type 2 diabetes research paper

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Type 2 diabetes

Affiliations.

1 Diabetes Research Centre, University of Leicester and the Leicester NIHR Biomedical Research Centre, Leicester General Hospital, Leicester, UK.
2 Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, South Korea.
3 Family Medicine Department, Korle Bu Teaching Hospital, Accra Ghana and Community Health Department, University of Ghana Medical School, Accra, Ghana.
4 Diabetes Research Centre, University of Leicester and the Leicester NIHR Biomedical Research Centre, Leicester General Hospital, Leicester, UK. Electronic address: [email protected].
PMID: 36332637
DOI: 10.1016/S0140-6736(22)01655-5

Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. The number affected is increasing rapidly with alarming trends in children and young adults (up to age 40 years). Early detection and proactive management are crucial for prevention and mitigation of microvascular and macrovascular complications and mortality burden. Access to novel therapies improves person-centred outcomes beyond glycaemic control. Precision medicine, including multiomics and pharmacogenomics, hold promise to enhance understanding of disease heterogeneity, leading to targeted therapies. Technology might improve outcomes, but its potential is yet to be realised. Despite advances, substantial barriers to changing the course of the epidemic remain. This Seminar offers a clinically focused review of the recent developments in type 2 diabetes care including controversies and future directions.

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Conflict of interest statement

Declaration of interests EA has received fellowship funding from AstraZeneca. SL has been a member on advisory boards or has consulted with Merck Sharp & Dohme, and NovoNordisk. He has received grant support from AstraZeneca, Merck Sharp & Dohme, and Astellas. He has also served on the speakers' bureau of AstraZeneca, Boehringer Ingelheim, Eli Lilly & Co, Merck Sharp & Dohme, Chong Kun Dang Pharmaceutical, and Novo Nordisk. RL has received a research grant from Novo Nordisk. She has also received funds for serving on an advisory board for Sanofi and consultancy fees from Sanofi, AstraZeneca, Novo Nordisk, and Boehringer Ingelheim. DRW has received honoraria as a speaker for AstraZeneca, Sanofi-Aventis, and Lilly, and received research funding support from Novo Nordisk. MJD has acted as consultant, advisory board member, and speaker for Boehringer Ingelheim, Lilly, Novo Nordisk, and Sanofi; an advisory board member and speaker for AstraZeneca; an advisory board member for Janssen, Lexicon, Pfizer, and ShouTi Pharma; and as a speaker for Napp Pharmaceuticals, Novartis, and Takeda Pharmaceuticals International. She has received grants in support of investigator and investigator-initiated trials from Novo Nordisk, Sanofi-Aventis, Lilly, Boehringer Ingelheim, AstraZeneca, and Janssen.

Cancer is becoming the leading cause of death in diabetes. Wang M, Sperrin M, Rutter MK, Renehan AG. Wang M, et al. Lancet. 2023 Jun 3;401(10391):1849. doi: 10.1016/S0140-6736(23)00445-2. Lancet. 2023. PMID: 37270233 No abstract available.

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Peer-reviewed

Research Article

Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses

Roles Conceptualization, Data curation, Formal analysis, Investigation, Software, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Methodology, Supervision, Writing – review & editing

Affiliations Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom

Roles Conceptualization, Methodology, Project administration, Supervision, Writing – review & editing

* E-mail: [email protected]

Vanesa Bellou,
Lazaros Belbasis,
Ioanna Tzoulaki,
Evangelos Evangelou

Published: March 20, 2018
https://doi.org/10.1371/journal.pone.0194127
Reader Comments

Type 2 diabetes mellitus (T2DM) is a global epidemic associated with increased health expenditure, and low quality of life. Many non-genetic risk factors have been suggested, but their overall epidemiological credibility has not been assessed.

We searched PubMed to capture all meta-analyses and Mendelian randomization studies for risk factors of T2DM. For each association, we estimated the summary effect size, its 95% confidence and prediction interval, and the I 2 metric. We examined the presence of small-study effects and excess significance bias. We assessed the epidemiological credibility through a set of predefined criteria.

We captured 86 eligible papers (142 associations) covering a wide range of biomarkers, medical conditions, and dietary, lifestyle, environmental and psychosocial factors. Adiposity, low hip circumference, serum biomarkers (increased level of alanine aminotransferase, gamma-glutamyl transferase, uric acid and C-reactive protein, and decreased level of adiponectin and vitamin D), an unhealthy dietary pattern (increased consumption of processed meat and sugar-sweetened beverages, decreased intake of whole grains, coffee and heme iron, and low adherence to a healthy dietary pattern), low level of education and conscientiousness, decreased physical activity, high sedentary time and duration of television watching, low alcohol drinking, smoking, air pollution, and some medical conditions (high systolic blood pressure, late menarche age, gestational diabetes, metabolic syndrome, preterm birth) presented robust evidence for increased risk of T2DM.

Conclusions

A healthy lifestyle pattern could lead to decreased risk for T2DM. Future randomized clinical trials should focus on identifying efficient strategies to modify harmful daily habits and predisposing dietary patterns.

Citation: Bellou V, Belbasis L, Tzoulaki I, Evangelou E (2018) Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses. PLoS ONE 13(3): e0194127. https://doi.org/10.1371/journal.pone.0194127

Editor: Pratibha V. Nerurkar, University of Hawai'i at Manoa College of Tropical Agriculture and Human Resources, UNITED STATES

Received: April 30, 2017; Accepted: February 26, 2018; Published: March 20, 2018

Copyright: © 2018 Bellou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Type 2 diabetes mellitus (T2DM) ranks highly on the international health agenda as a global pandemic and as a threat to human health and global economies. The number of people with T2DM worldwide has more than doubled during the past 20 years [ 1 ]. According to the International Diabetes Federation, 415 million people are living with T2DM in 2015, and by 2040 the number will be almost 642 million [ 2 ]. These estimates correspond to a global prevalence of 8.8% (95% confidence interval, 7.2–11.4%) in 2015, and a projected global prevalence of 10.4% (95% confidence interval, 8.5–13.5%) in 2040 [ 2 ]. Epidemiological data predict an inexorable and unsustainable increase in global health expenditure attributable to T2DM, so disease prevention should be given high priority.

T2DM results from an interaction between genetic and environmental factors [ 3 ]. Genes and the environment together are important determinants of insulin resistance and β-cell dysfunction [ 4 ]. Because changes in the gene pool cannot account for the rapid increase in prevalence of T2DM in recent decades, environmental changes are essential to the understanding of the epidemic.

Systematic reviews and meta-analyses of observational studies have indicated numerous risk factors for T2DM. However, the epidemiological credibility of these associations has not been appraised across the field. In the present work, we performed an umbrella review of the evidence across existing systematic reviews and meta-analyses of observational studies that examine any non-genetic risk factor for T2DM. We primarily aim to provide an overview of the range and validity of the reported associations of diverse environmental risk factors and biomarkers with T2DM. Furthermore, we assessed whether there is evidence for diverse biases and which of the previously studied associations have robust evidence.

Materials and methods

Search strategy and eligibility criteria.

We conducted an umbrella review, i.e. a comprehensive and systematic collection and evaluation of systematic reviews and meta-analyses performed on a specific research topic using previously described and applied methodology [ 5 – 12 ].

We systematically searched PubMed from inception until February 10, 2016 to identify systematic reviews and meta-analyses of observational studies examining associations of non-genetic risk factors with T2DM. We used the following search strategy: diabetes AND (“systematic review” OR meta-analysis). Two independent investigators (VB, LB) retrieved and abstracted the full text of potentially eligible articles. We excluded meta-analyses that investigated the association between genetic polymorphisms and risk for T2DM; that included less than 3 component studies; that included studies with overlapping populations; that included studies using different units of comparison of the same exposure without transforming the effect estimates appropriately. We further excluded meta-analyses performing comparison between drug agents and subsequent risk for developing T2DM in population at high risk. When an association was covered by more than one meta-analyses, we kept the meta-analysis including the largest number of component studies and adequately presenting the study-specific effect estimates and sample sizes of component studies. We did not apply any language restrictions in our search strategy.

Finally, in order to assess the causality of the associations between the reported risk factors and T2DM, we conducted an additional systematic search on PubMed to capture mendelian randomization (MR) studies for T2DM. This search algorithm used the keywords: “mendelian randomization” OR “mendelian randomisation”. MR studies were eligible if they studied T2DM and examined the potentially causal effect of a risk factor that was also included in our umbrella review. We excluded studies focused on impaired glucose tolerance, impaired fasting glucose or insulin resistance as outcomes.

Data extraction

Two independent investigators (VB, LB) extracted the data, and in case of discrepancies consensus was reached. From each eligible article, we abstracted information on the first author, journal and year of publication, the examined risk factors and the number of studies considered. We also extracted the study-specific risk estimates (i.e. risk ratio, odds ratio, hazard ratio, standardized mean difference) along with their 95% confidence interval (CI) and the number of cases and controls in each study. If a meta-analysis included multiple effect estimates from the same observational study using the same control group, we included only the effect estimate that corresponded to the largest sample size.

From each eligible MR study, we extracted the first author and year of publication, the definition of outcome, the risk factor considered, the level of comparison for exposure, the genetic instrument used, the applied statistical approach, the sample size, the causal odds ratio and its 95% CI, the P-value for the association, and whether the authors claimed that a causal relationship exists. If an MR study used a genetic instrument based on a single variant and a genetic instrument based on polygenic risk score (PRS), we extracted the information from the PRS, as this approach is more powerful.

Statistical analysis

For each meta-analysis, we estimated the summary effect size and its 95% CI using both fixed-effect and random-effects models. [ 13 , 14 ] We also estimated the 95% prediction interval (PI), which accounts for the between-study heterogeneity and evaluates the uncertainty for the effect that would be expected in a new study addressing that same association. [ 15 , 16 ]

Between-study heterogeneity was quantified using the I 2 metric. I 2 ranges between 0% and 100% and quantifies the variability in effect estimates that is due to heterogeneity rather than sampling error. [ 17 ] Values exceeding 50% or 75% are considered to represent large or very large heterogeneity, respectively. This step is necessary to ensure that all results from each meta-analysis are available to assess the epidemiological credibility of the associations.

We assessed small-study effects using the Egger’s regression asymmetry test. [ 18 , 19 ] A P <0.10 combined with a more conservative effect in the largest study than in random-effects meta-analysis was judged to provide adequate evidence for small-study effects. We further applied the excess statistical significance test, which evaluates whether there is a relative excess of formally significant findings in the published literature due to any reason. [ 20 ] We used the effect size of the largest study (smallest standard error) in each meta-analysis to calculate the power of each study using a non-central t distribution. [ 21 , 22 ] Excess statistical significance was claimed at two-sided P <0.10. [ 21 ] In two meta-analyses (glycemic load as dichotomous exposure, and breastfeeding), the excess significance test was not performed, because the sample size was not reported in some of the component studies.

Assessment of epidemiological credibility

We identified associations that had the strongest evidence and no signals of large heterogeneity or bias. We considered as convincing the associations that fulfilled all the following criteria: statistical significance per random-effects model at P <10 −6 ; based on >1,000 cases; without large between-study heterogeneity (I 2 <50%); 95% PI excluding the null value; and no evidence of small-study effects and excess significance bias. Associations with >1,000 cases, P <10 −6 and largest study presenting a statistically significant effect were graded as highly suggestive . The associations supported by >1,000 cases and a significant effect at P <10 −3 were considered as suggestive . The remaining nominally significant associations (P <0.05) were considered as having weak evidence .

For associations with convincing and highly suggestive evidence, we performed a sensitivity analysis limited to prospective cohort studies and nested case-control studies, and we examined whether there was a change in the level of epidemiological credibility. Also, we compared the findings from the meta-analyses of observational studies with the findings from MR studies.

The statistical analysis and the power calculations were done with STATA version 12.0 and RStudio version 1.0.44.

Eligible studies

Our literature search yielded 7,303 papers, of which 86 papers met our inclusion criteria ( Fig 1 ). Fourteen papers, including 16 associations (i.e., sedentary time, breakfast skipping, psoriasis, psoriatic arthritis, breastfeeding, adverse childhood experience, height, hip circumference, serum osteocalcin, spousal diabetes, osteoarthritis, polycystic ovary syndrome, schizophrenia, major depressive disorder, and bipolar disorder), combined cross-sectional studies with either cohort studies or case-control studies in their analysis.

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https://doi.org/10.1371/journal.pone.0194127.g001

The 86 eligible papers examined 109 unique risk factors and 142 associations related to risk for developing T2DM. These associations covered a wide range of exposures: biomarkers (n = 25 associations), dietary factors (n = 53 associations), lifestyle factors and environmental exposures (n = 22 associations), medical history (n = 16 associations), metabolic factors and anthropometric traits (n = 15 associations), and psychosocial factors (n = 11 associations). The median number of cases per meta-analysis was 8,825 (IQR, 2,892–17,782), and the median number of datasets was 10 (IQR, 6–14). Only 7 meta-analyses included less than 1,000 T2DM cases.

Statistically significant associations, heterogeneity and biases

One hundred and sixteen of 142 associations (82%) presented a statistically significant effect at P <0.05 under the random-effects model, whereas 46 associations had a statistically significant effect at P <10 −6 ( Table 1 ). Fig 2 displays the distribution of the P-values in each category of associations. Only 33 of 142 associations (23%) had a 95% PI that excluded the null value and 26 of these also had a P <10 −6 .

The horizontal line corresponds to the significance threshold of P <10 −6 .

https://doi.org/10.1371/journal.pone.0194127.g002

https://doi.org/10.1371/journal.pone.0194127.t001

Thirty-eight associations (27%) were very heterogeneous (I 2 >75%), and 50 associations (35%) had large heterogeneity estimates (I 2 ≥50% and I 2 ≤75%). The Egger’s test was statistically significant in 32 meta-analyses (23%), and 27 of them presented evidence for small-study effects. Thirty-nine meta-analyses (28%) had evidence for excess significance bias.

Eleven associations (8%) presented convincing evidence (>1,000 cases, P <10 −6 , not large between-study heterogeneity, 95% PI excluding the null value, no evidence for small-study effects and excess significance bias) for risk of T2DM. Low whole grains consumption, metabolically healthy obesity, increased sedentary time, low adherence to a healthy dietary pattern, high level of serum uric acid, low level of serum vitamin D, decreased conscientiousness, preterm birth, high consumption of sugar-sweetened beverages, high level of serum ALT, and exposure to high level of PM 10 were associated with increased risk for T2DM and supported by convincing evidence.

Thirty-four associations (24%) were supported by highly suggestive evidence. The associations that were linked with a higher risk for T2DM and presented highly suggestive evidence were the following: high BMI (obese vs. lean, overweight vs. lean, and per 1 SD increase), low educational status, gestational diabetes, increased processed meat consumption, high level of total and leisure-time physical activity, metabolically unhealthy obesity, psoriasis, low coffee consumption, high systolic blood pressure, high level of serum gamma-glutamyl transferase (highest vs. lowest category, and per 1 log unit increase), metabolic syndrome, increased time of television watching, low hip circumference, late age at menarche, weight gain in early adulthood, weight gain after the age of 25 years, increased dietary heme iron intake, high level of serum C-reactive protein (highest vs. lowest category, and per 1 log pm/mL), low level of serum adiponectin (per 1 log μg/ml increase), low alcohol consumption, smoking (former vs. never smokers, and current vs. never smokers), smoking cessation (new quitters vs. never smokers), major depressive disorder, bipolar disorder, high waist-height ratio, high waist circumference, high waist-to-hip ratio, and exposure to high level of NO 2 (per 10 μg/m 3 increase). Twenty-nine associations had suggestive evidence (20%), and 42 associations had weak evidence (30%) for risk of T2DM.

All but 6 associations with convincing or highly suggestive evidence were exclusively based on prospective cohort studies, case-cohort studies and/or nested case-control studies. The remaining six associations (i.e., sedentary time, psoriasis, hip circumference, age at menarche, bipolar disorder, and major depressive disorder) were based on a combination of cross-sectional studies and cohort studies. In a sensitivity analysis limited to prospective cohort studies, the associations for sedentary time, hip circumference, and age at menarche remained highly suggestive ( Table 2 ). For psoriasis, the level of evidence became suggestive due to a P-value greater than 10 −6 under random-effects model ( Table 2 ). In the meta-analysis for bipolar disorder, no prospective cohort studies were included. In the meta-analysis for major depressive disorder, only 1 retrospective cohort study was included. All the risk factors with convincing and highly suggestive evidence are summarized in Fig 3 , and they are graphically presented using forest plots in Figs 4 and 5 .

The symbol ↑ denotes a higher exposure to a risk factor, and the symbol ↓ represents a lower exposure to a risk factor. For alcohol consumption, never drinkers presented a higher risk for T2DM than moderate drinkers.

https://doi.org/10.1371/journal.pone.0194127.g003

https://doi.org/10.1371/journal.pone.0194127.g004

https://doi.org/10.1371/journal.pone.0194127.g005

https://doi.org/10.1371/journal.pone.0194127.t002

Mendelian randomization studies

We identified 22 MR studies assessing the causal effect of a risk factor that was included in our umbrella review ( Table 3 ). The median number of T2DM cases was 4,407 (IQR, 1,164–15,255). Two MR studies used a single SNP as instrumental variable and twenty MR studies constructed a polygenic risk score (PRS). In studies with PRS, the median number of variants was 5 (IQR, 3–8). The eligible MR studies assessed the following 13 exposures: alcohol intake, birth weight, BMI, coffee intake, milk intake, systolic blood pressure, serum adiponectin, serum CRP, serum ferritin, serum gamma-glutamyl transferase, serum uric acid, serum vitamin D, and waist circumference. Seven risk factors were examined by more than one MR study.

https://doi.org/10.1371/journal.pone.0194127.t003

A causal effect was claimed for 4 risk factors graded as highly suggestive in our umbrella review: BMI, systolic blood pressure, serum gamma-glutamyl transferase, and waist circumference. A causal association was also claimed for birth weight, but a relatively small number of T2DM cases was included in this analysis. The observed effects for alcohol intake, coffee intake, serum CRP, serum ferritin, serum uric acid and serum vitamin D were not causal. Milk intake presented weak evidence in our analysis and an MR study did not show a causal effect. Serum adiponectin was graded as highly suggestive in our analysis, but the findings from MR studies were conflicting, and the largest MR study indicated absence of a causal effect.

We performed a mapping of environmental factors and biomarkers examined for an association with T2DM in systematic reviews and meta-analyses. Overall, more than 100 associations were considered. We identified eleven associations supported by convincing evidence and thirty-four additional associations having highly suggestive evidence for risk of T2DM. These associations mainly pertained to comorbid medical conditions, lifestyle and dietary factors, as well as serum biomarkers.

Even though more than one third of the associations examined various dietary factors, only six of them showed convincing or highly suggestive relationship with T2DM and the demonstrated effect sizes were modest. These factors were processed meat, whole grain products, healthy dietary pattern, sugar-sweetened beverages and dietary heme iron. Increased processed meat and sugar-sweetened beverages consumption are linked with other unhealthy lifestyle factors which showed highly significant association with T2DM, such as physical inactivity, increased BMI, smoking and unhealthy dietary patterns. [ 23 , 24 ] The association between dietary heme iron and T2DM could be explained by the fact that red meat is the main dietary source of heme iron. [ 25 ] The observed protective effect of whole grain products is independent of BMI as almost all observational studies have adjusted for its effect. Whole grain products have high concentration of fibers, which delay gastric emptying, therefore slowing glucose release in circulation. This results in reduced postprandial insulin response and could improve insulin sensitivity [ 26 , 27 ] The aforementioned associations are also supported by the observed protective effect of healthy dietary pattern against developing T2DM. Although the term “healthy dietary pattern” includes a variety of diets, the same principles apply: reduced red and processed meat consumption, moderate alcohol drinking, low intake of sugar-sweetened beverages and increased consumption of whole grain products. [ 28 ]

Moderate alcohol consumption has a protective effect against developing T2DM. This relationship could be explained by increased insulin sensitivity, lower fasting insulin resistance and lower glycated hemoglobin concentrations, which are induced by moderate amounts of alcohol. Moreover, moderate amount of alcohol drinking is a common feature of healthy diet pattern, who also lowered the risk for developing T2DM. Furthermore, coffee consumption lowers the risk for T2DM, which is attributed to the reduction of insulin resistance and the improvement of glucose metabolism. However, it is unclear whether this association is causal, given the findings of a recently published MR study [ 29 ].

Most of the associations yielded from our analyses were proxies of obesity and include body mass index (BMI), weight gain, and anthropometric characteristics (i.e., hip circumference, waist-height ratio, waist-hip ratio, waist circumference). The observed association between BMI and T2DM demonstrated a large effect size and was highly significant (RR = 6.88, P = 4.2 × 10 −54 ). Increased BMI, waist-height ratio, waist-hip ratio and waist circumference express the presence of increased intra-abdominal visceral fat, which disrupts insulin metabolism through release of serum free fatty acids. [ 30 ] Not surprisingly, findings from MR studies further support a causal role of BMI in the pathogenesis of T2DM. [ 31 – 34 ] However, not all obese have the same risk for developing T2DM; it seems that the risk is affected by their metabolic profile. Metabolically unhealthy obese carry an about 10-fold risk for T2DM, whereas metabolically healthy obese have an about 4.5-fold risk for T2DM. Moreover, weight gain during early adulthood was more harmful than weight gain after the age of 25. On the contrary, peripheral fat accumulation has been linked to a better metabolic profile, which is depicted in the observed protective effect of larger hip circumference on T2DM.

Several lifestyle factors presented either convincing or highly suggestive evidence. Total and leisure-time physical activity lowered the relative risk for T2DM. High sedentary time and TV watching are inter-correlated, and they are surrogates of physical inactivity, which is a common feature in people with high BMI. Additionally, the convincing association of low conscientiousness with increased risk for T2DM could be explained by the correlation of this personality trait with physical inactivity and high risk for obesity. [ 35 ] Our analysis also indicated that there is highly suggestive evidence for the association of lower educational attainment and higher risk for T2DM. Educational level constitutes a component of socioeconomic status. Lower socioeconomic status is associated with higher stress levels, leading to disruption in endocrine function through perturbations in the neuroendocrine system. [ 36 ] Also, people with low socioeconomic status are more prone to an unhealthy lifestyle pattern and they have limited access to healthcare care facilities. [ 36 ]

Several medical conditions have been traditionally linked to increased risk for T2DM. Patients with metabolic syndrome and gestational diabetes presented higher risk for T2DM. The seven-fold increase of risk for developing T2DM in women with gestational diabetes could be attributed to common underlying genetic and environmental risk factors between the two conditions. [ 37 ] Metabolic syndrome is considered a predictor of T2DM and has a stronger association with T2DM than its components. [ 38 ] Furthermore, higher systolic blood pressure was associated with increased risk for T2DM, but this association might not be causal. Some antihypertensive drugs have been associated with an increased risk, whereas the use of antihypertensive drugs inhibiting the renin-angiotensin system showed a protective effect. In turn, increased activity of renin-angiotensin system induces systemic inflammation processes that may exert a diabetogenic effect. [ 39 ]

Our analysis showed that a set of serum biomarkers is highly associated with the risk for T2DM. These biomarkers pertained to serum level of alanine aminotransferase (ALT), gamma-glutamyl transferase, C-reactive protein (CRP), uric acid, adiponectin, and vitamin D. High serum ALT and gamma-glutamyl transferase in patients with T2DM could be a manifestation of ongoing low-grade hepatic inflammation or hepatocellular damage, which is common in T2DM and metabolic syndrome. Among hepatic enzymes, ALT is the most specific indicator of hepatic pathology in non-alcoholic fatty liver disease and most closely related to liver fat accumulation. The presence of systemic inflammation is linked to β-cell dysfunction, leading to impaired glucose metabolism and the development of T2DM. [ 4 ] Both CRP and uric acid are inflammatory markers associated with systemic inflammation. Also, meat consumption is directly associated with serum uric acid level, and, as we have already shown, processed meat consumption is linked to higher risk for T2DM. However, MR studies for serum CRP [ 40 ], and serum uric acid [ 41 – 43 ] suggested that the associations with T2DM might not be causal.

Furthermore, our results indicated an inverse association between vitamin D level and risk for T2DM. It is unclear if this is a true association or the effect of adiposity as a potential confounder or intermediate factor. Obesity leads to storage of vitamin D in adipose tissue and to less sun exposure, on the grounds of limited mobility and accumulation of subcutaneous fat [ 44 ]. All the former result in low circulating level of vitamin D in obese individuals. Also, vitamin D may directly affect adiposity and other metabolic parameters, such as dyslipidemia, hypertension, and systemic inflammation, that mediate the pathway from vitamin D status to T2DM. Adiponectin is another serum biomarker that expresses the body composition. It affects the glucose metabolism, and higher serum level of adiponectin are associated with higher insulin sensitivity. However, MR studies examining the role of serum vitamin D indicated a non-causal association that might be explained by confounding factors [ 31 , 45 – 48 ], whereas the evidence on the causal role of serum adiponectin are contradictory [ 49 – 51 ].

The association between smoking and T2DM has biological foundation because smoking is associated with central obesity and increased oxidative stress and inflammation, and eventually leads to insulin resistance and hyperglycaemia. However, residual confounding can be the case since smoking is often linked to other unhealthy lifestyle factors (e.g., poor diet, physical inactivity) and comorbidities. The increased risk of T2DM associated with smoking cessation in new quitters could be mediated by weight gain or be due to reverse causation because people who try to quit smoking are more likely to have preclinical conditions or high cumulative smoking exposure [ 52 ].

Based on our assessment, adults delivered preterm presented a larger risk for development of T2DM during adulthood than adults delivered full-term. According to the “fetal origin of disease” hypothesis, the biological mechanisms that mediate this association could be explained through intrauterine growth restriction. Preterm newborns have low birth weight and they are prone to disrupted glucose metabolism in later life [ 53 ], which in turn predisposes to an increased risk of T2DM. Although the association between birth weight and T2DM had weak epidemiological credibility [ 12 ], an MR study indicated that there is a potential causal association between birth weight and risk for T2DM [ 54 ].

Two components of ambient air pollution, PM 10 and NO 2 , were found to have robust association with risk for T2DM. It has been suggested that air pollution causes elevated systemic inflammation and oxidative stress, whereas it increases the insulin resistance leading to abnormal glucose metabolism and elevated fasting glucose. [ 55 ]

Furthermore, older age at menarche was associated with risk for T2DM. However, there are doubts whether it constitutes a genuine association. Observational studies found that this association is attenuated after adjustment for BMI in adulthood, suggesting that adult adiposity may mediate this association. The inverse association between age at menarche and BMI in adulthood could explain this finding. [ 56 ]

We presented an exposure-wide mapping of the meta-analyses on non-genetic risk factors for T2DM. Our umbrella review indicated that a very wide range of risk factors has been considered for T2DM. Compared to previously published umbrella reviews [ 6 – 10 ], there is tremendous amount of meta-analyses for risk factors of T2DM. Also, the majority of these associations were examined in large prospective cohort studies. The increasing incidence and large burden of T2DM could explain the observed interest in the field of non-genetic and modifiable risk factors for T2DM.

Our study has some caveats. First, the statistical test for small-study effects should be interpreted with caution in case of large between-study heterogeneity. Second, the observational studies did not often clearly report the sample sizes for the statistical analyses. Thus, the power calculations might be conservative, and the extent of excess significance bias is probably conservative. Furthermore, genetic instruments of the MR studies were not assessed, and power calculations for the MR studies could not be performed, because the percentage of variance explained often was not available. Consequently, the claims of MR studies should be interpreted with caution.

Our paper identified several robust risk factors for T2DM. Our findings indicate specific strategies for public health interventions to reduce the future incidence of T2DM. Interventions for the promotion of physical activity and a healthy lifestyle and dietary pattern combined with interventions against the increased incidence of obesity could alleviate the projections for an increase of T2DM incidence in near future. However, these findings are based on observational data and should be interpreted with caution. Even though MR studies may support or not causality, the power of those studies could not be assessed. Therefore, randomized clinical trials and additional well-designed MR studies are needed to clarify which of these observations are causal associations. Also, these findings should be replicated by large-scale environment-wide association studies in various ethnic groups, and they could be used for the development of reliable risk prediction models in combination with known genetic polymorphisms.

Supporting information

S1 file. prisma checklist..

https://doi.org/10.1371/journal.pone.0194127.s001

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2. International Diabetes Federation. IDF Diabetes Atlas. 7th ed. Brussels; 2015.

HYPOTHESIS AND THEORY article

Type 2 diabetes mellitus: a pathophysiologic perspective.

$\nEric C. Westman$

Department of Medicine, Duke University, Durham, NC, United States

Type 2 Diabetes Mellitus (T2DM) is characterized by chronically elevated blood glucose (hyperglycemia) and elevated blood insulin (hyperinsulinemia). When the blood glucose concentration is 100 milligrams/deciliter the bloodstream of an average adult contains about 5–10 grams of glucose. Carbohydrate-restricted diets have been used effectively to treat obesity and T2DM for over 100 years, and their effectiveness may simply be due to lowering the dietary contribution to glucose and insulin levels, which then leads to improvements in hyperglycemia and hyperinsulinemia. Treatments for T2DM that lead to improvements in glycemic control and reductions in blood insulin levels are sensible based on this pathophysiologic perspective. In this article, a pathophysiological argument for using carbohydrate restriction to treat T2DM will be made.

Introduction

Type 2 Diabetes Mellitus (T2DM) is characterized by a persistently elevated blood glucose, or an elevation of blood glucose after a meal containing carbohydrate ( 1 ) ( Table 1 ). Unlike Type 1 Diabetes which is characterized by a deficiency of insulin, most individuals affected by T2DM have elevated insulin levels (fasting and/or post glucose ingestion), unless there has been beta cell failure ( 2 , 3 ). The term “insulin resistance” (IR) has been used to explain why the glucose levels remain elevated even though there is no deficiency of insulin ( 3 , 4 ). Attempts to determine the etiology of IR have involved detailed examinations of molecular and intracellular pathways, with attribution of cause to fatty acid flux, but the root cause has been elusive to experts ( 5 – 7 ).

Table 1 . Definition of type 2 diabetes mellitus.

How Much Glucose Is in the Blood?

Keeping in mind that T2DM involves an elevation of blood glucose, it is important to understand how much glucose is in the blood stream to begin with, and then the factors that influence the blood glucose—both exogenous and endogenous factors. The amount of glucose in the bloodstream is carefully controlled—approximately 5–10 grams in the bloodstream at any given moment, depending upon the size of the person. To calculate this, multiply 100 milligrams/deciliter × 1 gram/1,000 milligrams × 10 deciliters/1 liter × 5 liters of blood. The “zeros cancel” and you are left with 5 grams of glucose if the individual has 5 liters of blood. Since red blood cells represent about 40% of the blood volume, and the glucose is in equilibrium, there may be an extra 40% glucose because of the red blood cell reserve ( 8 ). Adding the glucose from the serum and red blood cells totals about 5–10 grams of glucose in the entire bloodstream.

Major Exogenous Factors That Raise the Blood Glucose

Dietary carbohydrate is the major exogenous factor that raises the blood glucose. When one considers that it is common for an American in 2021 to consume 200–300 grams of carbohydrate daily, and most of this carbohydrate is digested and absorbed as glucose, the body absorbs and delivers this glucose via the bloodstream to the cells while attempting to maintain a normal blood glucose level. Thinking of it in this way, if 200–300 grams of carbohydrates is consumed in a day, the bloodstream that holds 5–10 grams of glucose and has a concentration of 100 milligrams/deciliter, is the conduit through which 200,000–300,000 milligrams (200 grams = 200,000 milligrams) passes over the course of a day.

Major Endogenous Factors That Raise the Blood Glucose

There are many endogenous contributors that raise the blood glucose. There are at least 3 different hormones that increase glucose levels: glucagon, epinephrine, and cortisol. These hormones increase glucose levels by increasing glycogenolysis and gluconeogenesis ( 9 ). Without any dietary carbohydrate, the normal human body can generate sufficient glucose though the mechanism of glucagon secretion, gluconeogenesis, glycogen storage and glycogenolysis ( 10 ).

Major Exogenous Factors That Lower the Blood Glucose

A reduction in dietary carbohydrate intake can lower the blood glucose. An increase in activity or exercise usually lowers the blood glucose ( 11 ). There are many different medications, employing many mechanisms to lower the blood glucose. Medications can delay sucrose and starch absorption (alpha-glucosidase inhibitors), slow gastric emptying (GLP-1 agonists, DPP-4 inhibitors) enhance insulin secretion (sulfonylureas, meglitinides, GLP-1 agonists, DPP-4 inhibitors), reduce gluconeogenesis (biguanides), reduce insulin resistance (biguanides, thiazolidinediones), and increase urinary glucose excretion (SGLT-2 inhibitors). The use of medications will also have possible side effects.

Major Endogenous Factors That Lower the Blood Glucose

The major endogenous mechanism to lower the blood glucose is to deliver glucose into the cells (all cells can use glucose). If the blood glucose exceeds about 180 milligrams/deciliter, then loss of glucose into the urine can occur. The blood glucose is reduced by cellular uptake using glut transporters ( 12 ). Some cells have transporters that are responsive to the presence of insulin to activate (glut4), others have transporters that do not require insulin for activation. Insulin-responsive glucose transporters in muscle cells and adipose cells lead to a reduction in glucose levels—especially after carbohydrate-containing meals ( 13 ). Exercise can increase the glucose utilization in muscle, which then increases glucose cellular uptake and reduce the blood glucose levels. During exercise, when the metabolic demands of skeletal muscle can increase more than 100-fold, and during the absorptive period (after a meal), the insulin-responsive glut4 transporters facilitate the rapid entry of glucose into muscle and adipose tissue, thereby preventing large fluctuations in blood glucose levels ( 13 ).

Which Cells Use Glucose?

Glucose can used by all cells. A limited number of cells can only use glucose, and are “glucose-dependent.” It is generally accepted that the glucose-dependent cells include red blood cells, white blood cells, and cells of the renal papilla. Red blood cells have no mitochondria for beta-oxidation, so they are dependent upon glucose and glycolysis. White blood cells require glucose for the respiratory burst when fighting infections. The cells of the inner renal medulla (papilla) are under very low oxygen tension, so therefore must predominantly use glucose and glycolysis. The low oxygen tension is a result of the countercurrent mechanism of urinary concentration ( 14 ). These glucose-dependent cells have glut transporters that do not require insulin for activation—i.e., they do not need insulin to get glucose into the cells. Some cells can use glucose and ketones, but not fatty acids. The central nervous system is believed to be able to use glucose and ketones for fuel ( 15 ). Other cells can use glucose, ketones, and fatty acids for fuel. Muscle, even cardiac muscle, functions well on fatty acids and ketones ( 16 ). Muscle cells have both non-insulin-responsive and insulin-responsive (glut4) transporters ( 12 ).

Possible Dual Role of an Insulin-Dependent Glucose-Transporter (glut4)

A common metaphor is to think of the insulin/glut transporter system as a key/lock mechanism. Common wisdom states that the purpose of insulin-responsive glut4 transporters is to facilitate glucose uptake when blood insulin levels are elevated. But, a lock serves two purposes: to let someone in and/or to keep someone out . So, one of the consequences of the insulin-responsive glut4 transporter is to keep glucose out of the muscle and adipose cells, too, when insulin levels are low. The cells that require glucose (“glucose-dependent”) do not need insulin to facilitate glucose entry into the cell (non-insulin-responsive transporters). In a teleological way, it would “make no sense” for cells that require glucose to have insulin-responsive glut4 transporters. Cells that require glucose have glut1, glut2, glut3, glut5 transporters—none of which are insulin-responsive (Back to the key/lock metaphor, it makes no sense to have a lock on a door that you want people to go through). At basal (low insulin) conditions, most glucose is used by the brain and transported by non-insulin-responsive glut1 and glut3. So, perhaps one of the functions of the insulin-responsive glucose uptake in muscle and adipose to keep glucose OUT of the these cells at basal (low insulin) conditions, so that the glucose supply can be reserved for the tissue that is glucose-dependent (blood cells, renal medulla).

What Causes IR and T2DM?

The current commonly espoused view is that “Type 2 diabetes develops when beta-cells fail to secrete sufficient insulin to keep up with demand, usually in the context of increased insulin resistance.” ( 17 ). Somehow, the beta cells have failed in the face of insulin resistance. But what causes insulin resistance? When including the possibility that the environment may be part of the problem, is it possible that IR is an adaptive (protective) response to excess glucose availability? From the perspective that carbohydrate is not an essential nutrient and the change in foods in recent years has increased the consumption of refined sugar and flour, maybe hyperinsulinemia is the cause of IR and T2DM, as cells protect themselves from excessive glucose and insulin levels.

Insulin Is Already Elevated in IR and T2DM

Clinical experience of most physicians using insulin to treat T2DM over time informs us that an escalation of insulin dose is commonly needed to achieve glycemic control (when carbohydrate is consumed). When more insulin is given to someone with IR, the IR seems to get worse and higher levels of insulin are needed. I have the clinical experience of treating many individuals affected by T2DM and de-prescribing insulin as it is no longer needed after consuming a diet without carbohydrate ( 18 ).

Diets Without Carbohydrate Reverse IR and T2DM

When dietary manipulation was the only therapy for T2DM, before medications were available, a carbohydrate-restricted diet was used to treat T2DM ( 19 – 21 ). Clinical experience of obesity medicine physicians and a growing number of recent studies have demonstrated that carbohydrate-restricted diets reverse IR and T2DM ( 18 , 22 , 23 ). Other methods to achieve caloric restriction also have these effects, like calorie-restricted diets and bariatric surgery ( 24 , 25 ). There may be many mechanisms by which these approaches may work: a reduction in glucose, a reduction in insulin, nutritional ketosis, a reduction in metabolic syndrome, or a reduction in inflammation ( 26 ). Though there may be many possible mechanisms, let's focus on an obvious one: a reduction in blood glucose. Let's assume for a moment that the excessive glucose and insulin leads to hyperinsulinemia and this is the cause of IR. On a carbohydrate-restricted diet, the reduction in blood glucose leads to a reduction in insulin. The reduction in insulin leads to a reduction in insulin resistance. The reduction in insulin leads to lipolysis. The resulting lowering of blood glucose, insulin and body weight reverses IR, T2DM, AND obesity. These clinical observations strongly suggest that hyperinsulinemia is a cause of IR and T2DM—not the other way around.

What Causes Atherosclerosis?

For many years, the metabolic syndrome has been described as a possible cause of atherosclerosis, but there are no RCTs directly targeting metabolic syndrome, and the current drug treatment focuses on LDL reduction, so its importance remains controversial. A recent paper compared the relative importance of many risk factors in the prediction of the first cardiac event in women, and the most powerful predictors were diabetes, metabolic syndrome, smoking, hypertension and BMI ( 27 ). The connection between dietary carbohydrate and fatty liver is well-described ( 28 ). The connection between fatty liver and atherosclerosis is well-described ( 29 ). It is very possible that the transport of excess glucose to the adipose tissue via lipoproteins creates the particles that cause the atherosclerotic damage (small LDL) ( Figure 1 ) ( 30 – 32 ). This entire process of dietary carbohydrate leading to fatty liver, leading to small LDL, is reversed by a diet without carbohydrate ( 26 , 33 , 34 ).

Figure 1 . Key aspects of the interconnection between glucose and lipoprotein metabolism.

Reducing dietary carbohydrate in the context of a low carbohydrate, ketogenic diet reduces hyperglycemia and hyperinsulinemia, IR and T2DM. In the evaluation of an individual for a glucose abnormality, measure the blood glucose and insulin levels. If the insulin level (fasting or after a glucose-containing meal) is high, do not give MORE insulin—instead, use an intervention to lower the insulin levels. Effective ways to reduce insulin resistance include lifestyle, medication, and surgical therapies ( 23 , 35 ).

The search for a single cause of a complex problem is fraught with difficulty and controversy. I am not hypothesizing that excessive dietary carbohydrate is the only cause of IR and T2DM, but that it is a cause, and quite possibly the major cause. How did such a simple explanation get overlooked? I believe it is very possible that the reductionistic search for intracellular molecular mechanisms of IR and T2DM, the emphasis on finding pharmaceutical (rather than lifestyle) treatments, the emphasis on the treatment of high total and LDL cholesterol, and the fear of eating saturated fat may have misguided a generation of researchers and clinicians from the simple answer that dietary carbohydrate, when consumed chronically in amounts that exceeds an individual's ability to metabolize them, is the most common cause of IR, T2DM and perhaps even atherosclerosis.

While there has historically been a concern about the role of saturated fat in the diet as a cause of heart disease, most nutritional experts now cite the lack of evidence implicating dietary saturated fat as the reason for lack of concern of it in the diet ( 36 ).

The concept of comparing medications that treat IR by insulin-sensitizers or by providing insulin itself was tested in the Bari-2D study ( 37 ). Presumably in the context of consuming a standard American diet, this study found no significant difference in death rates or major cardiovascular events between strategies of insulin sensitization or insulin provision.

While lifestyle modification may be ideal to prevent or cure IR and T2DM, for many people these changes are difficult to learn and/or maintain. Future research should be directed toward improving adherence to all effective lifestyle or medication treatments. Future research is also needed to assess the effect of carbohydrate restriction on primary or secondary prevention of outcomes of cardiovascular disease.

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.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

EW receives royalties from popular diet books and is founder of a company based on low-carbohydrate diet principles (Adapt Your Life, Inc.).

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: type 2 diabetes, insulin resistance, pre-diabetes, carbohydrate-restricted diets, hyperinsulinemia, hyperglycemia

Citation: Westman EC (2021) Type 2 Diabetes Mellitus: A Pathophysiologic Perspective. Front. Nutr. 8:707371. doi: 10.3389/fnut.2021.707371

Received: 09 May 2021; Accepted: 20 July 2021; Published: 10 August 2021.

Reviewed by:

Copyright © 2021 Westman. 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: Eric C. Westman, ewestman@duke.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Type 2 Diabetes Research At-a-Glance

The ADA is committed to continuing progress in the fight against type 2 diabetes by funding research, including support for potential new treatments, a better understating of genetic factors, addressing disparities, and more. For specific examples of projects currently funded by the ADA, see below.

Greg J. Morton, PhD

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Project: Neurocircuits regulating glucose homeostasis

“The health consequences of diabetes can be devastating, and new treatments and therapies are needed. My research career has focused on understanding how blood sugar levels are regulated and what contributes to the development of diabetes. This research will provide insights into the role of the brain in the control of blood sugar levels and has potential to facilitate the development of novel approaches to diabetes treatment.”

The problem: Type 2 diabetes (T2D) is among the most pressing and costly medical challenges confronting modern society. Even with currently available therapies, the control and management of blood sugar levels remains a challenge in T2D patients and can thereby increase the risk of diabetes-related complications. Continued progress with newer, better therapies is needed to help people with T2D.

The project: Humans have special cells, called brown fat cells, which generate heat to maintain optimal body temperature. Dr. Morton has found that these cells use large amounts of glucose to drive this heat production, thus serving as a potential way to lower blood sugar, a key goal for any diabetes treatment. Dr. Morton is working to understand what role the brain plays in turning these brown fat cells on and off.

The potential outcome: This work has the potential to fundamentally advance our understanding of how the brain regulates blood sugar levels and to identify novel targets for the treatment of T2D.

Tracey Lynn McLaughlin, MD

Stanford University

Project: Role of altered nutrient transit and incretin hormones in glucose lowering after Roux-en-Y gastric bypass surgery

“This award is very important to me personally not only because the enteroinsular axis (gut-insulin-glucose metabolism) is a new kid on the block that requires rigorous physiologic studies in humans to better understand how it contributes to glucose metabolism, but also because the subjects who develop severe hypoglycemia after gastric bypass are largely ignored in society and there is no treatment for this devastating and very dangerous condition.”

The problem: Roux-en-Y gastric bypass (RYGB) surgery is the single-most effective treatment for type 2 diabetes, with persistent remission in 85% of cases. However, the underlying ways by which the surgery improves glucose control is not yet understood, limiting the ability to potentially mimic the surgery in a non-invasive way. Furthermore, a minority of RYGB patients develop severe, disabling, and life-threatening low-blood sugar, for which there is no current treatment.

The project: Utilizing a unique and rigorous human experimental model, the proposed research will attempt to gain a better understanding on how RYGB surgery improves glucose control. Dr. McLaughlin will also test a hypothesis which she believes could play an important role in the persistent low-blood sugar that is observed in some patients post-surgery.

The potential outcome: This research has the potential to identify novel molecules that could represent targets for new antidiabetic therapies. It is also an important step to identifying people at risk for low-blood sugar following RYGB and to develop postsurgical treatment strategies.

Rebekah J. Walker, PhD

Medical College of Wisconsin

Project: Lowering the impact of food insecurity in African Americans with type 2 diabetes

“I became interested in diabetes research during my doctoral training, and since that time have become passionate about addressing social determinants of health and health disparities, specifically in individuals with diabetes. Living in one of the most racially segregated cities in the nation, the burden to address the needs of individuals at particularly high risk of poor outcomes has become important to me both personally and professionally.”

The problem: Food insecurity is defined as the inability to or limitation in accessing nutritionally adequate food and may be one way to address increased diabetes risk in high-risk populations. Food insecure individuals with diabetes have worse diabetes outcomes and have more difficulty following a healthy diet compared to those who are not food insecure.

The project: Dr. Walker’s study will gather information to improve and then will test an intervention to improve blood sugar control, dietary intake, self-care management, and quality of life in food insecure African Americans with diabetes. The intervention will include weekly culturally appropriate food boxes mailed to the participants and telephone-delivered diabetes education and skills training. It will be one of the first studies focused on the unique needs of food insecure African American populations with diabetes using culturally tailored strategies.

The potential outcome: This study has the potential to guide and improve policies impacting low-income minorities with diabetes. In addition, Dr. Walker’s study will help determine if food supplementation is important in improving diabetes outcomes beyond diabetes education alone.

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Reversing Type 2 Diabetes: A Narrative Review of the Evidence

Sarah j hallberg.

1 Virta Health, 535 Mission Street, San Francisco, CA 94105, USA; moc.htlaehatriv@einimahs

2 Indiana University Health Arnett, Lafayette, IN 47904, USA; gro.htlaehui@nubzaht

3 Indiana University School of Medicine, Indianapolis, IN 46202, USA

Victoria M Gershuni

4 Department of Surgery, Perelman School of Medicine University of Pennsylvania, Philadelphia, PA 19104, USA; moc.liamg@dminuhsregairotciv

Tamara L Hazbun

Shaminie j athinarayanan.

Background: Type 2 diabetes (T2D) has long been identified as an incurable chronic disease based on traditional means of treatment. Research now exists that suggests reversal is possible through other means that have only recently been embraced in the guidelines. This narrative review examines the evidence for T2D reversal using each of the three methods, including advantages and limitations for each. Methods: A literature search was performed, and a total of 99 original articles containing information pertaining to diabetes reversal or remission were included. Results: Evidence exists that T2D reversal is achievable using bariatric surgery, low-calorie diets (LCD), or carbohydrate restriction (LC). Bariatric surgery has been recommended for the treatment of T2D since 2016 by an international diabetes consensus group. Both the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) now recommend a LC eating pattern and support the short-term use of LCD for weight loss. However, only T2D treatment, not reversal, is discussed in their guidelines. Conclusion: Given the state of evidence for T2D reversal, healthcare providers need to be educated on reversal options so they can actively engage in counseling patients who may desire this approach to their disease.

1. Introduction

According to 2017 International Diabetes Federation (IDF) statistics, there are approximately 425 million people with diabetes worldwide [ 1 ]. In the United States, there are an estimated 30.3 million adults living with diabetes, and its prevalence has been rising rapidly, with at least 1.5 million new diabetes cases diagnosed each year [ 2 ]. Diabetes is a major public health epidemic despite recent advances in both pharmaceutical and technologic treatment options.

Type 2 diabetes (T2D) has long been identified as an incurable chronic disease. The best outcome that has been expected is amelioration of diabetes symptoms or slowing its inevitable progression. Approximately 50% of T2D patients will need insulin therapy within ten years of diagnosis [ 3 ] Although in the past diabetes has been called chronic and irreversible, the paradigm is changing [ 4 , 5 ].

The recent 2016 World Health Organization (WHO) global report on diabetes added a section on diabetes reversal and acknowledged that it can be achieved through weight loss and calorie restriction [ 4 ]. “Diabetes reversal” is a term that has found its way into scientific articles and the lay press alike; “remission” has also been used. While the exact criteria are still debated, most agree that a hemoglobin A1c (HbA1c) under the diabetes threshold of 6.5% for an extended period of time without the use of glycemic control medications would qualify [ 6 ]. Excluding metformin from the glycemic control medications list, as it has indications beyond diabetes, may also be a consideration [ 7 , 8 ]. Likewise, terms such as “partial” (HbA1c <6.5 without glycemic control medications for 1 year) or “complete” (HbA1c <5.7 without glycemic control medications for 1 year) remission have been defined by an expert panel as more evidence accumulates that points to the possibility of avoiding the presumably progressive nature of T2D [ 9 ]. It is important to note that the term “cure” has not been applied to T2D, as there does exist the potential for re-occurrence, which has been well documented in the literature.

Despite the growing evidence that reversal is possible, achieving reversal is not commonly encouraged by our healthcare system. In fact, reversal is not a goal in diabetes guidelines. Specific interventions aimed at reversal all have one thing in common: they are not first-line standard of care. This is important, because there is evidence suggesting that standard of care does not lead to diabetes reversal. This raises the question of whether standard of care is really the best practice. A large study by Kaiser Permanente found a diabetes remission rate of 0.23% with standard of care [ 10 ]. The status quo approach will not reverse the health crisis of diabetes.

A significant number of studies indicate that diabetes reversal is achievable using bariatric surgery, while other approaches, such as low-calorie diets (LCD) or carbohydrate restriction (LC), have also shown effectiveness in an increasing number of studies. This review will examine each of these approaches, identifying their beneficial effects, supporting evidence, drawbacks, and degree of sustainability.

2. Materials and Methods

A literature search was performed as appropriate for narrative reviews, including electronic databases of PubMed, EMBASE, and Google Scholar from 1970 through December 2018. We reviewed English-language original and review articles found under the subject headings diabetes, bariatric surgery, metabolic surgery, very low-calorie diet, calorie restriction, low carbohydrate diet, ketogenic diet, diabetes remission, and diabetes reversal. References of the identified publications were searched for more research articles to include in this review. Selected studies were reviewed and evaluated for eligibility for inclusion in this review based on their relevance for diabetes reversal and remission. Either remission or reversal needed to be discussed in the paper or the results were consistent with these terms for inclusion. Randomized clinical trials and intervention-based studies were given emphasis for inclusion.

A total of 99 original articles containing information pertaining to diabetes reversal or remission were included in this narrative review.

3. Results and Discussion

3.1. bariatric surgery.

Bariatric surgery has long been recognized as a potential treatment for both morbid obesity and the metabolic processes that accompany it, specifically T2D. While the efficacy of T2D reversal depends on the choice of procedure, there is unilateral improvement in glycemia following operation [ 11 ], and bariatric surgery has been found to be superior to intensive T2D medical management. Accordingly, in 2016, the second Diabetes Surgery Summit (DSS-II) released recommendations, endorsed by 45 medical and scientific societies worldwide, to use bariatric surgery as a treatment for T2D (bariatric surgery is currently approved by the 2016 recommendations for adults with a body mass index (BMI) >40, or >35 kg/m 2 with obesity-related comorbidities) [ 12 ]. Of interest is the consistent finding that glycemic improvements occur rapidly, often within hours to days, and precede weight loss, which likely represents the enteroendocrine responses to altered flow of intestinal contents (i.e., bile acid signaling and changes in microbiota and their metabolome) [ 13 , 14 , 15 , 16 , 17 , 18 , 19 ].

The most commonly performed bariatric surgeries in the United States include laparoscopic and robotic Roux-en-Y Gastric Bypass (RYGB) or Sleeve Gastrectomy (SG). While surgical treatment is based on the principles of restriction and intestinal malabsorption, evidence suggests that there are more complex mechanisms at play. Bariatric surgery has consistently been shown to dramatically and rapidly improve blood glucose [ 20 ] while allowing decreased oral hypoglycemic medications and insulin use, effectively reversing diabetes in up to 80% of patients [ 21 ] in the short term. In addition to early post-operative improvement in blood glucose and insulin sensitivity, bariatric surgery has also been shown to cause alterations in GI hormone release, including ghrelin, leptin, cholecystokinin (CCK), peptide-tyrosine-tyrosine (PYY), and glucagon-like peptide 1 (GLP-1), that may impact feeding behavior via the gut–brain axis in addition to modulating euglycemia [ 22 ]. Furthermore, microbial changes in the human gut have been linked to obesity, and surgical alterations to gastrointestinal anatomy have been associated with dramatic changes in gut microbiota populations with reversion from an “obesogenic” to a lean bacterial population [ 13 , 14 , 16 , 19 , 23 , 24 ].

Long-term outcomes from bariatric surgery depend on multiple factors, including type of surgery performed, patient comorbidities, patient readiness for lifelong dietary change, and ongoing surveillance. While bariatric surgery has been demonstrated to be safe and effective overall, it is important to recognize that it is not without risks. Each patient must weigh the risks and benefits associated with untreated morbid obesity versus those associated with surgery or effective dietary management and choose accordingly. Surgery of any type can be associated with complications leading to morbidity or mortality; the complication rates have been stated to be as high as 13% and 21% for SG and RYGB, respectively. The postoperative mortality rate is 0.28–0.34% for SG and 0.35–0.79% for RYGB; in comparison, an elective laparoscopic cholecystectomy is associated with overall complication rates of 9.29% and with a 30-day mortality rate of 0.15–0.6%, depending on the series [ 25 , 26 ]. Significant complications include anastomotic leak or hemorrhage, post-operative readmission, need for reoperation, post-operative hypoglycemia, dumping syndrome, worsening acid reflux, marginal ulceration, and micronutrient deficiencies [ 25 , 26 , 27 , 28 , 29 ].

It is important to consider that while short-duration studies have shown early resolution of comorbidities following bariatric procedures, when followed for multiple decades, there may be decreased efficacy of disease resolution and increased incidence of hospital admission long-term. Long-term reversal of T2D and true glucose homeostasis remain uncertain. Weight loss after surgery is a significant predictor of a return to euglycemia post-operatively. Multiple studies have reported initial T2D remission rates as high as 80% [ 30 , 31 ], however, long-term remission is less durable. The five-year follow-up outcomes of the SLEEVEPASS RCT found complete or partial remission of T2D in 37% of SG and 45% of RYGB patients, which is similar to other studies showing long-term T2D remission in up to a third of patients [ 32 ]. In the large prospective cohort study Longitudinal Assessment of Bariatric Surgery 2 (LABS-2), the investigators found that long-term diabetes remission after RYGB was higher than predicted by weight loss alone, which suggests that the surgery itself impacts metabolic factors that contribute to disease management [ 31 ]. Similarly, the STAMPEDE trial—an RCT that followed 150 patients with T2D who were randomized to intensive medical intervention (IMT) versus IMT plus RYGB versus IMT plus SG for diabetes resolution (defined as HbA1c <6.0%) and followed for five years—revealed increased rates of T2D resolution with RYGB (29%) and SG (23%) compared to IMT alone (5%) ( Figure 1 ). The surgery cohort also demonstrated greater weight loss and improvements in triglycerides, HDL, need for insulin, and overall quality of life [ 33 , 34 , 35 ].

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( A ) Mean changes of hemoglobin A1c (HbA1c) from baseline to last published date for each study retrieved to represent the three methods of reversal; ( B ) mean changes of weight from baseline to last published date for each studies retrieved to represent the three methods of reversal. Note: We chose these three studies to represent the three methods of reversal based on publication date and relevance to diabetes reversal. Note that baseline characteristics differ. Surgery trial examined by sleeve gastrectomy and Roux-en-Y gastric bypass separately and were represented as sleeve and bypass in the graph. Surgery: STAMPEDE [ 34 , 35 ]. Low-calorie diets (LCD): DIRECT [ 65 , 66 ]; carbohydrate restriction (LC): IUH [ 99 , 107 ].

Despite the likelihood of improved glycemic control, there are significant financial costs for the patient, health system, and insurance companies associated with bariatric surgery (U.S. average of $14,389) [ 36 ]. Despite the high initial cost of surgery, Pories and colleagues found that prior to surgery, patients spend over $10,000 per year on diabetes medications; after RYGB, the annual cost falls to less than $2000, which represents an $8000 cost savings at the individual level [ 30 ]. Furthermore, economic analyses show that surgery is likely to be cost-effective, especially in patients who are obese [ 37 , 38 ]. In a clinical effectiveness review of the literature that included 26 trials extracted from over 5000 references, Picot et al. found that bariatric surgery was a more effective intervention for weight loss than non-surgical options; however, there was extreme heterogeneity and questionable long-term adherence to the non-surgical interventions [ 39 ]. After surgery, metabolic syndrome improved, and there were higher rates of T2D remission compared to the non-surgical groups [ 39 ]. Further, while there were improvements in comorbidities after surgery independent of bariatric procedure, there was also an increased likelihood of adverse events. While the overall event rate remained low, major adverse events included medication intolerance, need for reoperation, infection, anastomotic leakage, and venous and thromboembolic events [ 39 ].

It is imperative to consider that one of the requirements of qualifying for bariatric surgery is demonstration of at least six months of unsuccessful attempts at weight loss using traditional dietary and exercise advice according to the 2016 Recommendations [ 12 ]. There are, however, no requirements as to what weight loss strategy is employed, which may represent a time point where dietary intervention, including low-calorie, ketogenic, or carbohydrate-restricted diets, should be utilized. At least two recent clinical trials have demonstrated safety and efficacy in pre-operative very low-carbohydrate ketogenic diets before bariatric surgery for increasing weight loss and decreasing liver volume [ 40 , 41 ].

Furthermore, despite technically adequate surgery, an alarming number of patients may still experience weight regain and/or recurrence of comorbid obesity-associated conditions. In these patients, effective strategies for dietary intervention are even more important. Approximately 10–15% of patients fail to lose adequate weight (failure defined as <50% of excess weight) or demonstrate significant weight regain after bariatric surgery without evidence of an anatomic or technical reason [ 42 ]. Additionally, in 25–35% of patients who undergo surgery, significant weight regain (defined as >15% of initial weight loss) occurs within two to five years post-operatively [ 43 ]. These patients often require further medical management with weight loss medications, further dietary and behavioral intervention, and, for some, reoperation. Reoperation can be for either revision for further weight loss (narrowing of the gastric sleeve, conversion of VSG to RYGB , and increasing the length of the roux limb) or reversal of RYGB due to health concerns, most commonly associated with malnutrition. A small cohort of patients (4%) may experience severe weight loss with significant malnutrition leading to hospitalization in over 50%, mortality rates of 18%, and need for reversal of RYGB anatomy. While the incidence of RYGB reversal is unknown, based upon a systematic review that included 100 patients spanning 1985–2015, the rate of reversal parallels the increasing rate of bariatric surgery [ 44 ].

In the short term, T2D reversal rates with surgery have been reported to be as high as 80%, with an additional 15% demonstrating partial improvement in T2D despite still requiring medication [ 17 ]. Within one week after RYGB, patients experience improved fasting hepatic insulin clearance, reduced basal de novo glucose production, and increased hepatic insulin sensitivity; by three months and one year after surgery, patients have improved beta-cell sensitivity to glucose, increased GLP-1 secretion from the gut, and improved insulin sensitivity in muscle and fat cells [ 45 ]. Over time, T2D remission rates remain high but do decline; Purnell and colleagues reported three-year remission rates of 68.7% after RYGB [ 29 ]. However, Pories published results from a 14-year prospective study with mean follow-up of 7.6 years, and found 10-year remission rates remained around 83% [ 46 ]. In a 10-year follow-up study of participants from the Swedish Obese Subjects (SOS) study that prospectively followed patients who underwent bariatric surgery, the authors reported a 72% ( n = 342) and 36% ( n = 118) recovery rate from T2D for RYGB at two years and 10 years, respectively [ 47 ].

The long-term metabolic impact and risk reduction from surgery remain high in a substantial number of patients and this route to reversal clearly has the most robust data to support its use. As evidenced by the dramatic improvements in metabolic state that precede weight loss, bariatric surgery is far more than merely a restrictive and/or malabsorptive procedure. Large shifts in bile acid signaling in the lumen of the small intestine, gut nutrient sensing, and changes in the microbiota community appear to greatly impact overall host health. Further research is ongoing using both basic and translational science models to identify the role of these various hormones and metabolites; perhaps there will be a way to one day harness the beneficial effects of bariatric surgery without the need for anatomic rearrangement.

3.2. Low-Calorie Diets (LCD)

As diabetes rates have risen to unprecedented levels [ 1 , 2 ], the number of studies examining diabetes reversal using non-surgical techniques has increased. A handful of studies have reported successful weight loss with decreased insulin resistance, plasma glucose, and medication use following a LCD. As early as 1976, Bistrian et al. [ 48 ] reported that a very low-calorie protein-sparing modified fast allowed for insulin elimination in all seven obese patients with T2D. The average time to insulin discontinuation was only 6.5 days, and the longest was 19 days. In a study by Bauman et al., a low-calorie diet of 900 kcal, including 115 g of protein, led to significant improvement in glycemic control that was mainly attributed to improvements in insulin sensitivity [ 49 ]. Furthermore, a study conducted in obese T2D patients found that a LCD and gastric bypass surgery were equally effective in achieving weight loss and improving glucose and HbA1c levels in the short term [ 50 ]. Weight loss, however, persisted in the diet-treated patients only for the first three months, indicating difficulty with long-term maintenance [ 47 ]. Similarly, other studies also reported similar pattern of early blood glucose normalization without medication use, but the improvements were not sustained long-term [ 51 , 52 , 53 ]. Likewise, the study by Wing et al., even though reported significant and greater improvements of HbA1c at 1 year in the intermittently delivered very low-calorie diet, the HbA1c improvement was not significantly different than what was reported in the patients receiving low-calorie diet (LCD) throughout the one year period [ 54 ]. Furthermore, the glycemic improvements observed at 1 year were not maintained through 2-years, even though the group with intermittent very low-calorie diet had less medication requirement than the group in the LCD arm at 2 years [ 54 ]. Lastly, micronutrient deficiencies with the use of calorie restricted diets has been shown and supplementation and monitoring for deficiencies is a consideration with their use [ 55 , 56 ].

While these previous studies were not assessing diabetes remission or reversal rate per se, they demonstrated the effectiveness of calorie restriction in achieving weight loss and improved glycemic control, which are the core goals of reversal. In 2003, the Look AHEAD trial randomized 5145 overweight or obese patients with T2D to an intervention group that received either an intensive lifestyle intervention (ILI) including calorie restriction and increased physical activity or to a control group that included diabetes support and education (DSE) [ 57 ]. Post hoc analysis of this study revealed that at one year, 11.5% of the participants in the ILI group achieved remission (partial or complete); however, remission rates subsequently decreased over time (9.2% at year two and 7.3% at year four). Nevertheless, the remission rates achieved through ILI were three to six times higher than those achieved in the DSE group. Lower baseline HbA1c, greater level of weight loss, shorter duration of T2D diagnosis, and lack of insulin use at baseline predicted higher remission rate in ILI participants [ 58 ].

Following the Look AHEAD study, other studies have evaluated a LCD for diabetes remission [ 59 , 60 , 61 ]. Most of these studies assessed remission over a short period of time in a small study sample. Bhatt et al. reported that six of the 12 individuals achieved partial remission at the end of the three-month intervention [ 61 ]. Ades et al. studied an intensive lifestyle program including calorie restriction and exercise, and reported that eight of the 10 individuals with recently diagnosed T2D achieved partial remission at six months, including one with complete remission [ 60 ]. The study ended at six months, therefore long term sustainability was not assessed. Another study assessing a one-year diabetes remission retrospectively among those undergoing 12 weeks of the intensive weight loss program “Why Wait” had a much lower remission rate of 4.5%, with 2.3% of them achieving partial remission, while another 2.3% had complete remission [ 59 ]. This study suggests that long-term maintenance of remission is a challenge. Moreover, diabetes remission was more likely reported in those who had a shorter diabetes duration, lower baseline HbA1c, and were taking fewer hypoglycemic medications [ 59 , 61 ].

An initial 2011 diabetes reversal study by Taylor and colleagues showed that a very low-calorie diet of 600 Kcal/day not only normalized glucose, HbA1c, and hepatic insulin sensitivity levels within a week, but also led to decreased hepatic and pancreatic triacylglycerol content and normalization of the insulin response within eight weeks [ 62 ]. At 12 weeks post-intervention, many of the improvements were maintained, but over a quarter of the patients had an early recurrence of diabetes. Further, average weight regain during the 12 weeks post-intervention was 20% [ 62 ]. As a follow-up to the 2011 study, the same group performed a larger and longer study with eight weeks of a very low-calorie meal replacement (624–700 kcal/day) followed by two weeks of solid food replacement and a weight maintenance program of up to six months [ 63 ]. In this study, those who achieved a fasting blood glucose of <7 mmol/L (<126 mg/dL) were categorized as responders, while others were categorized as non-responders. At six months, 40% of participants who initially responded to the intervention were still in T2D remission which was defined by achieving a fasting plasma glucose of <7mmol/L; the majority of those who remitted (60%) had a shorter diabetes duration (<4 years) [ 63 ].

These short-term studies were the foundation for a community-based cluster-randomized clinical trial called DiRECT (Diabetes Remission Clinical Trial). DiRECT enrolled a sample of 306 relatively healthy participants with T2D (people on insulin or with a diabetes duration longer than six years were excluded) [ 64 ] ( Figure 1 ). They were cluster randomized to either standard diabetes care or an intervention using low-calorie meal replacement diet (825–853 kcal/day) for three to five months, followed by stepwise food re-introduction and a long-term weight maintenance program. At one-year follow-up, 46% of patients met the study criteria of diabetes remission (HbA1c <6.5% without antiglycemic medications) [ 64 ] and at two years the remission rate was 36% [ 65 ]. The DiRECT study has extended their follow-up an additional three years to assess the long-term impact on remission.

Taken together, evidence suggests that a LCD is effective in reversing diabetes in the short term up to two years, and its effectiveness was predominantly demonstrated in those with shorter duration since diabetes diagnosis. It is important to note that a substantial level of calorie restriction is needed to generate a sufficient level of weight loss for reversing diabetes. Short-term intervention with moderate energy restriction and metformin for modest weight loss was not as effective in reversing diabetes as compared to standard diabetes care [ 66 ]. Lifestyle intervention with severe energy restriction may have some deleterious effect on the body composition and physiology, which poses a concern for long-term health [ 67 ]. Furthermore, long-term achievement of diabetes remission, adherence to the diet, and weight loss maintenance after the diet remain a challenge. Studies have also suggested that physiological and metabolic adaptation of the body in response to caloric restriction may shift energy balance and hormonal regulation of weight toward weight regain after weight loss [ 67 , 68 ]. Thus, it is crucial that future studies are directed towards assessing the long-term sustainability of diabetes remission led by LCD and feasibility of this diet on the physiological adaptation and body composition changes.

3.3. Carbohydrate-Restricted Diets (LC)

Before the discovery of insulin in 1921, low carbohydrate (LC) diets were the most frequently prescribed treatment for diabetes [ 69 , 70 ]. The paradigm shifted both with the development of exogenous insulin and later with the emergence of the low-fat diet paradigm. A diet low in fat, which by default is high in carbohydrate, became the standard recommendation in guidelines around the globe [ 71 ]. Rather than preventing elevations in glucose, the goal became maintenance of blood sugar control via the increased use of glycemic control medications, including insulin [ 72 ]. Over the last decade, clinical studies have begun to resurrect the pre-insulin LC dietary approach. In response to the new evidence on the efficacy of carbohydrate restriction, low-carbohydrate has recently been endorsed as an eating pattern by the ADA and the European Association for the Study of Diabetes (EASD) [ 5 , 73 ]. In addition, the Veterans Affairs/Department of Defense (VA/DOD) guidelines now recommend carbohydrate restriction as low as 14% of energy intake in its most recent guidelines for treatment of diabetes (VA) [ 74 ].

LC diets are based on macronutrient changes rather than a focus on calorie restriction [ 75 ]. Although the exact definition varies, a low-carbohydrate diet usually restricts total carbohydrates to less than 130 grams per day, while a very low-carbohydrate or ketogenic diet usually restricts total carbohydrates to as low as 20–30 grams per day. Protein consumption is generally unchanged from a standard ADA diet (around 20% of intake), with the remaining energy needs met by fat from either the diet or mobilized body fat stores. Carbohydrate sources are primarily non-starchy vegetables with some nuts, dairy, and limited fruit [ 75 ].

A total of 32 separate trials examining carbohydrate restriction as a treatment for T2D were found when our search was performed [ 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 ]. However, for reasons that may include varied levels of carbohydrate restriction and differing levels of support given, not all studies had results that would be consistent with diabetes reversal. A number of shorter-term trials have found a significant between-group advantage of a low-carbohydrate intervention for T2D [ 80 , 84 , 92 , 97 ]. Data from longer-term trials are limited, and in some follow-up studies, the between-group advantage seen initially was lost or reduced, although it often remains significantly improved from baseline. This raises the question of long-term sustainability using this approach. Due to heterogeneity in methodology and definition of carbohydrate restriction, the ability to fully examine T2D reversal based on the existing studies is limited. Based upon a recent systematic review of LC, it appears that the greatest improvements in glycemic control and greatest medication reductions have been associated with the lowest carbohydrate intake [ 109 ]. In consideration of these limitations, it appears important to assess the level of carbohydrate restriction, support or other methods given to encourage sustainability, and length of follow-up.

A study comparing an ad libitum very low-carbohydrate (<20 g total) diet to an energy-restricted low-glycemic diet in T2D found greater reduction in HbA1c, weight, and insulin levels in the low-carbohydrate arm [ 89 ]. Additionally, 95% of participants in the low-carbohydrate arm reduced or eliminated glycemic control medications, compared to 62% in the low glycemic index arm at 24 weeks. Instruction was given in a one-time session with a dietician and included take-home materials for reference. A slightly longer study (34 weeks) trial [ 85 ] found that a very low-carbohydrate ketogenic diet intervention (20–50 g net carbs per day) resulted in HbA1c below the threshold for diabetes in 55% of the patients, compared to 0% of patients in the low-fat arm. The education sessions were all online and included behavior modification strategies and mindful eating which was aimed to address binge eating. New lessons were emailed to the patients weekly for the first 16 weeks and then every two weeks for the remainder of the study.

A small (34 participants) one-year study of an ad libitum, very low-carbohydrate diet compared to a calorie-restricted moderate carbohydrate diet found a significant reduction in HbA1c between groups favoring the low-carbohydrate arm [ 86 ]. At one year, 78% of participants who began the trial with a HbA1c above 6.5% no longer met the cutoff for the diagnosis of diabetes, no longer required any non-metformin medication, and significantly reduced or eliminated metformin. Total kilocalorie intake was not significantly different between the two groups, even with moderate carbohydrate restriction. Despite equal energy intake, the low carbohydrate group lost significantly more weight and had improved glycemic control, which indicates a potential mechanistic role for carbohydrate restriction itself. The support given was 19 classes over the 12-month period, tapering in frequency over time.

Another one-year trial [ 76 ] found significant HbA1c reduction in the subset of patients with diabetes ( n = 54) assigned to an ad libitum low-carbohydrate diet (<30 total grams per day), compared to an energy-restricted low-fat diet. These results remained significant after adjusting the model for weight loss, indicating an effect of the carbohydrate reduction itself. The support given was four weekly sessions during the first month, followed by monthly sessions for the remaining 11 months.

A metabolic ward study on 10 patients with T2D [ 96 ] found that 24-h glucose curves normalized within two weeks on a very low-carbohydrate diet (<21 g total per day). This was in addition to medication reduction and elimination including insulin and sulfonylureas After accounting for body water changes, the average weight loss during the two-week period was 1.65 kg (average of <2% total body weight which is similar to the results of bariatric surgery, where normoglycemia is seen prior to significant weight loss. Interestingly, despite the diet being ad libitum other than the carbohydrate limit, the average energy intake decreased by 1000 kcal per day. Assuming no further change in glycemic control, HbA1c would be 5.6% after eight weeks, which would represent a reduction of 23% from baseline. The fact that HbA1c reductions were greater than in other, longer-term outpatient studies may indicate that support of dietary changes is the key to longer-term success.

In our published trial providing significant support through the use of a continuous care intervention (CCI), we examined using a low-carbohydrate diet aimed at inducing nutritional ketosis in patients with T2D ( n = 262), compared with usual care T2D patients ( n = 87) [ 98 ] ( Figure 1 ). At one year, the HbA1c decreased by 1.3% in the CCI, with 60% of completers achieving a HbA1c below 6.5% without hypoglycemic medication (not including metformin). Overall, medications were significantly reduced, including complete elimination of sulfonylureas and reduction or elimination of insulin therapy in 94% of users. Most cardiovascular risk factors showed significant improvement [ 110 ]. The one-year retention rate was 83%, which indicates that a non-calorie-restricted, low-carbohydrate intervention can be sustained. Improvements were not observed in the usual care patients. The newly released two-year results of this trial [ 106 ] show sustained improvements in normoglycemia, with 54% of completers maintaining HbA1c below 6.5% without medication or only on metformin. The retention rate at two years was 74%, further supporting the sustainability of this dietary intervention for diabetes reversal. Weight loss of 10% was seen at 2-years despite no intentional caloric restriction instruction. Additionally, this trial involved participants with a much longer duration of diabetes (8.4 years on average) than other nutrition trial interventions [ 58 , 64 , 65 ] and did not exclude anyone taking exogenous insulin. As duration of T2D and insulin use have both been identified to be negative factors in predicting remission after bariatric surgery [ 111 , 112 ], the 2-year results of this trial may be even more significant.

It is interesting to note that most studies utilize ad libitum intake in the carbohydrate-restricted arm. Despite this, in studies that have tracked energy intake, spontaneous calorie restriction has occurred [ 113 , 114 ]. In many trials where energy intake has been prescribed or weight loss has been equal, an advantage has been seen in glycemic control, weight, or both in the low-carbohydrate arm [ 86 , 91 , 107 ]. A better understanding of the role that caloric intake, whether prescribed or spontaneous, plays in the overall success is important. In cases of spontaneous energy intake reduction, elucidating the specific mechanism behind this reduction would help in the overall personalization of this approach.

Multiple studies have evaluated side effects or potential complications of carbohydrate restriction. The diet has been found to be safe and well tolerated although long term hard outcome data is lacking and should be a focus of future research. A transient rise in uric acid early in very low-carbohydrate restriction without an associated increase in gout or kidney stones has been documented [ 84 , 98 , 100 ]. Blood urea nitrogen (BUN) has been found to increase and decrease in different studies without an associated change in kidney function [ 87 , 98 , 100 , 115 , 116 ]. Recently, bone mineral density has been found to be unchanged despite significant weight loss after two years of a ketogenic diet intervention in patients with T2D [ 108 ]. While most studies show an improvement or no change in LDL-C levels in patients with T2D on a low-carbohydrate diet, there have been two studies that have found an increase in LDL-C in participants with T2D [ 99 , 111 ]. In one of the studies that found an increase in calculated LDL-C, a non-significant reduction in measured ApoB lipoproteins and unchanged non-HDL cholesterol were seen. Monitoring LDL-C or a measured value of potentially atherogenic lipoproteins such as ApoB should be considered. Lastly, micronutrient deficiency has been seen with a carbohydrate restricted diet, supplementation and monitoring should be given consideration with this intervention [ 56 ].

Although the use of very low-carbohydrate diets for diabetes reversal shows promising results, the lack of longer-term follow-up studies remains a limitation. Follow up is limited to two years, and therefore longer-term studies are needed to determine the sustainability of the metabolic improvements. Determining the appropriate method of support may be a key to the overall success with disease reversal.

Additional evidence has become available in recent years suggesting that diabetes reversal is a possible alternative to consider in place of traditional diabetes treatment and management. In this paper, we provide a review of three methods that have been shown to successfully reverse type 2 diabetes. The current body of evidence suggests that bariatric surgery is the most effective method for overall efficacy and prolonged remission, even though concerns associated with surgical complications, treatment cost and complete lifestyle modification after surgery remain challenges for wide adoption of this approach. While both the LCD and LC dietary approaches are convincing for reversing diabetes in the short term (up to two years), long term maintenance of diabetes remission is still unproven. There are limited available data supporting long term maintenance of weight loss and its associated glycemic improvements in response to LCD; similarly, long-term adherence to a low carbohydrate diet will likely remain an obstacle without the development of proper patient education and optimal support for long-term behavioral change. Moreover, research in understanding the mechanism of diabetes reversibility in all three approaches and its overlapping mechanistic pathways are lacking; this is an area for future research emphasis.

There are similar identified negative predictors of remission for all three approaches. These factors include longer diabetes duration and increased severity, lower BMI, advanced age, poor glycemic control, and low C-peptide levels (indicating decreased endogenous insulin production) [ 117 ]. Further exploration into the heterogeneity of these factors will help personalize the approach, determine realistic goals for each patient, and should be considered during treatment discussions. Ongoing research into algorithm development will be helpful in this regard.

5. Conclusions

Overall, as a society we can no longer afford or tolerate the continued rising rates of diabetes. Despite many barriers within the healthcare system as a whole, providers are responsible on a daily basis for the lives of patients caught up in this unprecedented epidemic. The current standard of care may be suitable for some, but others would surely choose reversal if they understood there was a choice. The choice can only be offered if providers are not only aware that reversal is possible but have the education needed to review these options in a patient-centric discussion.

Acknowledgments

We thank James McCarter and Stephen Phinney for their edits, which greatly improved the manuscript.

Abbreviations:

C	carbohydrate restriction
DSS-II	Diabetes Surgery Summit
RYGB	Roux-en-Y Gastric Bypass
SG	Sleeve Gastrectomy
CCK	cholecystokinin
PYY	peptide-tyrosine-tyrosine
GLP-1	glucagon-like peptide 1
LABS-2	Longitudinal Assessment of Bariatric Surgery 2
LCD	low-calorie diet
IMT	intensive medical intervention
DiRECT	Diabetes Remission Clinical Trial
ASD	European Association for the Study of Diabetes
VA/DOD	Veterans Affairs/Department of Defense

Author Contributions

Conceptualization, S.J.H. and S.J.A. Investigation, S.J.H., V.M.G., T.L.H., S.J.A. Writing—original draft, S.J.H., V.M.G., S.J.A. Writing—review and editing, S.J.H., V.M.G., T.L.H., S.J.A. All authors approved of the final manuscript.

Conflicts of Interest

S.J.H. is an employee and shareholder of Virta Health, a for-profit company that provides remote diabetes care using a low-carbohydrate nutrition intervention, and serves as an advisor for Atkins Corp. V.M.G. has no conflicts of interest to declare. T.L.H. is an employee of Virta Health. S.J.A. is an employee and shareholder of Virta Health.

IMAGES

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Pathophysiology of Type 2 Diabetes Mellitus
Pathophysiology of Type 2 Diabetes Mellitus - PMC
Type 2 Diabetes Mellitus: A Review of Current Trends
Introduction. Diabetes mellitus (DM) is probably one of the oldest diseases known to man. It was first reported in Egyptian manuscript about 3000 years ago. 1 In 1936, the distinction between type 1 and type 2 DM was clearly made. 2 Type 2 DM was first described as a component of metabolic syndrome in 1988. 3 Type 2 DM (formerly known as non-insulin dependent DM) is the most common form of DM ...
Management of Type 2 Diabetes: Current Strategies, Unfocussed Aspects
Introduction. Insulin resistance and β-cell dysfunction are the 2 major hallmarks of type 2 diabetes mellitus (T2DM) that appear as the result of disturbed homeostasis [].Failure of β-cells (∼80% of their β-cell function) and insulin resistance in muscles and the liver is a vicious triumvirate responsible for the core physiological defects.
Trends in Diabetes Treatment and Control in U.S. Adults, 1999-2018
However, type 2 diabetes makes up more than 90% of diagnosed diabetes cases in the United States. 35 Thus, our findings largely reflect risk-factor treatment and control in those with type 2 diabetes.
Type 2 diabetes
Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. The number affected is increasing rapidly with alarming trends in children and young adults (up to age 40 years). Early detection and proactive management are crucial for prevention and mitigation of microvascular and macrovascular complications and mortality burden. Access to novel therapies ...
Type 2 diabetes
Type 2 diabetes mellitus, the most frequent subtype of diabetes, is a disease characterized by high levels of blood glucose (hyperglycaemia). It arises from a resistance to and relative deficiency ...
Type 2 diabetes
Abstract. Type 2 diabetes accounts for nearly 90% of the approximately 537 million cases of diabetes worldwide. The number affected is increasing rapidly with alarming trends in children and young adults (up to age 40 years). Early detection and proactive management are crucial for prevention and mitigation of microvascular and macrovascular ...
The burden and risks of emerging complications of diabetes mellitus
Chatterjee, S. et al. Type 2 diabetes as a risk factor for dementia in women compared with men: a pooled analysis of 2.3 million people comprising more than 100,000 cases of dementia. Diabetes ...
Global, regional, and national burden of diabetes from 1990 to 2021
Global, regional, and national burden of diabetes from ...
Risk factors for type 2 diabetes mellitus: An exposure-wide ...
Background Type 2 diabetes mellitus (T2DM) is a global epidemic associated with increased health expenditure, and low quality of life. Many non-genetic risk factors have been suggested, but their overall epidemiological credibility has not been assessed. Methods We searched PubMed to capture all meta-analyses and Mendelian randomization studies for risk factors of T2DM. For each association ...
(PDF) Type-2 Diabetes Mellitus: A Review of Current Trends
Recent research into the biology of type 2 diabetes has led to the development of new medications such as glucagon-like peptide 1 analogues: dipeptidyl peptidase inhibitors, sodium glucose ...
Association of risk factors with type 2 diabetes: A systematic review
1. Introduction. Diabetes Mellitus (DM) commonly referred to as diabetes, is a chronic disease that affects how the body turns food into energy .It is one of the top 10 causes of death worldwide causing 4 million deaths in 2017 , .According to a report by the International Diabetes Federation (IDF) , the total number of adults (20-79 years) with diabetes in 2045 will be 629 million from 425 ...
Journal of Diabetes Research
Journal of Diabetes Research is an open access journal that publishes articles related to type 1 and type 2 diabetes. Topics include etiology, pathogenesis, management, and prevention of diabetes, as well as associated complications such as nephropathy. As part of Wiley's Forward Series, this journal offers a streamlined, faster publication ...
PDF Type 2 diabetes
Pathophysiology. The pathophysiology of type 2 diabetes is characterised by insulin resistance and initial hyperinsulinaemia, followed by progressive decline in the capacity of pancreatic β cells to produce insulin. The variable mix of β-cell dysfunction and insulin resistance ultimately underlies the complexity of type 2 diabetes.
Type 2 Diabetes Mellitus: A Pathophysiologic Perspective
Introduction. Type 2 Diabetes Mellitus (T2DM) is characterized by a persistently elevated blood glucose, or an elevation of blood glucose after a meal containing carbohydrate ().Unlike Type 1 Diabetes which is characterized by a deficiency of insulin, most individuals affected by T2DM have elevated insulin levels (fasting and/or post glucose ingestion), unless there has been beta cell failure ...
Clinical Research on Type 2 Diabetes: A Promising and Multifaceted
The chronic complications of type 2 diabetes are a major cause of mortality and disability worldwide [1, 2]. Clinical research is the main way to gain knowledge about long-term diabetic complications and reduce the burden of diabetes. This allows for designing effective programs for screening and follow-up and fine-targeted therapeutic ...
Review Type II diabetes mellitus: a review on recent drug based
This review explores the current conventional drugs used in the treatment of type 2 DM, the associated limitations related to their usage and the cutting edge novel nanoformulations that are under continual research for circumventing the stated drawbacks of the conventional drug use. 2. Pathophysiology of diabetes.
Diabetes
Research Open Access 28 Aug 2024 Nutrition & Diabetes Volume: 14, P: 69 Linear effects of glucose levels on voice fundamental frequency in type 2 diabetes and individuals with normoglycemia
Diabetes‐related distress in people with type 2 diabetes: experience
Diabetes distress is commonly observed in people with type 2 diabetes and is associated with suboptimal self-management, poor glycaemic control and adverse health outcomes. 2, 3 In the Diabetes Attitudes, Wishes and Needs second study (DAWN2) multinational study, 45% of people living with diabetes had experienced diabetes distress, and a ...
Type 2 diabetes
415 million people live with diabetes worldwide, and an estimated 193 million people have undiagnosed diabetes. Type 2 diabetes accounts for more than 90% of patients with diabetes and leads to microvascular and macrovascular complications that cause profound psychological and physical distress to both patients and carers and put a huge burden on health-care systems. Despite increasing ...
New Aspects of Diabetes Research and Therapeutic Development
I. Introduction. Diabetes mellitus, a metabolic disease defined by elevated fasting blood glucose levels due to insufficient insulin production, has reached epidemic proportions worldwide (World Health Organization, 2020).Type 1 and type 2 diabetes (T1D and T2D, respectively) make up the majority of diabetes cases with T1D characterized by autoimmune destruction of the insulin-producing ...
Diabetes: a defining disease of the 21st century
In 2021, type 2 diabetes accounted for 90% of all diabetes prevalence. Most of this burden is attributable to social risk factors—such as high BMI, dietary risks, environmental and occupational risks, tobacco use, alcohol use, and low physical activity—that thrive on the obesogenic way our environments are designed and the inequitable way ...
Type 2 Diabetes Research At-a-Glance
The ADA is committed to continuing progress in the fight against type 2 diabetes by funding research, including support for potential new treatments, a better understating of genetic factors, addressing disparities, and more. For specific examples of projects currently funded by the ADA, see below. Greg J. Morton, PhD.
Reversing Type 2 Diabetes: A Narrative Review of the Evidence
Abstract. Background: Type 2 diabetes (T2D) has long been identified as an incurable chronic disease based on traditional means of treatment. Research now exists that suggests reversal is possible through other means that have only recently been embraced in the guidelines. This narrative review examines the evidence for T2D reversal using each ...

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Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses

Conclusions

Materials and methods

Data extraction

Statistical analysis

Assessment of epidemiological credibility

Eligible studies

Statistically significant associations, heterogeneity and biases

Mendelian randomization studies

Supporting information

HYPOTHESIS AND THEORY article

Introduction

How Much Glucose Is in the Blood?

Major Exogenous Factors That Raise the Blood Glucose

Major Endogenous Factors That Raise the Blood Glucose

Major Exogenous Factors That Lower the Blood Glucose

Major Endogenous Factors That Lower the Blood Glucose

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What Causes IR and T2DM?

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Diets Without Carbohydrate Reverse IR and T2DM

What Causes Atherosclerosis?

Data Availability Statement

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Type 2 Diabetes Research At-a-Glance

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Reversing Type 2 Diabetes: A Narrative Review of the Evidence

Victoria M Gershuni

Tamara L Hazbun

1. Introduction

2. Materials and Methods

3. Results and Discussion

3.2. Low-Calorie Diets (LCD)

3.3. Carbohydrate-Restricted Diets (LC)

5. Conclusions

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