Identification of type 2 diabetes loci in 433,540 East Asian individuals

ALDH2 polymorphism and myocardial infarction: From alcohol metabolism to redox regulation

Acute myocardial infarction (AMI) remains a leading cause of death worldwide. Increased formation of reactive oxygen species (ROS) during the early reperfusion phase is thought to trigger lipid peroxidation and disrupt redox homeostasis, leading to myocardial injury. Whilst the mitochondrial enzyme aldehyde dehydrogenase 2 (ALDH2) is chiefly recognised for its central role in ethanol metabolism, substantial experimental evidence suggests an additional cardioprotective role for ALDH2 independent of alcohol intake, which mitigates myocardial injury by detoxifying breakdown products of lipid peroxidation including the reactive aldehydes, malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE). Epidemiological evidence suggests that an ALDH2 mutant variant with reduced activity that is highly prevalent in the East Asian population increases AMI risk. Additional studies have uncovered a strong association between coronary heart disease and this ALDH2 mutant variant. It appears this enzyme polymorphism (in particular, in ALDH2*2/2 carriers) has the potential to have wide-ranging effects on thiol reactivity, redox tone and therefore numerous redox-related signaling processes, resilience of the heart to cope with lifestyle-related and environmental stressors, and the ability of the whole body to achieve redox balance. In this review, we summarize the journey of ALDH2 from a mitochondrial reductase linked to alcohol metabolism, via pre-clinical studies aimed at stimulating ALDH2 activity to reduce myocardial injury to clinical evidence for its protective role in the heart.

Effects of Herbal Tea (Non-Camellia sinensis) on Glucose Homeostasis and Serum Lipids in Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

CONTEXT

Hyperglycemia and hyperlipidemia increase the risk for diabetes and its complications, atherosclerosis, heart failure, and stroke. Identification of safe and cost-effective means to reduce risk factors is needed. Herbal teas may be a vehicle to deliver antioxidants and polyphenols for prevention of complications.

OBJECTIVE

This systematic review and meta-analysis were conducted to evaluate and summarize the impact of herbal tea (non-Camellia sinensis) on glucose homeostasis and serum lipids in individuals with type 2 diabetes (T2D).

DATA SOURCES

PubMed, FSTA, Web of Science, CINAHL, MEDLINE, and Cochrane Library databases were searched from inception through February 2023 using relevant keyword proxy terms for diabetes, serum lipids, and "non-Camellia sinensis" or "tea."

DATA EXTRACTION

Data from 14 randomized controlled trials, totaling 551 participants, were included in the meta-analysis of glycemic and serum lipid profile end points.

RESULTS

Meta-analysis suggested a significant association between drinking herbal tea (prepared with 2-20 g d-1 plant ingredients) and reduction in fasting blood glucose (FBG) (P = .0034) and glycated hemoglobin (HbA1c; P = .045). In subgroup analysis based on studies using water or placebo as the control, significant reductions were found in serum total cholesterol (TC; P = .024), low-density lipoprotein cholesterol (LDL-C; P = .037), and triglyceride (TG; P = .043) levels with a medium effect size. Meta-regression analysis suggested that study characteristics, including the ratio of male participants, trial duration, and region, were significant sources of FBG and HbA1c effect size heterogeneity; type of control intervention was a significant source of TC and LDL-C effect size heterogeneity.

CONCLUSIONS

Herbal tea consumption significantly affected glycemic profiles in individuals with T2D, lowering FBG levels and HbA1c. Significance was seen in improved lipid profiles (TC, TG, and LDL-C levels) through herbal tea treatments when water or placebo was the control. This suggests water or placebo may be a more suitable control when examining antidiabetic properties of beverages. Additional research is needed to corroborate these findings, given the limited number of studies.

Associations between time in range and insulin secretory capacity in Japanese patients with type 2 diabetes

Impaired insulin secretory capacity is associated with high glycemic variability in patients with type 2 diabetes (T2DM). However, there are no existing reports on the association between insulin secretory capacity and time in range (TIR). This retrospective study involved 330 T2DM admitted for diabetes education who underwent intermittently scanned continuous glucose monitoring (isCGM) and had their fasting serum C-peptide immunoreactivity (S-CPR) measured within 5 days of admission. The baseline characteristics were as follows: age, 60.2 years; glycated hemoglobin (HbA1c), 9.2%; S-CPR, 2.2 ng/mL; S-CPR index (S-CPR [ng/mL]/fasting plasma glucose [mg/dL] × 100), 1.6; and TIR, 60.3%. TIR correlated significantly with the S-CPR index, which was confirmed by multivariate analysis that included various factors such as HbA1c. Receiver operating characteristic (ROC) analysis showed that 1.88 was the optimal S-CPR index level to predict TIR ≥ 70%. In addition to HbA1c and biguanide use, the S-CPR index was a significant factor associated with TIR > 70%. S-CPR index values of ≥ 1.88 also correlated significantly with TIR > 70%. In conclusion, insulin secretory capacity is associated with TIR in Japanese T2DM, suggesting that the S-CPR index might be a potentially useful biomarker insulin secretory capacity, in association with TIR.Trial registration UMIN0000254333.

Causal effects of inflammatory bowel disease on risk of type 2 diabetes: a two-sample multivariable Mendelian randomization study

AIM

This study aimed to explore the causal association between inflammatory bowel disease (IBD) and the risk of type 2 diabetes (T2D) based on a two-sample Mendelian randomization (MR) study.

METHODS

Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published two genome-wide association studies (GWAS) including SNPs related to IBD, UC, or CD in European participants (n = 71,997) and East Asian participants (n = 16,805). Two GWAS including SNPs associated with T2D included 655,666 Europeans and 433,540 East Asians. A series of screening processes were performed to select qualified instrumental SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the MR-Egger regression, and the weighted median to estimate the causal effects of IBD, ulcerative colitis (UC) or Crohn' disease (CD) on T2D. Cochran's Q test was conducted to evaluate the statistical heterogeneity between SNPs in the IVW method. The leave-one-out analysis was employed to assess whether the results were caused by any single SNP associated with IBD, UC, or CD. Odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

The IVW results demonstrated that IBD could increase the risk of T2D in the European population (OR = 1.0230, 95%CI: 1.0073-1.0390). UC was positively associated with the risk of T2D according to the weighted median (OR = 1.0274, 95%CI: 1.0009-1.0546) and IVW (OR = 1.0244, 95%CI: 1.0071-1.0421) results in the European population. The IVW results indicated that the CD was positively associated with the risk of T2D in the European population (OR = 1.0187, 95%CI: 1.0045-1.0330). In the East Asian population, there are no associations between the IBD, UC, or CD and the risk of T2D (all P > 0.05). MVMR results revealed that the causal effect UC on T2D was still statistically significant after including body mass index (BMI) or low-density lipoprotein (LDL).

CONCLUSION

IBD, UC, or CD had causal effects on the risk of T2D in the European population, which might provide evidence for the prevention of T2D in patients with IBD, UC, or CD.

Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes

OBJECTIVE

Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D.

RESULTS

Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D.

CONCLUSIONS

Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.

Impact of polygenic risk score for triglyceride trajectory and diabetic complications in subjects with type 2 diabetes based on large electronic medical record data from Taiwan: a case control study

BACKGROUND

The prevalence of diabetic dyslipidemia has gradually increased worldwide and individuals with hypertriglyceridemia often have a high polygenic burden of triglyceride (TG)-increasing variants. However, the contribution of genetic variants to dyslipidemia in patients with type 2 diabetes (T2D) remains limited. Therefore, in this study, we aimed to investigate the genetic characteristics of longitudinal changes in TG levels among patients with T2D and summarize the genetic effects of polygenic risk score (PRS) on TG trajectory and risk of diabetic complications.

METHODS

We conducted a case-control study. A total of 11,312 patients with T2D with longitudinal TG and genetic data were identified from a large hospital database in Taiwan. We then performed a genome-wide association study and calculated the relative PRS.

RESULTS

In total, 21 single-nucleotide polymorphisms (SNPs) related to TG trajectory were identified and yielded an area under the receiver operating characteristic curve (ROC) of 0.712 for high TG trajectory risk among Taiwanese patients with T2D. A cumulative genetic effect was observed for high TG trajectory, even when considering the adherence of a lipid-lowering agent in stratified analysis. An increased PRS increases high TG trajectory risk in a logistic regression model (odds ratio = 1.55; 95% confidence interval [CI] = 1.31-1.83 in the validation cohort). The TG-specific PRS was associated with the risk of diabetic microvascular complications, including diabetic retinopathy and nephropathy (with hazard ratios of 1.11 [95% CI = 1.01-1.21, P = 0.027] and 1.05 [95% CI = 1.01-1.1, P = 0.018], respectively).

CONCLUSIONS

This study may contribute to the identification of patients with T2D who are at risk of abnormal TG levels and diabetic microvascular complications using polygenic information.

AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes

Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating prevalence, underscoring the critical need for precision health strategies and early detection initiatives. Leveraging artificial intelligence, particularly eXtreme Gradient Boosting (XGBoost), we devise robust risk assessment models for T2D. Drawing upon comprehensive genetic and medical imaging datasets from 68,911 individuals in the Taiwan Biobank, our models integrate Polygenic Risk Scores (PRS), Multi-image Risk Scores (MRS), and demographic variables, such as age, sex, and T2D family history. Here, we show that our model achieves an Area Under the Receiver Operating Curve (AUC) of 0.94, effectively identifying high-risk T2D subgroups. A streamlined model featuring eight key variables also maintains a high AUC of 0.939. This high accuracy for T2D risk assessment promises to catalyze early detection and preventive strategies. Moreover, we introduce an accessible online risk assessment tool for T2D, facilitating broader applicability and dissemination of our findings.

Impact of the trans-ancestry polygenic risk score on type 2 diabetes risk, onset age and progression among population in Taiwan

Type 2 diabetes (T2D) prevalence in adults at a younger age has increased but the disease status may go unnoticed. This study aimed to determine whether the onset age and subsequent diabetic complications can be attributed to the polygenic architecture of T2D in the Taiwan Han population. A total of 9,627 cases with T2D and 85,606 controls from the Taiwan Biobank were enrolled. Three diabetic polygenic risk scores (PRSs), PRS_EAS and PRS_EUR, and a trans-ancestry PRS (PRS_META), calculated using summary statistic from East Asian and European populations. The onset age was identified by linking to the National Taiwan Insurance Research Database, and the incidence of different diabetic complications during follow-up was recorded. PRS_META (7.4%) explained a higher variation for T2D status. And the higher percentile of PRS is also correlated with higher percentage of T2D family history and prediabetes status. More, the PRS was negatively associated with onset age (β = -0.91 yr), and this was more evident among males (β = -1.11 vs. -0.76 for males and females, respectively). The hazard ratio of diabetic retinopathy (DR) and diabetic foot were significantly associated with PRS_EAS and PRS_META, respectively. However, the PRS was not associated with other diabetic complications, including diabetic nephropathy, cardiovascular disease, and hypertension. Our findings indicated that diabetic PRS which combined susceptibility variants from cross-population could be used as a tool for early screening of T2D, especially for high-risk populations, such as individuals with high genetic risk, and may be associated with the risk of complications in subjects with T2D. NEW & NOTEWORTHY Our findings indicated that diabetic polygenic risk score (PRS) which combined susceptibility variants from Asian and European population affect the onset age of type 2 diabetes (T2D) and could be used as a tool for early screening of T2D, especially for individuals with high genetic risk, and may be associated with the risk of diabetic complications among people in Taiwan.

Genome-wide association study and trans-ethnic meta-analysis identify novel susceptibility loci for type 2 diabetes mellitus

BACKGROUND

The genetic basis of type 2 diabetes (T2D) is under-investigated in the Middle East, despite the rapidly growing disease prevalence. We aimed to define the genetic determinants of T2D in Qatar.

METHODS

Using whole genome sequencing of 11,436 participants (2765 T2D cases and 8671 controls) from the population-based Qatar Biobank (QBB), we conducted a genome-wide association study (GWAS) of T2D with and without body mass index (BMI) adjustment.

RESULTS

We replicated 93 known T2D-associated loci in a BMI-unadjusted model, while 96 known loci were replicated in a BMI-adjusted model. The effect sizes and allele frequencies of replicated SNPs in the Qatari population generally concurred with those from European populations. We identified a locus specific to our cohort located between the APOBEC3H and CBX7 genes in the BMI-unadjusted model. Also, we performed a transethnic meta-analysis of our cohort with a previous GWAS on T2D in multi-ancestry individuals (180,834 T2D cases and 1,159,055 controls). One locus in DYNC2H1 gene reached genome-wide significance in the meta-analysis. Assessing polygenic risk scores derived from European- and multi-ancestries in the Qatari population showed higher predictive performance of the multi-ancestry panel compared to the European panel.

CONCLUSION

Our study provides new insights into the genetic architecture of T2D in a Middle Eastern population and identifies genes that may be explored further for their involvement in T2D pathogenesis.

Trans-Ancestral Genetic Risk Factors for Treatment-Related Type 2 Diabetes Mellitus in Survivors of Childhood Cancer

PURPOSE

Type 2 diabetes mellitus (T2D) is a prevalent long-term complication of treatment in survivors of childhood cancer, with marked racial/ethnic differences in burden. In this study, we investigated trans-ancestral genetic risks for treatment-related T2D.

PATIENTS AND METHODS

Leveraging whole-genome sequencing data from the St Jude Lifetime Cohort (N = 3,676, 304 clinically ascertained cases), we conducted ancestry-specific genome-wide association studies among survivors of African and European genetic ancestry (AFR and EUR, respectively) followed by trans-ancestry meta-analysis. Trans-/within-ancestry replication including data from the Childhood Cancer Survivor Study (N = 5,965) was required for prioritization. Three external general population T2D polygenic risk scores (PRSs) were assessed, including multiancestry PRSs. Treatment risk effect modification was evaluated for prioritized loci.

RESULTS

Four novel T2D risk loci showing trans-/within-ancestry replication evidence were identified, with three loci achieving genome-wide significance (P < 5 × 10-8). Among these, common variants at 5p15.2 (LINC02112), 2p25.3 (MYT1L), and 19p12 (ZNF492) showed evidence of modifying alkylating agent-related T2D risk in both ancestral groups, but showed disproportionately greater risk in AFR survivors (AFR odds ratios [ORs], 3.95-17.81; EUR ORs, 2.37-3.32). In survivor-specific RNA-sequencing data (N = 207), the 19p12 locus variant was associated with greater ZNF492 expression dysregulation after exposures to alkylators. Elevated T2D risks across ancestry groups were only observed with increasing values for multiancestry T2D PRSs and were especially increased among survivors treated with alkylators (top v bottom quintiles: ORAFR, 20.18; P = .023; OREUR, 13.44; P = 1.3 × 10-9).

CONCLUSION

Our findings suggest therapy-related genetic risks contribute to the increased T2D burden among non-Hispanic Black childhood cancer survivors. Additional study of how therapy-related genetic susceptibility contributes to this disparity is needed.

Pancreatic β-cell failure, clinical implications, and therapeutic strategies in type 2 diabetes

ABSTRACT

Pancreatic β-cell failure due to a reduction in function and mass has been defined as a primary contributor to the progression of type 2 diabetes (T2D). Reserving insulin-producing β-cells and hence restoring insulin production are gaining attention in translational diabetes research, and β-cell replenishment has been the main focus for diabetes treatment. Significant findings in β-cell proliferation, transdifferentiation, pluripotent stem cell differentiation, and associated small molecules have served as promising strategies to regenerate β-cells. In this review, we summarize current knowledge on the mechanisms implicated in β-cell dynamic processes under physiological and diabetic conditions, in which genetic factors, age-related alterations, metabolic stresses, and compromised identity are critical factors contributing to β-cell failure in T2D. The article also focuses on recent advances in therapeutic strategies for diabetes treatment by promoting β-cell proliferation, inducing non-β-cell transdifferentiation, and reprograming stem cell differentiation. Although a significant challenge remains for each of these strategies, the recognition of the mechanisms responsible for β-cell development and mature endocrine cell plasticity and remarkable advances in the generation of exogenous β-cells from stem cells and single-cell studies pave the way for developing potential approaches to cure diabetes.

Genome-wide association and Mendelian randomisation analysis among 30,699 Chinese pregnant women identifies novel genetic and molecular risk factors for gestational diabetes and glycaemic traits

AIMS/HYPOTHESIS

Gestational diabetes mellitus (GDM) is the most common disorder in pregnancy; however, its underlying causes remain obscure. This study aimed to investigate the genetic and molecular risk factors contributing to GDM and glycaemic traits.

METHODS

We collected non-invasive prenatal test (NIPT) sequencing data along with four glycaemic and 55 biochemical measurements from 30,699 pregnant women during a 2 year period at Shenzhen Baoan Women's and Children's Hospital in China. Genome-wide association studies (GWAS) were conducted between genotypes derived from NIPTs and GDM diagnosis, baseline glycaemic levels and glycaemic levels after glucose challenges. In total, 3317 women were diagnosed with GDM, while 19,565 served as control participants. The results were replicated using two independent cohorts. Additionally, we performed one-sample Mendelian randomisation to explore potential causal associations between the 55 biochemical measurements and risk of GDM and glycaemic levels.

RESULTS

We identified four genetic loci significantly associated with GDM susceptibility. Among these, MTNR1B exhibited the highest significance (rs10830963-G, OR [95% CI] 1.57 [1.45, 1.70], p=4.42×10-29), although its effect on type 2 diabetes was modest. Furthermore, we found 31 genetic loci, including 14 novel loci, that were significantly associated with the four glycaemic traits. The replication rates of these associations with GDM, fasting plasma glucose levels and 0 h, 1 h and 2 h OGTT glucose levels were 4 out of 4, 6 out of 9, 10 out of 11, 5 out of 7 and 4 out of 4, respectively. Mendelian randomisation analysis suggested that a genetically regulated higher lymphocytes percentage and lower white blood cell count, neutrophil percentage and absolute neutrophil count were associated with elevated glucose levels and an increased risk of GDM.

CONCLUSIONS/INTERPRETATION

Our findings provide new insights into the genetic basis of GDM and glycaemic traits during pregnancy in an East Asian population and highlight the potential role of inflammatory pathways in the aetiology of GDM and variations in glycaemic levels.

DATA AVAILABILITY

Summary statistics for GDM; fasting plasma glucose; 0 h, 1 h and 2h OGTT; and the 55 biomarkers are available in the GWAS Atlas (study accession no.: GVP000001, https://ngdc.cncb.ac.cn/gwas/browse/GVP000001) .

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.

Perspectives on genetic studies of type 2 diabetes from the genome-wide association studies era to precision medicine

Genome-wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS until 2023. From 2018 to 2022, hundreds of type 2 diabetes susceptibility loci with smaller effect sizes were identified through large-scale GWAS with sample sizes of 200,000 to >1 million. The clinical translation of genetic information for type 2 diabetes includes the development of novel therapeutics and risk predictions. Although drug discovery based on loci identified in GWAS remains challenging owing to the difficulty of functional annotation, global efforts have been made to identify novel biological mechanisms and therapeutic targets by applying multi-omics approaches or searching for disease-associated coding variants in isolated founder populations. Polygenic risk scores (PRSs), comprising up to millions of associated variants, can identify individuals with higher disease risk than those in the general population. In populations of European descent, PRSs constructed from base GWAS data with a sample size of approximately 450,000 have predicted the onset of diseases well. However, European GWAS-derived PRSs have limited predictive performance in non-European populations. The predictive accuracy of a PRS largely depends on the sample size of the base GWAS data. The results of GWAS meta-analyses for multi-ethnic groups as base GWAS data and cross-population polygenic prediction methodology have been applied to establish a universal PRS applicable to small isolated ethnic populations.

The ALDH2 gene rs671 polymorphism is associated with cardiometabolic risk factors in East Asian population: an updated meta-analysis

Introduction

Acetaldehyde dehydrogenase 2 (ALDH2) had reported as a prominent role in the development of cardiometabolic diseases among Asians. Our study aims to investigate the relationship between ALDH2 polymorphism and cardiometabolic risk factors in East Asian population.

Method

We searched databases of PubMed, Web of Science, and Embase updated to Oct 30th, 2023. We extracted data of BMI, Hypertension, SBP, DBP, T2DM, FBG, PPG, HbA1c, TG, TC, LDL-C and HDL-C.

Result

In total, 46 studies were finally included in our meta-analysis, containing, 54068 GG and, 36820 GA/AA participants. All outcomes related to blood pressure revealed significant results (hypertension OR=0.83 [0.80, 0.86]; SBP MD=-1.48 [-1.82, -1.14]; DBP MD=-1.09 [-1.58, -0.61]). FBG showed a significant difference (MD=-0.10 [-0.13, -0.07]), and the lipid resulted significantly in some outcomes (TG MD=-0.07 [-0.09, -0.04]; LDL-C MD=-0.04 [-0.05, -0.02]). As for subgroups analysis, we found that in populations without severe cardiac-cerebral vascular diseases (CCVDs), GG demonstrated a significantly higher incidence of T2DM (T2DM OR=0.88 [0.79, 0.97]), while the trend was totally opposite in population with severe CCVDs (T2DM OR=1.29 [1.00, 1.66]) with significant subgroup differences.

Conclusion

Our updated meta-analysis demonstrated that ALDH2 rs671 GG populations had significantly higher levels of BMI, blood pressure, FBG, TG, LDL-C and higher risk of hypertension than GA/AA populations. Besides, to the best of our knowledge, we first report GG had a higher risk of T2DM in population without severe CCVDs, and GA/AA had a higher risk of T2DM in population with severe CCVDs.Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023389242.

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Shared genetic architectures of educational attainment in East Asian and European populations

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

New insights into the role of immunity and inflammation in diabetic kidney disease in the omics era

Diabetic kidney disease (DKD) is becoming the leading cause of chronic kidney disease, especially in the industrialized world. Despite mounting evidence has demonstrated that immunity and inflammation are highly involved in the pathogenesis and progression of DKD, the underlying mechanisms remain incompletely understood. Substantial molecules, signaling pathways, and cell types participate in DKD inflammation, by integrating into a complex regulatory network. Most of the studies have focused on individual components, without presenting their importance in the global or system-based processes, which largely hinders clinical translation. Besides, conventional technologies failed to monitor the different behaviors of resident renal cells and immune cells, making it difficult to understand their contributions to inflammation in DKD. Recently, the advancement of omics technologies including genomics, epigenomics, transcriptomics, proteomics, and metabolomics has revolutionized biomedical research, which allows an unbiased global analysis of changes in DNA, RNA, proteins, and metabolites in disease settings, even at single-cell and spatial resolutions. They help us to identify critical regulators of inflammation processes and provide an overview of cell heterogeneity in DKD. This review aims to summarize the application of multiple omics in the field of DKD and emphasize the latest evidence on the interplay of inflammation and DKD revealed by these technologies, which will provide new insights into the role of inflammation in the pathogenesis of DKD and lead to the development of novel therapeutic approaches and diagnostic biomarkers.

Genome-wide association study implicates lipid pathway dysfunction in antipsychotic-induced weight gain: multi-ancestry validation

Antipsychotic-induced weight gain (AIWG) is a common side effect of antipsychotic medication and may contribute to diabetes and coronary heart disease. To expand the unclear genetic mechanism underlying AIWG, we conducted a two-stage genome-wide association study in Han Chinese patients with schizophrenia. The study included a discovery cohort of 1936 patients and a validation cohort of 534 patients, with an additional 630 multi-ancestry patients from the CATIE study for external validation. We applied Mendelian randomization (MR) analysis to investigate the relationship between AIWG and antipsychotic-induced lipid changes. Our results identified two novel genome-wide significant loci associated with AIWG: rs10422861 in PEPD (P = 1.373 × 10-9) and rs3824417 in PTPRD (P = 3.348 × 10-9) in Chinese Han samples. The association of rs10422861 was validated in the European samples. Fine-mapping and functional annotation revealed that PEPD and PTPRD are potentially causal genes for AIWG, with their proteins being prospective therapeutic targets. Colocalization analysis suggested that AIWG and type 2 diabetes (T2D) shared a causal variant in PEPD. Polygenic risk scores (PRSs) for AIWG and T2D significantly predicted AIWG in multi-ancestry samples. Furthermore, MR revealed a risky causal effect of genetically predicted changes in low-density lipoprotein cholesterol (P = 7.58 × 10-4) and triglycerides (P = 2.06 × 10-3) caused by acute-phase of antipsychotic treatment on AIWG, which had not been previously reported. Our model, incorporating antipsychotic-induced lipid changes, PRSs, and clinical predictors, significantly predicted BMI percentage change after 6-month antipsychotic treatment (AUC = 0.79, R2 = 0.332). Our results highlight that the mechanism of AIWG involves lipid pathway dysfunction and may share a genetic basis with T2D through PEPD. Overall, this study provides new insights into the pathogenesis of AIWG and contributes to personalized treatment of schizophrenia.

COPD and T2DM: a Mendelian randomization study

Introduction

Type 2 diabetes (T2DM) stands as a global chronic illness, exerting a profound impact on health due to its complications and generating a significant economic burden. Recently, observational studies have pointed toward a potential link between Chronic Obstructive Pulmonary Disease (COPD) and T2DM. To elucidate this causal connection, we employed the Mendelian randomization analysis.

Method

Our study involved a two-sample Mendelian randomization (MR) analysis on COPD and T2DM. Additionally, tests for heterogeneity and horizontal pleiotropy were performed.

Results

For the MR analysis, 26 independent single nucleotides polymorphisms (SNPs) with strong associations to COPD were chosen as instrumental variables. Our findings suggest a pronounced causal relationship between COPD and T2DM. Specifically, COPD emerges as a risk factor for T2DM, with an odds ratio (OR) of 1.06 and a 95% confidence interval ranging from 1.01 to 1.11 (P = 0.006). Notably, all results were devoid of any heterogeneity or pleiotropy.

Conclusion

The MR analysis underscores a significant causal relationship between COPD and T2DM, highlighting COPD as a prominent risk factor for T2DM.

ECHDC3 Variant Regulates the Right Hippocampal Microstructural Integrity and Verbal Memory in Type 2 Diabetes Mellitus

ECHDC3 is a risk gene for white matter (WM) hyperintensity and is associated with insulin resistance. This study aimed to investigate whether ECHDC3 variants selectively regulate brain WM microstructures and episodic memory in patients with type 2 diabetes mellitus (T2DM). We enrolled 106 patients with T2DM and 111 healthy controls. A voxel-wise general linear model was employed to explore the interaction effect between ECHDC3 rs11257311 polymorphism and T2DM diagnosis on fractional anisotropy (FA). A linear modulated mediation analysis was conducted to examine the potential of FA value to mediate the influence of T2DM on episodic memory in an ECHDC3-dependent manner. We observed a noteworthy interaction between genotype and diagnosis on FA in the right inferior temporal WM, right anterior limb of the internal capsule, right frontal WM, and the right hippocampus. Modulated mediation analysis revealed a significant ECHDC3 modulation on the T2DM → right hippocampal FA → short-term memory pathway, with only rs11257311 G risk homozygote demonstrating significant mediation effect. Together, our findings provide evidence of ECHDC3 modulating the effect of T2DM on right hippocampal microstructural impairment and short-term memory decline, which might be a neuro-mechanism for T2DM related episodic memory impairment.

Predicting cell-type specific disease genes of diabetes with the biological network

Type 2 diabetes (T2D) is a chronic condition that can lead to significant harm, such as heart disease, kidney disease, nerve damage, and blindness. Although T2D-related genes have been identified through Genome-wide association studies (GWAS) and various computational methods, the biological mechanism of T2D at the cell type level remains unclear. Exploring cell type-specific genes related to T2D is essential to understand the cellular mechanisms underlying the disease. To address this issue, we introduce DiGCellNet (predicting Disease Genes with Cell type specificity based on biological Networks), a model that integrates graph convolutional network (GCN) and multi-task learning (MTL) to predict T2D-associated cell type-specific genes based on the biological network. Our work represents the first attempt to predict cell type-specific disease genes using GCN and MTL. We evaluate our approach by predicting genes specific to four cell types and demonstrate that the proposed DiGCellNet outperforms other models that combine node embeddings with traditional machine learning algorithms. Moreover, DiGCellNet successfully identifies CALM1 as a gene specific to beta cell type in T2D cases, and this association is confirmed using an independent dataset. The code is available at https://github.com/23AIBox/23AIBox-DiGCellNet.

Efficacy and Safety of Once-Weekly Semaglutide Versus Once-Daily Sitagliptin as Metformin Add-on in a Korean Population with Type 2 Diabetes

INTRODUCTION

Glucagon-like peptide-1 receptor agonists are well-established type 2 diabetes (T2D) treatments. As variations among populations and culture might influence treatment effects, this post hoc analysis evaluates the efficacy and safety of once-weekly (OW) semaglutide in a Korean population.

METHODS

Korean adults with T2D inadequately controlled on metformin included in a 30-week, phase 3a, international, multicentre trial (NCT03061214) compared OW subcutaneous semaglutide (0.5 mg and 1.0 mg) with once-daily sitagliptin (100 mg). Key endpoints included change in glycated haemoglobin (HbA1c) and body weight; additional endpoints assessed proportions of participants reaching targets of HbA1c < 7.0% and ≤ 6.5%, ≥ 5% weight loss, and a composite endpoint of HbA1c < 7.0% without severe/blood glucose-confirmed symptomatic hypoglycaemia and no weight gain.

RESULTS

Korean participants (n = 110) showed a greater reduction in HbA1c and body weight with semaglutide 0.5 mg (-1.6%, -2.7 kg) and 1.0 mg (-1.8%, -4.8 kg) versus sitagliptin (-0.9%, 0.5 kg). HbA1c targets of < 7.0% and ≤ 6.5% were achieved by more participants treated with semaglutide 0.5 mg (80.0% and 60.0%, respectively) and 1.0 mg (87.5% and 67.5%, respectively) versus sitagliptin (54.3% and 25.7%, respectively); ≥ 5% weight loss was observed in 42.9% and 65.0% of participants treated with semaglutide 0.5 mg and 1.0 mg versus 0.0% with sitagliptin. The composite endpoint was achieved by 71.4%, 77.5%, and 31.4% of the population in the semaglutide 0.5 mg, 1.0 mg, and sitagliptin group, respectively. No new safety concerns were observed.

CONCLUSION

This analysis confirms efficacy and safety of OW semaglutide (0.5 and 1.0 mg) in a Korean population with T2D.

CLINICAL TRIAL REGISTRATION NUMBER

NCT03061214.

GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region

Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.

Evaluating polygenic risk scores for predicting cardiometabolic traits and disease risks in the Taiwan Biobank

Type 2 diabetes (T2D) and hypertension are common comorbidities and, along with hyperlipidemia, serve as risk factors for cardiovascular diseases. This study aimed to evaluate the predictive value of polygenic risk scores (PRSs) on cardiometabolic traits related to T2D, hypertension, and hyperlipidemia and the incidence of these three diseases in Taiwan Biobank samples. Using publicly available, large-scale genome-wide association studies summary statistics, we constructed cross-ethnic PRSs for T2D, hypertension, body mass index, and nine quantitative traits typically used to define the three diseases. A composite PRS (cPRS) for each of the nine traits was constructed by aggregating the significant PRSs of its genetically correlated traits. The associations of each of the nine traits at baseline as well as the change of trait values during a 3- to 6-year follow-up period with its cPRS were evaluated. The predictive performances of cPRSs in predicting future incidences of T2D, hypertension, and hyperlipidemia were assessed. The cPRSs had significant associations with baseline and changes of trait values in 3-6 years and explained a higher proportion of variance for all traits than individual PRSs. Furthermore, models incorporating disease-related cPRSs, along with clinical features and relevant trait measurements achieved area under the curve values of 87.8%, 83.7%, and 75.9% for predicting future T2D, hypertension, and hyperlipidemia in 3-6 years, respectively.

Parental and child genetic burden of glycaemic dysregulation and early-life cognitive development: an Asian and European prospective cohort study

Insulin resistance and glucose metabolism have been associated with neurodevelopmental disorders. However, in the metabolically more susceptible Asian populations, it is not clear whether the genetic burden of glycaemic dysregulation influences early-life neurodevelopment. In a multi-ethnic Asian prospective cohort study in Singapore (Growing Up in Singapore Towards healthy Outcomes (GUSTO)), we constructed child and parental polygenic risk scores (PRS) for glycaemic dysregulation based on the largest genome-wide association studies of type 2 diabetes and fasting glucose among Asians. We found that child PRS for HOMA-IR was associated with a lower perceptual reasoning score at ~7 years (β = -0. 141, p-value = 0.024, 95% CI -0. 264 to -0. 018) and a lower WIAT-III mean score at ~9 years (β = -0.222, p-value = 0.001, 95% CI -0.357 to -0.087). This association were consistent in direction among boys and girls. These inverse associations were not influenced by parental PRS and were likely mediated via insulin resistance rather than mediators such as birth weight and childhood body mass index. Higher paternal PRS for HOMA-IR was suggestively associated with lower child perceptual reasoning at ~7 years (β = -0.172, p-value = 0.002, 95% CI -0.280 to -0.064). Replication analysis in a European cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort, showed that higher child PRS for fasting glucose was associated with lower verbal IQ score while higher maternal PRS for insulin resistance was associated with lower performance IQ score in their children at ~8.5 years. In summary, our findings suggest that higher child PRS for HOMA-IR was associated with lower cognitive scores in both Asian and European replication cohorts. Differential findings between cohorts may be attributed to genetic and environmental factors. Further investigation of the functions of the genetic structure and ancestry-specific PRS and a more comprehensive investigation of behavioural mediators may help to understand these findings better.

Inverse association between type 2 diabetes and hepatocellular carcinoma in East Asian populations

Aims

To investigate the potential association between type 2 diabetes (T2D) and hepatocellular carcinoma (HCC) in East Asian populations using Mendelian randomization (MR) analyses.

Methods

Bidirectional Mendelian randomization (MR) studies were conducted using summary statistics from genome-wide association studies (GWAS) related to T2D and HCC. The potential effects of confounders such as chronic hepatitis B, chronic hepatitis C, body mass index, and alcohol intake frequency were corrected using a multivariate MR study. Various MR methods, including the inverse variance weighted (IVW) approach, were used to estimate the associations between T2D and HCC. Sensitivity analysis and assessment of heterogeneity were performed to ensure the robustness of the results.

Results

In the forward MR study, the IVW approach of MR analysis suggested an inverse association between T2D and HCC, with a risk odds ratio of 0.8628 (95% confidence interval [CI], 0.7888-0.9438). Furthermore, even after adjusting for BMI, chronic hepatitis B, and alcohol intake frequency, this study still supports the inverse association between T2D and HCC. Additional MR methods provided further support for this relationship. Sensitivity analysis and assessment of heterogeneity confirmed the robustness of the results. The reverse MR analysis did not show a clear impact of genetic liability to HCC on reduced risk of T2D(OR=0.9788; 95% CI, 0.9061-1.0574).

Conclusion

This study provides evidence of an inverse association between T2D and HCC in East Asian populations using MR analysis. Further studies are warranted to validate these findings.

Association of RPS26 gene polymorphism with different types of diabetes in Chinese individuals

AIMS/INTRODUCTION

Different types of diabetes show distinct genetic characteristics, but the specific genetic susceptibility factors remain unclear. Our study aimed to explore the associations between the ribosomal protein S26 (RPS26) gene rs1131017 polymorphisms and susceptibility to type 1 diabetes mellitus, latent autoimmune diabetes in adults (LADA) and type 2 diabetes mellitus in the Chinese Han population, and their correlations with clinical features.

MATERIALS AND METHODS

Genotyping of the rs1131017 variant was carried out for 1,006 type 1 diabetes mellitus patients, 210 LADA patients, 642 type 2 diabetes mellitus patients and 2,099 control individuals.

RESULTS

We found that the rs1131017 C allele was a risk locus for both type 1 diabetes mellitus and LADA (odds ratio [OR] 1.50, 95% confidence interval [CI] 1.33-1.69, P < 0.001; OR 1.31, 95% CI 1.04-1.64, P = 0.021, respectively). Nevertheless, this association was not found for type 2 diabetes mellitus. Carrying the C allele genotype was associated with a lower postprandial C-peptide for type 1 diabetes mellitus (OR 1.41, 95% CI 1.11-1.80, P = 0.006) and lower fasting C-peptide for LADA (OR 1.55, 95% CI 1.01-2.38, P = 0.047). Interestingly, a lower GC frequency was noted for LADA than for type 1 diabetes mellitus, regardless of classification based on age at diagnosis, C-peptide or glutamic acid decarboxylase antibody positivity.

CONCLUSIONS

The RPS26 polymorphism was associated with susceptibility and clinical characteristics of type 1 diabetes mellitus and LADA in the Chinese population, but was not related to type 2 diabetes mellitus. Thus, it might serve as a novel biomarker for particular types of diabetes.

Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension

Hypertension, defined as persistently elevated systolic blood pressure (SBP) >140 mmHg and/or diastolic blood pressure (DBP) at least 90 mmHg (International Society of Hypertension guidelines), affects over 1.5 billion people worldwide. Hypertension is associated with increased risk of cardiovascular disease (CVD) events (e.g. coronary heart disease, heart failure and stroke) and death. An international panel of experts convened by the International Society of Hypertension College of Experts compiled lifestyle management recommendations as first-line strategy to prevent and control hypertension in adulthood. We also recommend that lifestyle changes be continued even when blood pressure-lowering medications are prescribed. Specific recommendations based on literature evidence are summarized with advice to start these measures early in life, including maintaining a healthy body weight, increased levels of different types of physical activity, healthy eating and drinking, avoidance and cessation of smoking and alcohol use, management of stress and sleep levels. We also discuss the relevance of specific approaches including consumption of sodium, potassium, sugar, fibre, coffee, tea, intermittent fasting as well as integrated strategies to implement these recommendations using, for example, behaviour change-related technologies and digital tools.

Whole Blood-based Transcriptional Risk Score for Nonobese Type 2 Diabetes Predicts Dynamic Changes in Glucose Metabolism

CONTEXT

The performance of peripheral blood transcriptional markers in evaluating risk of type 2 diabetes (T2D) with normal body mass index (BMI) is unknown.

OBJECTIVE

We developed a whole blood-based transcriptional risk score (wb-TRS) for nonobese T2D and assessed its contributions on disease risk and dynamic changes in glucose metabolism.

METHODS

Using a community-based cohort with blood transcriptome data, we developed the wb-TRS in 1105 participants aged ≥40 years who maintained a normal BMI for up to 10 years, and we validated the wb-TRS in an external dataset. Potential biological significance was explored.

RESULTS

The wb-TRS included 144 gene transcripts. Compared to the lowest tertile, wb-TRS in tertile 3 was associated with 8.91-fold (95% CI, 3.53-22.5) higher risk and each 1-unit increment was associated with 2.63-fold (95% CI, 1.87-3.68) higher risk of nonobese T2D. Furthermore, baseline wb-TRS significantly associated with dynamic changes in average, daytime, nighttime, and 24-hour glucose, HbA1c values, and area under the curve of glucose measured by continuous glucose monitoring over 6 months of intervention. The wb-TRS improved the prediction performance for nonobese T2D, combined with fasting glucose, triglycerides, and demographic and anthropometric parameters. Multi-contrast gene set enrichment (Mitch) analysis implicated oxidative phosphorylation, mTORC1 signaling, and cholesterol metabolism involved in nonobese T2D pathogenesis.

CONCLUSION

A whole blood-based nonobese T2D-associated transcriptional risk score was validated to predict dynamic changes in glucose metabolism. These findings suggested several biological pathways involved in the pathogenesis of nonobese T2D.

Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation

Skeletal muscle, the largest human organ by weight, is relevant to several polygenic metabolic traits and diseases including type 2 diabetes (T2D). Identifying genetic mechanisms underlying these traits requires pinpointing the relevant cell types, regulatory elements, target genes, and causal variants. Here, we used genetic multiplexing to generate population-scale single nucleus (sn) chromatin accessibility (snATAC-seq) and transcriptome (snRNA-seq) maps across 287 frozen human skeletal muscle biopsies representing 456,880 nuclei. We identified 13 cell types that collectively represented 983,155 ATAC summits. We integrated genetic variation to discover 6,866 expression quantitative trait loci (eQTL) and 100,928 chromatin accessibility QTL (caQTL) (5% FDR) across the five most abundant cell types, cataloging caQTL peaks that atlas-level snATAC maps often miss. We identified 1,973 eGenes colocalized with caQTL and used mediation analyses to construct causal directional maps for chromatin accessibility and gene expression. 3,378 genome-wide association study (GWAS) signals across 43 relevant traits colocalized with sn-e/caQTL, 52% in a cell-specific manner. 77% of GWAS signals colocalized with caQTL and not eQTL, highlighting the critical importance of population-scale chromatin profiling for GWAS functional studies. GWAS-caQTL colocalization showed distinct cell-specific regulatory paradigms. For example, a C2CD4A/B T2D GWAS signal colocalized with caQTL in muscle fibers and multiple chromatin loop models nominated VPS13C, a glucose uptake gene. Sequence of the caQTL peak overlapping caSNP rs7163757 showed allelic regulatory activity differences in a human myocyte cell line massively parallel reporter assay. These results illuminate the genetic regulatory architecture of human skeletal muscle at high-resolution epigenomic, transcriptomic, and cell state scales and serve as a template for population-scale multi-omic mapping in complex tissues and traits.

Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits

Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.

Effect of Genetic and Dietary Perturbation of Glycine Metabolism on Atherosclerosis in Humans and Mice

Objective

Epidemiological and genetic studies have reported inverse associations between circulating glycine levels and risk of coronary artery disease (CAD). However, these findings have not been consistently observed in all studies. We sought to evaluate the causal relationship between circulating glycine levels and atherosclerosis using large-scale genetic analyses in humans and dietary supplementation experiments in mice.

Methods

Serum glycine levels were evaluated for association with prevalent and incident CAD in the UK Biobank. A multi-ancestry genome-wide association study (GWAS) meta-analysis was carried out to identify genetic determinants for circulating glycine levels, which were then used to evaluate the causal relationship between glycine and risk of CAD by Mendelian randomization (MR). A glycine feeding study was carried out with atherosclerosis-prone apolipoprotein E deficient (ApoE-/-) mice to determine the effects of increased circulating glycine levels on amino acid metabolism, metabolic traits, and aortic lesion formation.

Results

Among 105,718 subjects from the UK Biobank, elevated serum glycine levels were associated with significantly reduced risk of prevalent CAD (Quintile 5 vs. Quintile 1 OR=0.76, 95% CI 0.67-0.87; P<0.0001) and incident CAD (Quintile 5 vs. Quintile 1 HR=0.70, 95% CI 0.65-0.77; P<0.0001) in models adjusted for age, sex, ethnicity, anti-hypertensive and lipid-lowering medications, blood pressure, kidney function, and diabetes. A meta-analysis of 13 GWAS datasets (total n=230,947) identified 61 loci for circulating glycine levels, of which 26 were novel. MR analyses provided modest evidence that genetically elevated glycine levels were causally associated with reduced systolic blood pressure and risk of type 2 diabetes, but did provide evidence for an association with risk of CAD. Furthermore, glycine-supplementation in ApoE-/- mice did not alter cardiometabolic traits, inflammatory biomarkers, or development of atherosclerotic lesions.

Conclusions

Circulating glycine levels were inversely associated with risk of prevalent and incident CAD in a large population-based cohort. While substantially expanding the genetic architecture of circulating glycine levels, MR analyses and in vivo feeding studies in humans and mice, respectively, did not provide evidence that the clinical association of this amino acid with CAD represents a causal relationship, despite being associated with two correlated risk factors.

Rare Variant in Metallothionein 1E Increases the Risk of Type 2 Diabetes in a Chinese Population

OBJECTIVE

To uncover novel targets for the treatment of type 2 diabetes (T2D) by investigating rare variants with large effects in monogenic forms of the disease.

RESEARCH DESIGN AND METHODS

We performed whole-exome sequencing in a family with diabetes. We validated the identified gene using Sanger sequencing in additional families and diabetes- and community-based cohorts. Wild-type and variant gene transgenic mouse models were used to study the gene function.

RESULTS

Our analysis revealed a rare variant of the metallothionein 1E (MT1E) gene, p.C36Y, in a three-generation family with diabetes. This risk allele was associated with T2D or prediabetes in a community-based cohort. MT1E p.C36 carriers had higher HbA1c levels and greater BMI than those carrying the wild-type allele. Mice with forced expression of MT1E p.C36Y demonstrated increased weight gain, elevated postchallenge serum glucose and liver enzyme levels, and hepatic steatosis, similar to the phenotypes observed in human carriers of MT1E p.C36Y. In contrast, mice with forced expression of MT1E p.C36C displayed reduced weight and lower serum glucose and serum triglyceride levels. Forced expression of wild-type and variant MT1E demonstrated differential expression of genes related to lipid metabolism.

CONCLUSIONS

Our results suggest that MT1E could be a promising target for drug development, because forced expression of MT1E p.C36C stabilized glucose metabolism and reduced body weight, whereas MT1E p.C36Y expression had the opposite effect. These findings highlight the importance of considering the impact of rare variants in the development of new T2D treatments.

Emerging therapeutic options in the management of diabetes: recent trends, challenges and future directions

Diabetes is a serious health issue that causes a progressive dysregulation of carbohydrate metabolism due to insufficient insulin hormone, leading to consistently high blood glucose levels. According to the epidemiological data, the prevalence of diabetes has been increasing globally, affecting millions of individuals. It is a long-term condition that increases the risk of various diseases caused by damage to small and large blood vessels. There are two main subtypes of diabetes: type 1 and type 2, with type 2 being the most prevalent. Genetic and molecular studies have identified several genetic variants and metabolic pathways that contribute to the development and progression of diabetes. Current treatments include gene therapy, stem cell therapy, statin therapy, and other drugs. Moreover, recent advancements in therapeutics have also focused on developing novel drugs targeting these pathways, including incretin mimetics, SGLT2 inhibitors, and GLP-1 receptor agonists, which have shown promising results in improving glycemic control and reducing the risk of complications. However, these treatments are often expensive, inaccessible to patients in underdeveloped countries, and can have severe side effects. Peptides, such as glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), are being explored as a potential therapy for diabetes. These peptides are postprandial glucose-dependent pancreatic beta-cell insulin secretagogues and have received much attention as a possible treatment option. Despite these advances, diabetes remains a major health challenge, and further research is needed to develop effective treatments and prevent its complications. This review covers various aspects of diabetes, including epidemiology, genetic and molecular basis, and recent advancements in therapeutics including herbal and synthetic peptides.

Circulating organochlorine pesticide levels, genetic predisposition and the risk of incident type 2 diabetes

Persistent organochlorine pesticide (OCP) has been associated with type 2 diabetes (T2D), and genetic polymorphism might modify such an association. However, prospective evidence remains scarce. We conducted a nested case-control study comprising 1006 incident diabetic cases and 1006 matched non-diabetic controls [sex and age (±5 years)] from 2008 to 2013 (mean follow-up period: ∼4.6 years) based on the Dongfeng-Tongji cohort in Shiyan City of China, determined baseline levels of nineteen OCPs, and examined the associations of circulating OCPs, both individually and collectively, with incident T2D risk. We also constructed overall genetic risk score (GRS) based on 161 T2D-associated variants and five pathway-specific cluster GRSs based on established variants derived from the Asian population. Compared with the first quartile of serum β-BHC levels, the multivariable-adjusted ORs (95% CIs) of incident T2D risk in the second, third, and fourth quartiles were 0.98 (0.70-1.39), 1.43 (0.99-2.07), and 1.75 (1.14-2.68), respectively (FDR-adjusted Ptrend = 0.03). A positive association was observed between serum OCP mixture and incident T2D risk and can be largely attributed to β-BHC. Furthermore, serum β-BHC and p,p'-DDE showed significant interactions with the GRS for lipodystrophy, a T2D-related pathway representing fat redistribution to viscera, on T2D risk (Pinteraction < 0.05). In conclusion, higher circulating OCP levels were independently associated with an increased risk of T2D, with β-BHC possibly being the major contributor. Genetic predisposition to T2D-related morbidity, such as visceral adiposity, should be considered when assessing the risk of T2D conferred by OCPs.

Unraveling genetic causality between type 2 diabetes and pulmonary tuberculosis on the basis of Mendelian randomization

BACKGROUND

The comorbidity rate between type 2 diabetes mellitus (T2DM) and pulmonary tuberculosis (PTB) is high and imposes enormous strains on healthcare systems. However, whether T2DM is causally associated with PTB is unknown owing to limited evidence from prospective studies. Consequently, the present study aimed to clarify the genetic causality between T2DM and PTB on the basis of Mendelian randomization (MR) analysis.

METHODS

Genetic variants for T2DM and PTB were obtained from the IEU OpenGWAS project. The inverse variance weighted method was used as the main statistical analysis method and was supplemented with MR-Egger, weighted median, simple mode, and weighted mode methods. Heterogeneity was analyzed using Cochran's Q statistic. Horizontal pleiotropy was assessed using the MR-PRESSO global test and MR-Egger regression. Robustness of the results was verified using the leave-one-out method.

RESULTS

A total of 152 independent single-nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) to assess the genetic causality between T2DM and PTB. Patients with T2DM had a higher risk of PTB at the genetic level (odds ratio (OR) for MR-Egger was 1.550, OR for weighted median was 1.540, OR for inverse variance weighted was 1.191, OR for simple mode was 1.629, OR for weighted mode was 1.529). There was no horizontal pleiotropy or heterogeneity among IVs. The results were stable when removing the SNPs one by one.

CONCLUSIONS

This is the first comprehensive MR analysis that revealed the genetic causality between T2DM and PTB in the East Asian population. The study provides convincing evidence that individuals with T2DM have a higher risk of developing PTB at the genetic level. This offers a significant basis for joint management of concurrent T2DM and PTB in clinical practice.

Modeling diabetic endothelial dysfunction with patient-specific induced pluripotent stem cells

Diabetes is a known risk factor for various cardiovascular complications, mediated by endothelial dysfunction. Despite the high prevalence of this metabolic disorder, there is a lack of in vitro models that recapitulate the complexity of genetic and environmental factors associated with diabetic endothelial dysfunction. Here, we utilized human induced pluripotent stem cell (iPSC)-derived endothelial cells (ECs) to develop in vitro models of diabetic endothelial dysfunction. We found that the diabetic phenotype was recapitulated in diabetic patient-derived iPSC-ECs, even in the absence of a diabetogenic environment. Subsequent exposure to culture conditions that mimic the diabetic clinical chemistry induced a diabetic phenotype in healthy iPSC-ECs but did not affect the already dysfunctional diabetic iPSC-ECs. RNA-seq analysis revealed extensive transcriptome-wide differences between cells derived from healthy individuals and diabetic patients. The in vitro disease models were used as a screening platform which identified angiotensin receptor blockers (ARBs) that improved endothelial function in vitro for each patient. In summary, we present in vitro models of diabetic endothelial dysfunction using iPSC technology, taking into account the complexity of genetic and environmental factors in the metabolic disorder. Our study provides novel insights into the pathophysiology of diabetic endothelial dysfunction and highlights the potential of iPSC-based models for drug discovery and personalized medicine.

Additional Evidence for the Relationship Between Type 2 Diabetes and Stroke Through Observational and Genetic Analyses

While type 2 diabetes mellitus (T2DM) is commonly considered a putative causal risk factor for stroke, the effect of stroke on T2DM remains unclear. The intrinsic link underlying T2DM and stroke has not been thoroughly examined. We aimed to evaluate the phenotypic and genetic relationships underlying T2DM and stroke. We evaluated phenotypic associations using data from the UK Biobank (N = 472,050). We then investigated genetic relationships by leveraging genomic data in European ancestry for T2DM, with and without adjusting (adj) for BMI (T2DM: n = 74,124 case subjects/824,006 control subjects; T2DMadjBMI: n = 50,409 case subjects/523,897 control subjects), and for stroke (n = 73,652 case subjects/1,234,808 control subjects). We performed additional analyses using genomic data in East Asian ancestry for T2DM (n = 77,418 case subjects/356,122 control subjects) and for stroke (n = 27,413 case subjects/237,242 control subjects). Observational analyses suggested a significantly increased hazard of stroke among individuals with T2DM (hazard ratio 2.28 [95% CI 1.97-2.64]), but a slightly increased hazard of T2DM among individuals with stroke (1.22 [1.03-1.45]) which attenuated to 1.14 (0.96-1.36) in sensitivity analysis. A positive global T2DM-stroke genetic correlation was observed (rg = 0.35; P = 1.46 × 10-27), largely independent of BMI (T2DMadjBMI-stroke: rg = 0.27; P = 3.59 × 10-13). This was further corroborated by 38 shared independent loci and 161 shared expression-trait associations. Mendelian randomization analyses suggested a putative causal effect of T2DM on stroke in Europeans (odds ratio 1.07 [95% CI 1.06-1.09]), which remained significant in East Asians (1.03 [1.01-1.06]). Conversely, despite a putative causal effect of stroke on T2DM also observed in Europeans (1.21 [1.07-1.37]), it attenuated to 1.04 (0.91-1.19) in East Asians. Our study provides additional evidence to underscore the significant relationship between T2DM and stroke.

ARTICLE HIGHLIGHTS

Comparison of beta-cell function between Hong Kong Chinese with young-onset type 2 diabetes and late-onset type 2 diabetes

AIMS

We compared beta-cell function in Chinese with type 2 diabetes diagnosed at age < 40 years (young-onset diabetes, YOD) and ≥ 40 years (late-onset diabetes, LOD).

METHODS

In this cross-sectional study, we selected participants from two cohorts of people with type 2 diabetes recruited in 1996-2012 (n = 4,376) and 2020-2021 (n = 794). Multivariable linear regression models were applied to compare homeostasis model assessment of beta-cell function (HOMA2-%B) and fasting plasma C-peptide across diabetes duration at enrolment between YOD and LOD.

RESULTS

The YOD group (n = 1,876, mean [SD] age: 39.9 [7.5] years, median [IQR] diabetes duration: 6 [2-12] years) was more likely to have family history of diabetes (61.6 % vs 43.6 %), obesity (41.9 % vs 26.8 %), dyslipidaemia (61.7 % vs 54.4 %), and worse glycaemic control (mean HbA1c 7.7 % vs 7.4 %) than those with LOD (n = 3,294, age: 60.8 [10.6] years, diabetes duration: 5 [1-10] years). When compared to people with LOD, HOMA2-%B and fasting plasma C-peptide were lower in the YOD group, consistently among those with BMI < 27.5 kg/m2 and HOMA2-IR ≤ 1.6 (median value), adjusted for year at enrolment, sex, diabetes duration, family history of diabetes, HbA1c, weight and lipid indices (p < 0.01). Cross-sectionally, the slopes of decline in HOMA2-%B by diabetes duration were greater in YOD than LOD among individuals with BMI < 27.5 kg/m2 (p-interaction = 0.015).

CONCLUSIONS

Chinese with YOD had accelerated loss of beta-cell function than those with LOD especially in non-obese individuals.

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

Rare Heterozygous Loss-of-Function Variants in the Human GLP-1 Receptor Are Not Associated With Cardiometabolic Phenotypes

CONTEXT

Lost glucagon-like peptide 1 receptor (GLP-1R) function affects human physiology.

OBJECTIVE

This work aimed to identify coding nonsynonymous GLP1R variants in Danish individuals to link their in vitro phenotypes and clinical phenotypic associations.

METHODS

We sequenced GLP1R in 8642 Danish individuals with type 2 diabetes or normal glucose tolerance and examined the ability of nonsynonymous variants to bind GLP-1 and to signal in transfected cells via cyclic adenosine monophosphate (cAMP) formation and β-arrestin recruitment. We performed a cross-sectional study between the burden of loss-of-signaling (LoS) variants and cardiometabolic phenotypes in 2930 patients with type 2 diabetes and 5712 participants in a population-based cohort. Furthermore, we studied the association between cardiometabolic phenotypes and the burden of the LoS variants and 60 partly overlapping predicted loss-of-function (pLoF) GLP1R variants found in 330 566 unrelated White exome-sequenced participants in the UK Biobank cohort.

RESULTS

We identified 36 nonsynonymous variants in GLP1R, of which 10 had a statistically significant loss in GLP-1-induced cAMP signaling compared to wild-type. However, no association was observed between the LoS variants and type 2 diabetes, although LoS variant carriers had a minor increased fasting plasma glucose level. Moreover, pLoF variants from the UK Biobank also did not reveal substantial cardiometabolic associations, despite a small effect on glycated hemoglobin A1c.

CONCLUSION

Since no homozygous LoS nor pLoF variants were identified and heterozygous carriers had similar cardiometabolic phenotype as noncarriers, we conclude that GLP-1R may be of particular importance in human physiology, due to a potential evolutionary intolerance of harmful homozygous GLP1R variants.

Lipids, Blood Pressure, and Diabetes Mellitus on Risk of Cardiovascular Diseases in East Asians: A Mendelian Randomization Study

Elevated blood pressure, dyslipidemia, and impaired glycemic control are well-established cardiovascular risk factors in Europeans, but there are comparatively few studies focused on East Asian populations. This study evaluated the potential causal relations between traditional cardiovascular risk factors and disease risk in East Asians through a 2-sample Mendelian randomization approach. We collected summary statistics for blood pressure parameters, lipid subsets, and type 2 diabetes mellitus liability from large genome-wide association study meta-analyses conducted in East Asians and Europeans. These were paired with summary statistics for ischemic heart disease (IHD), ischemic stroke (IS), peripheral vascular disease, heart failure (HF) and atrial fibrillation (AF). We performed univariable Mendelian randomization analyses for each exposure-outcome pair, followed by multivariable analyses for the available lipid subsets. The genetically predicted risk factors associated with IHD and AF were similar between East Asians and Europeans. However, in East Asians only genetically predicted elevated blood pressure was significantly associated with IS (odds ratio 1.05, 95% confidence interval 1.04 to 1.06, p <0.0001) and HF (odds ratio 1.05, 95% confidence interval 1.04 to 1.06, p <0.0001), whereas nearly all genetically predicted risk factors were significantly associated with IS and HF in Europeans. In conclusion, this study provides supportive evidence for similar causal relations between traditional cardiovascular risk factors and IHD and AF in both East Asian and European ancestry populations. However, the identified risk factors for IS and HF differed between East Asians and Europeans, potentially highlighting distinct disease etiologies between these populations.

Using a modular massively parallel reporter assay to discover context-specific regulatory grammars in type 2 diabetes

Recent genome-wide association studies have established that most complex disease-associated loci are found in noncoding regions where defining their function is nontrivial. In this study, we leverage a modular massively parallel reporter assay (MPRA) to uncover sequence features linked to context-specific regulatory activity. We screened enhancer activity across a panel of 198-bp fragments spanning over 10k type 2 diabetes- and metabolic trait-associated variants in the 832/13 rat insulinoma cell line, a relevant model of pancreatic beta cells. We explored these fragments' context sensitivity by comparing their activities when placed up-or downstream of a reporter gene, and in combination with either a synthetic housekeeping promoter (SCP1) or a more biologically relevant promoter corresponding to the human insulin gene ( INS ). We identified clear effects of MPRA construct design on measured fragment enhancer activity. Specifically, a subset of fragments (n = 702/11,656) displayed positional bias, evenly distributed across up- and downstream preference. A separate set of fragments exhibited promoter bias (n = 698/11,656), mostly towards the cell-specific INS promoter (73.4%). To identify sequence features associated with promoter preference, we used Lasso regression with 562 genomic annotations and discovered that fragments with INS promoter-biased activity are enriched for HNF1 motifs. HNF1 family transcription factors are key regulators of glucose metabolism disrupted in maturity onset diabetes of the young (MODY), suggesting genetic convergence between rare coding variants that cause MODY and common T2D-associated regulatory variants. We designed a follow-up MPRA containing HNF1 motif-enriched fragments and observed several instances where deletion or mutation of HNF1 motifs disrupted the INS promoter-biased enhancer activity, specifically in the beta cell model but not in a skeletal muscle cell line, another diabetes-relevant cell type. Together, our study suggests that cell-specific regulatory activity is partially influenced by enhancer-promoter compatibility and indicates that careful attention should be paid when designing MPRA libraries to capture context-specific regulatory processes at disease-associated genetic signals.

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.

Genome-wide polygenic risk score, cardiometabolic risk factors, and type 2 diabetes mellitus in the Chinese population

OBJECTIVE

Type 2 diabetes (T2D) is caused by both genetic and cardiometabolic risk factors. However, the magnitude of the genetic predisposition of T2D in the Chinese population remains largely unknown.

METHODS

This study included 93,488 participants from the China Kadoorie Biobank, and multiple polygenic risk scores (PRS) were calculated. A common cardiometabolic risk score (CRS) using smoking, alcohol consumption, physical activity, diet, obesity, blood pressure, and blood lipids was constructed to investigate the effects of cardiometabolic risk factors on T2D. Furthermore, an equation based on ideal PRS, CRS, and their interaction was established to explore the combined effects on T2D.

RESULTS

An ideally fitting PRS model (variance explained, R2  = 7.6%) was reached based on multiple PRS calculation methods. An additive interaction between PRS and CRS (coefficient = 28%, 95% CI: 0.20-0.36, p < 0.001) was found. The R2 of the T2D predictive model could increase to 8.3% when CRS and the interaction terms of PRS × CRS were considered. In the etiological composition of T2D, the ratio of genetic risk effect, cardiometabolic risk effect, and interaction between genetic and cardiometabolic factors was 67:16:17.

CONCLUSIONS

This study identified an ideally fitting PRS model for identifying and predicting the risk of T2D suitable for the Chinese population. The quantified proportional structure of genetic risk factors, cardiometabolic risk factors, and their interaction was detected, which elucidated the critical effect of genetic factors.

Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

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.

A common East-Asian ALDH2 mutation causes metabolic disorders and the therapeutic effect of ALDH2 activators

Obesity and type 2 diabetes have reached pandemic proportion. ALDH2 (acetaldehyde dehydrogenase 2, mitochondrial) is the key metabolizing enzyme of acetaldehyde and other toxic aldehydes, such as 4-hydroxynonenal. A missense Glu504Lys mutation of the ALDH2 gene is prevalent in 560 million East Asians, resulting in reduced ALDH2 enzymatic activity. We find that male Aldh2 knock-in mice mimicking human Glu504Lys mutation were prone to develop diet-induced obesity, glucose intolerance, insulin resistance, and fatty liver due to reduced adaptive thermogenesis and energy expenditure. We find reduced activity of ALDH2 of the brown adipose tissue from the male Aldh2 homozygous knock-in mice. Proteomic analyses of the brown adipose tissue from the male Aldh2 knock-in mice identifies increased 4-hydroxynonenal-adducted proteins involved in mitochondrial fatty acid oxidation and electron transport chain, leading to markedly decreased fatty acid oxidation rate and mitochondrial respiration of brown adipose tissue, which is essential for adaptive thermogenesis and energy expenditure. AD-9308 is a water-soluble, potent, and highly selective ALDH2 activator. AD-9308 treatment ameliorates diet-induced obesity and fatty liver, and improves glucose homeostasis in both male Aldh2 wild-type and knock-in mice. Our data highlight the therapeutic potential of reducing toxic aldehyde levels by activating ALDH2 for metabolic diseases.