Precision subclassification of type 2 diabetes: a systematic review

Multi-ancestry polygenic mechanisms of type 2 diabetes

Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

Exploring the Anti-Diabetic Potential of Quercetagitrin through Dual Inhibition of PTPN6 and PTPN9

Protein tyrosine phosphatases (PTPs) are pivotal contributors to the development of type 2 diabetes (T2DM). Hence, directing interventions towards PTPs emerges as a valuable therapeutic approach for managing type 2 diabetes. In particular, PTPN6 and PTPN9 are targets for anti-diabetic effects. Through high-throughput drug screening, quercetagitrin (QG) was recognized as a dual-target inhibitor of PTPN6 and PTPN9. We observed that QG suppressed the catalytic activity of PTPN6 (IC50 = 1 μM) and PTPN9 (IC50 = 1.7 μM) in vitro and enhanced glucose uptake by mature C2C12 myoblasts. Additionally, QG increased the phosphorylation of adenosine monophosphate-activated protein kinase (AMPK) and insulin-dependent phosphorylation of Akt in mature C2C12 myoblasts. It further promoted the phosphorylation of Akt in the presence of palmitic acid, suggesting the attenuation of insulin resistance. In summary, our results indicate QG's role as a potent inhibitor targeting both PTPN6 and PTPN9, showcasing its potential as a promising treatment avenue for T2DM.

Treatment responses to basal insulin glargine 300 U/ml and glargine 100 U/ml in newly defined subphenotypes of type 2 diabetes: A post hoc analysis of the EDITION 3 randomized clinical trial

INTRODUCTION

To compare responses to basal insulin glargine 300 U/ml (IGlar-300) and 100 U/ml (IGlar-100) in newly defined subphenotypes of type 2 diabetes.

METHODS

Insulin-naive participants (n = 858) from the EDITION 3 trial were assigned to subphenotypes 'Mild Age-Related Diabetes (MARD)', 'Mild Obesity Diabetes (MOD)', 'Severe Insulin Resistant Diabetes (SIRD)' and 'Severe Insulin Deficient Diabetes (SIDD)'. Key variables were analysed at baseline and 26 weeks.

RESULTS

Participants were comprised of MOD 56.1% (n = 481), SIDD 22.1% (n = 190), MARD 18.2% (n = 156) and SIRD 3.0% (n = 26). After 26 weeks a similar decrease in glycated haemoglobin (HbA1c) and fasting plasma glucose (FPG) of 16-19 mmol/mol and 1.4-1.7 mmol/L, respectively, occurred in MARD and MOD with both insulins. SIDD had the most elevated HbA1c and FPG (80-83 mmol/mol/11.1-11.4 mmol/L) and reduction in both HbA1c and FPG was greater with IGlar-100 than with IGlar-300 (-18 vs. -15 mmol/mol and -1.6 vs. -1.3 mmol/L, respectively; each p = .03). In SIDD, despite receiving the highest basal insulin doses, HbA1c decline (57-60 mmol/mol/7.3-7.6%) was suboptimal at week 26. In MOD and SIDD lower incidences with IGlar-300 were found for level 1 nocturnal hypoglycaemia [odds ratio (OR) 0.59, 95% confidence intervals (CI) 0.36-0.97; OR 0.49, 95% CI 0.24-0.99]. In addition, fewer level 2 hypoglycaemia episodes occurred at any time with IGlar-300 in SIDD (OR 0.31, 95% CI 0.13-0.77).

CONCLUSION

Both insulins produce comparable outcomes in type 2 diabetes subphenotypes, but in SIDD, add-on treatment to basal insulin is required to achieve glycaemic targets.

Analysis of type 2 diabetes heterogeneity with a tree-like representation: insights from the prospective German Diabetes Study and the LURIC cohort

BACKGROUND

Heterogeneity in type 2 diabetes can be represented by a tree-like graph structure by use of reversed graph-embedded dimensionality reduction. We aimed to examine whether this approach can be used to stratify key pathophysiological components and diabetes-related complications during longitudinal follow-up of individuals with recent-onset type 2 diabetes.

METHODS

For this cohort analysis, 927 participants aged 18-69 years from the German Diabetes Study (GDS) with recent-onset type 2 diabetes were mapped onto a previously developed two-dimensional tree based on nine simple clinical and laboratory variables, residualised for age and sex. Insulin sensitivity was assessed by a hyperinsulinaemic-euglycaemic clamp, insulin secretion was assessed by intravenous glucose tolerance test, hepatic lipid content was assessed by 1 H magnetic resonance spectroscopy, serum interleukin (IL)-6 and IL-18 were assessed by ELISA, and peripheral and autonomic neuropathy were assessed by functional and clinical measures. Participants were followed up for up to 16 years. We also investigated heart failure and all-cause mortality in 794 individuals with type 2 diabetes undergoing invasive coronary diagnostics from the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort.

FINDINGS

There were gradients of clamp-measured insulin sensitivity (both dimensions: p<0·0001) and insulin secretion (pdim1<0·0001, pdim2=0·00097) across the tree. Individuals in the region with the lowest insulin sensitivity had the highest hepatic lipid content (n=205, pdim1<0·0001, pdim2=0·037), pro-inflammatory biomarkers (IL-6: n=348, pdim1<0·0001, pdim2=0·013; IL-18: n=350, pdim1<0·0001, pdim2=0·38), and elevated cardiovascular risk (nevents=143, pdim1=0·14, pdim2<0·00081), whereas individuals positioned in the branch with the lowest insulin secretion were more prone to require insulin therapy (nevents=85, pdim1=0·032, pdim2=0·12) and had the highest risk of diabetic sensorimotor polyneuropathy (nevents=184, pdim1=0·012, pdim2=0·044) and cardiac autonomic neuropathy (nevents=118, pdim1=0·0094, pdim2=0·06). In the LURIC cohort, all-cause mortality was highest in the tree branch showing insulin resistance (nevents=488, pdim1=0·12, pdim2=0·0032). Significant gradients differentiated individuals having heart failure with preserved ejection fraction from those who had heart failure with reduced ejection fraction.

INTERPRETATION

These data define the pathophysiological underpinnings of the tree structure, which has the potential to stratify diabetes-related complications on the basis of routinely available variables and thereby expand the toolbox of precision diabetes diagnosis.

FUNDING

German Diabetes Center, German Federal Ministry of Health, Ministry of Culture and Science of the state of North Rhine-Westphalia, German Federal Ministry of Education and Research, German Diabetes Association, German Center for Diabetes Research, European Community, German Research Foundation, and Schmutzler Stiftung.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles.

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.