-CoV, responsible for the epidemic of 2003, was shown to bind to ACE2 receptors through its spike protein, similarly to SARS-CoV-2 ( 10 ). Diabetes has been recognized as a risk factor for increased COVID-19 morbidity and mortality in adults since the onset of the SARS-CoV-2 pandemic ( 11 ). More recently, data from adults suggest that COVID-19 may lead to worse outcomes in patients with pre-established diabetes, and may trigger diabetic ketoacidosis ( 12 ). New-onset diabetes during the course of COVID-19 infection is recognized in both adults and children, with a small number of case reports described to date ( 2 , 13 ). A study of SARS patients with diabetes strongly suggested that the localization of ACE2 expression in the endocrine part of the pancreas allowed SARS coronavirus to enter and damage pancreatic islets, leading to acute diabetes ( 10 ). Both SARS-CoV and SARS-CoV-2 have been reported to trigger transient insulin resistance and hyperglycemia ( 10 , 11 ).

A report of a 19 year-old male with autoantibody negative Type 1 diabetes mellitus (T1DM) following COVID-19 infection acquired following exposure to symptomatic parents highlights the important consideration of whether SARS-CoV-2 infection may directly damage pancreatic islet cells abundantly expressing ACE2 viral receptors ( 6 ). Another possibility is that immune dysregulation during the course of COVID-19 disease may induce development of autoantibodies against pancreatic beta cells. Potentially both circumstances may occur in parallel, with infection of cells expressing ACE2 receptors triggering a dysregulated humoral immune response resulting in the death of pancreatic islet cells. Deferred medical care which discourages patients and parents of children to seek help during lockdown situations may likely contribute to more patients with new onset T1DM present in DKA ( 9 , 14 ). Decline in pediatric medical care occurs COVID-19 pandemic, where for example childhood immunization programs have suffered despite best efforts ( 15 ). In the case of our patient, symptoms went unrecognized for nearly 3 weeks, and upon diagnosis, off-scale levels of autoantibodies were present, a common finding in T1DM. Both mechanisms of pathogenesis and the underlying issues associated with pandemic situations and unavailability of hospital beds are likely leading to an unprecedented number of DKA cases in youth with COVID-19. Table 3 summarizes current pediatric studies on the topic to date.

Table 3 . Reports of DKA in children and youth during the COVID-19 pandemic.

Although SARS CoV-2 infection of pancreatic beta cells has not been yet demonstrated, there is enough evidence of direct viral damage leading to organ failure in different body compartments, as in the case of COVID-19 myocarditis ( 16 ). Cases of pancreatitis in patients with COVID-19 have been reported in both adults and children ( 17 , 18 ). It is difficult to discern which cases of new onset T1DM are due to direct viral damage, and which are due to immune dysregulation induced by COVID-19. While DM is a risk factor for severe COVID-19, SARS-CoV-2 infection also triggers T1DM, a bidirectional relationship shown to occur in adults and now increasingly demonstrable in youth. It is critical that awareness regarding this specific complication of SARS-CoV-2 infection in children be heightened, not only to enable early identification of DM, but also to counteract the belief that COVID-19 poses no threat to young patients.

In summary, our intent with this case report was to raise awareness among pediatricians about the potential for a large increase in the number of COVID-19 associated T1DM and DKA cases in children and youth following pandemic surges. Other institutions might be witnessing the same phenomenon and through this publication we wished to share this unique presentation of COVID-19 in children. Because the number of COVID-19 cases have sky-rocketed in recent months globally (December 2020/ January 2021), it is very likely that we will be seeing a very sharp rise in the number of T1DM and DKA events in children exposed to the virus through their family members. These children often require admission to critical care, and it is very important to recognize this potential complication of this condition in pediatric populations.

Patient Perspective

Despite the difficult circumstances, the patient and his family are adapting to the diagnosis of T1DM and mother and child are now heavily engaged with our institution's pediatric diabetes clinic. The child continues to be closely monitored with bi-monthly in person and telehealth visits. Family support through pediatric diabetes networks has been instrumental.

Data Availability Statement

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author/s.

Ethics Statement

The patient's mother provided informed consent for the publication of this case report.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fped.2021.628810/full#supplementary-material

1. Kamrath C, Mönkemöller K, Biester T, Rohrer TR, Warncke K, Hammersen J, et al. Ketoacidosis in children and adolescents with newly diagnosed type 1 diabetes during the COVID-19 pandemic in Germany. JAMA. (2020) 324:801–4. doi: 10.1001/jama.2020.13445

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Unsworth R, Wallace S, Oliver NS, Yeung S, Kshirsagar A, Naidu H, et al. New-onset Type 1 diabetes in children during COVID-19: multicenter regional findings in the U.K. Diab Care. (2020) 43:e170–e1. doi: 10.2337/dc20-1551

3. Lönnrot M, Lynch KF, Elding Larsson H, Lernmark Å, Rewers MJ, Törn C, et al. Respiratory infections are temporally associated with initiation of type 1 diabetes autoimmunity: the TEDDY study. Diabetologia. (2017) 60:1931–40. doi: 10.1007/s00125-017-4365-5

4. Tittel SR, Rosenbauer J, Kamrath C, Ziegler J, Reschke F, Hammersen J, et al. Did the COVID-19 lockdown affect the incidence of pediatric type 1 diabetes in Germany? Diabetes Care. (2020) 43:e172–e3. doi: 10.2337/dc20-1633

5. Rubino F, Amiel SA, Zimmet P, Alberti G, Bornstein S, Eckel RH, et al. New-onset diabetes in Covid-19. N Engl J Med. (2020) 383:789–90. doi: 10.1056/NEJMc2018688

CrossRef Full Text | Google Scholar

6. Hollstein T, Schulte DM, Schulz J, Glück A, Ziegler AG, Bonifacio E, et al. Autoantibody-negative insulin-dependent diabetes mellitus after SARS-CoV-2 infection: a case report. Nat Metab. (2020) 2:1021–4. doi: 10.1038/s42255-020-00281-8

7. Rush T, McGeary M, Sicignano N, Buryk MA. A plateau in new onset type 1 diabetes: Incidence of pediatric diabetes in the United States Military Health System. Pediatr Diabetes. (2018) 19:917–22. doi: 10.1111/pedi.12659

8. Kim L, Whitaker M, O'Halloran A, Kambhampati A, Chai SJ, Reingold A, et al. Hospitalization rates and characteristics of children aged <18 years hospitalized with laboratory-confirmed COVID-19 - COVID-NET, 14 States, March 1-July 25, 2020. MMWR Morb Mortal Wkly Rep. (2020) 69:1081–88. doi: 10.15585/mmwr.mm6932e3

9. Rabbone I, Schiaffini R, Cherubini V, Maffeis C, Scaramuzza A, Diabetes Study Group of the Italian Society for Pediatric Endocrinology and Diabetes. Has COVID-19 delayed the diagnosis and worsened the presentation of Type 1 diabetes in children? Diab Care . (2020) 43:2870–2. doi: 10.2337/dc20-1321

10. Yang JK, Lin SS, Ji XJ, Guo LM. Binding of SARS coronavirus to its receptor damages islets and causes acute diabetes. Acta Diabetol. (2010) 47:193–9. doi: 10.1007/s00592-009-0109-4

11. Abdi A, Jalilian M, Sarbarzeh PA, Vlaisavljevic Z. Diabetes and COVID-19: a systematic review on the current evidences. Diab Res Clin Pract. (2020) 166:108347. doi: 10.1016/j.diabres.2020.108347

12. Goldman N, Fink D, Cai J, Lee YN, Davies Z. High prevalence of COVID-19-associated diabetic ketoacidosis in UK secondary care. Diab Res Clin Pract. (2020) 166:108291. doi: 10.1016/j.diabres.2020.108291

13. Reddy PK, Kuchay MS, Mehta Y, Mishra SK. Diabetic ketoacidosis precipitated by COVID-19: A report of two cases and review of literature. Diabetes Metab Syndr. (2020) 14:1459–62. doi: 10.1016/j.dsx.2020.07.050

14. DiMeglio LA, Albanese-O'Neill A, Muñoz CE, Maahs DM. COVID-19 and children with diabetes-updates, unknowns, and next steps: first, do no extrapolation. Diabetes Care. (2020) 43:2631–4. doi: 10.2337/dci20-0044

15. Khan A, Bibi A, Sheraz Khan K, Raza Butt A, Alvi HA, Zahra Naqvi A, Mushtaq S, et al. Routine pediatric vaccination in Pakistan during COVID-19: how can healthcare professionals help? Front Pediatr. (2020) 10:613433. doi: 10.3389/fped.2020.613433

16. Dolhnikoff M, Ferreira Ferranti J, de Almeida Monteiro RA, Duarte-Neto AN, Soares Gomes-Gouvêa M, Viu Degaspare N, et al. SARS-CoV-2 in cardiac tissue of a child with COVID-19-related multisystem inflammatory syndrome. Lancet Child Adolesc Health. (2020) 4:790–4. doi: 10.1016/S2352-4642(20)30257-1

17. Inamdar S, Benias PC, Liu Y, Sejpal DV, Satapathy SK, Trindade AJ, et al. Prevalence, risk factors, and outcomes of hospitalized patients with COVID-19 presenting as acute pancreatitis. Gastroenterology. (2020) 159:2226–8.e2. doi: 10.1053/j.gastro.2020.08.044

18. Stevens JP, Brownell JN, Freeman AJ, Bashaw H. COVID-19-Associated multisystem inflammatory syndrome in children presenting as acute pancreatitis. J Pediatr Gastroenterol Nutr. (2020) 71:669–71. doi: 10.1097/MPG.0000000000002860

Keywords: COVID-19, children, type 1 diabetes mellitus (T1DM), diabetic keto-acidosis (DKA), SARS CoV-2, pediatric COVID-19

Citation: Nielsen-Saines K, Li E, Olivera AM, Martin-Blais R and Bulut Y (2021) Case Report: Insulin-Dependent Diabetes Mellitus and Diabetic Keto-Acidosis in a Child With COVID-19. Front. Pediatr. 9:628810. doi: 10.3389/fped.2021.628810

Received: 13 November 2020; Accepted: 12 January 2021; Published: 10 February 2021.

Reviewed by:

Copyright © 2021 Nielsen-Saines, Li, Olivera, Martin-Blais and Bulut. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Erica Li, ericali@mednet.ucla.edu

Nursing Case Study for Type 1 Diabetes

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Michael is a 14-year-old male brought into a small ER by his mother. They were driving a long distance after he competed in a wrestling tournament. He had not felt well on the bus ride with the team so his mother decided he should ride with her. His mother denies a history of chronic illness but did say he had “like a cold but with a stomachache” about 3 months ago.

She also says that he has been very thirsty, and they had to stop several times for him to urinate. She is also worried because he almost missed his wrestling “weight class” parameters because he was significantly lighter this past weekend than he has been in the past. And that is even with him eating more than usual.

What symptoms are most worrisome to the triage nurse?

• He has 2 of the 3 “p’s” – polydipsia (thirst), polyuria (frequent urination), polyphagia (hunger) which are trademarks of diabetes mellitus (DM) and/or diabetic ketoacidosis (DKA). They happen in response to the body lacking insulin and its response is to try to achieve homeostasis with these mechanisms. His weight loss could be indicative of DM as well. 
• They describe a recent viral-like illness which may precipitate a diagnosis of DM (it is thought the body has an inappropriate immune response to the illness leading to DM)

In triage, the nurse obtains a point-of-care blood glucose (BG) level and the machine gives no value. Instead, an error message indicating “hi” displays on the machine.

Why did the nurse do this test? What should they do next?

• Clues point to possible DM or DKA. Getting a BG immediately can help guide care. Always follow the facility protocol/procedure on “hi” or “lo” (often spelled this way on glucometers) readings. The protocol might dictate (standing order) stat venous draw and send it to the lab. It may be advised to try again on a different machine with a new sample. Whatever the guidance, a BG level is imperative for this patient.

Michael is AAO x 4. He complains of a “stomachache” and reports he has nausea and experienced vomiting shortly before arrival. His skin is warm and dry, but his face is flushed. When asked about pain, he says he has a headache, and his vision is blurry. The nurse notices a fruity odor on his breath when obtaining vital signs. 

BP 90/54 mmHg SpO 2 98% on Room Air

HR 122 bpm and regular

RR 26 bpm at rest

The patient and his mother are placed into an exam room immediately and the triage nurse verbally reports this to the accepting nurse.

How does the nurse interpret these symptoms?

• Michael’s symptoms are consistent with hyperglycemia (link here to cheatsheet?) DKA

What orders does the accepting nurse anticipate?

• Labs, ABGs, urinalysis, IV access (bilateral upper extremities, largest possible in case patient deteriorates). One lab, in particular, can give the provider an idea of the last 2-3 month BG average, the hemoglobin A1C.

The provider orders stat labs, urinalysis and ABGs then examines the patient. 

Why stat orders?

• This patient’s condition could deteriorate rapidly, and treatment should begin ASAP. Labs are needed to guide the plan of care. The nurse should watch for changes in the level of consciousness, respiratory changes, his response to potential fluid & electrolyte imbalances. Place on continuous cardiac monitoring as well.

Lab results are as follows:

WBC 15000 cells/mcL

Glucose 420 mg/dl

BUN 21 mg/dl

Creatinine 0.77 mg/dl

Anion gap 12

Glucose positive

Ketones positive

What do these results mean?

• CBC WBC 15000 cells/mcL – an immune response, possibly to viral illness or another issue HgbA1C 9% – indicates the average BG over the past 2-3 months has been about 212mg/dLBMP Glucose 420 mg/dl – hyperglycemia K 5.8 – electrolyte imbalance, can cause cardiac changes and need to monitor closely if IV insulin is started (will need frequent checks of this and BG) BUN 21 mg/dL – fluid imbalance Creatinine 0.77 mg/dL – normal but necessary to check for kidney function Anion gap 12 – indicative of DKAABG – metabolic acidosis Ph 7.25 HCO3 15 PaCo2 35 PaO2 88Urine – indicative of DKA Glucose positive Ketones positive

What medication orders should the nurse anticipate?

• IV fluids, insulin (either IV or SQ). NOTE: only REGULAR INSULIN can be given IV, and if it is, then IV dextrose and potassium chloride should be included in the insulin IV titration protocol/order). SQ insulin may be ordered using a sliding scale. O2 via NC possibly due to potential respiratory concerns (Kussmaul respirations)

The provider tells Michael and his mother that he suspects diabetic ketoacidosis which is not uncommon for new type I diabetics. He plans to transfer Michael to a nearby city via helicopter for a higher level of care.  The patient’s mother asks why he has to be transferred.

How does the nurse explain the transfer to the mother and patient?

• DKA requires monitoring in a critical care unit. Because of his age and new-onset DM, a higher level of care is recommended in order to have access to the best resources

The flight team arrives and assesses the patient. The ER completes a report using SBAR format at the bedside. The patient and his mother are given the chance to ask questions.

What are the transport team’s priorities as they move this patient?

• Airway, breathing, and circulation (ABC) status; Mental status; Volume status.

Upon arrival to the higher level of care, Michael is admitted to the ICU overnight. By the morning he is transferred to a pediatric floor for further observation. His mother remains at his bedside. They plan to return to their home after discharge. 

How should the pediatric medical unit prepare this family for discharge? What specific teaching should be provided?

• Condition-specific education is vital including DM management with medications, exercise, nutrition, psychosocial concerns, preventative care (i.e. vaccinations), parental/family involvement. A specialized diabetic educator and/or dietician would be ideal. Assessing their education preferences and literacy level is important as well. How to give insulin injections and check BG (glucometer use) are key takeaways (have patient and parent return-demonstrate). Case management may need to get involved for prescription/supplies. An endocrinologist may be consulted so education about his specialist is also important.

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Nursing case studies.

This nursing case study course is designed to help nursing students build critical thinking.  Each case study was written by experienced nurses with first hand knowledge of the “real-world” disease process.  To help you increase your nursing clinical judgement (critical thinking), each unfolding nursing case study includes answers laid out by Blooms Taxonomy  to help you see that you are progressing to clinical analysis.We encourage you to read the case study and really through the “critical thinking checks” as this is where the real learning occurs.  If you get tripped up by a specific question, no worries, just dig into an associated lesson on the topic and reinforce your understanding.  In the end, that is what nursing case studies are all about – growing in your clinical judgement.

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Depression and Type 1 diabetes: case studies

January 26, 2020 by Diabetes Care

Here are two case studies to further understand how depression and type 1 diabetes can be intertwined and can affect teens.

In my last blog, I quoted from the Diabetes Care Journal- June 2006/vol. 29 pg 1389 that the level of depressive symptoms in children and adolescents with type 1 diabetes is nearly double that of the highest estimate of depression in youth in general.

Due to the rise of depression and suicides in the teen and young adult population, I thought I would describe two case studies that may illustrate what young people experience and feel, and their frustrations in life as they manage their lives and their type 1 diabetes.

The first case is about a girl who was diagnosed with type 1 diabetes at an early age. Her parents assisted her with her management until, at age 9, she told them that she could do it on her own. She did this until she was 14 or 15 years of age. At this time she was given a new insulin regimen, which confused her and ended up causing her to have extreme hypoglycemia (low blood sugar levels) and hyperglycemia (high blood sugar levels). She could not figure this out. She could not understand why she could not work out the carb ratio and insulin intake. She was an A student, so why could she not figure out this new regimen? She found the situation very frustrating.

With these extreme hypo and hyper glucose levels, the teen had difficulty concentrating in school and became angry about her diabetes. She could not figure her diabetes management out. She asked for the old regimen to be implemented, but this was not supported by her diabetes endocrinologist. She became angry, frustrated, and anxious. She could not sleep and became depressed. She started to sleep longer during the day, not wanting to eat and she did not want to take her insulin. She started to ask herself questions: Why me? Why do I have to have diabetes? Why can’t I be like everyone else…normal? She ended up in hospital with Diabetic ketoacidosis ( DKA).

While in hospital, the teen worked with the hospital healthcare team and figured out how to manage her diabetes. At home she continued this management and started to see a counsellor on living with diabetes and how to manage life struggles. She is doing very well today.

My last case is about a young man, age 16. He was diagnosed at 7 years of age with type 1 diabetes. His management during elementary and junior high school was very well monitored, which he was very pleased about. He praised himself on his strict management and therefore good glucose level readings. When he reached 16 years of age, he could not regulate his glucose levels very well. His levels would fluctuate, which frightened him. He had heard stories about people he knew with type 1 diabetes experiencing DKA (diabetic ketoacidosis) – see Ketones…what are they and what do they mean? , lows, and not having control over their lives. He became very anxious. He did not sleep at night, worrying about not waking up in the morning. He constantly tested his glucose levels and made readjustments. He became so tired, that he just wanted to sleep, but could not. He relayed this information to his endocrinology team and started to see the social worker. With this assistance, support and counselling, he has learned to be mindful of his body’s reactions to lows and highs, and has put his fears into perspective and is able to cope with them way better. He is happier and enjoying life more.

These cases illustrate the frustrations that can arise as individuals manage their diabetes. These are only two case examples; there are definitely other cases that may be worse.  As I stated in my last blog, if someone you know is experiencing problems with their diabetes management and is exhibiting depressive signs, please consult the endo team, family doctor or go to your nearest hospital emergency department for help.

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Case Report

Newly diagnosed type 1 diabetes complicated by ketoacidosis and peripheral thrombosis leading to transfemoral amputation, line bisgaard jørgensen.

1 Department of Medical Endocrinology, Odense University Hospital (OUH), Odense C, Denmark

2 Department of Orthopaedic Surgery, Odense University Hospital (OUH),, Odense C, Denmark

Knud Yderstræde

Peripheral vascular thromboembolism is a rarely described complication of diabetic ketoacidosis. We report a 41-year-old otherwise healthy man admitted with ketoacidosis and ischaemia of the left foot. The patient was unsuccessfully treated with thromboendarterectomy, and the extremity was ultimately amputated. The patient had no family history of cardiovascular disease, and all blood sample analyses for hypercoagulability were negative. We recommend an increased focus on peripheral thromboembolism, when treating patients with severe ketoacidosis.

Diabetes mellitus is associated with an increased incidence of thromboembolic complications. In type 2 diabetes mellitus there is clear evidence of thrombophilia partly explained by an increased level of plasminogen activator inhibitor . 1 It is not certain whether there is an increased risk of peripheral vascular thrombosis/embolism in patients with diabetic ketoacidosis. We present a case of diabetic ketoacidosis in a newly diagnosed individual with type 1 diabetes complicated by peripheral vascular insufficiency.

Case presentation

A 41-year-old man was admitted to hospital in a serious medical condition. Besides a history of herniated lumbar disc the patient was healthy. The patient had no history of hypertension, but blood pressure was 156/111 mmHg on admission. During the stay in hospital blood pressure stabilised at around 135/80 mmHg. There was no family history of cardiovascular disease. A few days before admission the patient had episodes of nausea, vomiting and abdominal pain. Additionally, he had polyuria and polydipsia. A few hours before admission, the patient reported acute pain in his left foot and was found to have a pulseless foot without vital signs. On admission an arterial blood gas showed metabolic acidosis (pH 7.02, base excess 24.6 , blood glucose 26 mmol/L) and blood ketones (acetone, acetoacetic acid and β-hydroxybutyric acid) were 6.6 mmol/L.

Investigations

The patient was diagnosed with type 1 diabetes mellitus supported by a low C peptide level of 43 (370–1470 pmol/L) and an antiglutamic acid decarboxylase (GAD) antibody titre of 4.7 (ref. 0–1.0). The complete blood count showed high white cell count of 20.9×10 9 /L but normal haemoglobin level of 8.4 mmol/L and platelet count of 199×10 9 /L. C reactive protein was below 1.0. Screening for a diversity of systemic inflammatory disorders including vasculitis and systemic lupus erythematosus (eg, antinuclear antibodies, antineutrophil cytoplasmic antibodies, lupus anticoagulant and cardiolipin antibodies) were all negative. Protein S and C levels were normal, antithrombin III level was reduced and the coagulation factors were increased (factor II, VII and X were 1.40 units (0.70–1.30) and factor VIII was 3.89 (0.60–1.30)). APTT (activated partial thromboplastin time) was prolonged to 46 s (27–40). Blood lipids were normal with total cholesterol 2.6 mmol/L, LDL-cholesterol 1.5 mmol/L, HDL-cholesterol 0.8 mmol/L and triglycerides 0.72 mmol/L. The ECG showed sinus rhythm without ischaemia, and an echocardiogram also was found normal. A duplex ultrasonography of the lower limbs showed no blood flow in the arteries of the left crus and foot.

Differential diagnosis

Buerger's disease, which is caused by inflammation of the arterial wall, is a relevant differential diagnosis. It mostly appears in smoking men between 20 and 40 years of age, corresponding to the individual in this case who reported smoking 10 cigarettes daily. However, symptoms are mostly less acute in Buerger's disease and the vascular surgeons found no evidence for this condition.

The patient was treated according to the guidelines for management of diabetic ketoacidosis and subsequently referred to a university hospital. Vascular surgery was performed including thromboendarterectomy in several large arteries in the left leg and medication to provide fibrinolysis was injected in the small arteries in the foot, which were too peripherally located to be accessible to surgery. But sufficient blood flow was not obtained due to peripheral thrombosis, and a below-knee amputation was performed. The amputation related wound did not heal after 1 week of observation, and eventually a transfemoral amputation was performed.

Only a few case reports on diabetic ketoacidosis complicated by thrombosis are present in the literature. The fibrinolytic system is disturbed in conditions of metabolic acidosis. Carl et al 2 described the haemolytic factors during diabetic ketoacidosis. They found decreased activity of proteins S and C, which are some of the most important inhibitors of the coagulation process. They also found increased activity of von Willebrand factor, which facilitates platelet adhesion. 3

Thus, it can be speculated that there is an increased risk of venous and arterial thrombosis and atheromatous plaques are prevailing, related to endothelial factors. In the case report presented here, the coagulation factors were affected in a way which indicated increased activity. Proteins S and C were normal, however, they were analysed 36 h after the initial treatment for ketoacidosis. The level of antithrombin III was reduced, probably related to the use of heparin.

Zipser et al 4 described a similar case report of a newly diagnosed individual with diabetes with ketoacidosis and acute aortoiliac and femoral artery occlusion. The patient was also amputated below the knee, but had a fatal outcome. Lin et al 5 describe a case report of ketoacidosis complicated by acute brachial artery thrombosis in a patient with a diabetes duration of 4 years. The brachial artery was rescued by surgical thrombectomy. Insufficiently regulated diabetes can also cause dyslipidemia with increased risk of atheroma formation and embolism arising from vascular endothelium with disintegrated morphology. Congenital hyperlipidaemia has been described to cause coronary artery disease and acute myocardial infarction in children. 6

In the case report presented here, the patient was newly diagnosed with diabetes with a short duration of symptoms of the disease. The patient had no history of thromboembolism and an echocardiogram could not identify any cardiac source of the embolism. The patient had sinus rhythm but it cannot conclusively exclude the likelihood of a transient arrhythmia precipitated by ketoacidosis, which could have caused the embolism. 7 The patient was not influenced by any intercurrent disease, but he was dehydrated because of vomiting during a couple of days. Dehydration in combination with diabetic ketoacidosis increases venous stasis and thereby the risk of deep venous thrombosis according to Virchow's triad. However, it has not been shown to be an independent variable as a cause of venous thrombosis. 5

The marked peripheral vascular changes resulted in significant oedema of the affected extremity, and even though compartment syndrome was excluded, it was not possible to achieve adequate healing. Abrupt onset of peripheral ischaemic symptoms without any history of claudication mitigated the possibility of Buerger's disease.

We present a case of diabetic ketoacidosis complicated by peripheral thromboembolism, which is a rare complication of diabetic ketoacidosis but can have devastating consequences with limb amputation or even death. We recommend an increased focus on peripheral thromboembolism, including assessment of pulse and general signs of peripheral vascular insufficiency (eg, pallor, pain and coldness), when treating patients with severe ketoacidosis. However, other causes of thromboembolism should be excluded before establishing diabetic ketoacidosis as the cause.

Learning points

• Diabetic ketoacidosis can promote a prothrombotic state.
• Peripheral thrombosis/embolism is a rarely described complication of diabetic ketoacidosis, and can have a devastating consequence with limb amputation or death.
• Other causes of thrombosis including cardiac source, thrombophilia, dyslipidemia should be excluded before determining diabetic ketoacidosis as a causative agent.

Contributors: LBJ was involved in the concept and design, literature search and drafting the article. KY was involved in the management of the patient, concept and design, drafting and critical review. OS participated in the management of the patient, reviewed and edited the article.

Competing interests: None.

Patient consent: Obtained.

Provenance and peer review: Not commissioned; externally peer reviewed.

A case report of type 1 diabetes mellitus coexistent with Charcot–Marie–Tooth type 1A and a literature review

• Case Report
• Published: 02 May 2024

Cite this article

• Ting Li 1 , 2 ,
• Xiangyang Chen 1 ,
• Xiaochi Tang 1 ,
• Ying Li 1 ,
• Hongmei Huang 1 &
• Nanwei Tong 2 , 3  

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Introduction

Charcot–Marie–Tooth disease (CMTD) is a common group of single-gene hereditary neuropathy characterized by chronic progressive exacerbation of distal limb weakness, sensory abnormalities, and nerve conduction dysfunction. It can be grouped into various subtypes based on the median nerve motor conduction velocity (MNCV) and gene mapping. CMTD1A is the most common subtype, accounting for > 50% of all subtypes, caused by the duplication of the peripheral myelin protein 22 (PMP22) gene on chromosome 17. Diabetes mellitus is a common metabolic disorder that frequently causes predominant sensory neuropathy. Diabetes with CMTD is not commonly reported. Especially diabetes type 1 (T1D) with CMTD1A has not been reported so far. This study reports a case of T1D with CMTD1A diagnosed by a gene test.

Upon the clinical manifestations, physical examination, EMG and genetic testing results, we diagnosed the patient as T1D with CMTD1A, and the related literatures were reviewed.

It is not yet clear whether there is a genetic association between the CMTD and diabetes, the genes causing CMTD are perhaps related to T1D and T2D genes. When CMTD and diabetes coexist, the resulting neuropathy is more severe than that observed with either condition alone. We recommend that such patients should strictly control their blood-glucose level to slow down the progression of the disease.

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Identification and clinical characterization of Charcot-Marie-Tooth disease type 1C patients with LITAF p.G112S mutation

Clinical and genetic features of a cohort of patients with MFN2-related neuropathy

Charcot-Marie-Tooth Disease

Timmerman V, Strickland AV, Zuchner S. Genetics of Charcot–Marie–Tooth (CMT) disease within the frame of the Human Genome Project Success. Genes (Basel). 2014;5(1):13–32.

Article   CAS   PubMed   Google Scholar  

Llewelyn JG, Tomlinson DR, Thomas PK. Diabetic neuropathies. In: Dyck Peter J, Thomas PK, editors. Peripheral neuropathy. Elsevier Saunders; 2005.

Google Scholar  

Gentile L, Russo M, Fabrizi GM, Taioli F, Ferrarini M, Testi S, et al. Charcot-Marie-Tooth disease: Experience experience from a large Italian tertiary neuromuscular center. Neurol Sci. 2020;41(5):1239–43.

Article   PubMed   Google Scholar  

Laura M, Hutton EJ, Blake J, Lunn MP, Fox Z, Pareyson D, et al. Pain and small fiber function in Charcot-Marie-Tooth disease type 1A. Muscle Nerve. 2014;50(3):366–71.

Valentijn LJ, Bolhuis PA, Zorn I, Hoogendijk JE, van den Bosch N, Hensels GW, et al. The peripheral myelin gene PMP22/GAS3 is duplicated in Charcot-Marie-Tooth disease type 1A. Nat Genet. 1992;1(3):166–70.

Pantera H, Moran JJ, Hung HA, Pak E, Dutra A, Svaren J. Regulation of the neuropathy-associated Pmp22 gene by a distal super-enhancer. Hum Mol Genet. 2018;27(16):2830–9.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Ohnishi A, Kashiwada E, Hashimoto T, Yamamoto T, Murai Y, Ohashi H, et al. A family of hereditary motor and sensory neuropathy type I with a mutation (Arg98–>His) in myelin Po-report on a second Japanese family. J UOEH. 1996;18:19–29.

Celik M, Forta H, Parman Y, Bissar-Tadmouri N, Demirkirkan K, Battaloglu E. Charcot-Marie-Tooth disease associated with Type 2 diabetes mellitus. Diabet Med. 2001;18:685–6.

Koc F, Sarica Y, Yerdelen D, Baris I, Battaloglu E, Sert M. A large family with Charcot-Marie-Tooth Type1a type 1a and Type type 2 diabetes mellitus. Int J Neurosci. 2006;116:103–14.

Yu Z, Wu X, Xie H, Han Y, Guan Y, Qin Y, et al. Characteristics of demyelinating Charcot-Marie-Tooth disease with concurrent diabetes mellitus. Clin Exp Pathol. 2014;7(7):4329–38.

CAS   Google Scholar  

Sun AP, Tang L, Liao Q, Zhang H, Zhang YS, Zhang J. Coexistent Charcot-Marie-Tooth type 1A and type 2 diabetes mellitus neuropathies in a Chinese family. Neural Regen Res. 2015;10(10):1696–9.

Article   PubMed   PubMed Central   Google Scholar  

Yan Z, Chen D, Yao L, Wang C, Ran XW. Diabetes coexistent with Charcot–Marie–Tooth disease presenting as a recurrent foot ulcer misdiagnosed as diabetic foot: A a case report. J Diabetes Investig. 2021;12:2099–101.

Win HH, Davenport C, Delaney S, Kelly M, Smith D. Charcot-Marie-Tooth disease complicating type 2 diabetes. J Am Podiatr Med Assoc. 2011;101(4):349–52.

Takakura Y, Furuya H, Yamashita K, Murai H, Araki T, Kikuchi H, et al. A case of Charcot-Marie-Tooth disease (CMT) type 1 complicated by diabetes mellitus (DM) showing bilateral phrenic nerve palsy. Rinsho Shinkeigaku. 2002;42:320–2.

PubMed   Google Scholar  

Sheth S, Francies K, Siskind CE, Feely SM, Lewis RA, Shy ME. Diabetes mellitus exacerbates motor and sensory impairment in CMT1A. J Peripher Nerv Syst. 2008;13:299–304.

Vega P, Farini ET, Carpio M, Carnelutto N, Chiaradia V, Pisarevsky AA. Diagnosis of Charcot–Marie–Tooth disease in a patient with type 1 diabetes. Medicina (Buenos Aires). 2017;77(4):329.

Secchin JB, Leal RC, Lourenco CM, Marques VD, Nogueira PTL, Santos ACJ, et al. High glucose level as a modifier factor in CMT1A patients. Peripher Nerv Syst. 2020;25(2):132–7.

Article   CAS   Google Scholar  

Sheth S, Francies K, Siskind CE, Feely SM, Lewis RA, Shy ME. Diabetes mellitus exacerbates motor and sensory impairment in CMT1A. J Peripher Nerv Syst. 2008;13(4):299–304.

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Li, T., Chen, X., Tang, X. et al. A case report of type 1 diabetes mellitus coexistent with Charcot–Marie–Tooth type 1A and a literature review. Int J Diabetes Dev Ctries (2024). https://doi.org/10.1007/s13410-024-01340-6

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Case Study of Type 1 Diabetes

Diabetes mellitus (DM) is a multisystem disease with both biochemical and anatomical/structural consequences. (Wolfsdorf et al: 2009) 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. Type 1 DM can occur at any age.It occurs most commonly in juveniles but can also occur in adults, especially in those in their late 30s and early 40s.

Unlike people with Type 2 DM, those with Type 1 DM are generally not obese and may 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, patients are dependent on exogenous insulin. Vanelli et al: 2007) Treatment of Type 1 DM in a young child requires a multidisciplinary approach inclusive of doctors, nurses, dieticians, parent/s and others who may have care for the child for periods longer than a few hours; so care and responsibility for Type 1 DM in a child, may also include teachers and extended family etc. (NICE 2004) In patients with new-onset Type 1 diabetes, lifelong insulin therapy must be started.As a chronic disease, Type 1 DM requires long-term medical attention, both to limit the development of its devastating complications and to manage them when they do occur, it is therefore essential that those caring for a child with Type 1 DM have a good working knowledge of the disease, and a practical understanding of how to manage and respond to this disease, if the child is too young to be able to manage this disease for themselves.

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(Craig et al: 2007) This case study examines the roles and responsibilities of those adults, who might have some element of accountability for managing and caring for a young child with Type 1 DMCase Study of V V, a 6 year old female, was taken to the doctor’s clinic with an approximate 10 lb. weight loss over the last few weeks; symptom’s included nausea, increased thirst and urination. When asked by the doctor, V denied having any abdominal pain. V’s father has had Type 1 DM for 14 years and one of V’s cousin’s was diagnosed with Type 1 DM at age 18 months. As a result of an existing family condition, the doctor tested V for Type 1 DM.

Medical tests confirmed that V was suffering from Type 1 DM.Because Type 1 DM is a catabolic disorder in which circulating insulin is very low or absent, plasma glucagon is elevated, and the pancreatic beta cells fail to respond to all insulin-secretory stimuli. Tests also disclosed that V’s pancreas evidenced lymphocytic infiltration and destruction of insulin-secreting cells of the islets of Langerhans, causing insulin deficiency. As a result of the confirmation of Type 1 DM, the doctor administered exogenous insulin to reverse V’s catabolic condition, prevent ketosis, decrease hyperglucagonemia, and normalise V’s lipid and protein metabolism.Prognosis for V. Whilst the family have an above average comprehension of the difficulties that V will experience for the rest of her life, despite their own experiences and knowledge, the doctor still had a duty of care to outline to V’s parents how he intended to advise and support V.

This is in keeping with best clinical practice, because every case of Type 1 DM has to be managed on an individual basis, according to the National Institute for Health and Clinical Excellence. NICE 2004) NICE guidelines also recommend that children and young people with Type 1 DM should be offered an on-going integrated package of care, by a multidisciplinary paediatric diabetes care team. The reasons for this are to optimise the efficacy of care and to reduce the risk of difficulties or complications that a child might experience, as a result of this disease. NICE also recommend that the careteam should include members with appropriate training in clinical, educational, dietetic, lifestyle, mental health and foot care aspects of diabetes for children and young people.Due to distance, as well as parental knowledge, the doctor advised that he thought it would be more practical for V to receive home based treatment and management, and arranged for the specialist diabetic nurse (SDN) within the practice to schedule home visits.

Medical tests for V were also organised to be held at the clinic, initially on a monthly basis, so that a professional monitoring of V’s condition could take place, as well as providing a forum for oversight and support, in respect of any family concerns that might arise as a result ofV’s disease. Clinical/ homecare of V by specialist diabetic nurse. Outside of her responsibility for scheduling home visits, the SDN organised for the clinics dietician to accompany her on V’s home visits for a three month period, to assess V’s progress and to formulate a dietary plan that provides V and her parents with all the necessary dietary information, to sustain and manage V’s disease, whilst providing a best outcomes scenario for V.Diet is an exceptionally important factor when managing Type 1 DM because the NICE target for long-term glycaemic control is an HbA1c level of less than 7. 5% without frequent disabling hypoglycaemia, therefore, V’s care package should be designed to attempt to achieve this. V will have a greater chance of keeping within desired levels if her diet is coordinated with her insulin management; consequently it is essential that a specialist diet is created that will account for the individual needs of V, to accomplish this.

Lawrence 2005) V’s parents will also require additional understanding in respect of their daughter’s dietary considerations, as they will have to cater to their daughter’s dietary needs for the foreseeable future, and these will differ to those of her father. The SDN has also arranged for the other specialists within her clinical team to arrange to visit V’s home or to attend to V on clinical visits, resulting in compliance with the current NICE guidelines.The SDN has also contacted V’s school, and arranged to assess the schools ability to respond to the management of V’s disease. Whilst the school nurse may have some training in managing Type 1 DM, there are likely to be occasions when they are not available to provide the necessary support, therefore it is essential that the school has an alternative/s to the school nurse, who also have the necessary training to be able to deal with V’s disease.The SDN’s assessment may result in training being provided to a number of other school staff, to offset the potential for the school nurse not being available, and this is also in keeping with best care outcomes. Although type 1 diabetes is a medical condition, it has a direct impact on cognitive functions when the blood sugar levels are out of range.

This means that children at school need access to their medication, insulin, and blood glucose testing equipment, in order to control this serious medical condition.Young children need help with injections, blood tests and interpretation of the results. All children will need help to monitor hypoglycaemia and moderate or severe episodes will be likely to need treating by a third party, especially if a child is young. High blood sugar effects the concentration levels significantly and is very harmful to the health of the child. In the short term high blood sugar causes frequent urination, blurred vision and difficulty concentrating and can make children feel very unwell.

High blood sugar is extremely harmful to the cells in the body, particularly those of the eyes, kidneys, circulatory system and nerves. Not treating high blood glucose levels can eventually lead to a condition called ketoacidosis, which, if not treated can be fatal. Hypoglycaemic episodes can occur despite best care practice, and it is therefore essential that an alternative trained school staff member is available within school hours; to respond to a hypoglycaemic episode, should one occur.This training is essential, because on rare occasions, a child with hypoglycaemic coma may not recover within 10 minutes, despite appropriate therapy. It has been advised that under no circumstances should further treatment be given, especially intravenous glucose, until the blood glucose level is checked and still found to be subnormal, without specialist training, overtreatment might occur.

Overtreatment of hypoglycaemia can lead to cerebral edema and death. (Craig et al: 2009) Another concern for the SDN is likely to be the fact that Type 1 DM is not a statemented concern within schools.Because Type 1 DM is as disease, there is no provision within education, to treat a child with this disease under any educational ‘Special Needs’ criteria. Nonetheless, a child with Type 1 DM is likely to suffer from educational deprivation, as they will require attention by the school nurse, lasting approximately 20 minutes per session, twice daily, five a days a week, resulting in 3. 35 hours of lost education weekly, and this could be more, if the needs of V require more than two interventions a day within school hours.Since there is no funding in place for extra support, whether this be for children needing general supervision with snacks and blood tests, for help to administer injections or for an extra trained staff member, to ensure safety on a school trip etc.

, whilst most parents do not consider their child with diabetes, to be disabled, or to have “learning difficulties” as such, all children diagnosed with diabetes should be considered under the Code of Practice (DfES 2001) as having SENs due to their medical needs.The Code of Practice acknowledges a relationship between a child’s medical status and educational needs, at paragraph 7. 65, it says that: “Medical conditions may have a significant impact on a child’s experiences and the way they function at school. The impact may be direct in that the condition may affect cognitive or physical abilities, behaviour or emotional state. The impact may also be indirect, perhaps disrupting access to education through unwanted effects of treatments or through the psychological effects that serious or chronic illness or disability can have on a child and their family. Type 1 diabetes, and its treatment, has a substantial effect on a child’s health and education because of the wide-ranging impact on the ability to learn and upon cognitive functions.

It is vital for schools to fully understand diabetes and how best to support a child with this medical condition in order for the child to access the full curriculum. Discussion with the parents and the school is therefore advisable, so that V is not marginalised educationally as a result of her disease. Parental role and responsibilitiesProvided the correct support and information is given to the parents, V’s disease can be regulated and managed appropriately to achieve best outcomes. Nonetheless, as V gets older, it is likely that she will want to manage her own medication and she should be taught and encouraged to do so. This training falls primarily within the role and responsibility of the parents, and they are likely to be the people who will provide V with the correct training, as well as the dietary information that V will require to enable and empower her to manage her disease.

Appropriate exercise, coupled to a healthy diet can minimise the impact that V will experience as a result of her condition. It is also the responsibility of the parents to ensure that V attends the clinic at the arranged times, and that she is encouraged to participate as fully as she is able in all of the schools curricula and non-curricular activities. Other social aspects of V’s life must also be considered and addressed. For normalisation to occur, (Osburn 2006) V must be encouraged to view her disease in the most productive manner.Others must also be encouraged to view V’s disease in a way that does not lead to V’s friends and other social relationships, treating V as anything other than a normal child.

Other parents should be encouraged to invite V to their children’s birthday parties, without becoming concerned that V might become hypoglycaemic if she has a slice of birthday cake. Conclusion As evidenced in this case study, as identified by NICE, it is important to have a multidisciplinary approach to the care and management of Type 1 DM.If the appropriate care package is provided for V, her condition need not become a life burdening millstone around her neck, and V can look forward to having a quality of life that is on Parr with other people who do not have a disability or disease. Whilst the prognosis for V is dependent upon other factors outside of her control, provided her parents, as well as those professionals who are involved with the well-being of V, contribute to a best outcomes approach, then hypoglycaemic episodes in V’s life will be greatly reduced, as a consequence of their input.Word count 2166 References Craig ME, Wong CH, Alexander J, Maguire AM, Silink M.

Delayed referral of new-onset type 1 diabetes increases the risk of diabetic ketoacidosis. Med J Aust 2009;190:219. DfES 2001 Special Education Needs: Code of Practice https://www. education. gov. uk/publications/standard/publicationDetail/Page1/DfES%200581%202001 last accessed on 15/1/2012 National Institute for Health and Clinical Excellence.

(2004) http://www. nice. org. uk/nicemedia/live/10944/29402/29402. pdf last accessed on

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Type 1 diabetes mellitus in childhood: a matched case control study in Lancashire and Cumbria, UK

Affiliation.

• 1 AstraZeneca Pharmaceuticals, Macclesfield, UK.
• PMID: 15317611
• DOI: 10.1111/j.1464-5491.2004.01282.x

Aims: The aim of the study was to identify environmental risk factors for insulin-dependent diabetes mellitus (Type 1 DM) in childhood.

Methods: A matched case-control study of Type 1 DM conducted in Lancashire and Cumbria, UK, using a structured interview. Cases (n=196, participation rate 83%) were children under 16 years of age diagnosed prior to October 1998 and attending diabetic clinics. Controls (n=381) were healthy children from the community matched by gender and by age (within a few days of birth). The data were analysed by logistic regression using the technique of Breslow and Day for matched case control studies.

Results: The multivariate regression model showed that the following factors were significantly associated with the risk of developing Type 1 DM (odds ratio, 95% confidence intervals): sharing a room with a sibling (0.458, 0.290-0.721), social contact with other children when aged 6-11 months (0.439, 0.256-0.752), consumption of sugary food (0.080, 0.024-0.261), parental insulin dependent diabetes mellitus (10.651, 3.086-36.761), maternal thyroid disease (4.861, 1.681-14.058), consuming more than one pint of milk per day prior to school entry (0.498, 0.310-0.802), maternal smoking during pregnancy (0.373, 0.218-0.636), a father with no academic qualifications (0.504, 0.278-0.913), maternal age at time of birth (0.900, 0.854-0.948), maternal infections in pregnancy (2.453, 1.011-5.948), other maternal illnesses or conditions in pregnancy (2.007, 1.139-3.535), belonging to an Asian family (0.104, 0.028-0.394), and regular contact with pets and other animals (0.552, 0.309-0.987).

Conclusion: Many of the results are consistent with the hygiene hypothesis which links improved living standards with decreased exposure to microorganisms and increased risk of immune mediated disease in childhood. These findings challenge the idea that improved hygiene acts exclusively through a Th2 mechanism leading to atopic disease as Type 1 DM is mediated by a Th1 reaction. The association with maternal smoking could be due to recall bias but a causal link cannot be excluded with confidence.

• Animals, Domestic
• Case-Control Studies
• Child, Preschool
• Diabetes Mellitus, Type 1 / ethnology
• Diabetes Mellitus, Type 1 / etiology*
• Dietary Carbohydrates / administration & dosage
• Family Health
• Infant Formula / administration & dosage
• Pregnancy Complications
• Risk Factors
• Smoking / adverse effects
• Social Environment
• Socioeconomic Factors
• Typhoid-Paratyphoid Vaccines / administration & dosage
• Dietary Carbohydrates
• Typhoid-Paratyphoid Vaccines

• Diabetes Care for Children & Young People

Vol:10 | No:03

Case study: A five-year-old boy with Down’s syndrome recently diagnosed with type 1 diabetes

• 18 Aug 2021

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He was started on insulin therapy with multiple daily injections and received a Dexcom G6™ (Dexcom Inc, San Diego, CA, USA) for real-time continuous glucose monitoring (rtCGM). The insulin regimen chosen was 1.5 units of long-acting insulin analogue (Levemir) with breakfast and 2.5 units at bedtime; and meal-time fast-acting insulin aspart (Fiasp). His parents were given carbohydrate counting education and he was started on insulin aspart injection with ratios of 1:15 for breakfast, 1:16 for lunch and 1:21 for dinner. A month after starting insulin therapy, his HbA 1c was 75 mmol/mol (11.7%).

There is a higher incidence of T1D in individuals with DS compared with the general population (Bergholdt et al, 2006, Rohrer et al, 2010). Furthermore, Bergholdt et al (2006) considered the prevalence of T1D in all children born in Denmark from 1981–2000 and found the prevalence of children with DS and T1D was 4.2 times higher than the prevalence of T1D in the background population. DS is also associated with a higher risk of developing other autoimmune conditions, such as coeliac disease and hypothyroidism (Lämmer et al, 2008; Aitken et al, 2013). In one study, the incidence of individuals with diabetes and DS who were diagnosed with thyroid disease and coeliac disease was 74% and 14%, respectively (Aitken et al, 2013). The child presented in this case study did not have a co-existing autoimmune condition at diagnosis, but there is an increased risk that he will develop  one in the future.

Additional challenges

A diagnosis of T1D has a huge impact on the lives of both the child and their parents. It involves a lifetime of daily injections, monitoring glucose levels and accounting for every meal and snack eaten. For all families of a recently diagnosed child this is a challenging time (Lindström et al, 2011), but for the family of a child with DS, there are additional challenges for both them and the diabetes care teams (Pikora et al, 2014). The aim of diabetes care is to provide education and support for the child and family, and ultimately to empower the developing adolescent to become independent in their daily diabetes management. DS adds additional challenges to this process (McVilly et al, 2014; Pikora et al, 2014).

The characteristics associated with DS need to be considered by the diabetes team when implementing insulin therapy. Cognitive development varies between individuals with DS, particularly with regards to language, processing language and verbal working memory (Silverman, 2007; Couzens et al, 2012). Additionally, Couzens et al (2012) suggested that long-term medical conditions affecting daily lives were associated with a negative impact on cognitive ability and development of the child with DS. The child in this case report is still very young and it is unclear how his cognitive development will progress. He currently attends a mainstream primary school and both parents have university level education; these two factors have been shown to be supportive of cognitive growth (Couzens et al, 2012).

Learning disability (LD) associated with DS may also affect the communication of common T1D symptoms such as thirst, headaches, blurred vision and mood change. These may not be well communicated, making it more difficult to monitor and manage the condition (Taggart et al, 2013). LD does not preclude common emotions, such as feeling different and self-conscious when monitoring glucose levels in front of others (Dysch et al, 2012; McVilly et al, 2014). This could be the reason why LD has also been associated with sub-optimal glycaemic control (Taggart et al, 2013). This may not always be the case, however. In contrast, Rohrer et al (2010) found individuals with DS and T1D achieved better HbA 1c and used less insulin than people with T1D without DS, despite their intellectual impairment. The authors speculated that this may be due to their simpler lifestyle and acceptance of routine. We should be mindful of these possibilities as the child develops.

Continuous glucose monitoring

The diabetes team opted to use continuous glucose monitoring (CGM) to overcome some of the issues of more challenging glycaemic control associated with LD. CGM is beneficial for children and young people (CYP) who have an impaired awareness of hypoglycaemia, or are unable to articulate symptoms of hypoglycaemia or hyperglycaemia, as was the situation with the  child in this case study (Danne et al, 2018). The internationally agreed target range for glucose levels is 3.9–10 mmol/L (Battelino et al, 2019) and CGM has been shown to improve “time in range”, regardless of the type of insulin therapy used.

The Dexcom G6 was chosen because it offers rtCGM and has been shown to increase time in range from 47.4% to 57.0% in children, when combined with a structured education programme (Pemberton et al, 2020). NICE (2015) recommends rtCGM with a hypoglycaemia alarm system for children with an inability to recognise and communicate the symptoms of hypoglycaemia. Puhr et al (2019) found the switch to Dexcom G6 with hypoglycaemia alarms reduced the time in hypoglycaemia by 40% for those with a hypoglycaemia threshold setting of 3.9 mmol/L, and by 33.3% for those with a threshold setting of 4.4 mmol/L. Pemberton et al (2020) report that the Dexcom G6 is currently the only device available in the UK which meets the Food and Drug Administration requirements for use in the ages 2–70 years, has four hypoglycaemia prevention alarms and does not require frequent finger-prick calibrations.

In the current case it was thought that, based on his age and current cognitive development, this child might not recognise and be able to communicate symptoms associated with low blood glucose levels (Taggart et al, 2013). The Dexcom G6 offers a solution to this and enables his parents to monitor real-time data, as well as reducing the frequency of finger-prick blood glucose tests. As with all children with T1D, DS does not reduce the perceived impact on daily life, and children with DS may still have a needle phobia (Pikora et al, 2014). His parents have found the ability to monitor his glucose levels throughout the day when he is at school reassuring. In addition, rtCGM allows overnight monitoring for nocturnal hypoglycaemia.

Fast-acting insulin

This child has a regular meal pattern and routine regarding his meal choices. Following discussions with his parents regarding meal patterns, a view was taken that although he tended to eat from a limited range of meals, the actual portion size of his meal varied and was often difficult to predict until during, or even after, the meal. The team decided that the most appropriate bolus insulin would be Fiasp, which has been shown to start acting 5 minutes earlier than insulin aspart (Heise et al, 2017; Russell-Jones et al, 2017; Shiramoto et al, 2018). The speed of onset offered the parents more flexibility at mealtimes to accommodate the fluctuating appetite of a five-year-old.

Diabetes education

The aim of education for CYP with T1D is to empower children and adolescents to manage their own diabetes according to their chosen management plan (Phelan et al, 2018). The same is true of education for children with special educational needs and LD (Dysch et al, 2012; McVilly et al, 2014). DS is associated with delays in overall cognitive development and language development (Finestack and Abbeduto, 2010; Quinn et al, 2020). As a team, we will need to adapt our style of education to reflect this child’s cognitive learning. This will involve working with the family to ensure that all diabetes-related education is unambiguous and to establish their  preferred style of communication.

Augmentative and alternative communication

As a team, we will need to consider different teaching strategies to help engage the child to participate in his own care as he gets older. One such strategy is augmentative and alternative communication (AAC). AAC is often used to support CYP with cognitive disabilities, including children with DS. Symbols are used to teach instructions and to communicate needs (Binger and Light, 2007; Finke et al, 2017; Quinn et al, 2020).

Multi-symbol messages and using symbols in different combinations can convey simple requests and tasks, such as “more milk” or “drink milk” (Binger and Light, 2007). AAC modelling (AAC-MOD) involves a combination of symbols while simultaneously modelling the spoken messages and is used to aid the child’s understanding of those messages (Quinn et al, 2020). AAC-MOD provides a method of communication to aid participation in daily routines.

Similarly, objects could be used as an alternative to symbols. Diabetes-related objects of reference could include an empty insulin pen with a symbol prior to receiving an injection, so the child understands what is about to happen. Symbols could then be used to create a schedule to help this child understand what he needs to do throughout  the day to manage his diabetes. These could be combined with a task schedule board. When a task is completed, it is removed from the schedule board. This can help remind a person which tasks have been completed and which are still to be done. At the time of writing, AAC-MOD had not yet been implemented in practice.

Children spend a significant proportion of their day at school, and maintaining glucose levels as near normal as possible is important in order to optimise their learning ability (Bratina et al, 2018). Schools in England should support children with medical conditions, so that they have full access to education (Department of Education, 2015). In pupils with medical conditions who have special education needs, this provision should be delivered in a coordinated way (Department of Education, Department of Health, 2015). Education, Health and Care Plans (EHCPs) are used to identify additional needs and are designed to increase collaboration between education, health and care teams (Boesley and Crane, 2018).

This child already had a comprehensive EHCP due to his pre-existing healthcare needs and has one-to-one support from a teaching assistant (TA) throughout the school day. This has enabled the school to accommodate his additional care needs as a result of diabetes. For example, his parents requested his insulin injections to be given in his classroom rather than in the school office, as had been the case with previous pupils with T1D. His mother describes him as stubborn and knew he could potentially refuse to go to the office. To minimise the negative associations with his diabetes, it was agreed his injections could be administered in the lobby area of his classroom. Due to the fact that this child had one-to-one support already in place through his existing EHCP, the school felt able to accommodate this and the additional medical care required as a result of his new diagnosis of T1D.

This child’s response to insulin injections varies and he will sometimes say “no, don’t hurt me” to his TA. To address concerns that his classmates might be distressed by this, parental permission was obtained for the Year 1 children to watch the BBC Get Well Soon episode “Learning more about diabetes”. This enabled the children to ask questions and was well received by the parents. His mother reports that he is comfortable engaging in his care in the classroom and his classmates appear happy to chat openly about it.

This child’s current primary school is working with his parents and healthcare team to tailor his support to meet his specific needs, and it has the resources to do so. As he progresses through secondary education, the healthcare team need to be cognizant that this may not always be the case. They  will need to continue to work collaboratively with future schools to ensure this tailored support can continue where practicable.

Future challenges

As a team we will need to develop our service and practice over the coming years to ensure this child has the support he needs to manage his diabetes. In the meantime, there is a paucity of studies about DS and the management of T1D, and McVilly et al (2014) suggest further research is needed to determine the type of support techniques and organisational support that are required to maximise active involvement by individuals with LD in the self-management of their diabetes. Whichever strategies are chosen, it will require ongoing collaboration, clear communication and coordinated planning between us, the healthcare team, his family, school staff and, at a later stage, the individual himself, to ensure he gains the support he needs and is empowered to manage his diabetes care as independently as possible.

Acknowledgement

The author would like to acknowledge Birmingham City University’s Children & Young Persons Diabetes Care Module.

Aitken R, Mehers K, Williams A et al (2013) Early-onset coexisting autoimmunity and decreased HLA-mediated susceptibility are the characteristics of diabetes in Down Syndrome. Diabetes Care 36 : 1181–85 Battelino T, Danne T, Bergenstal R et al (2019) Clinical targets for continuous glucose monitoring data interpretation: Recommendations from the International Consensus on Time in Range. Diabetes Care 42 : 1593–1603 Bergholdt R, Eising S, Nerup J, Pociot F (2006) Increased prevalence of Down’s syndrome in individuals with type 1 diabetes in Denmark: A nationwide population-based study. Diabetologia 49 : 1179–1182 Binger C, Light J (2007) The effect of aided AAC modeling on the expression of multi-symbol messages by preschoolers who use AAC. Augment Altern Commun 23 : 30–43 Boesley L, Crane L (2018) Forget the Health and Care and just call them Education Plans’: SENCOs’ perspectives on Education, Health and Care plans. J Res Spec Educ Needs 18 : 36–47 Bratina N, Forsander G, Annan F et al (2018) ISPAD Clinical Practice Consensus Guidelines 2018: Management and support of children and adolescents with type 1 diabetes in school. Pediatr Diabetes 19 : 287–301 Couzens D, Haynes M and Cuskelly M (2012) Individual and environmental characteristics associated with cognitive development in Down Syndrome: A longitudinal study. J Appl Res Intellect Disabil 25 : 396–413 Danne T, Phillip M, Buckingham B et al (2018) ISPAD Clinical Practice Consensus Guidelines 2018: Insulin treatment in children and adolescents with diabetes. Pediatr Diabetes 19 : 115–35 Department of Education (2015) Supporting pupils at school with medical conditions: Statutory guidance for governing bodies of maintained schools and proprietors of academies in England . Available at: https://bit.ly/3uegTdc(acessed 04.05.21) Department of Education, Department of Health (2015) Special educational needs and disability code of practice 0 to 25 years: Statutory guidance for organisations which work with and support children and young people who have special educational needs or disabilities. Available at: https://bit.ly/3gZ7zWK (accessed 04.05.21) Dysch C, Chung M, Fox J (2012) How do people with intellectual disabilities and diabetes experience and perceive their illness? J Appl Res Intellect Disabil 25 : 39–49 Finke EH, Davis JM, Benedict M et al (2017) Effects of a least-to-most prompting procedure on multisymbol message production in children with autism spectrum disorder who use augmentative and alternative communication. Am J Speech Lang Pathol 26 : 81–98 Finestack LH, Abbeduto L (2010) Expressive language profiles of verbally expressive adolescents and young adults with Down syndrome or fragile X syndrome. J Speech Lang Hear Res 53 : 1334–8 Heise T, Pieber TR,  Danne T et al (2017) A pooled analysis of clinical pharmacology trials investigating the pharmacokinetic and pharmacodynamic characteristics of fast-acting insulin aspart in adults with type 1 diabetes. Clin Pharmacokinet 56 : 551–9 Lämmer C, Weimann E (2008) Early onset of type I diabetes mellitus, Hashimoto’s thyroiditis and celiac disease in a 7-yr-old boy with Down’s syndrome. Pediatr Diabetes 9 : 423–5 Lindström C, Aman J, Norberg AL (2011) Parental burnout in relation to sociodemographic, psychosocial and personality factors as well as disease duration and glycaemic control in children with type 1 diabetes mellitus. Acta Paediatr 100 : 1011–7 McVilly K, McGillivray J, Curtis A et al (2014) Diabetes in people with an intellectual disability: A systematic review of prevalence, incidence and impact. Diabet Med 31 : 897–904 NICE (2015) Diabetes (type 1 and type 2) in children and young people: Diagnosis and management . NICE, London [NG18]. Available from: https://www.nice.org.uk/NG18 (accessed 04.05.21) Pemberton J, Kershaw M, Dias R et al (2020) DYNAMIC: Dynamic glucose management strategies delivered through a structured education program improves time in range in a socioeconomically deprived cohort of children and young people with type 1 diabetes with a history of hypoglycemia. Pediatr Diabetes 22 : 249–60 Phelan H, Lange K, Cengiz E et al (2018) ISPAD Clinical Practice Consensus Guidelines 2018: Diabetes education in children and adolescents. Pediatr Diabetes 19 : 75–83 Pikora T, Bourke J, Bathgate K et al (2014) Health conditions and their impact among adolescents and young adults with Down Syndrome PloS One 9 : e96868 Puhr S, Derdzinski M, Welsh JB et al (2019) Real-world hypoglycemia avoidance with a continuous glucose monitoring system’s predictive low glucose alert. Diabetes Technol Ther 21 : 155–8 Quinn ED, Kaiser AP, Ledford JR (2020) Teaching preschoolers with Down Syndrome using Augmentative and Alternative Communication Modeling during small group dialog reading. Am J Speech Lang Pathol 29 : 80–100 Rohrer T, Hennes P, Thon A et al (2010) Down’s syndrome in diabetic patients aged <20 years: An analysis of metabolic status, glycaemic control and autoimmunity in comparison with type 1 diabetes. Diabetologia 53 : 1070–5 Russell-Jones D, Bode B, DeBlock C et al (2017) Fast-acting insulin aspart improves glycemic control in basal-bolus treatment for type 1 diabetes: Results of a 26-week multicenter, active-controlled, treat-to-target, randomized, parallel-group trial. Diabetes Care 40 : 943–50 Shiramoto M, Nishida T, Hansen AK, Haahr H (2018) Fast-acting insulin aspart in Japanese patients with type 1 diabetes: Faster onset, higher early exposure and greater early glucose-lowering effect relative to insulin aspart. J Diabetes Investig 9 : 303–10 Silverman W (2007) Down syndrome: cognitive phenotype. Ment Retard Dev Disabil Res Rev 13 : 228–36 Taggart L, Coates V, Truesdale-Kennedy M (2013) Management and quality indicators of diabetes mellitus in people with intellectual disabilities. J Intellect Disabil Res 57 : 1152–63

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• Open access
• Published: 13 May 2024

Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes

• Mingqian He 1   na1 ,
• Guixue Hou 2   na1 ,
• Mengmeng Liu 1   na1 ,
• Zhaoyi Peng 1 ,
• Hui Guo 1 ,
• Yue Wang 1 ,
• Jing Sui 3 ,
• Hui Liu 4 ,
• Xiaoming Yin 5 ,
• Meng Zhang 1 ,
• Ziyi Chen 1 ,
• Patrick C.N. Rensen 1 , 6 ,
• Liang Lin 2 , 8 ,
• Yanan Wang 1 , 7 &
• Bingyin Shi 1  

Journal of Translational Medicine volume  22 , Article number:  448 ( 2024 ) Cite this article

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The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR.

A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi’an JiaoTong University were selected as the discovery set. One-to-one case–control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography–mass spectrometry (LC–MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry.

The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients.

Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.

Introduction

Type 2 diabetes mellitus (T2DM) is a common chronic disease in many countries, and its prevalence is growing as people’s lifestyles are changing [ 1 ]. Diabetes causes various complications, classified as either macrovascular complications (such as cardiovascular disease and stroke) or microvascular complications (such as kidney disease) [ 2 ]. Diabetic retinopathy (DR), a specific microvascular complication of diabetes, is the most common cause of vision loss in people of working age [ 3 , 4 ]. Poor glycemic control, hypertension, and diabetes duration are major risk factors for DR [ 5 ]. Although intensive risk factor control reduces the risk of DR progression and vision loss, many diabetic patients continue to develop DR with strict glycemic and blood pressure control [ 6 ]. Despite increasing research supporting the efficacy of routine DR screening to prevent DR and early treatment to reduce the risk of vision loss, there are no specific biomarkers for diagnosing the onset and early progression of DR. Additionally, new and more effective strategies are awaited to prevent and treat the progression of DR.

Accumulating evidence suggests that disruption in lipid metabolism is an early event in the pathogenesis of diabetes complications. Previous studies found that levels of multiple lipid species, including glycerophospholipids, sphingolipids and glycerolipids, are critical risk factors for T2DM and its complications [ 7 , 8 ]. Lysophosphatidylcholine (LPC) is a main glycerophospholipid known for its essential role in lipid and glucose metabolism, and LPC has been intensively studied in the development of metabolic diseases including T2DM [ 9 ]. Sphingolipids, including ceramides (Cer), sphingomyelins (SM) and gangliosides, have a variety of intra- and extracellular effects on glucose homeostasis and metabolic disease [ 10 ] Numerous studies suggest Cer, a crucial lipid intermediate in sphingolipid metabolism, is a major contributing factor for insulin resistance, and inhibition or depletion of enzymes driving de novo ceramide synthesis can prevent the development of diabetes in mice [ 7 , 11 , 12 ]. In contrast, a decrease in very long chain Cer is correlated with the development of macroalbuminuria in diabetes [ 13 ]. Accelerated sphingolipid catabolism’ leading to an increase in glucosylceramide or glycosphingolipids might contribute to the neuronal pathologies of DR [ 14 ]. In addition, SM produced by the transfer of a phosphocholine moiety from phosphatidylcholine to the ceramide backbone has been linked to insulin resistance [ 15 , 16 ] and is also an independent marker of cardiovascular disease [ 17 ]. Thus, dysregulated lipid metabolism is a major contributor to the pathogenesis of T2DM and its complications, and specific lipid species that are responsible for the occurrence of DR are rather obscure.

Lipidomics offers solid platforms for identifying novel lipid mediates in biochemical processes of lipid metabolism, thus providing new opportunities for disease prediction and detection [ 18 , 19 ]. Lipidome analysis is performed by liquid chromatography and electrospray ionization-tandem mass spectrometry (LC–MS/MS) for molecular lipid identification and quantification and multiple reaction monitoring (MRM) for targeted quantification of those lipid species. Lipid-based biomarkers offer unique options for precision medicine by providing sensitive diagnostic tools for disease prediction and monitoring [ 20 ]. Using a quantitative metabolomics approach, Emil et al. compared the aqueous humor and serum concentrations of metabolites in senior adults with an without diabetes who underwent cataract surgery [ 21 ]. However, the field of lipidomics studies of DR is still in its early stages, with few studies published and little replication of results [ 22 ].

In this study, we aimed to find reliable serum lipid-based biomarkers for the presence of DR in patients with T2DM by using two cohorts. To this end, serum samples of the discovery cohort was subjected to untargeted lipidomics analysis to search for differentially abundant lipids between individuals without and with DR. In the validation cohort, the observed differential lipid molecules were validated using mass spectrometry MRM targeting techniques. We hypothesized that DR has a distinctive serum lipid signature and that particular lipid species can act as biomarkers for T2DM patients with DR.

Research design and methods

Participants.

A total of 622 participants with T2DM hospitalized in the Endocrinology Department of the First Affiliated Hospital of Xi’an JiaoTong University were screened as the discovery set. Participants with chronic kidney disease [estimated glomerular filtration rate (eGFR) < 90 (mL/min/1.73 m 2 )] were excluded from the selection. We conducted pair matching according to the traditional risk factors for DR (including age, duration of diabetes, HbA1c level, and hypertension). For the discovery cohort, we selected 42 T2DM patients with DR (DR group). The control participants were 42 T2DM patients without DR (NDR group), and they were matched to patients in the DR group by age (in 5-year bands), diabetes duration (in 5-year bands), HbA1c levels (in 0.5% bands), and hypertension status.

Lipid markers of DR identified from the discovery cohort were quantified in a separate sample cohort (validation cohort). We first screened 531 T2DM patients. Individuals with chronic kidney disease [eGFR < 90 (mL/min/1.73 m 2 )] were excluded from the selection. Then, we conducted 1:1 propensity score matching (PSM) (matching tolerance = 0.02) by age, diabetes duration, HbA1c level, hypertension status, sex, BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), and eGFR. For the validation cohort, 95 T2DM patients with DR (DR group) and 95 T2DM patients without DR (NDR group) were included.

Sample collection

Fasting blood samples and clinical data were collected from the individuals. All blood samples were collected at the First Affiliated Hospital of Xi’an JiaoTong University physical examination center. Blood samples were centrifuged for 20 min at 1500 rpm and 4 °C. Then, serum was collected and stored at -80 °C until analysis. HbA1c was measured using an automatic HbA1c analyzer (TOSOH BIOSCIENCE, INC.; HLC-723G8). Total cholesterol (CHOL), triglyceride (TG), high density lipoprotein-cholesterol (HDL-c), low density lipoprotein-cholesterol (LDL-c), uric acid (UA), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), total bilirubin (TBIL), direct bilirubin (DBIL), total protein (TP), albumin (ALB), glucose (GLU), blood urea nitrogen (BUN), creatinine (CRE) were measured using standard reagents on an automatic biochemistry analyzer (HITACHI, Inc.; LAbOSPECT, 008AS). Blood pressure was measured in triplicate using an Omron HBP-9020 digital automatic blood pressure machine (Kyoto, Japan).

Lipid extraction

The serum samples were thawed slowly at 4 °C, 100 µL of the sample was placed in a 96-well plate, 300 µL of isopropanol (prechilled at -20 °C) spiked with internal standards (SPLASH® LIPIDOMIX® Mass Spec Standard, Avanti, USA) was added, and the samples were vortexed and mixed for 1 min and then centrifuged at 4 °C for 20 min at 4000 rcf after resting overnight at -20 °C as previously reported [ 23 ]. The supernatant was injected for LC–MS/MS analysis, and 10 µL of each supernatant was mixed into quality control (QC) samples to assess the reproducibility and stability of the LC–MS analysis process.

LC–MS/MS analysis

Lipids were separated and detected by an UPLC (CSH C18 column, 1.7 μm 2.1*100 mm, Waters, USA) equipped with a Q Exactive Plus high-resolution mass spectrometer (Thermo Fisher Scientific, USA) as previously reported [ 24 ]. The following gradient was used for elution: 0–2 min, 40-43% mobile phase B (10 mM ammonia formate, 0.1% formic acid, 90% isopropyl alcohol, and 10% acetonitrile); 2–2.1 min, 43-50% liquid B; 2.1–7 min, 50-54% solution B; 7–7.1 min, 54-70% liquid B; 7.1–13 min, 70-99% liquid B with a flow rate of 0.35 mL/min. Mobile phase A was an aqueous solution containing 10 mM ammonia formate, 0.1% formic acid and 60% acetonitrile in water.

All samples were analyzed in data-dependent acquisition (DDA) mode with the following positive/negative ionization settings: spray voltage, 3.8/–3.2 kV; aux gas heater temperature, 350 °C; and capillary temperature, 320 °C. The full scan mass range was 200–2000 m/z with 70,000 mass resolution at m/z 200 and AGC set to 3e6 with a maximum ion injection time of 100 ms. The top three precursors were selected for subsequent MS fragmentation with a maximum ion injection time of 50 ms and resolution of 17,500 at m/z 200, and the AGC was 1e5. The stepped normalized collision energy was set to 15, 30, and 45 eV.

Data preprocessing and quality control

The raw data obtained from the LC–MS/MS detection were imported into LipidSearch v.4.1 (Thermo Fisher Scientific, USA) for lipid identification and quantification. The following parameters were used for lipid identification and peak extraction: the type of identification was Product, the mass deviation of the parent and daughter ions was 5 ppm, and the response threshold was set to 5.0% of the relative response deviation of the daughter ions; the quantitative parameters were set to calculate the peak areas of all identified lipids, and the peak extraction mass deviation was set to 5 ppm. For ESI + data, [M + H]+, [M + NH4]+, and [M + Na] + were selected as adducts, while for ESI- data, [M-H]-, [M-2 H]-, and [M-HCOO]- were selected as adducts. The peak alignment was performed for all identified lipids, and those not marked as “rejected” were considered for inclusion in the subsequent analysis.

For data preprocessing, raw data exported from LipidSearch were further analyzed by meta X [ 25 ]. The data preprocessing included (1) Removing lipid molecules with more than 50% missing information in QC samples and more than 80% missing information in experimental samples (i.e., LipidIon in the table); (2) Filling the missing values using the k-nearest neighbor (KNN) algorithm; (3) Correcting the batch effect using quality control-based robust LOESS signal correction (QC-RLSC); (4) Using probabilistic quotient normalization (PQN) to normalize the data to obtain the relative peak areas; and (5) Removing the lipid molecules with a coefficient of variation (CV) greater than 30% of the relative peak areas from all QC samples.

Data quality was assessed by the reproducibility of QC sample assays. The assessment included chromatogram overlap of QC samples, principal component analysis (PCA), number of extracted peaks, and differences in peak response intensity.

Data processing

A combination of multivariate statistical analysis and univariate analysis was used to screen for lipids of which the abundance differed between groups. The multivariate statistical analysis methods used were principal component analysis (PCA) and partial least squares method-discriminant analysis (PLS-DA). PCA is an unsupervised pattern recognition method, and PLS-DA is a supervised pattern recognition method. The univariate analyses were fold change (FC) and Student’s t test. The FC was obtained by fold change analysis, and the p  value pairs of the t test were corrected for the false discovery rate (FDR) to obtain a q-value. The differential lipid molecule screening conditions were as follows: (1) variable importance in the projection (VIP) ≥ 1 for the first two principal components of the PLS-DA model; (2) fold change ≥ 1.2 or ≤ 0.83; and (3) p  value < 0.05.

Targeted lipid quantification by MRM in validation samples

The identified differential lipids were further quantified by multiple reaction monitoring (MRM). For lipid extraction, the procedure was consistent with the untargeted experiment as described. The MRM transition list is shown in Table S1 . For MRM quantification, all validation samples were analyzed on a QTRAP 5500 mass spectrometer with a CSH C18 column (1.7 μm 2.1*100 mm, Waters, USA) for separation. All lipids were subjected to targeted quantification in ESI + mode with a specific transition setting.

Statistical analysis

The clinical data of samples are presented as the mean ± standard deviation (SD) for normally distributed variables or the median (interquartile range) for abnormal distribution. Comparisons between the case group and the control group were made using a two-tailed t test or Mann-Whitney U test for continuous data and the X 2 test for categorical data. The calculation of the area under the curve (AUC) in receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminatory ability of the markers. Logistic regression models were applied to assess the relationship between lipid molecules and the presence of DR. The odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for the molecules with 1-SD changes. The known risk factors for DR, such as CHOL, TGs, LDL-c, and HDL-c, were added to multivariate logistic regression to calculate the adjusted odds ratios. Ordinal logistic regression models were used to assess the relationships between lipid molecules and DR stages [NDR, nonproliferative DR (NPDR) and proliferative DR (PDR)].

Characteristics of the discovery cohort

Table  1 shows the clinical characteristics of individuals selected for the discovery cohort. There were no significant differences in age and sex between the DR and NDR groups. In fact, these groups were comparable for most metabolic characteristics, such as BMI, diabetes duration, and HbA1c, and there were no significant between-group differences for hypertension status, antihypertensive agent use, hypoglycemic therapy status or NSAID use. The blood pressure and glucose of the participants were treated and controlled. Compared with control subjects with T2DM, T2DM patients with DR had higher levels of LDL-c levels, AST, TBIL, and BUN (Table  1 and Table S2 ).

Untargeted lipidome-derived biomarkers for diabetic retinopathy: results from the discovery cohort

A total of 1721 lipids were detected. The number of lipids with an RSD (CV) less than or equal to 30% in the QC samples was 1421. The ratio of the number of lipids with CV less than or equal to 30% to the number of all detected lipids in QC samples was 81%.

Fifteen candidate lipids were identified from the discovery cohort. Compared with those of the NDR group, the levels of three Cer and seven SM were significantly lower in the DR group. In contrast, two SM, two LPC and one PC were significantly higher in the DR group (Fig.  1 A and B). More specifically, compared with T2DM patients without DR, T2DM patients with DR showed lower levels of Cer(d18:0/24:0), Cer(d18:0/22:0), Cer(d42:3), SM(d22:0/16:0), SM(d18:1/24:1), SM(d42:0), SM(d40:0), SM(d39:0), SM(d38:0), and SM(d36:0), and higher levels of SM(d20:1/16:1), SM(d34:1), LPC(18:2), LPC(16:0) and PC(34:2). The heat map shows the distribution of these lipids between individuals of the NDR and DR groups (Fig.  1 C). The results of ROC analysis and the odds ratios of the lipid markers in the basic logistic regression models are shown in Table  2 . The AUC values for the 15 lipids ranged from 0.72 to 0.94. All lipids retained significant ORs after adjusted for CHOL, TG, LDL-c, and HDL-c (adjusted ORs are shown in Table  2 ). Furthermore, we used ordinal logistic regression, which estimated the odds of being in one higher category of the DR stage (from NDR to PDR) for lipid species, to test the associations between lipid species and DR stage (Table S3 ; n  = 42 in the NDR group, n  = 37 in the NPDR group, n  = 5 in the PDR group), and we analyzed the data while excluding participants with diabetic macular edema (DME) ( n  = 4 in the DR group), as before, all lipids retained significant ORs (Table S4 ).

Lipidome-derived markers identified from the discovery cohort. Lipidomic analysis identified fifteen candidate lipids of which serum levels were different between 42 T2DM patients with DR (DR group) and 42 T2DM patients without DR (NDR group) from the discovery cohort. ( A ) Mean peak intensity of lipids was analyzed after Log2 transformation of the data. ( B ) Fold change in DR/NDR was analyzed after Log2 transformation of the data. ( C ) Heatmap showing the distribution of lipid markers. Each row in the figure represents a different lipid, and each column represents a sample. Different colors indicate different intensities, and Log2 conversion was used for the data

Characteristics of the validation cohort and targeted lipidomics analysis

The 15 differential lipids found from the discovery cohort were validated in another set of samples. The clinical characteristics of individuals selected for the validation cohort are shown in Table  3 . Most metabolic and clinical features were comparable (Table S5 ), and there was no significant difference in LDL-c between the DR and NDR groups.

In the validation cohort, when compared with subjects in the NDR group, T2DM patients with DR showed lower levels of Cer(d18:0/24:0), Cer(d18:0/22:0), Cer(d42:3) and SM(d18:1/24:1) by univariate logistic regression, which was consistent with the results of the discovery cohort. However, the levels of SM(d20:1/16:1), LPC(18:2) and LPC(16:0) were lower in T2DM patients with DR from the validation cohort, opposite to the result obtained in the discovery cohort (Fig.  2 A and B). The AUC values for these lipids were higher than 0.61. The other 8 lipids did not significantly differ between the DR and NDR groups in the validation cohort (Table  4 ). Of note, compared with those in T2DM patients, the peak area (after Log2 transformation) of Cer(d18:0/24:0) (20.48 ± 0.82 vs. 20.12 ± 0.99, p  = 0.006, Fig.  2 C) and Cer(d18:0/22:0) (19.91 ± 0.75 vs. 19.64 ± 0.92, p  = 0.028, Fig.  2 C) remained significantly lower in T2DM patients with DR, and the levels of these two lipids retained significant ORs when adjusted for known risk factors (i.e., CHOL, TG, LDL-c and HDL-c). In the ordinal regression, these two lipids maintained significant ORs (Table S7 , n  = 95 in the NDR group, n  = 87 in the NPDR group; n  = 8 in the PDR group), and were also significant while excluding patients with DME (Table S6 , n  = 2 in the DR group). These findings imply that levels of Cer(d18:0/24:0) and Cer(d18:0/22:0) were independent markers for T2DM patients with DR in both the discovery cohort (Table  2 ) and validation cohort (Table  4 ).

The results of targeted lipidomics analysis in the validation cohort. For the validation cohort, the cases were 95 T2DM patients with DR (DR group), and the control subjects were 95 T2DM patients who had no DR (NDR group). ( A ) Peak area of lipids was analyzed after Log2 transformation of the data. ( B ) Fold change in DR/NDR was analyzed after Log2 transformation of the data. ( C ) The log2 conversion was used for the intensities of Cer(d18:0/24:0) and Cer(d18:0/22:0). All data are presented as the mean ± standard deviation (SD). Each symbol represents an individual participant. * p  < 0.05, ** p  < 0.01, pairwise comparisons of change scores between the groups were evaluated by t test

DR is the most common microvascular complication of diabetes and the main factor contributing to visual impairment in working-age individuals [ 3 ]. T2DM patients often develop DR despite of proper control of systemic risk factors, indicating the involvement of other pathogenic factors for DR development. To find new and more effective strategies for preventing and treating DR, it is necessary for us to identify novel biomarkers for DR screening or detection. Lipidomics will aid in understanding the mechanism of DR at various stages of the disease, early diagnosis, and the identification of new therapeutic targets. In this study, by using two clinical cohorts, we found that the serum lipidomic profiles in T2DM patients with DR showed significant differences from those in T2DM patients without DR. The differential lipid species in the DR group were linked to disturbances in sphingolipid metabolism. Compared with those in the NDR group, the levels of Cer(d18:0/24:0) and Cer(d18:0/22:0) were significantly lower in the DR group after adjusting for covariates, i.e. known risk factors in both the discovery and validation cohorts. These findings suggest that these two lipid species may be potential serological markers for the diagnosis of DR in patients with T2DM.

In this study, we found two ceramide molecules that were significantly lower in T2DM patients with DR, indicating that they may have disturbed ceramide metabolism compared to T2DM patients without DR. Ceramide is sphingolipid [ 11 ] and can be found in VLDL, LDL, and HDL. Consistent with our findings, Fort et al. found a significantly lower abundance of Cer in central retinal tissue obtained postmortem from T2DM patients with DR compared to those without DR [ 26 ]. Similarly, ceramide levels were shown to be lower and glucosylceramide levels higher in the retinas of diabetic rodents [ 27 ]. This indicates that diabetes reduces the retinal ceramide content and may suggest that dysregulated sphingolipid metabolism may cause retinal resistance to insulin action [ 27 ]. These findings imply that ceramide is diverted from the overall pools of retinal sphingolipids toward the glycosylated forms due to hyperglycemia. In contrast, Levitsky et al. found that diabetes-induced increases in mitochondrial ceramide led to impaired mitochondrial function in the retinal pigment epithelial (RPE) cells of the retina [ 28 ], and disruption of the blood-retinal barrier might be caused by diabetes-induced overexpression of acid sphingomyelinase. Additionally, inflammation is a common underlying factor in DR, and inflammation generates Cer from SM in the serum membrane. This induces death receptor ligand formation and leads to apoptosis of RPE and photoreceptor cells [ 29 ]. In addition to diabetes, circulating Cer was shown to strongly correlate with future adverse cardiovascular events. It has recently been discovered that in individuals with atherosclerotic CVD, serum levels of specific Cer species can predict the future risk of cardiovascular death. In the Corogene study, higher concentrations of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) and lower concentrations of Cer(d18:1/24:0) were associated with a higher risk of fatal myocardial infarction [ 30 ]. Our study found that Cer(d18:0/24:0) and Cer(d18:0/22:0) were significantly lower in T2DM patients with DR compared to those without DR, which suggests that different numbers of carbons and double bonds in ceramides might play differential roles in DR and CVD. The distinct ceramides and ceramide metabolites involved in metabolic regulation play unanticipated roles [ 31 ]. Watt et al. discovered that circulating ceramides present in LDL particles were sufficient to induce insulin resistance in vitro and in vivo [ 32 ]. However, how these two identified ceramides influence lipid metabolism in T2DM remains unclear and needs further exploration. Thus, disturbed Cer metabolism may contribute to dysfunction in DR, and therapeutic strategies to restore normal Cer metabolism might be an effective approach for treatment of DR.

In the discovery cohort, LPC(18:2) and LPC(16:0) were significantly higher in T2DM patients with DR. However, these two lipids were significantly lower in DR in the validation cohort. The previous findings point to a change in sphingolipid composition between control and T2DM [ 33 ]. LPC is an inflammatory phospholipid and an important atherogenic substance in LDL that contributes to diabetic complications [ 34 ]. Lipoprotein-associated phospholipase A2 (Lp-PLA2) plays a crucial role in diabetes-related retinal vasopermeability, a response mediated by LPC, and inhibiting Lp-PLA2 reduces diabetes-induced retinal vasopermeability [ 35 ]. LPC O-16:0, LPC P-16:0, LPC O-18:0, and LPC 18:1 were all found to be inversely related to incident T2DM [ 36 ]. The differences between the discovery and validation cohorts may be related to the populations studied, medications used, and stages of diabetic retinopathy [ 37 ].

There are some limitations of this study. First, only a Chinese ethnic group was selected, and future validation of our findings in other races or ethnic groups is warranted. Second, instead of chronic risk factors associated with the development of DR, some of the identified lipid markers might only represent temporary metabolic perturbations in this cross-sectional study. Third, the exact mechanism of DR development in patients with T2DM through which ceramide functions has not been explained. Therefore, more extensive preclinical and clinical studies are needed to clarify the mechanisms behind the potential effects of specific lipids.

Overall, the deregulation of sphingolipid metabolism in the diabetic retina appears to be a significant and seldom-studied element of DR pathophysiology. The precise mechanism underlying this disease is still unknown and requires further investigation. We showed the potential value of lipidomics research in understanding the pathophysiology of DR, and the results suggest that lipidomics profiling may be capable of identifying early-stage DR diagnostic indicators in high-risk Chinese populations. In addition, the findings from this study may help in the elucidation of new therapeutic targets for DR prevention and treatment.

Data availability

All relevant data and materials have been included in the article and its supplementary data files. Further inquiries can be directed to the corresponding authors.

Abbreviations

• Type 2 diabetes mellitus

Diabetic retinopathy

Liquid chromatography–mass spectrometry

Partial least squares discriminant analysis

Variable importance in the projection

Propensity score matching

Sphingomyelins

Phosphatidylcholine

Lysophosphatidylcholines

Multiple reaction monitoring

Systolic blood pressure

Diastolic blood pressure

Total cholesterol

Triglyceride

High density lipoprotein-cholesterol

Low density lipoprotein-cholesterol

Aspartate aminotransferase

Alanine aminotransferase

Alkaline phosphatase

Gamma-glutamyl transpeptidase

Total bilirubin

Direct bilirubin

Total protein

Blood urea nitrogen

Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010;87:4–14.

Article   CAS   PubMed   Google Scholar  

Wong TY, Cheung CM, Larsen M, Sharma S, Simo R. Diabetic retinopathy. Nat Rev Dis Primers. 2016;2:16012.

Article   PubMed   Google Scholar  

American Diabetes A. 10. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41:S105-S18.

Jampol LM, Glassman AR, Sun J. Evaluation and care of patients with Diabetic Retinopathy. N Engl J Med. 2020;382:1629–37.

Yau JW, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012;35:556–64.

Article   PubMed   PubMed Central   Google Scholar  

Beulens JW, Patel A, Vingerling JR, Cruickshank JK, Hughes AD, Stanton A, et al. Effects of blood pressure lowering and intensive glucose control on the incidence and progression of retinopathy in patients with type 2 diabetes mellitus: a randomised controlled trial. Diabetologia. 2009;52:2027–36.

Meikle PJ, Summers SA. Sphingolipids and phospholipids in insulin resistance and related metabolic disorders. Nat Reviews Endocrinol. 2017;13:79–91.

Article   CAS   Google Scholar  

Zeng W, Beyene HB, Kuokkanen M, Miao G, Magliano DJ, Umans JG, et al. Lipidomic profiling in the strong heart study identified American indians at risk of chronic kidney disease. Kidney Int. 2022;102:1154–66.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Knuplez E, Marsche G. An updated review of Pro- and Anti-inflammatory properties of plasma lysophosphatidylcholines in the Vascular System. Int J Mol Sci. 2020;21.

Tonks KT, Coster ACF, Christopher MJ, Chaudhuri R, Xu AM, Gagnon-Bartsch J, et al. Skeletal muscle and plasma lipidomic signatures of insulin resistance and overweight/obesity in humans. Obesity. 2016;24:908–16.

Hannun YA, Obeid LM. Sphingolipids and their metabolism in physiology and disease. Nat Rev Mol Cell Biol. 2018;19:175–91.

Chaurasia B, Tippetts TS, Mayoral Monibas R, Liu J, Li Y, Wang L, et al. Targeting a ceramide double bond improves insulin resistance and hepatic steatosis. Volume 365. New York, NY: Science; 2019. pp. 386–92.

Google Scholar  

Klein RL, Hammad SM, Baker NL, Hunt KJ, Al Gadban MM, Cleary PA, et al. Decreased plasma levels of select very long chain ceramide species are associated with the development of nephropathy in type 1 diabetes. Metab Clin Exp. 2014;63:1287–95.

Fox TE, Han X, Kelly S, Merrill AH 2nd, Martin RE, Anderson RE, et al. Diabetes alters sphingolipid metabolism in the retina: a potential mechanism of cell death in diabetic retinopathy. Diabetes. 2006;55:3573–80.

Coen PM, Goodpaster BH. Role of intramyocelluar lipids in human health. Trends Endocrin Met. 2012;23:391–8.

Hannun YA, Obeid LM. Many ceramides. J Biol Chem. 2011;286:27855–62.

Jiang XC, Paultre F, Pearson TA, Reed RG, Francis CK, Lin M et al. Plasma sphingomyelin level as a risk factor for coronary artery disease. Arteriosclerosis, thrombosis, and vascular biology. 2000;20:2614–8.

Hyotylainen T, Oresic M. Analytical Lipidomics in metabolic and clinical research. Trends Endocrin Met. 2015;26:671–3.

Xuan Q, Ouyang Y, Wang Y, Wu L, Li H, Luo Y, et al. Multiplatform Metabolomics reveals novel serum metabolite biomarkers in Diabetic retinopathy subjects. Adv Sci (Weinh). 2020;7:2001714.

Hyotylainen T, Oresic M. Optimizing the lipidomics workflow for clinical studies-practical considerations. Anal Bioanal Chem. 2015;407:4973–93.

Grochowski ET, Pietrowska K, Godlewski A, Gosk W, Buczynska A, Wojnar M et al. Simultaneous comparison of aqueous humor and serum metabolic profiles of Diabetic and nondiabetic patients undergoing cataract Surgery—A targeted and quantitative Metabolomics Study. Int J Mol Sci. 2023;24.

Liew G, Lei Z, Tan G, Joachim N, Ho IV, Wong TY, et al. Metabolomics of Diabetic Retinopathy. Curr Diab Rep. 2017;17:102.

Sarafian MH, Gaudin M, Lewis MR, Martin FP, Holmes E, Nicholson JK, et al. Objective set of criteria for optimization of sample preparation procedures for ultra-high throughput untargeted blood plasma lipid profiling by ultra performance liquid chromatography-mass spectrometry. Anal Chem. 2014;86:5766–74.

Li J, Li L, Liu R, Zhu L, Zhou B, Xiao Y, et al. Integrative lipidomic features identify plasma lipid signatures in chronic urticaria. Front Immunol. 2022;13:933312.

Wen B, Mei Z, Zeng C, Liu S. metaX: a flexible and comprehensive software for processing metabolomics data. BMC Bioinformatics. 2017;18:183.

Fort PE, Rajendiran TM, Soni T, Byun J, Shan Y, Looker HC et al. Diminished retinal complex lipid synthesis and impaired fatty acid β-oxidation associated with human diabetic retinopathy. Jci Insight. 2021;6.

Fox TE, Han XL, Kelly S, Merrill AH, Martin RE, Anderson RE, et al. Diabetes alters sphingolipid metabolism in the retina - A potential mechanism of cell death in diabetic retinopathy. Diabetes. 2006;55:3573–80.

Levitsky Y, Hammer SS, Fisher KP, Huang C, Gentles TL, Pegouske DJ et al. Mitochondrial Ceramide effects on the retinal pigment epithelium in diabetes. Int J Mol Sci. 2020;21.

Mondal K, Mandal N. Role of bioactive sphingolipids in inflammation and Eye diseases. Adv Exp Med Biol. 2019;1161:149–67.

Laaksonen R, Ekroos K, Sysi-Aho M, Hilvo M, Vihervaara T, Kauhanen D, et al. Plasma ceramides predict cardiovascular death in patients with stable coronary artery disease and acute coronary syndromes beyond LDL-cholesterol. Eur Heart J. 2016;37:1967–76.

Summers SA, Chaurasia B, Holland WL. Metabolic messengers: ceramides. Nat Metabolism. 2019;1:1051–8.

Article   Google Scholar  

Zhang QJ, Holland WL, Wilson L, Tanner JM, Kearns D, Cahoon JM, et al. Ceramide mediates vascular dysfunction in Diet-Induced obesity by PP2A-Mediated dephosphorylation of the eNOS-Akt complex. Diabetes. 2012;61:1848–59.

Wilmott LA, Grambergs RC, Allegood JC, Lyons TJ, Mandal N. Analysis of sphingolipid composition in human vitreous from control and diabetic individuals. J Diabetes Complications. 2019;33:195–201.

Shi AH, Yoshinari M, Wakisaka M, Iwase M, Fujishima M. Lysophosphatidylcholine molecular species in low density lipoprotein of type 2 diabetes. Horm Metab Res. 1999;31:283–6.

Canning P, Kenny BA, Prise V, Glenn J, Sarker MH, Hudson N, et al. Lipoprotein-associated phospholipase A2 (Lp-PLA2) as a therapeutic target to prevent retinal vasopermeability during diabetes. Proc Natl Acad Sci U S A. 2016;113:7213–8.

Zhong J, Cheung CYY, Su X, Lee CH, Ru Y, Fong CHY, et al. Specific triacylglycerol, diacylglycerol, and lyso-phosphatidylcholine species for the prediction of type 2 diabetes: a  ∼  16-year prospective study in Chinese. Cardiovasc Diabetol. 2022;21:234.

Krischer JP, Liu X, Lernmark A, Hagopian WA, Rewers MJ, She JX, et al. The influence of type 1 diabetes genetic susceptibility regions, Age, Sex, and Family History on the Progression from multiple autoantibodies to type 1 diabetes: a TEDDY Study Report. Diabetes. 2017;66:3122–9.

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Acknowledgements

Y.N.W. is supported by the China “Thousand Talents Plan” (Young Talents), Shaanxi province “Thousand Talents Plan” (Young Talents) and Foundation of Xi’an Jiaotong University (Plan A).

This study was supported by grants from The Natural Science Foundation Program of Shaanxi (2024JC-YBQN-0828) and National Key R&D Program of China (No. 2018YFC1311501).

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Mingqian He, Guixue Hou and Mengmeng Liu contributed equally to this work.

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Department of Endocrinology, the First Affiliated Hospital of Xi’an JiaoTong University, No.277, West Yanta Road, Xi’an, Shaanxi, 710061, P.R. China

Mingqian He, Mengmeng Liu, Zhaoyi Peng, Hui Guo, Yue Wang, Meng Zhang, Ziyi Chen, Patrick C.N. Rensen, Yanan Wang & Bingyin Shi

BGI-SHENZHEN, No. 21 Hongan 3rd Street, Yantian District, Shenzhen, Guangdong, 518083, P.R. China

Guixue Hou & Liang Lin

Department of Endocrinology and International Medical Center, the First Affiliated Hospital of Xi’an JiaoTong University, No.277, West Yanta Road, Xi’an, Shaanxi, 710061, P.R. China

Biobank, The First Affiliated Hospital of Xi’an JiaoTong University, Xi’an, Shaanxi, 710061, China

Chengdu HuiXin Life Technology, Chengdu, Sichuan, 610091, P.R. China

Xiaoming Yin

Department of Medicine, Division of Endocrinology, Leiden University Medical Center, P.O. Box 9600, Leiden, 2300 RA, The Netherlands

Patrick C.N. Rensen

Med-X institute, Center for Immunological and Metabolic Diseases, the First Affiliated Hospital of Xi’an JiaoTong University, Xi’an JiaoTong university, Xi’an, Shaanxi, 710061, P.R. China

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B.S., Y.W., and L.L. conceived this review and critically revised the manuscript. M.H., G.H., and M.L. drafted the manuscript. Z.P., H.G., Y.W., and J.S. drew the figures and collected the related references. H.L., X.Y., M.Z., Z.C. and P.C.N. supervised and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Liang Lin , Yanan Wang or Bingyin Shi .

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He, M., Hou, G., Liu, M. et al. Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes. J Transl Med 22 , 448 (2024). https://doi.org/10.1186/s12967-024-05274-9

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Received : 21 August 2023

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DOI : https://doi.org/10.1186/s12967-024-05274-9

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