Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

A Mendelian randomization analysis of cardiac MRI measurements as surrogate outcomes for heart failure and atrial fibrillation

BACKGROUND

Drug development and disease prevention of heart failure (HF) and atrial fibrillation (AF) are impeded by a lack of robust early-stage surrogates. We determined to what extent cardiac magnetic resonance (CMR) measurements act as surrogates for the development of HF or AF.

METHODS

Genetic data were sourced on the association with 21 atrial and ventricular CMR measurements. Mendelian randomization was used to determine CMR associations with AF, HF, non-ischaemic cardiomyopathy (NICM), and dilated cardiomyopathy (DCM), noting that the definition of NICM includes DCM as a subset. Additionally, for the CMR surrogates of AF and HF, we explored their association with non-cardiac traits potentially influenced by cardiac disease liability.

RESULTS

In total we find that 7 CMR measures (biventricular ejection fraction (EF) and end-systolic volume (ESV), as well as LV systolic volume (SV), end-diastolic volume (EDV), and mass to volume ratio (MVR)) associate with the development of HF, 5 with the development of NICM (biventricular EDV and ESV, LV-EF), 7 with DCM (biventricular EF, ESV, EDV, and LV end-diastolic mass (EDM), and 3 associate with AF (LV-ESV, RV-EF, RV-ESV). Higher EF of both ventricles associate with lower risk of HF and DCM, with biventricular ESV associating with all four cardiac outcomes. Higher values of biventricular EDV associate with lower risk of HF, and DCM. Exploring the associations of these CMR cardiac disease surrogates with non-cardiac traits confirms a strong link with diastolic blood pressure, as well as more specific associations with lung function (LV-ESV), HbA1c (LV-EDM), and type 2 diabetes (LV-SV).

CONCLUSIONS

The current paper identifies key CMR measurements that may act as surrogate endpoints for the development of HF (including NICM and DCM) or AF.

Identification and validation of five novel protein targets for type 2 diabetes mellitus

Despite advances in type 2 diabetes mellitus (T2DM) therapy, challenges remain due to the lack of novel therapeutic targets. We used Mendelian randomization to integrate cis-expression quantitative trait loci data for circulating proteins from the eQTLGen Consortium (31,684 individuals) with T2DM summary statistics from the Integrative Epidemiology Unit Open Genome-Wide Association Studies Project (61,714 cases, 593,952 controls). 42 genes were significantly associated with T2DM. Colocalization analysis revealed that six genes (CLSTN1, KCNJ11, MLX, DLD, RELA, and ULK1) shared common causal variants with T2DM. Among them, CLSTN1 (OR = 0.80, 95% CI: 0.70-0.90), KCNJ11 (OR = 0.66, 95% CI: 0.60-0.73), and MLX (OR = 0.73, 95% CI: 0.65-0.82) were negatively associated with T2DM, while DLD (OR = 1.38, 95% CI: 1.15-1.65), RELA (OR = 1.90, 95% CI: 1.41-2.55), and ULK1 (OR = 1.42, 95% CI: 1.17-1.71) were positively associated with T2DM. A matched case-control study further validated these associations, except for DLD, showing significant downregulation of CLSTN1, KCNJ11, and MLX (P < 0.05) alongside upregulation of RELA and ULK1 (P < 0.05) in T2DM patients. These findings underscore the potential of these proteins as drug targets, warranting further clinical investigation to confirm their therapeutic relevance.

Clinical use of polygenic scores in type 2 diabetes: challenges and possibilities

Resulting from a combination of genetic and environmental factors, type 2 diabetes is highly heterogeneous in manifestation and disease progression, with the only common feature being chronic hyperglycaemia. In spite of vigorous efforts to elucidate the pathogenetic origins and natural course of the disease, there is still a lack of biomarkers and tools for prevention, disease stratification and treatment. Genome-wide association studies have reported over 1200 variants associated with type 2 diabetes, and the decreased cost of generating genetic data has facilitated the development of polygenic scores for estimating an individual's genetic disease risk based on combining effects from most-or all-genetic variants. In this review, we summarise the current knowledge on type 2 diabetes-related polygenic scores in different ancestries and outline their possible clinical role. We explore the potential applicability of type 2 diabetes polygenic scores to quantify genetic liability for prediction, screening and risk stratification. Given that most genetic risk loci are determined from populations of European origin while other ancestries are under-represented, we also discuss the challenges around their global applicability. To date, the potential for clinical utility of polygenic scores for type 2 diabetes is limited, with such scores outperformed by clinical measures. In the future, rather than predicting risk of type 2 diabetes, the value of polygenic scores may be in stratification of the severity of disease (risk for comorbidities) and treatment response, in addition to aiding in dissecting the pathophysiological mechanisms involved.

Common-variant and rare-variant genetic architecture of heart failure across the allele-frequency spectrum

Heart failure is a complex trait, influenced by environmental and genetic factors, affecting over 30 million individuals worldwide. Here we report common-variant and rare-variant association studies of all-cause heart failure and examine how different classes of genetic variation impact its heritability. We identify 176 common-variant risk loci at genome-wide significance in 2,358,556 individuals and cluster these signals into five broad modules based on pleiotropic associations with anthropomorphic traits/obesity, blood pressure/renal function, atherosclerosis/lipids, immune activity and arrhythmias. In parallel, we uncover exome-wide significant associations for heart failure and rare predicted loss-of-function variants in TTN, MYBPC3, FLNC and BAG3 using exome sequencing of 376,334 individuals. We find that total burden heritability of rare coding variants is highly concentrated in a small set of Mendelian cardiomyopathy genes, while common-variant heritability is diffusely spread throughout the genome. Finally, we show that common-variant background modifies heart failure risk among carriers of rare pathogenic truncating variants in TTN. Together, these findings discern genetic links between dysregulated metabolism and heart failure and highlight a polygenic component to heart failure not captured by current clinical genetic testing.

Assessing the effect of modifiable risk factors on hepatocellular carcinoma: evidence from a bidirectional Mendelian randomization analysis

BACKGROUND

The pathogenesis of hepatocellular carcinoma (HCC) involves a variety of environmental risk factors, some of which have yet to be fully clarified. Using the Mendelian randomization (MR) approach, this study comprehensively investigates the causal effect of genetically predicted modifiable risk factors on HCC.

METHODS

Genetic variants related to the 50 risk factors that had been identified in previous research were derived from genome-wide association studies. Summary statistics for the discovery cohort and validation cohort of HCC were sourced from the FinnGen consortium and the UK Biobank, respectively. Bidirectional MR analysis and sensitivity analysis were performed to establish causative risk factors for HCC.

RESULTS

Through the inverse variance weighted method, the results of the discovery cohort indicated that waist circumference, nonalcoholic fatty liver disease (NAFLD), alanine aminotransferase (ALT) levels, and aspartate aminotransferase (AST) levels were significantly linked to HCC occurrence risk. Furthermore, body fat percentage, glycated hemoglobin (HbA1c), obesity class 1-3, waist-to-hip ratio, iron, ferritin, transferrin saturation, and urate had suggestive associations with HCC. The validation cohort further confirmed that NAFLD and ALT levels were strongly related to HCC. Reverse MR indicated that genetic susceptibility to HCC was connected to NAFLD and transferrin saturation. Sensitivity analyses showed that most of the findings were robust.

CONCLUSION

This MR study delivers evidence of the complex causal relationship between modifiable risk factors and HCC. These findings offer new insights into potential prevention and treatment strategies for HCC.

Causal associations between gut microbiota and type 2 diabetes mellitus subtypes: a mendelian randomization analysis

PURPOSE

To investigate the causal relationships between gut microbiota and novel adult-onset type 2 diabetes mellitus(T2DM) subtypes.

METHODS

We conducted Mendelian randomization (MR) analyses using genome-wide association data from European populations. Initial MR analyses examined associations between gut microbiota and four T2DM subtypes, followed by validation analyses using type 1 diabetes mellitus(T1DM) and T2DM GWAS data. We also performed bidirectional MR analyses and tested for heterogeneity and pleiotropy across all analyses.

RESULTS

Our MR analyses revealed distinctive associations between gut microbiota and T2DM subtypes: six bacterial taxa with severe insulin-deficient diabetes (SIDD), four with severe insulin-resistant diabetes (SIRD), eight with mild obesity-related diabetes (MOD), and eight with mild age-related diabetes (MARD). These associations were distinct from T1DM findings. Six bacterial taxa were validated in T2DM analyses, with four showing directionally consistent effects: Class Clostridia (OR = 0.57, P = 0.045) and Order Clostridiales (OR = 0.57, P = 0.045) were associated with reduced MOD risk, while species Catus (OR = 1.80, P = 0.007) was associated with increased MOD risk, and genus Holdemania (OR = 2.51, P = 0.004) was associated with increased SIRD risk. No significant heterogeneity or pleiotropy was observed across analyses.

CONCLUSIONS

Our MR analyses reveal novel causal relationships between gut microbiota and adult-onset T2DM subtypes, though further validation studies are warranted.

Type 2 diabetes pathway-specific polygenic risk scores elucidate heterogeneity in clinical presentation, disease progression and diabetic complications in 18,217 Chinese individuals with type 2 diabetes

AIMS/HYPOTHESIS

Type 2 diabetes is a complex and heterogeneous disease and the aetiological components underlying the heterogeneity remain unclear in the Chinese and East Asian population. Therefore, we aimed to investigate whether specific pathophysiological pathways drive the clinical heterogeneity in type 2 diabetes.

METHODS

We employed newly developed type 2 diabetes hard-clustering and soft-clustering pathway-specific polygenic risk scores (psPRSs) to characterise individual genetic susceptibility to pathophysiological pathways implicated in type 2 diabetes in 18,217 Chinese patients from Hong Kong. The 'total' type 2 diabetes polygenic risk score (PRS) was summed by genome-wide significant type 2 diabetes signals (n=1289). We examined the associations between psPRSs and cardiometabolic profile, age of onset, two glycaemic deterioration outcomes (clinical requirement of insulin treatment, defined by two consecutive HbA1c values ≥69 mmol/mol [8.5%] more than 3 months apart during treatment with two or more oral glucose-lowering drugs, and insulin initiation), three renal (albuminuria, end-stage renal disease and chronic kidney disease) outcomes and five cardiovascular outcomes.

RESULTS

Although most psPRSs and total type 2 diabetes PRS were associated with an earlier and younger onset of type 2 diabetes, the psPRSs showed distinct associations with clinical outcomes. In particular, individuals with normal weight showed higher psPRSs for beta cell dysfunction and lipodystrophy than those who were overweight. The psPRSs for obesity were associated with faster progression to clinical requirement of insulin treatment (adjusted HR [95% CI] 1.09 [1.05, 1.13], p<0.0001), end-stage renal disease (1.10 [1.04, 1.16], p=0.0007) and CVD (1.10 [1.05, 1.16], p<0.0001) while the psPRSs for beta cell dysfunction were associated with reduced incident end-stage renal disease (0.90 [0.85, 0.95], p=0.0001) and heart failure (0.83 [0.73, 0.93], p=0.0011). Major findings remained significant after adjusting for a set of clinical variables.

CONCLUSIONS/INTERPRETATION

Beta cell dysfunction and lipodystrophy could be the driving pathological pathways in type 2 diabetes in individuals with normal weight. Genetic risks of beta cell dysfunction and obesity represent two major genetic drivers of type 2 diabetes heterogeneity in disease progression and diabetic complications, which are shared across ancestry groups. Type 2 diabetes psPRSs may help inform patient stratification according to aetiology and guide precision diabetes care.

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

A Research Roadmap to Address the Heterogeneity of Diabetes and Advance Precision Medicine

The current classification of diabetes had its genesis over 85 years ago, when individuals with diabetes were first subclassified into insulin sensitive and insulin insensitive states based on the response to an oral glucose tolerance test. About 35 years later, the contemporary classifications of type 1 and type 2 diabetes were coined. Today's evidence, however, suggests that multiple etiologic and pathogenic processes lead to both type 1 and type 2 diabetes, reflecting significant heterogeneity in factors associated with initiation, progression, and clinical presentation of each disorder of glucose homeostasis. Further, the current classification fails to recognize what is currently defined as "atypical" diabetes. Heterogeneity of diabetes continues through the life-course of an individual, with modification of prognosis risk (eg, diabetic complications) altered by genetics, life experience, comorbidities, and therapy. Understanding the sources of heterogeneity in diabetes will likely improve diagnosis, prevention, treatment, and prediction of complications in both the medical and public health settings. Such knowledge will help inform progress in the emerging era of precision diabetes medicine. This article presents NIDDK's Heterogeneity of Diabetes Initiative and a corresponding roadmap for future research in type 2 diabetes heterogeneity.

Causal association of inflammation with ischemic stroke and its subtypes: a bidirectional Mendelian randomization study

BACKGROUND

Emerging evidence underscores a bidirectional relationship between ischemic stroke (IS) and inflammation, yet the causality of this association remains uncertain. We conducted a two-sample bidirectional Mendelian randomization (MR) study aimed at investigating the causal links between inflammation and IS.

METHODS

Single nucleotide polymorphism from genome-wide association studies of 112 inflammatory cytokines and IS were chosen as instrumental variables. We evaluated the causal effects of inflammatory factors on IS outcomes and examined the mediating effects of risk factors for IS. Additionally, reverse MR analysis was conducted to determine whether the occurrence of IS influenced levels of inflammatory cytokines. Causal associations were assessed using inverse variance weighting, complemented by sensitivity analyses incorporating weighted median and MR-Egger methods.

RESULTS

We found associations between genetically predicted plasma levels of 25 inflammatory factors and IS along with its subtypes. MR supports smoking, body mass index, atrial fibrillation, coronary artery disease, heart failure, systolic blood pressure, diastolic blood pressure and type 2 diabetes as risk factors for IS. Notably, coronary artery disease and heart failure seemed to mediate the RANTES, HGF, IL-5 associations with IS. In addition, reverse MR analysis suggested a causal relationship between IS and its subtypes and 19 inflammatory factors.

CONCLUSION

In summary, inflammation was suggestively causally associated with the risk of IS, and inflammatory cytokines had downstream effect on IS. Future studies should explore whether inflammatory factors found to have significant associations with IS risk could be manipulated to reduce IS risk, and the neuroinflammatory mechanisms after IS.

Diabetes exerts a causal impact on the nervous system within the right hippocampus: substantiated by genetic data

INTRODUCTION

Diabetes and neuronal loss in the hippocampus have been observed to be correlated in several studies; however, the exact causality of this association remains uncertain. This study aims to explore the potential causal relationship between diabetes and the hippocampal nervous system.

METHODS

We utilized the two-sample Mendelian randomization (MR) analysis to investigate the potential causal connection between diabetes and the hippocampal nervous system. The summary statistics of Genome-wide association study (GWAS) for diabetes and hippocampus neuroimaging measurement were acquired from published GWASs, all of which were based on European ancestry. Several two-sample MR analyses were conducted in this study, utilizing inverse-variance weighted (IVW), MR Egger, and Weight-median methods. To ensure the reliability of the results and identify any horizontal pleiotropy, sensitivity analyses were undertaken using Cochran's Q test and the MR-PRESSO global test.

RESULTS

Causal associations were found between diabetes and the nervous system in the hippocampus. Type 1 and type 2 diabetes were both identified as having adverse causal connections with the right hippocampal nervous system. This was supported by specific ranges of IVW-OR values (P < 0.05). The consistency of the sensitivity analyses further reinforced the main findings, revealing no significant heterogeneity or presence of horizontal pleiotropy.

CONCLUSIONS

This study delved into the causal associations between diabetes and the hippocampal nervous system, revealing that both type 1 and type 2 diabetes have detrimental effects on the right hippocampal nervous system. Our findings have significant clinical implications as they indicate that diabetes may play a role in the decline of neurons in the right hippocampus among European populations, often resulting in cognitive decline.

ZHX3 interacts with CEBPB to repress hepatic gluconeogenic gene expression and uric acid secretion

ZHX3, which encodes for a transcriptional repressor, is associated with fasting blood glucose (FBG) levels and increased type 2 diabetes (T2D) risk but its role in cell types involved in glucose metabolism is not well understood. Here, we show that the deletion of ZHX3 in the human pancreatic β-cell line EndoC-βH1 did not impair glucose-stimulated insulin secretion (GSIS) nor perturb its transcriptome. On the other hand, we found that ZHX3 represses the expression of gluconeogenic genes PCK1 and G6PC1 in the human hepatoma line HepG2. Transcriptomic analysis of ZHX3-deficient HepG2 cells revealed that the uric acid transporter gene SLC17A1 was up-regulated, which consequentially led to increased uric acid secretion. High levels of uric acid could then impair GSIS in EndoC-βH1 cells. Subsequently, in-depth co-immunoprecipitation followed by mass spectrometry analysis of ZHX3 in HepG2 cells identified transcription factor CEBPB as its binding partner, required to repress the transcription of PCK1, G6PC1, and partially SLC17A1 in HepG2 cells. Overall, our study uncovered the role of ZHX3 in regulating glucose metabolism in hepatocytes, thereby influencing FBG levels and their association with T2D risk.

GWAS of CRP response to statins further supports the role of APOE in statin response: A GIST consortium study

Statins are first-line treatments in the primary and secondary prevention of cardiovascular disease. Clinical studies show statins act independently of lipid-lowering mechanisms to decrease C-reactive protein (CRP), an inflammation marker. We aim to elucidate genetic loci associated with CRP statin response. CRP statin response is the change in log-CRP between off-treatment and on-treatment measurements. Cohort-level Genome-Wide Association Studies (GWAS) of CRP response were performed using 1000 Genomes imputed data, testing ∼10 million common genetic variants. GWAS meta-analysis combined results from seven cohorts and clinical trials totalling 14,070 statin-treated individuals of European ancestry within the GIST consortium. Secondary analyses included statin-by-placebo interaction analyses, and lookups in African ancestry cohorts. Our GWAS identified two genome-wide significant (P < 5e-8) loci: APOE and HNF1A for CRP statin response corrected for baseline CRP. The missense lead variant rs429358 at APOE, contributing to the APOE-E4 haplotype, is a risk locus for dyslipidaemia, Alzheimer's and coronary artery disease (CAD). The HNF1A locus is associated with diabetes, cholesterol levels, and CAD. Both loci are also associated with baseline CRP levels, and neither locus achieved a significant (P < 0.05) result from the statin v. placebo interaction meta-analysis using randomized clinical trial data. However, the interaction result (P-int=0.09) for APOE was suggestive and possibly underpowered. The APOE-E4 signal may therefore be associated with both CRP and LDL-cholesterol statin response. Combined with suggestions in the literature that APOE also leads to differential statin benefit in Alzheimer's, the APOE locus warrants further investigation for potential genetic effects on healthcare with statin treatment.

Lipoprotein Lipase: Structure, Function, and Genetic Variation

Biallelic rare pathogenic loss-of-function (LOF) variants in lipoprotein lipase (LPL) cause familial chylomicronemia syndrome (FCS). Heterozygosity for these same variants is associated with a highly variable plasma triglyceride (TG) phenotype ranging from normal to severe hypertriglyceridemia (HTG), with longitudinal variation in phenotype severity seen often in a given carrier. Here, we provide an updated overview of genetic variation in LPL in the context of HTG, with a focus on disease-causing and/or disease-associated variants. We provide a curated list of 300 disease-causing variants discovered in LPL, as well as an exon-by-exon breakdown of the LPL gene and protein, highlighting the impact of variants and the various functional residues of domains of the LPL protein. We also provide a curated list of variants of unknown or uncertain significance, many of which may be upgraded to pathogenic/likely pathogenic classification should an additional case and/or segregation data be reported. Finally, we also review the association between benign/likely benign variants in LPL, many of which are common polymorphisms, and the TG phenotype.

Diabetes and obesity: leveraging heterogeneity for precision medicine

The increasing prevalence of diabetes, obesity, and their cardiometabolic sequelae present major global health challenges and highlight shortfalls of current approaches to the prevention and treatment of these conditions. Representing the largest global burden of morbidity and mortality, the pathobiological processes underlying cardiometabolic diseases are in principle preventable and, even when disease is manifest, sometimes reversable. Nevertheless, with current clinical and public health strategies, goals of widespread prevention and remission remain largely aspirational. Application of precision medicine approaches that reduce errors and improve accuracy in medical and health recommendations has potential to accelerate progress towards these goals. Precision medicine must also maintain safety and ideally be cost-effective, as well as being compatible with an individual's preferences, capabilities, and needs. Initial progress in precision medicine was made in the context of rare diseases, with much focus on pharmacogenetic studies, owing to the cause of these diseases often being attributable to highly penetrant single gene mutations. By contrast, most obesity and type 2 diabetes are heterogeneous in aetiology and clinical presentation, underpinned by complex interactions between genetic and non-genetic factors. The heterogeneity of these conditions can be leveraged for development of approaches for precision therapies. Adequate characterization of the heterogeneity in cardiometabolic disease necessitates diversity of and synthesis across data types and research methods, ideally culminating in precision trials and real-world application of precision medicine approaches. This State-of-the-Art Review provides an overview of the current state of the science of precision medicine, as well as outlining a roadmap for study designs that maximise opportunities and address challenges to clinical implementation of precision medicine approaches in obesity and diabetes.

The multi-scale complexity of human genetic variation beyond continental groups

Traditional clustering and visualization approaches in human genetics often operate under frameworks that assume inherent, discrete groupings1,2. These methods can inadvertently simplify multifaceted relationships, functioning to entrench the idea of typological groups3. We introduce a network-based pipeline and visualization tool grounded in relational thinking4, which constructs networks from a variety of genetic similarity metrics. We identify communities at multiple resolutions, departing from typological models of analysis and interpretation that categorize individuals into a (predefined) number of sets. We applied our pipeline to a dataset merged from the 1000 Genomes and Human Genome Diversity Project5, revealing the limitations of traditional groupings and capturing the complexities introduced by demographic events and evolutionary processes. This method embraces the context-specificity of genetic similarities that are salient depending on the question, markers of interest, and study individuals. Different numbers of communities are revealed depending on the resolution chosen and metric used, underscoring a fluid spectrum of genetic relationships and challenging the notion of universal categorization. We provide a web application (https://sohail-lab.shinyapps.io/GG-NC/) for interactive visualization and engagement with these intricate genetic landscapes.

Personalized phosphoproteomics of skeletal muscle insulin resistance and exercise links MINDY1 to insulin action

Type 2 diabetes is preceded by a defective insulin response, yet our knowledge of the precise mechanisms is incomplete. Here, we investigate how insulin resistance alters skeletal muscle signaling and how exercise partially counteracts this effect. We measured parallel phenotypes and phosphoproteomes of insulin-resistant (IR) and insulin-sensitive (IS) men as they responded to exercise and insulin (n = 19, 114 biopsies), quantifying over 12,000 phosphopeptides in each biopsy. Insulin resistance involves selective and time-dependent alterations to signaling, including reduced insulin-stimulated mTORC1 and non-canonical signaling responses. Prior exercise promotes insulin sensitivity even in IR individuals by "priming" a portion of insulin signaling prior to insulin infusion. This includes MINDY1 S441, which we show is an AKT substrate. We found that MINDY1 knockdown enhances insulin-stimulated glucose uptake in rat myotubes. This work delineates the signaling alterations in IR skeletal muscle and identifies MINDY1 as a regulator of insulin action.

Systems biology approaches identify metabolic signatures of dietary lifespan and healthspan across species

Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabolites as markers to reveal how different genotypes respond to diet to influence longevity and healthspan traits. We analyzed data from Drosophila Genetic Reference Panel (DGRP) strains raised under AL and DR conditions, combining metabolomic, phenotypic, and genome-wide information. We employed two computational and complementary methods across species-random forest modeling within the DGRP as our primary analysis and Mendelian randomization in human cohorts as a secondary analysis. We pinpointed key traits with cross-species relevance as well as underlying heterogeneity and pleiotropy that influence lifespan and healthspan. Notably, orotate was linked to parental age at death in humans and blocked the DR lifespan extension in flies, while threonine supplementation extended lifespan, in a strain- and sex-specific manner. Thus, utilizing natural genetic variation data from flies and humans, we employed a systems biology approach to elucidate potential therapeutic pathways and metabolomic targets for diet-dependent changes in lifespan and healthspan.

A regulatory variant rs9379874 in T1D risk region 6p22.2 affects BTN3A1 expression regulating T cell function

OBJECTIVE

Genome-wide association studies (GWAS) have identified that 6p22.2 region is associated with type 1 diabetes (T1D) risk in the Chinese Han population. This study aims to reveal associations between this risk region and T1D subgroups and related clinical features, and further identify causal variant(s) and target gene(s) in this region.

METHODS

2608 T1D and 4814 healthy controls were recruited from East, Central, and South China. Baseline data and genotyping for rs4320356 were collected. The most likely causal variant and gene were identified by bioinformatics analysis, dual-luciferase reporter assays, expression quantitative trait loci (eQTL), and functional annotation of the non-coding region within the 6p22.2 region.

RESULTS

The leading variant rs4320356 in the 6p22.2 region was associated with T1D risk in the Chinese and Europeans. However, this variant was not significantly associated with islet function or autoimmunity. In silico analysis suggested rs9379874 was the most potential causal variant for T1D risk among thymus, spleen, and T cells, overlapping with the enhancer-related histone mark in multiple T cell subsets. Dual luciferase reporter assay and eQTL showed that the T allele of rs9379874 increased BTN3A1 expression by binding to FOXA1. Public single-cell RNA sequencing analysis indicated that BTN3A1 was related to T-cell activation, ATP metabolism, and cytokine metabolism pathways, which might contribute to T1D development.

CONCLUSION

This study indicates that a functional variant rs9379874 regulates BTN3A1 expression, expanding the genomic landscape of T1D risk and offering a potential target for developing novel therapies.

Understanding the cause of type 2 diabetes

Type 2 diabetes has long been thought to have heterogenous causes, even though epidemiological studies uniformly show a tight relationship with overnutrition. The twin cycle hypothesis postulated that interaction of self-reinforcing cycles of fat accumulation inside the liver and pancreas, driven by modest but chronic positive calorie balance, could explain the development of type 2 diabetes. This hypothesis predicted that substantial weight loss would bring about a return to the non-diabetic state, permitting observation of the pathophysiology determining the transition. These changes were postulated to reflect the basic mechanisms of causation in reverse. A series of studies over the past 15 years has elucidated these underlying mechanisms. Together with other research, the interaction of environmental and genetic factors has been clarified. This knowledge has led to successful implementation of a national programme for remission of type 2 diabetes. This Review discusses the paucity of evidence for heterogeneity in causes of type 2 diabetes and summarises the in vivo pathophysiological changes, which cause this disease of overnutrition. Type 2 diabetes has a homogenous cause expressed in genetically heterogenous individuals.

Causal association of type 2 diabetes with central retinal artery occlusion: a Mendelian randomization study

Background

Central retinal artery occlusion (CRAO) is a medical condition characterized by sudden blockage of the central retinal artery, which leads to a significant and often irreversible loss of vision. Observational studies have indicated that diabetes mellitus is a risk factor for CRAO; however, there is no research on the causal relationship between diabetes mellitus, particularly type 2 diabetes, and CRAO. This study aimed to perform Mendelian randomization (MR) analysis to clarify the causal relationship between type 2 diabetes and CRAO.

Methods

Genetic variants associated with type 2 diabetes were selected from two different datasets. A recent genome-wide association study of CRAO conducted using the FinnGen database was used as the outcome data. A two-sample MR was performed to evaluate the causal relationship between type 2 diabetes and CRAO. Inverse variance weighting was the primary method, and MR-Egger, maximum likelihood, and median weighting were used as complementary methods. A multivariate MR (MVMR) analysis was performed to further evaluate the robustness of the results. Cochran's Q test, MR-Egger intercept test, and MR-PRESSO global test were used for the sensitivity analyses.

Results

Genetically predicted type 2 diabetes was causally associated with CRAO(odds ratio [OR] =2.108, 95% confidence interval [CI]: 1.221-3.638, P=7.423×10-3), which was consistent with the results from the validation dataset (OR=1.398, 95%CI: 1.015-1.925, P=0.040). The MVMR analysis suggested that type 2 diabetes may be an independent risk factor for CRAO (adjusted OR=1.696; 95%CI=1.150-2.500; P=7.655×10-3), which was assumed by the validation dataset (adjusted OR=1.356; 95%CI=1.015-1.812; P=0.039).

Conclusion

Our results show that genetically predicted type 2 diabetes may be causally associated with CRAO in European populations. This suggests that preventing and controlling type 2 diabetes may reduce the risk of CRAO.

Childhood Adiposity and Risk of Major Clinical Heart Diseases in Adulthood: A Mendelian Randomization Study

BACKGROUND

The causal relationship between childhood adiposity and adult risk of heart diseases has not been clearly demonstrated. This study aims to ascertain whether genetically predicted childhood body mass index (BMI) and childhood obesity are causally associated with adult coronary heart disease, myocardial infarction, heart failure, atrial fibrillation, hypertrophic cardiomyopathy, and pulmonary heart disease.

METHODS AND RESULTS

To investigate the causative relationships and underlying mechanisms between childhood adiposity and adult heart diseases, 3 main methods of Mendelian randomization were used: 2-sample Mendelian randomization, multivariable Mendelian randomization with controlling for several cardiometabolic risk variables, and mediation analysis. Every 1-SD rise in genetically predicted childhood body mass index was associated with 24% (odds ratio [OR], 1.24 [95% CI, 1.12-1.37]), 28% (OR, 1.28 [95% CI, 1.14-1.42]), 28% (OR, 1.28 [95% CI, 1.14-1.42]), and 27% (OR, 1.27 [95% CI, 1.04-1.49]) higher risk of coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation, respectively. Every 1-unit increase in log-odds in childhood obesity was associated with 11% (OR, 1.11 [95% CI, 1.06-1.16]), 14% (OR, 1.14 [95% CI, 1.04-1.23]), 10% (OR, 1.10 [95% CI, 1.03-1.18]), and 20% (OR, 1.20 [95% CI, 1.08-1.32]) higher risk of coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation, respectively. The link between childhood adiposity and adult heart diseases was found to be mediated by high-density lipoprotein cholesterol, triglyceride, hypertension, and type 2 diabetes.

CONCLUSIONS

Our findings support the causal relationships between childhood adiposity and risk of adult coronary heart disease, myocardial infarction, heart failure, and atrial fibrillation. Blood lipids, hypertension, and type 2 diabetes are factors that mediate the aforementioned associations.

Increased Genetic Risk for β-Cell Failure Is Associated With β-Cell Function Decline in People With Prediabetes

Partitioned polygenic scores (pPS) have been developed to capture pathophysiologic processes underlying type 2 diabetes (T2D). We investigated the association of T2D pPS with diabetes-related traits and T2D incidence in the Diabetes Prevention Program. We generated five T2D pPS (β-cell, proinsulin, liver/lipid, obesity, lipodystrophy) in 2,647 participants randomized to intensive lifestyle, metformin, or placebo arms. Associations were tested with general linear models and Cox regression with adjustment for age, sex, and principal components. Sensitivity analyses included adjustment for BMI. Higher β-cell pPS was associated with lower insulinogenic index and corrected insulin response at 1-year follow-up with adjustment for baseline measures (effect per pPS SD -0.04, P = 9.6 × 10-7, and -8.45 μU/mg, P = 5.6 × 10-6, respectively) and with increased diabetes incidence with adjustment for BMI at nominal significance (hazard ratio 1.10 per SD, P = 0.035). The liver/lipid pPS was associated with reduced 1-year baseline-adjusted triglyceride levels (effect per SD -4.37, P = 0.001). There was no significant interaction between T2D pPS and randomized groups. The remaining pPS were associated with baseline measures only. We conclude that despite interventions for diabetes prevention, participants with a high genetic burden of the β-cell cluster pPS had worsening in measures of β-cell function.

ARTICLE HIGHLIGHTS

Pathological evaluation of the pathogenesis of diabetes mellitus and diabetic peripheral neuropathy

Currently, there are more than 10 million patients with diabetes mellitus in Japan. Therefore, the need to explore the pathogenesis of diabetes and the complications leading to its cure is becoming increasingly urgent. Pathological examination of pancreatic tissues from patients with type 2 diabetes reveals a decrease in the volume of beta cells because of a combination of various stresses. In human type 2 diabetes, islet amyloid deposition is a unique pathological change characterized by proinflammatory macrophage (M1) infiltration into the islets. The pathological changes in the pancreas with islet amyloid were different according to clinical factors, which suggests that type 2 diabetes can be further subclassified based on islet pathology. On the other hand, diabetic peripheral neuropathy is the most frequent diabetic complication. In early diabetic peripheral neuropathy, M1 infiltration in the sciatic nerve evokes oxidative stress or attenuates retrograde axonal transport, as clearly demonstrated by in vitro live imaging. Furthermore, islet parasympathetic nerve density and beta cell volume were inversely correlated in type 2 diabetic Goto-Kakizaki rats, suggesting that diabetic peripheral neuropathy itself may contribute to the decrease in beta cell volume. These findings suggest that the pathogenesis of diabetes mellitus and diabetic peripheral neuropathy may be interrelated.

Loss of RREB1 reduces adipogenesis and improves insulin sensitivity in mouse and human adipocytes

There are multiple independent genetic signals at the Ras-responsive element binding protein 1 (RREB1) locus associated with type 2 diabetes risk, fasting glucose, ectopic fat, height, and bone mineral density. We have previously shown that loss of RREB1 in pancreatic beta cells reduces insulin content and impairs islet cell development and function. However, RREB1 is a widely expressed transcription factor and the metabolic impact of RREB1 loss in vivo remains unknown. Here, we show that male and female global heterozygous knockout (Rreb1 +/-) mice have reduced body length, weight, and fat mass on high-fat diet. Rreb1+/- mice have sex- and diet-specific decreases in adipose tissue and adipocyte size; male mice on high-fat diet had larger gonadal adipocytes, while males on standard chow and females on high-fat diet had smaller, more insulin sensitive subcutaneous adipocytes. Mouse and human precursor cells lacking RREB1 have decreased adipogenic gene expression and activated transcription of genes associated with osteoblast differentiation, which was associated with Rreb1 +/- mice having increased bone mineral density in vivo. Finally, human carriers of RREB1 T2D protective alleles have smaller adipocytes, consistent with RREB1 loss-of-function reducing diabetes risk.

Multi-omics characterization of type 2 diabetes associated genetic variation

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

HNF4A and HNF1A exhibit tissue specific target gene regulation in pancreatic beta cells and hepatocytes

HNF4A and HNF1A encode transcription factors that are important for the development and function of the pancreas and liver. Mutations in both genes have been directly linked to Maturity Onset Diabetes of the Young (MODY) and type 2 diabetes (T2D) risk. To better define the pleiotropic gene regulatory roles of HNF4A and HNF1A, we generated a comprehensive genome-wide map of their binding targets in pancreatic and hepatic cells using ChIP-Seq. HNF4A was found to bind and regulate known (ACY3, HAAO, HNF1A, MAP3K11) and previously unidentified (ABCD3, CDKN2AIP, USH1C, VIL1) loci in a tissue-dependent manner. Functional follow-up highlighted a potential role for HAAO and USH1C as regulators of beta cell function. Unlike the loss-of-function HNF4A/MODY1 variant I271fs, the T2D-associated HNF4A variant (rs1800961) was found to activate AKAP1, GAD2 and HOPX gene expression, potentially due to changes in DNA-binding affinity. We also found HNF1A to bind to and regulate GPR39 expression in beta cells. Overall, our studies provide a rich resource for uncovering downstream molecular targets of HNF4A and HNF1A that may contribute to beta cell or hepatic cell (dys)function, and set up a framework for gene discovery and functional validation.

Tirzepatide Improved Markers of Islet Cell Function and Insulin Sensitivity in People With T2D (SURPASS-2)

CONTEXT

In previous SURPASS studies tirzepatide reduced hemoglobin glycated A1c (HbA1c) and body weight and improved markers of insulin sensitivity and β-cell function to a greater extent than comparators.

OBJECTIVE

Explore changes in biomarkers of β-cell function and insulin sensitivity and in efficacy profiles in baseline biomarker quartile analyses with tirzepatide compared to semaglutide.

DESIGN

Post hoc analysis of SURPASS-2 phase 3 trial (participants randomly assigned to receive weekly subcutaneous tirzepatide or semaglutide for 40 weeks).

SETTING

Post hoc analysis of 128 sites in 8 countries.

PARTICIPANTS

A total of 1879 participants with type 2 diabetes.

INTERVENTIONS

Once-weekly tirzepatide (5, 10, 15 mg) or semaglutide 1 mg.

MAIN OUTCOMES MEASURES

Change in homeostatic model assessment indices for pancreatic β-cell function (HOMA2-B) and for insulin resistance (HOMA2-IR), fasting glucagon, fasting C-peptide, and fasting insulin.

RESULTS

At week 40, a greater increase in HOMA2-B was seen with tirzepatide (5, 10, 15 mg) doses (96.9-120.4%) than with semaglutide 1 mg (84.0%) (P < .05). There was a greater reduction in HOMA2-IR with all doses of tirzepatide (15.5%-24.0%) than with semaglutide 1 mg (5.1%) (P < .05). Tirzepatide 10 and 15 mg resulted in a significant reduction in both fasting C-peptide (5.2%-6.0%) and fasting glucagon (53.0%-55.3%) compared with an increase of C-peptide (3.3%) and a reduction of glucagon (47.7%) with semaglutide 1 mg (P < .05). HbA1c and body weight reductions were greater with all tirzepatide doses than semaglutide within each HOMA2-B and HOMA2-IR baseline quartile.

CONCLUSION

In this post hoc analysis, improvements in HbA1c and weight loss were consistent and significantly higher with tirzepatide, regardless of baseline β-cell function and insulin resistance, compared with semaglutide.

Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials

AIMS

To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability.

METHODS

We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta-regression analyses were performed with respect to variability of body weight after treatment and potential predictors.

RESULTS

A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta-regression model, the difference in body weight log(SD) was -0.026 (95% confidence interval -0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo).

CONCLUSIONS

We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting.

Novel insights into the complex interplay of immune dysregulation and inflammatory biomarkers in preeclampsia and fetal growth restriction: A two-step Mendelian randomization analysis

Background

The relationship between genetic immune dysregulation and the occurrence of preeclampsia (PE) or PE with fetal growth restriction (PE with FGR) has yielded inconsistent findings, and the underlying mediators of this association remain elusive. We aimed to explore the causal impact of genetic immune dysregulation on the risk of PE or PE with FGR and to elucidate the role of specific transcriptomes in mediating this relationship.

Methods

A two-step Mendelian randomization (MR) analysis was performed to explore the link between immune dysregulation and PE or PE with FGR, as well as to identify potential inflammatory biomarkers that act as mediators. GWAS summary data for outcomes were obtained from the FinnGen dataset. The analyses encompassed five systemic immune-associated diseases, four chronic genital inflammatory diseases, and thirty-one inflammatory biomarkers. Summary-data-based MR (SMR) and HEIDI analysis were conducted to test whether the effect size of single nucleotide polymorphisms (SNPs) on outcomes was mediated by the expression of immune-associated genes.

Results

The primary univariable analysis revealed a significant positive correlation between systemic lupus erythematosus (SLE), type 1 diabetes (T1D), type 2 diabetes (T2D), and rheumatoid arthritis (RA) with the risk of PE or PE with FGR. Surprisingly, a counterintuitive finding showed a significant negative association between endometriosis of pelvic peritoneum (EMoP) and the risk of PE with FGR. None of the inflammatory factors had a causal relationship with PE or PE with FGR. However, there was a significant association between lymphocyte count and the risk of PE with FGR. Within the lymphocyte subset, both the proportion of Natural Killer (NK) cells and absolute counts of naïve CD4+ T cells demonstrated significant effects on the risk of PE with FGR. Two-step MR analysis underscored the genetically predicted lymphocyte count as a significant mediator between T1D and PE with FGR. Additionally, SMR analysis indicated the potential involvement of SH2B3 in the occurrence of PE with FGR.

Conclusions

Our findings provided substantial evidence of the underlying causal relationship between immune dysregulation and PE or PE with FGR and some of these diseases proved to accelerate immune cells disorders and then contribute to the risk of incident PE or PE with FGR.

Differential ischemic stroke risk linked to novel subtypes of type 2 diabetes: insights from a Mendelian randomization analysis

PURPOSE

This study employs a two-sample Mendelian randomization (MR) approach to investigate the variation in ischemic stroke risk across novel subtypes of adult-onset type 2 diabetes.

METHODS

Leveraging pooled genome-wide association study (GWAS) data from the Swedish ANDIS cohort, we explored the association of four newly identified type 2 diabetes subtypes-severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD)-with ischemic stroke risk. The outcome data for ischemic stroke and its three subtypes (large artery, cardioembolic, and small vessel stroke) were sourced from the MEGASTROKE Consortium. Our analysis applied multiple MR methods, focusing on the inverse-variance weighted (IVW) technique, complemented by thorough sensitivity analyses to examine heterogeneity and potential horizontal pleiotropy.

RESULTS

Our findings reveal a significant causal relationship between the SIDD subtype and small vessel stroke (OR = 1.06, 95% CI: 1.01-1.11, p = 0.025), while no causal associations were observed for SIRD with any stroke subtype. MOD was causally linked to small vessel stroke (OR = 1.07, 95% CI: 1.02-1.12, p = 0.004) and large artery stroke (OR = 1.07, 95% CI: 1.01-1.13, p = 0.015). Similarly, MARD showed a causal relationship with small vessel stroke (OR = 1.09, 95% CI: 1.03-1.16, p = 0.006) and overall ischemic stroke risk (OR = 1.04, 95% CI: 1.01-1.08, p = 0.010).

CONCLUSIONS

Our study highlights distinct causal links between specific type 2 diabetes subtypes and ischemic stroke risks, emphasizing the importance of subtype-specific prevention and treatment strategies.

Causal relationship between type 2 diabetes mellitus and aortic dissection: insights from two-sample Mendelian randomization and mediation analysis

Objective

Some evidence suggests a reduced prevalence of type 2 diabetes mellitus (T2DM) in patients with aortic dissection (AD), a catastrophic cardiovascular illness, compared to general population. However, the conclusions were inconsistent, and the causal relationship between T2DM and AD remains unclear.

Methods

In this study, we aimed to explore the causal relationship between T2DM and AD using bidirectional Mendelian randomization (MR) analysis. Mediation MR analysis was conducted to explore and quantify the possible mediation effects of 1400 metabolites in T2DM and AD.

Results

The results of 26 datasets showed no causal relationship between T2DM and AD (P>0.05). Only one dataset (ebi-a-GCST90006934) showed that T2DM was a protective factor for AD (I9-AORTDIS) (OR=0.815, 95%CI: 0.692-0.960, P=0.014), and did not show horizontal pleiotropy (P=0.808) and heterogeneity (P=0.525). Vanillic acid glycine plays a mediator in the causal relationship between T2DM and AD. The mediator effect for vanillic acid glycine levels was -0.023 (95%CI: -0.066-0.021).

Conclusion

From the perspective of MR analysis, there might not be a causal relationship between T2DM and AD, and T2DM might not be a protective factor for AD. If a causal relationship does exist between T2DM and AD, with T2DM serving as a protective factor, vanillic acid glycine may act as a mediator and enhance such a protective effect.

Functional characterization of HNF4A gene variants identify promoter and cell line specific transactivation effects

Hepatocyte nuclear factor-4 alpha (HNF-4A) regulates genes with roles in glucose metabolism and β-cell development. Although pathogenic HNF4A variants are commonly associated with maturity-onset diabetes of the young (MODY1; HNF4A-MODY), rare phenotypes also include hyperinsulinemic hypoglycemia, renal Fanconi syndrome and liver disease. While the association of rare functionally damaging HNF1A variants with HNF1A-MODY and type 2 diabetes is well established owing to robust functional assays, the impact of HNF4A variants on HNF-4A transactivation in tissues including the liver and kidney is less known, due to lack of similar assays. Our aim was to investigate the functional effects of seven HNF4A variants, located in the HNF-4A DNA binding domain and associated with different clinical phenotypes, by various functional assays and cell lines (transactivation, DNA binding, protein expression, nuclear localization) and in silico protein structure analyses. Variants R85W, S87N and R89W demonstrated reduced DNA binding to the consensus HNF-4A binding elements in the HNF1A promoter (35, 13 and 9%, respectively) and the G6PC promoter (R85W ~10%). While reduced transactivation on the G6PC promoter in HepG2 cells was shown for S87N (33%), R89W (65%) and R136W (35%), increased transactivation by R85W and R85Q was confirmed using several combinations of target promoters and cell lines. R89W showed reduced nuclear levels. In silico analyses supported variant induced structural impact. Our study indicates that cell line specific functional investigations are important to better understand HNF4A-MODY genotype-phenotype correlations, as our data supports ACMG/AMP interpretations of loss-of-function variants and propose assay-specific HNF4A control variants for future functional investigations.

Genetic determinants of plasma protein levels in the Estonian population

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

Association of birth weight with type 2 diabetes mellitus and the mediating role of fatty acids traits: a two-step mendelian randomization study

BACKGROUND

Observational studies have suggested an association between birth weight and type 2 diabetes mellitus, but the causality between them has not been established. We aimed to obtain the causal relationship between birth weight with T2DM and quantify the mediating effects of potential modifiable risk factors.

METHODS

Two-step, two-sample Mendelian randomization (MR) techniques were applied using SNPs as genetic instruments for exposure and mediators. Summary data from genome-wide association studies (GWAS) for birth weight, T2DM, and a series of fatty acids traits and their ratios were leveraged. The inverse variance weighted (IVW) method was the main analysis approach. In addition, the heterogeneity test, horizontal pleiotropy test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test, and leave-one-out analysis were carried out to assess the robustness.

RESULTS

The IVW method showed that lower birth weight raised the risk of T2DM (β: -1.113, 95% CI: -1.573 ∼ -0.652). Two-step MR identified 4 of 17 candidate mediators partially mediating the effect of lower birth weight on T2DM, including ratio of polyunsaturated fatty acids to monounsaturated fatty acids (proportion mediated: 7.9%), ratio of polyunsaturated fatty acids to total fatty acids (7.2%), ratio of omega-6 fatty acids to total fatty acids (8.1%) and ratio of linoleic acid to total fatty acids ratio (6.0%).

CONCLUSIONS

Our findings supported a potentially causal effect of birth weight against T2DM with considerable mediation by modifiable risk factors. Interventions that target these factors have the potential to reduce the burden of T2DM attributable to low birth weight.

Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies

Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia.

PURPOSE

Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory.

METHODS

Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD.

RESULTS

After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect.

CONCLUSION

No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.

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.

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.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

Investigation of the causal relationship between inflammatory bowel disease and type 2 diabetes mellitus: a Mendelian randomization study

Background: Type 2 diabetes mellitus (T2DM) and inflammatory bowel disease (IBD) have been associated, according to various epidemiological research. This study uses Mendelian randomization (MR) to investigate the causal link between T2DM and IBD. Methods: To investigate the causal relationship between IBD and T2DM risk using European population data from the genome-wide association study (GWAS) summary datasets, we constructed a two-sample MR study to evaluate the genetically predicted impacts of liability towards IBD outcomes on T2DM risk. As instrumental variables (IVs), we chose 26 single nucleotide polymorphisms (SNPs) associated with IBD exposure data. The European T2DM GWAS data was obtained from the IEU OpenGWAS Project database, which contains 298,957 cases as the outcome data. The causal relationship between T2DM and IBD using a reverse MR analysis was also performed. Results: The two-sample MR analysis, with the Bonferroni adjustment for multiple testing, revealed that T2DM risk in Europeans is unaffected by their IBD liability (odds ratio (OR): 0.950-1.066, 95% confidence interval (CI): 0.885-1.019, p = 0.152-0.926). The effects of liability to T2DM on IBD were not supported by the reverse MR analysis either (OR: 0.739-1.131, 95% confidence interval (CI): 0.651-1.100, p = 0.058-0.832). MR analysis of IBS on T2DM also have no significant causal relationship (OR: 0.003-1.007, 95% confidence interval (CI): 1.013-5.791, p = 0.069-0.790). FUMA precisely mapped 22 protein-coding genes utilizing significant SNPs of T2DM acquired from GWAS. Conclusion: The MR study showed that the existing evidence did not support the significant causal effect of IBD on T2DM, nor did it support the causal impact of T2DM on IBD.

Sick individuals, sick populations revisited: a test of the Rose hypothesis for type 2 diabetes disparities

Introduction

The Rose hypothesis predicts that since genetic variation is greater within than between populations, genetic risk factors will be associated with individuals' risk of disease but not population disparities, and since socioenvironmental variation is greater between than within populations, socioenvironmental risk factors will be associated with population disparities but not individuals' disease risk.

Methods

We used the UK Biobank to test the Rose hypothesis for type 2 diabetes (T2D) ethnic disparities in the UK. Our cohort consists of 26 912 participants from Asian, black and white ethnic groups. Participants were characterised as T2D cases or controls based on the presence or absence of T2D diagnosis codes in electronic health records. T2D genetic risk was measured using a polygenic risk score (PRS), and socioeconomic deprivation was measured with the Townsend Index (TI). The variation of genetic (PRS) and socioeconomic (TI) risk factors within and between ethnic groups was calculated using analysis of variance. Multivariable logistic regression was used to associate PRS and TI with T2D cases, and mediation analysis was used to analyse the effect of PRS and TI on T2D ethnic group disparities.

Results

T2D prevalence differs for Asian 23.34% (OR=5.14, CI=4.68 to 5.65), black 16.64% (OR=3.81, CI=3.44 to 4.22) and white 7.35% (reference) ethnic groups in the UK. Both genetic and socioenvironmental T2D risk factors show greater within (w) than between (b) ethnic group variation: PRS w=64.60%, b=35.40%; TI w=71.18%, b=28.19%. Nevertheless, both genetic risk (PRS OR=1.96, CI=1.87 to 2.07) and socioeconomic deprivation (TI OR=1.09, CI=1.08 to 1.10) are associated with T2D individual risk and mediate T2D ethnic disparities (Asian PRS=22.5%, TI=9.8%; black PRS=32.0%, TI=25.3%).

Conclusion

A relative excess of within-group versus between-group variation does not preclude T2D risk factors from contributing to T2D ethnic disparities. Our results support an integrative approach to health disparities research that includes both genetic and socioenvironmental risk factors.

The first exome wide association study in Tunisia: identification of candidate loci and pathways with biological relevance for type 2 diabetes

Introduction

Type 2 diabetes (T2D) is a multifactorial disease involving genetic and environmental components. Several genome-wide association studies (GWAS) have been conducted to decipher potential genetic aberrations promoting the onset of this metabolic disorder. These GWAS have identified over 400 associated variants, mostly in the intronic or intergenic regions. Recently, a growing number of exome genotyping or exome sequencing experiments have identified coding variants associated with T2D. Such studies were mainly conducted in European populations, and the few candidate-gene replication studies in North African populations revealed inconsistent results. In the present study, we aimed to discover the coding genetic etiology of T2D in the Tunisian population.

Methods

We carried out a pilot Exome Wide Association Study (EWAS) on 50 Tunisian individuals. Single variant analysis was performed as implemented in PLINK on potentially deleterious coding variants. Subsequently, we applied gene-based and gene-set analyses using MAGMA software to identify genes and pathways associated with T2D. Potential signals were further replicated in an existing large in-silico dataset, involving up to 177116 European individuals.

Results

Our analysis revealed, for the first time, promising associations between T2D and variations in MYORG gene, implicated in the skeletal muscle fiber development. Gene-set analysis identified two candidate pathways having nominal associations with T2D in our study samples, namely the positive regulation of neuron apoptotic process and the regulation of mucus secretion. These two pathways are implicated in the neurogenerative alterations and in the inflammatory mechanisms of metabolic diseases. In addition, replication analysis revealed nominal associations of the regulation of beta-cell development and the regulation of peptidase activity pathways with T2D, both in the Tunisian subjects and in the European in-silico dataset.

Conclusions

The present study is the first EWAS to investigate the impact of single genetic variants and their aggregate effects on T2D risk in Africa. The promising disease markers, revealed by our pilot EWAS, will promote the understanding of the T2D pathophysiology in North Africa as well as the discovery of potential treatments.

Type 2 diabetes mellitus and the risk of male infertility: a Mendelian randomization study

Objective

To assess the causal effect of type 2 diabetes mellitus (T2DM) on male infertility (MI) and erectile dysfunction (ED) by Mendelian randomization (MR) analysis.

Methods

Data for T2DM, MI, and ED were obtained from genome-wide association studies (GWAS) involving 298, 957, 73, 479, and 223, 805 Europeans, respectively. We performed univariate MR analysis using MR Egger, Weighted median (WM) and Inverse variance weighted (IVW) methods to assess causal effects among the three. Through the Genotype Tissue Expression (GTEx) database, single-nucleotide polymorphisms (SNPs) that affect the expression levels of T2DM-related genes were located using expression quantitative trait loci (eQTL).

Results

MR analysis showed a significant causal relationship between T2DM and ED (WM, OR: 1.180, 95%CI: 1.010-1.378, P = 0.037; IVW, OR: 1.190, 95%CI: 1.084-1.300, P < 0.001). There is also a significant causal relationship between T2DM and MI (MR Egger, OR: 0.549, 95%CI: 0.317-0.952, P = 0.037; WM, OR: 0.593, 95%CI: 0.400, P = 0.010; IVW, OR: 0.767, 95%CI: 0.600-0.980, P = 0.034). ED may not cause MI (P > 0.05). We also found that rs6585827 corresponding to the PLEKHA1 gene associated with T2DM is an eQTL variant affecting the expression of this gene.

Conclusion

T2DM has a direct causal effect on ED and MI. The level of PLEKHA1 expression suppressed by rs6585827 is potentially associated with a lower risk of T2DM.

Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-β and ISIMatusda in the middle-aged T2D individuals

This study aims to investigate the correlations between islet function/ insulin resistance and serum lipid levels, as well as to assess whether the strength of such correlations is affected by the GCKR rs1260326 variant in healthy and T2D individuals. We performed an oral glucose tolerance test (OGTT) on 4889 middle-aged adults, including 3135 healthy and 1754 T2D individuals from the REACTION population study in the Nanjing region. We also measured their serum lipid levels and genotyped for rs1260326. We found that serum high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels were independently correlated with indexes of islet function (HOMA-β and IGI [insulinogenic index]) and insulin resistance (HOMO-IR and ISIMatsuda) in both healthy and T2D individuals. The correlations were significantly decreased in T2D individuals, with significant heterogeneities compared to healthy controls (I2 > 75%, Phet < 0.05). Although no correlation was observed between serum total cholesterol (TC) level and islet function/ insulin resistance in healthy controls, significant correlations were found in T2D individuals, with significant heterogeneity to healthy controls in the correlation with ISIMatsuda(I2 = 85.3%, Phet = 0.009). Furthermore, we found significant interactions of the GCKR rs1260326 variant for the correlations between serum HDL cholesterol and HOMA-β/ISIMatsuda in T2D subjects (P = 0.015 and 0.038, respectively). These findings illustrate that distinct correlations between serum lipid levels and islet function/ insulin resistance occurred in T2D subjects compared to healthy individuals. Common gene variants, such as rs1260326, might interact substantially when studied in specific populations, especially T2D disease status.

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.

Causal relationships between type 2 diabetes, glycemic traits and keratoconus

Purpose

The relationship between diabetes mellitus and keratoconus remains controversial. This study aimed to assess the potential causal relationships among type 2 diabetes, glycemic traits, and the risk of keratoconus.

Methods

We used a two-sample Mendelian randomization (MR) design based on genome-wide association summary statistics. Fasting glucose, proinsulin levels, adiponectin, hemoglobin A1c (HbA1c) and type 2 diabetes with and without body mass index (BMI) adjustment were used as exposures and keratoconus was used as the outcome. MR analysis was performed using the inverse-variance weighted method, MR-Egger regression method, weighted-mode method, weighted median method and the MR-pleiotropy residual sum and outlier test (PRESSO).

Results

Results showed that genetically predicted lower fasting glucose were significantly associated with a higher risk of keratoconus [IVW: odds ratio (OR) = 0.382; 95% confidence interval (CI) = 0.261-0.560; p = 8.162 × 10-7]. Genetically predicted lower proinsulin levels were potentially linked to a higher risk of keratoconus (IVW: OR = 0.739; 95% CI = 0.568-0.963; p = 0.025). In addition, genetically predicted type 2 diabetes negatively correlated with keratoconus (IVW: BMI-unadjusted: OR = 0.869; 95% CI = 0.775-0.974, p = 0.016; BMI-adjusted: OR = 0.880, 95% CI = 0.789-0.982, p = 0.022). These associations were further corroborated by the evidence from all sensitivity analyses.

Conclusion

These findings provide genetic evidence that higher fasting glucose levels are associated with a lower risk of keratoconus. However, further studies are required to confirmed this hypothesis and to understand the mechanisms underlying this putative causative relationship.

Precision medicine for cardiometabolic disease: a framework for clinical translation

Cardiometabolic disease is a major threat to global health. Precision medicine has great potential to help to reduce the burden of this common and complex disease cluster, and to enhance contemporary evidence-based medicine. Its key pillars are diagnostics; prediction (of the primary disease); prevention (of the primary disease); prognosis (prediction of complications of the primary disease); treatment (of the primary disease or its complications); and monitoring (of risk exposure, treatment response, and disease progression or remission). To contextualise precision medicine in both research and clinical settings, and to encourage the successful translation of discovery science into clinical practice, in this Series paper we outline a model (the EPPOS model) that builds on contemporary evidence-based approaches; includes precision medicine that improves disease-related predictions by stratifying a cohort into subgroups of similar characteristics, or using participants' characteristics to model treatment outcomes directly; includes personalised medicine with the use of a person's data to objectively gauge the efficacy, safety, and tolerability of therapeutics; and subjectively tailors medical decisions to the individual's preferences, circumstances, and capabilities. Precision medicine requires a well functioning system comprised of multiple stakeholders, including health-care recipients, health-care providers, scientists, health economists, funders, innovators of medicines and technologies, regulators, and policy makers. Powerful computing infrastructures supporting appropriate analysis of large-scale, well curated, and accessible health databases that contain high-quality, multidimensional, time-series data will be required; so too will prospective cohort studies in diverse populations designed to generate novel hypotheses, and clinical trials designed to test them. Here, we carefully consider these topics and describe a framework for the integration of precision medicine in cardiometabolic disease.

Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

Background

Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways.

Methods

To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses.

Results

Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology.

Conclusions

Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Multiple genetic variants at the SLC30A8 locus affect local super-enhancer activity and influence pancreatic β-cell survival and function

Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, combined allele-specific expression (cASE) analysis in human islets revealed multiple variants that influence SLC30A8 expression. Epigenomic mapping identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighbouring genes. Deletions of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-βH3 cells lowered the expression of SLC30A8 and several neighbouring genes, and improved insulin secretion. Whilst down-regulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21 or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.