Association of Diabetes Subgroups With Race/Ethnicity, Risk Factor Burden and Complications: The MASALA and MESA Studies

Cultural Considerations in Healthcare for Older Asian Indian US Adults

Approximately 4.8 million Asian Indians were documented by the US Census Bureau in 2023. Members of this population follow different religious practices, speak a multitude of languages, and belong to different socioeconomic classes. Asian Indians immigrated to this country in different waves, leading to transgenerational diversity. Immigration, financial, religious, and cultural factors uniquely impact how Asian Indians interact with their healthcare providers. Asian Indians have settled throughout the country, and it is important that clinicians familiarize themselves with the specific health concerns that affect this rapidly growing population.

Diabetes in South Asians: Uncovering Novel Risk Factors With Longitudinal Epidemiologic Data: Kelly West Award Lecture 2023

South Asian populations have a higher prevalence and earlier age of onset of type 2 diabetes and atherosclerotic cardiovascular diseases than other race and ethnic groups. To better understand the pathophysiology and multilevel risk factors for diabetes and cardiovascular disease, we established the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study in 2010. The original MASALA study cohort (n = 1,164) included 83% Asian Indian immigrants, with an ongoing expansion of the study to include individuals of Bangladeshi and Pakistani origin. We have found that South Asian Americans in the MASALA study had higher type 2 diabetes prevalence, lower insulin secretion, more insulin resistance, and an adverse body composition with higher liver and intermuscular fat and lower lean muscle mass compared with four other U.S. race and ethnic groups. MASALA study participants with diabetes were more likely to have the severe hyperglycemia subtype, characterized by β-cell dysfunction and lower body weight, and this subtype was associated with a higher incidence of subclinical atherosclerosis. We have found several modifiable factors for cardiometabolic disease among South Asians including diet and physical activity that can be influenced using specific social network members and with cultural adaptations to the U.S. context. Longitudinal data with repeat cardiometabolic measures that are supplemented with qualitative and mixed-method approaches enable a deeper understanding of disease risk and resilience factors. Studying and contrasting Asian American subgroups can uncover the causes for cardiometabolic disease heterogeneity and reveal novel methods for prevention and treatment.

Real-World Systolic and Diastolic Blood Pressure Levels and Cardiovascular Mortality in Patients With Type 2 Diabetes-Results From a Large Registry Cohort in Asia

BACKGROUND

Elevated blood pressure (BP) is associated with increased risk of cardiovascular mortality. However, there is ongoing debate whether intensive BP lowering may paradoxically increase the risk of cardiovascular disease (CVD), especially in patients with type 2 diabetes (T2D). We investigated the association of BP with risk of CVD mortality in patients with T2D.

METHODS AND RESULTS

We used data on 83 721 patients with T2D from a multi-institutional diabetes registry in Singapore from 2013 to 2019. BP was analyzed as categories and restricted cubic splines using Cox multivariable regression analysis stratified by preexisting CVD and age (<65 years versus ≥65 years). The primary outcome was CVD mortality, determined via linkage with the national registry. Among 83 721 patients with T2D (mean age 65.3 years, 50.6% women, 78.9% taking antihypertensive medications), 7.6 per 1000 person-years experienced the primary outcome. Systolic BP had a graded relationship with a significant increase in CVD mortality at levels >120 to 129 mm Hg. Diastolic BP levels >90 mm Hg were significantly associated with CVD mortality in those aged ≥65 years. In addition, diastolic BP <70 mm Hg was associated with a significantly higher risk of CVD mortality in all patients.

CONCLUSIONS

In patients with T2D, clinic systolic BP levels ≥130 mm Hg or diastolic BP levels ≥90 mm Hg are associated with higher risk of CVD mortality. Diastolic BP <70 mm Hg is also associated with the risk of adverse CVD outcomes, although reverse causality cannot be ruled out.

Precision subclassification of type 2 diabetes: a systematic review

BACKGROUND

Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients.

METHODS

We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches.

RESULTS

Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes.

CONCLUSION

Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Association of diabetes with coronary artery calcium in South Asian adults and other race/ethnic groups: The multi-ethnic study of atherosclerosis and the mediators of atherosclerosis in South Asians living in America study

PURPOSE

South Asian (SA) persons have increased risks for diabetes mellitus (DM) and atherosclerotic cardiovascular disease (ASCVD). We examined whether the association of DM with subclinical atherosclerosis assessed by coronary artery calcium (CAC) differs in SA versus other ethnic groups.

METHODS

We studied adults from the Multi-Ethnic Study of Atherosclerosis and the Mediators of Atherosclerosis in South Asians Living in America studies without ASCVD. CAC was examined among those normoglycemic, pre-DM and DM. Logistic regression examined pre-DM and DM with the odds of any CAC > 0 and CAC ≥ 100.

RESULTS

Among 7562 participants, CAC > 0 and CAC ≥ 100 in those with DM was highest in non-Hispanic White (NHW) (80% and 48%) and SA (72% and 41%) persons. Adjusted Ln (CAC + 1) was highest in NHW (3.68 ± 0.21) and SA (3.60 ± 0.23) (p < .01) DM patients. SA and NHW adults with DM (vs normoglycemic) had highest odds of CAC > 0 (2.13 and 2.27, respectively, p < .01). For CAC ≥ 100, SA and Chinese adults had the highest odds (2.28 and 2.27, respectively, p < .01). Fasting glucose and glycated hemoglobin were most strongly associated with CAC among SA.

CONCLUSIONS

Diabetes mellitus most strongly relates to any CAC in SA and NHW adults and CAC ≥ 100 in SA and Chinese adults, helping to explain the relation of DM with ASCVD in these populations.

Subtypes of Type 2 Diabetes and Incident Cardiovascular Disease Risk: UK Biobank and All of Us Cohorts

OBJECTIVE

To characterize and validate the subtypes of type 2 diabetes (T2D) using a novel clustering algorithm and to further assess their associations with the risk of incident cardiovascular disease (CVD) events.

METHODS

Unsupervised k-means clustering based on glycated hemoglobin level, age at onset of T2D, body mass index, and estimated glomerular filtration rate was conducted among participants with T2D from the UK Biobank (March 13, 2006, to October 1, 2010) and replicated in the All of Us cohort (May 30, 2017, to April 1, 2021).

RESULTS

Five distinct T2D clusters were identified in the UK Biobank and validated in the All of Us cohort, characterizing the phenotypically heterogeneous subtypes. With a median follow-up of 11.69 years for patients with T2D in the UK Biobank, risks of incident CVD events varied considerably between the clusters after adjustment for potential confounders and multiple testing (all P<.001). With cluster 1 characterized by early onset of T2D and mild abnormalities of other variables as the reference, patients in cluster 5 characterized by poor renal function had the highest risk of CVD events (hazard ratio [95% CI], 1.72 [1.45 to 2.03], 2.41 [1.93 to 3.02], and 1.62 [1.35 to 1.94] for composite CVD event, CVD mortality, and CVD incidence, respectively; all P<.001), followed by cluster 4 characterized by poor glycemic control and cluster 3 characterized by severe obesity. No consistently significant difference was found between cluster 2 characterized by late onset of T2D and cluster 1.

CONCLUSION

Our study, using a novel clustering algorithm to identify robust subtypes of T2D, found heterogeneous associations with incident CVD risk among patients with diabetes.

Disparities in diabetes prevalence and management by race and ethnicity in the USA: defining a path forward

Type 2 diabetes disparities in the USA persist in both the prevalence of disease and diabetes-related complications. We conducted a literature review related to diabetes prevention, management, and complications across racial and ethnic groups in the USA. The objective of this review is to summarise the current understanding of diabetes disparities by examining differences between and within racial and ethnic groups and among young people (aged <18 years). We also examine the pathophysiology of diabetes as it relates to race and ethnic differences. We use a conceptual framework built on the socioecological model to categorise the causes of diabetes disparities across the lifespan looking at factors in five domains of health behaviours and social norms, public awareness, structural racism, economic development, and access to high-quality care. The range of disparities in diabetes prevalence and management in the USA calls for a community-engaged and multidisciplinary approach that must involve community partners, researchers, practitioners, health system administrators, and policy makers. We offer recommendations for each of these groups to help to promote equity in diabetes prevention and care in the USA.

Systematic review of precision subclassification of type 2 diabetes

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Enrollment of underrepresented racial and ethnic groups in the Rare and Atypical Diabetes Network (RADIANT)

Introduction

Diabetes mellitus in underrepresented racial and ethnic groups (URG) is rapidly increasing in incidence and has worse outcomes than diabetes in non-Hispanic White individuals. Rare and Atypical Diabetes Network (RADIANT) established recruitment targets based on the racial and ethnic distribution of the USA to enroll a diverse study population. We examined participation of URG across RADIANT study stages and described strategies to enhance recruitment and retention of URG.

Materials and Methods

RADIANT is a multicenter NIH-funded study of people with uncharacterized forms of atypical diabetes. RADIANT participants consent online and progress through three sequential study stages, as eligible.

Results

We enrolled 601 participants with mean age 44 ± 16.8 years, 64.4% female. At Stage 1, 80.6% were White, 7.2% African American (AA), 12.2% other/more than one race, and 8.4% Hispanic. Enrollment of URG was significantly below preset targets across most stages. Referral sources differed by race (p < 0.001) but not ethnicity (p = 0.15). Most AA participants were referred by RADIANT investigators (58.5% vs. 24.5% in Whites), whereas flyers, news, social media, and family or friends were more frequent referral sources for White individuals (26.4% vs. 12.2% in AA). Ongoing initiatives to increase enrollment of URG in RADIANT include engaging with clinics/hospitals serving URG, screening electronic medical records, and providing culturally competent study coordination and targeted advertisement.

Conclusions

There is low participation of URG in RADIANT, potentially limiting the generalizability of its discoveries. Investigations into barriers and facilitators for recruitment and retention of URG in RADIANT, with implications for other studies, are ongoing.

Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes

AIMS/HYPOTHESIS

We sought to subtype South East Asian patients with type 2 diabetes by de novo cluster analysis on clinical variables, and to determine whether the novel subgroups carry distinct genetic and lipidomic features as well as differential cardio-renal risks.

METHODS

Analysis by k-means algorithm was performed in 687 participants with recent-onset diabetes in Singapore. Genetic risk for beta cell dysfunction was assessed by polygenic risk score. We used a discovery-validation approach for the lipidomics study. Risks for cardio-renal complications were studied by survival analysis.

RESULTS

Cluster analysis identified three novel diabetic subgroups, i.e. mild obesity-related diabetes (MOD, 45%), mild age-related diabetes with insulin insufficiency (MARD-II, 36%) and severe insulin-resistant diabetes with relative insulin insufficiency (SIRD-RII, 19%). Compared with the MOD subgroup, MARD-II had a higher polygenic risk score for beta cell dysfunction. The SIRD-RII subgroup had higher levels of sphingolipids (ceramides and sphingomyelins) and glycerophospholipids (phosphatidylethanolamine and phosphatidylcholine), whereas the MARD-II subgroup had lower levels of sphingolipids and glycerophospholipids but higher levels of lysophosphatidylcholines. Over a median of 7.3 years follow-up, the SIRD-RII subgroup had the highest risks for incident heart failure and progressive kidney disease, while the MARD-II subgroup had moderately elevated risk for kidney disease progression.

CONCLUSIONS/INTERPRETATION

Cluster analysis on clinical variables identified novel subgroups with distinct genetic, lipidomic signatures and varying cardio-renal risks in South East Asian participants with type 2 diabetes. Our study suggests that this easily actionable approach may be adapted in other ethnic populations to stratify the heterogeneous type 2 diabetes population for precision medicine.

Diet Patterns Are Associated with Circulating Metabolites and Lipid Profiles of South Asians in the United States

BACKGROUND

South Asians are at higher risk for cardiometabolic disease than many other racial/ethnic minority groups. Diet patterns in US South Asians have unique components associated with cardiometabolic disease.

OBJECTIVES

We aimed to characterize the metabolites associated with 3 representative diet patterns.

METHODS

We included 722 participants in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort study aged 40-84 y without known cardiovascular disease. Fasting serum specimens and diet and demographic questionnaires were collected at baseline and diet patterns previously generated through principal components analysis. LC-MS-based untargeted metabolomic and lipidomic analysis was conducted with targeted integration of known metabolite and lipid signals. Linear regression models of diet pattern factor score and log-transformed metabolites adjusted for age, sex, caloric intake, and BMI and adjusted for multiple comparisons were performed, followed by elastic net linear regression of significant metabolites.

RESULTS

There were 443 metabolites of known identity extracted from the profiling data. The "animal protein" diet pattern was associated with 61 metabolites and lipids, including glycerophospholipids phosphatidylethanolamine PE(O-16:1/20:4) and/or PE(P-16:0/20:4) (β: 0.13; 95% CI: 0.11, 0.14) and N-acyl phosphatidylethanolamines (NAPEs) NAPE(O-18:1/20:4/18:0) and/or NAPE(P-18:0/20:4/18:0) (β: 0.13; 95% CI: 0.11, 0.14), lysophosphatidylinositol (LPI) (22:6/0:0) (β: 0.14; 95% CI: 0.12, 0.17), and fatty acid (FA) (22:6) (β: 0.15; 95% CI: 0.13, 0.17). The "fried snacks, sweets, high-fat dairy" pattern was associated with 12 lipids, including PC(16:0/22:6) (β: -0.08; 95% CI: -0.09, -0.06) and FA (22:6) (β: 0.14; 95% CI: -0.17, -0.10). The "fruits, vegetables, nuts, and legumes" pattern was associated with 5 metabolites including proline betaine (β: 0.17; 95% CI: 0.09, 0.25) (P < 0.0002).

CONCLUSIONS

Three predominant dietary patterns in US South Asians are associated with circulating metabolites differentiated by lipids including glycerophospholipids and PUFAs and the amino acid proline betaine.

A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

The current classification of diabetes, based on hyperglycaemia, islet-directed antibodies and some insufficiently defined clinical features, does not reflect differences in aetiological mechanisms and in the clinical course of people with diabetes. This review discusses evidence from recent studies addressing the complexity of diabetes by proposing novel subgroups (subtypes) of diabetes. The most widely replicated and validated approach identified, in addition to severe autoimmune diabetes, four subgroups designated severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes subgroups. These subgroups display distinct patterns of clinical features, disease progression and onset of comorbidities and complications, with severe insulin-resistant diabetes showing the highest risk for cardiovascular, kidney and fatty liver diseases. While it has been suggested that people in these subgroups would benefit from stratified treatments, RCTs are required to assess the clinical utility of any reclassification effort. Several methodological and practical issues also need further study: the statistical approach used to define subgroups and derive recommendations for diabetes care; the stability of subgroups over time; the optimal dataset (e.g. phenotypic vs genotypic) for reclassification; the transethnic generalisability of findings; and the applicability in clinical routine care. Despite these open questions, the concept of a new classification of diabetes has already allowed researchers to gain more insight into the colourful picture of diabetes and has stimulated progress in this field so that precision diabetology may become reality in the future.

Disease heterogeneity of adult diabetes based on routine clinical variables at diagnosis: Results from the German/Austrian Diabetes Follow-up Registry

AIM

To cluster adults with diabetes using variables from real-world clinical care at manifestation.

MATERIALS AND METHODS

We applied hierarchical clustering using Ward's method to 56 869 adults documented in the prospective Diabetes Follow-up Registry (DPV). Clustering variables included age, sex, body mass index (BMI), HbA1c, diabetic ketoacidosis (DKA), components of the metabolic syndrome (hypertension/dyslipidaemia/hyperuricaemia) and beta-cell antibody status. Time until use of oral antidiabetic drugs (OADs), use of insulin, chronic kidney disease (CKD), cardiovascular disease (CVD), retinopathy or neuropathy were assessed using Kaplan-Meier analysis and Cox regression models.

RESULTS

We identified eight clusters: four clusters comprised early diabetes onset (median age 40-50 years) but differed with regard to BMI, HbA1c, DKA and antibody positivity. Two clusters included adults with diabetes onset aged in their early 60s who met target HbA1c, but differed in BMI and sex distribution. Two clusters were characterized by late diabetes onset (median age 69 and 77 years) and comparatively low BMI, but differences in HbA1c. Earlier insulin use was observed in adults with high HbA1c, and earlier OAD use was observed in those with high BMI. Time until CKD or CVD was shorter in those with late onset, whereas retinopathy occurred earlier in adults with late onset and high HbA1c, and in adults with early onset, but high HbA1c and high percentage of antibody positivity.

CONCLUSIONS

Adult diabetes is heterogeneous beyond classical type 1/type 2 diabetes, based on easily available variables in clinical practice using an automated clustering algorithm that allows both continuous and binary variables.

Were US Asian Indian decedents with atherosclerosis more likely to have concurrent diabetes mellitus? Analysis of national multiple cause of mortality data (2012-2019)

BACKGROUND

Asian Indians (AI) are at high risk for both atherosclerotic diseases (ATH) and diabetes mellitus (DM). We analyze the clustering of these two comorbidities as contributing causes of death in AI versus Non-AI populations in the US.

METHODS

Using Mortality Multiple Cause-of-Death Files (2012-2019) from the National Center for Health Statistics, we included deaths at age ≥ 45 years among US residents where AI versus Non-AI status could be ascertained (n = 55,461 AI; n = 20,090,038 Non-AI) and identsified ATH (ICD10: I20-I25, I63, I70) and DM (ICD10: E10-E14) as contributing causes of death. We calculated the tetrachoric correlation (Rho) between these contributing causes and the difference in the fraction of deaths involving DM in those with versus without ATH.

RESULTS

Among AI decedents, 29.9% of deaths included ATH as a contributing cause, 16.4% included DM as a contributing cause with 8.3% deaths being included in the overlap (Rho = 0.36, SE = 0.007) whereas, among Non-AI, 22.4% of deaths included ATH as a contributing cause, 10.0% included DM as a contributing cause with 4.1% deaths being included in the overlap (Rho = 0.31, SE = 0.001). Thus, DM and ATH as co-occurring causes correlated more strongly in AI versus Non-AI (p < 0.001). Further, this difference in clustering of DM with ATH was highest for younger AI women (age < 60 years) compared to comparable Non-AI women.

CONCLUSIONS

The more frequent co-occurrence of DM and ATH as causes of death among AI compared to Non-AI suggest that the increased burden of these diseases among AI during life has vicious synergistic consequences in terms of mortality. Public health strategies targeted to AI should focus on prevention and clinical treatment of both conditions jointly, in all adults, and especially in women < 60 years.

Pathophysiology, phenotypes and management of type 2 diabetes mellitus in Indian and Chinese populations

Nearly half of all adults with type 2 diabetes mellitus (T2DM) live in India and China. These populations have an underlying predisposition to deficient insulin secretion, which has a key role in the pathogenesis of T2DM. Indian and Chinese people might be more susceptible to hepatic or skeletal muscle insulin resistance, respectively, than other populations, resulting in specific forms of insulin deficiency. Cluster-based phenotypic analyses demonstrate a higher frequency of severe insulin-deficient diabetes mellitus and younger ages at diagnosis, lower β-cell function, lower insulin resistance and lower BMI among Indian and Chinese people compared with European people. Individuals diagnosed earliest in life have the most aggressive course of disease and the highest risk of complications. These characteristics might contribute to distinctive responses to glucose-lowering medications. Incretin-based agents are particularly effective for lowering glucose levels in these populations; they enhance incretin-augmented insulin secretion and suppress glucagon secretion. Sodium-glucose cotransporter 2 inhibitors might also lower blood levels of glucose especially effectively among Asian people, while α-glucosidase inhibitors are better tolerated in east Asian populations versus other populations. Further research is needed to better characterize and address the pathophysiology and phenotypes of T2DM in Indian and Chinese populations, and to further develop individualized treatment strategies.

Subgroups of patients with young-onset type 2 diabetes in India reveal insulin deficiency as a major driver

AIM/HYPOTHESIS

Five subgroups were described in European diabetes patients using a data driven machine learning approach on commonly measured variables. We aimed to test the applicability of this phenotyping in Indian individuals with young-onset type 2 diabetes.

METHODS

We applied the European-derived centroids to Indian individuals with type 2 diabetes diagnosed before 45 years of age from the WellGen cohort (n = 1612). We also applied de novo k-means clustering to the WellGen cohort to validate the subgroups. We then compared clinical and metabolic-endocrine characteristics and the complication rates between the subgroups. We also compared characteristics of the WellGen subgroups with those of two young European cohorts, ANDIS (n = 962) and DIREVA (n = 420). Subgroups were also assessed in two other Indian cohorts, Ahmedabad (n = 187) and PHENOEINDY-2 (n = 205).

RESULTS

Both Indian and European young-onset type 2 diabetes patients were predominantly classified into severe insulin-deficient (SIDD) and mild obesity-related (MOD) subgroups, while the severe insulin-resistant (SIRD) and mild age-related (MARD) subgroups were rare. In WellGen, SIDD (53%) was more common than MOD (38%), contrary to findings in Europeans (Swedish 26% vs 68%, Finnish 24% vs 71%, respectively). A higher proportion of SIDD compared with MOD was also seen in Ahmedabad (57% vs 33%) and in PHENOEINDY-2 (67% vs 23%). Both in Indians and Europeans, the SIDD subgroup was characterised by insulin deficiency and hyperglycaemia, MOD by obesity, SIRD by severe insulin resistance and MARD by mild metabolic-endocrine disturbances. In WellGen, nephropathy and retinopathy were more prevalent in SIDD compared with MOD while the latter had higher prevalence of neuropathy.

CONCLUSIONS /INTERPRETATION

Our data identified insulin deficiency as the major driver of type 2 diabetes in young Indians, unlike in young European individuals in whom obesity and insulin resistance predominate. Our results provide useful clues to pathophysiological mechanisms and susceptibility to complications in type 2 diabetes in the young Indian population and suggest a need to review management strategies.

Poor In Utero Growth, and Reduced β-Cell Compensation and High Fasting Glucose From Childhood, Are Harbingers of Glucose Intolerance in Young Indians

OBJECTIVE

India is a double world capital of early-life undernutrition and type 2 diabetes. We aimed to characterize life course growth and metabolic trajectories in those developing glucose intolerance as young adults in the Pune Maternal Nutrition Study (PMNS).

RESEARCH DESIGN AND METHODS

PMNS is a community-based intergenerational birth cohort established in 1993, with serial information on parents and children through pregnancy, childhood, and adolescence. We compared normal glucose-tolerant and glucose-intolerant participants for serial growth, estimates of insulin sensitivity and secretion (HOMA and dynamic indices), and β-cell compensation accounting for prevailing insulin sensitivity.

RESULTS

At 18 years (N = 619), 37% of men and 20% of women were glucose intolerant (prediabetes n = 184; diabetes n = 1) despite 48% being underweight (BMI <18.5 kg/m²). Glucose-intolerant participants had higher fasting glucose from childhood. Mothers of glucose-intolerant participants had higher glycemia in pregnancy. Glucose-intolerant participants were shorter at birth. Insulin sensitivity decreased with age in all participants, and those with glucose intolerance had consistently lower compensatory insulin secretion from childhood. Participants in the highest quintile of fasting glucose at 6 and 12 years had 2.5- and 4.0-fold higher risks, respectively, of 18-year glucose intolerance; this finding was replicated in two other cohorts.

CONCLUSIONS

Inadequate compensatory insulin secretory response to decreasing insulin sensitivity in early life is the major pathophysiology underlying glucose intolerance in thin rural Indians. Smaller birth size, maternal pregnancy hyperglycemia, and higher glycemia from childhood herald future glucose intolerance, mandating a strategy for diabetes prevention from early life, preferably intergenerationally.

Toward an Improved Classification of Type 2 Diabetes: Lessons From Research into the Heterogeneity of a Complex Disease

CONTEXT

Accumulating evidence indicates that type 2 diabetes (T2D) is phenotypically heterogeneous. Defining and classifying variant forms of T2D are priorities to better understand its pathophysiology and usher clinical practice into an era of "precision diabetes."

EVIDENCE ACQUISITION AND METHODS

We reviewed literature related to heterogeneity of T2D over the past 5 decades and identified a range of phenotypic variants of T2D. Their descriptions expose inadequacies in current classification systems. We attempt to link phenotypically diverse forms to pathophysiology, explore investigative methods that have characterized "atypical" forms of T2D on an etiological basis, and review conceptual frameworks for an improved taxonomy. Finally, we propose future directions to achieve the goal of an etiological classification of T2D.

EVIDENCE SYNTHESIS

Differences among ethnic and racial groups were early observations of phenotypic heterogeneity. Investigations that uncover complex interactions of pathophysiologic pathways leading to T2D are supported by epidemiological and clinical differences between the sexes and between adult and youth-onset T2D. Approaches to an etiological classification are illustrated by investigations of atypical forms of T2D, such as monogenic diabetes and syndromes of ketosis-prone diabetes. Conceptual frameworks that accommodate heterogeneity in T2D include an overlap between known diabetes types, a "palette" model integrated with a "threshold hypothesis," and a spectrum model of atypical diabetes.

CONCLUSION

The heterogeneity of T2D demands an improved, etiological classification scheme. Excellent phenotypic descriptions of emerging syndromes in different populations, continued clinical and molecular investigations of atypical forms of diabetes, and useful conceptual models can be utilized to achieve this important goal.

Diabetes subgroups and risk for complications: The Multi-Ethnic Study of Atherosclerosis (MESA)

AIMS

To characterize diabetes subgroups among a multi-ethnic cohort and assess risk for incident complications.

METHODS

We included 1587 participants from the Multi-Ethnic Study of Atherosclerosis with diabetes. We characterized eight diabetes subgroups according to absolute thresholds for disease characteristics: age at diabetes diagnosis (≤45 years), fasting glucose (FG ≥7.7 mmol/L; ≥140 mg/dL), and waist circumference (women ≥105 cm; men ≥110 cm). We estimated risk for mortality, incident cardiovascular disease, chronic kidney disease, heart failure, dementia, and retinopathy, respectively, over 17 years after adjustment for demographics, behavioral, clinical risk factors, and cohort attrition.

RESULTS

The subgroup with both high FG and early age at onset was associated with higher risk for death, CVD, heart failure, CKD, and retinopathy and the subgroup with both early age at onset and high waist circumference was associated CVD, heart failure, CKD, and retinopathy. The subgroup that met all three high-risk thresholds had greater risk for death, heart failure, CKD, and retinopathy. We did not observe evidence for synergistic or antagonistic joint effects of the high-risk characteristics for any outcome.

CONCLUSIONS

Our work supports differential risk for various diabetes complications among exclusive subgroups defined by age at diabetes onset, fasting glucose, and central adiposity.

Dysglycemia in adults at risk for or living with non-insulin treated type 2 diabetes: Insights from continuous glucose monitoring

BACKGROUND

Continuous glucose monitoring (CGM) has demonstrable benefits for people living with diabetes, but the supporting evidence is almost exclusively from White individuals with type 1 diabetes. Here, we have quantified CGM profiles in Hispanic/Latino adults with or at-risk of non-insulin treated type 2 diabetes (T2D).

METHODS

100 participants (79 female, 86% Hispanic/Latino [predominantly Mexican], age 54·6 [±12·0] years) stratified into (i) at risk of T2D, (ii) with pre-diabetes (pre-T2D), and (iii) with non-insulin treated T2D, wore blinded CGMs for 2 weeks. Beyond standardized CGM measures (average glucose, glucose variability, time in 70-140 mg/dL and 70-180 mg/dL ranges), we also examined additional CGM measures based on the time of day.

FINDINGS

Standardized CGM measures were significantly different for participants with T2D compared to at-risk and pre-T2D participants (p<0·0001). In addition, pre-T2D participants spent more time between 140 and 180 mg/dL during the day than at-risk participants (p<0·01). T2D participants spent more time between 140 and 180 mg/dL both during the day and overnight compared to at-risk and pre-T2D participants (both p<0·0001). Time in 70-140 mg/dL range during the day was significantly correlated with HbA_1c (r=-0·72, p<0·0001), after adjusting for age, sex, BMI, and waist circumference (p<0·0001).

INTERPRETATION

Standardized CGM measures show a progression of dysglycemia from at-risk of T2D, to pre-T2D, and to T2D. Stratifying CGM readings by time of day and the range 140-180 mg/dL provides additional metrics to differentiate between the groups.

FUNDING

US Department of Agriculture (Grant #2018-33800-28404) and NSF PATHS-UP ERC (Award #1648451).

Dementia and Adherence to Anti-Diabetic Medications: A Meta-Analysis

Introduction Diabetes mellitus (DM) and dementia (DN) are common morbid disorders with high mortality, the two disorders shared the pathogenesis of proinflammation and insulin resistance. Polypharmacy is expected when DM and DN co-exist and medication adherence is essential to an effective self-care and management plan. This meta-analysis aimed to assess medication persistence among patients with diabetes and cognitive impairment (CogImp). Methods We systematically searched the literature through PubMed, Medline, Cochrane library, and the first 100 articles published in Google Scholar. We included articles publishes in English and conducted on humans, no limitation was set to the date of publication, all the articles were approached from the first published up to March 15, 2021. The keywords used were Dementia, cognitive impairment, cognitive decline, cognitive dysfunction, diabetes self-care, compliance to anti-diabetic drugs, and medication adherence. One hundred-seventy-six were identified, the 12 full texts screened, only four fulfilled the inclusion and exclusion criteria. Results The studies were published in Europe, the United States, and Asia (all were observational). The results showed no effects of dementia on medication adherence, P-value of 0.41, odd ratio: 1.09, 95% CI: 0.89-1.32, Chi-square for heterogeneity: 12.15, I² = 75%, and standard difference = 3. The P-value for heterogeneity was 0.007. The studies included 2,556 patients and 1,854 events. Conclusion No association was found between dementia and compliance to anti-diabetic medications. Further prospective studies are needed to solve the issue.