The trans-ancestral genomic architecture of glycemic traits

Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer's disease at CPT1A locus

BACKGROUND

Insulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD.

METHODS

We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P < 1.1 × 10-7) and evaluated their association with neurological traits in participants from the FHS (N = 3040) and the Religious Orders Study/Memory and Aging Project (ROSMAP, N = 707). DNA methylation profiles were measured in blood (FHS) or dorsolateral prefrontal cortex (ROSMAP) using the Illumina HumanMethylation450 BeadChip. Linear regressions (ROSMAP) or mixed-effects models accounting for familial relatedness (FHS) adjusted for age, sex, cohort, self-reported race, batch, and cell type proportions were used to assess associations between DNA methylation and neurological traits accounting for multiple testing.

RESULTS

We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10-11 and P = 9.0 × 10-8), larger total brain volumes (P = 0.03 and P = 9.7 × 10-4), and smaller log lateral ventricular volumes (P = 0.07 and P = 0.03). In ROSMAP, higher levels of brain DNA methylation at the same two CPT1A markers were associated with greater risk of cognitive impairment (P = 0.005 and P = 0.02) and higher AD-related indices (CERAD score: P = 5 × 10-4 and 0.001; Braak stage: P = 0.004 and P = 0.01).

CONCLUSIONS

Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus.

Relationships between body fat distribution and metabolic syndrome traits and outcomes: A mendelian randomization study

BACKGROUND

Obesity is a complex, multifactorial disease associated with substantial morbidity and mortality worldwide. Although it is frequently assessed using BMI, many epidemiological studies have shown links between body fat distribution and obesity-related outcomes. This study examined the relationships between body fat distribution and metabolic syndrome traits using Mendelian Randomization (MR).

METHODS/FINDINGS

Genetic variants associated with visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and gluteofemoral adipose tissue (GFAT), as well as their relative ratios, were identified from a genome wide association study (GWAS) performed with the United Kingdom BioBank. GWAS summary statistics for traits and outcomes related to metabolic syndrome were obtained from the IEU Open GWAS Project. Two-sample MR and BMI-controlled multivariable MR (MVMR) were performed to examine relationships between each body fat measure and ratio with the outcomes. Increases in absolute GFAT were associated with a protective cardiometabolic profile, including lower low density lipoprotein cholesterol (β: -0.19, [95% CI: -0.28, -0.10], p < 0.001), higher high density lipoprotein cholesterol (β: 0.23, [95% CI: 0.03, 0.43], p = 0.025), lower triglycerides (β: -0.28, [95% CI: -0.45, -0.10], p = 0.0021), and decreased systolic (β: -1.65, [95% CI: -2.69, -0.61], p = 0.0019) and diastolic blood pressures (β: -0.95, [95% CI: -1.65, -0.25], p = 0.0075). These relationships were largely maintained in BMI-controlled MVMR analyses. Decreases in relative GFAT were linked with a worse cardiometabolic profile, with higher levels of detrimental lipids and increases in systolic and diastolic blood pressures.

CONCLUSION

A MR analysis of ASAT, GFAT, and VAT depots and their relative ratios with metabolic syndrome related traits and outcomes revealed that increased absolute and relative GFAT were associated with a favorable cardiometabolic profile independently of BMI. These associations highlight the importance of body fat distribution in obesity and more precise means to categorize obesity beyond BMI.

The association of metabolic syndrome with rotator cuff tendinopathy: a two-sample Mendelian randomization study

BACKGROUND

Observational research reported the underlying correlation of metabolic syndrome (MetS) and its components with rotator cuff tendinopathy (RCT), but their causality remained unclear. This study aimed to investigate whether genetically predicted MetS was related to the risk of RCT.

METHODS

Both univariable and multivariable Mendelian randomization (MR) analysis was applied using summary-level data from the most comprehensive genome-wide association studies to estimate the associations of MetS and its component with RCT, with the inverse variance weighted (IVW) as the primary method, and the method of Causal Analysis Using Summary Effect Estimates (CAUSE) as a supplement for false positives detection. The mediation analysis was furtherly used for the assessment of direct and indirect effects.

RESULTS

Univariable analysis revealed that genetically predicted MetS (OR: 1.0793; 95% CI 1.0311 to 1.1297), body mass index (BMI) (OR 1.2239; 95% CI 1.1357 to 1.3189), and waist circumference (WAC) (OR 1.3177; 95% CI 1.2015 to 1.4451) had a significant positive association with the risk of RCT. Triglycerides and systolic blood pressure were suggestively associated with RCT risk. These associations were also identified by CAUSE. There was independent causality of BMI (OR: 1.1806; 95% CI 1.0788 to 1.2920) and WAC (OR 1.3716; 95% CI 1.2076 to 1.5580) on RCT after adjustment for confounders. No mediator was found in the causal associations.

CONCLUSION

Our study revealed the genetic causality of MetS and its components, especially BMI and WAC, with RCT risk. Early prevention and diagnosis of excess central adiposity contributing to MetS are significant in the RCT risk management.

Apolipoprotein B and interleukin 1 receptor antagonist: reversing the risk of coronary heart disease

Aims

Epidemiological evidence for the link of interleukin 1 (IL-1) and its inhibition with cardiovascular diseases (CVDs) remains controversial. We aim to investigate the cardiovascular effects of IL-1 receptor antagonist (IL-1Ra) and underlying mechanisms.

Methods

Genetic variants identified from a genome-wide association study involving 30,931 individuals were used as instrumental variables for the serum IL-1Ra concentrations. Genetic associations with CVDs and cardiometabolic risk factors were obtained from international genetic consortia. Inverse-variance weighted method was utilized to derive effect estimates, while supplementary analyses employing various statistical approaches.

Results

Genetically determined IL-1Ra level was associated with increased risk of coronary heart disease (CHD; OR, 1.07; 95% CI: 1.03-1.17) and myocardial infarction (OR, 1.13; 95% CI: 1.04-1.21). The main results remained consistent in supplementary analyses. Besides, IL-1Ra was associated with circulating levels of various lipoprotein lipids, apolipoproteins and fasting glucose. Interestingly, observed association pattern with CHD was reversed when adjusting for apolipoprotein B (OR, 0.84; 95%CI: 0.71-0.99) and slightly attenuated on accounting for other cardiometabolic risk factors. Appropriate lifestyle intervention was found to lower IL-1Ra concentration and mitigate the heightened CHD risk it posed.

Conclusion

Apolipoprotein B represents the key driver, and a potential target for reversal of the causal link between serum IL-1Ra and increased risk of CHD/MI. The combined therapy involving IL-1 inhibition and lipid-modifying treatment aimed at apolipoprotein B merit further exploration.

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.

An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals

Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.

Birth Weight, Cardiometabolic Factors, and Coronary Heart Disease: A Mendelian Randomization Study

CONTEXT

Observational studies have shown associations of birth weight (BW) with coronary heart disease (CHD), but results are inconsistent and do not distinguish the fetal or maternal effect of BW.

OBJECTIVE

This study aims to explore the causal association between BW and CHD, analyze the fetal and maternal contribution, and quantify mediating effects of cardiometabolic factors.

METHODS

Genetic variants from genome-wide association study summary-level data of own BW (N = 298 142), offspring BW (N = 210 267 mothers), and 16 cardiometabolic (anthropometric, glycemic, lipidemic, and blood pressure) factors were extracted as instrumental variables. We used two-sample Mendelian randomization study (MR) to estimate the causal effect of BW on CHD (60 801 cases and 123 504 controls from mixed ancestry) and explore the fetal and maternal contributions. Mediation analyses were conducted to analyze the potential mediating effects of 16 cardiometabolic factors using two-step MR.

RESULTS

Inverse variance weighted analysis showed that lower BW raised the CHD risk (β -.30; 95% CI: -0.40, -0.20) and consistent results were observed in fetal-specific/maternal-specific BW. We identified 5 mediators in the causal pathway from BW to CHD, including body mass index-adjusted hip circumference, triglycerides, fasting insulin, diastolic blood pressure, and systolic blood pressure (SBP), with mediated proportion ranging from 7.44% for triglycerides to 27.75% for SBP. Causality between fetal-specific and maternal-specific BW and CHD was mediated by glycemic factors and SBP, respectively.

CONCLUSION

Our findings supported that lower BW increased CHD risk and revealed that fetal-specific and maternal-specific BW may both contribute to this effect. The causality between BW and CHD was mediated by several cardiometabolic factors.

Exhaustive Variant Interaction Analysis using Multifactor Dimensionality Reduction

One of the main goals of human genetics is to understand the connections between genomic variation and the predisposition to develop a complex disorder. These disease-variant associations are usually studied in a single independent manner, disregarding the possible effect derived from the interaction between genomic variants. In particular, in a background of complex diseases, these interactions can be directly linked to the disorder and may play an important role in disease development. Although their study has been suggested to help to complete the understanding of the genetic bases of complex diseases, this still represents a big challenge due to large computing demands. Here, we have taken advantage of High-Performance Computing technologies to tackle this problem using a combination of machine learning methods and statistical approaches. As a result, we have created a containerized framework that uses Multifactor Dimensionality Reduction to detect pairs of variants associated with Type 2 Diabetes (T2D). This methodology has been tested in the Northwestern University NUgene project cohort using a dataset of 1,883,192 variant pairs with a certain degree of association with T2D. Out of the pairs studied, we have identified 104 significant pairs, two of which exhibit a potential functional relationship with T2D.

Genomic insights into the comorbidity between type 2 diabetes and schizophrenia

Multimorbidity represents an increasingly important public health challenge with far-reaching implications for health management and policy. Mental health and metabolic diseases have a well-established epidemiological association. In this study, we investigate the genetic intersection between type 2 diabetes and schizophrenia. We use Mendelian randomization to examine potential causal relationships between the two conditions and related endophenotypes. We report no compelling evidence that type 2 diabetes genetic liability potentially causally influences schizophrenia risk and vice versa. Our findings show that increased body mass index (BMI) has a protective effect against schizophrenia, in contrast to the well-known risk-increasing effect of BMI on type 2 diabetes risk. We identify evidence of colocalization of association signals for these two conditions at 11 genomic loci, six of which have opposing directions of effect for type 2 diabetes and schizophrenia. To elucidate these colocalizing signals, we integrate multi-omics data from bulk and single-cell gene expression studies, along with functional information. We identify high-confidence effector genes and find that they are enriched for homeostasis and lipid-related pathways. We also highlight drug repurposing opportunities including N-methyl-D-aspartate (NMDA) receptor antagonists. Our findings provide insights into shared biological mechanisms for type 2 diabetes and schizophrenia, highlighting common factors that influence the risk of the two conditions in opposite directions and shedding light on the complex nature of this comorbidity.

Type 1 diabetes, glycemic traits, and risk of dental caries: a Mendelian randomization study

Background: Regarding past epidemiological studies, there has been disagreement over whether type 1 diabetes (T1DM) is one of the risk factors for dental caries. The purpose of this study was to determine the causative links between genetic susceptibility to T1DM, glycemic traits, and the risk of dental caries using Mendelian randomization (MR) approaches. Methods: Summary-level data were collected on genome-wide association studies (GWAS) of T1DM, fasting glucose (FG), glycated hemoglobin (HbA1c), fasting insulin (FI), and dental caries. MR was performed using the inverse-variance weighting (IVW) method, and sensitivity analyses were conducted using the MR-Egger method, weighted median, weighted mode, replication cohort, and multivariable MR conditioning on potential mediators. Results: The risk of dental caries increased as a result of genetic susceptibility to T1DM [odds ratio (OR) = 1.044; 95% confidence interval (CI) = 1.015-1.074; p = 0.003], with consistent findings in the replication cohort. The relationship between T1DM and dental caries was stable when adjusted for BMI, smoking, alcohol intake, and type 2 diabetes (T2DM) in multivariable MR. However, no significant correlations between the risk of dental caries and FG, HbA1c, or FI were found. Conclusion: These results indicate that T1DM has causal involvement in the genesis of dental caries. Therefore, periodic reinforcement of oral hygiene instructions must be added to the management and early multidisciplinary intervention of T1DM patients, especially among adolescents and teenagers, who are more susceptible to T1DM.

A causal relationship between antioxidants, minerals and vitamins and metabolic syndrome traits: a Mendelian randomization study

BACKGROUND

The available evidence regarding the association of antioxidants, minerals, and vitamins with the risk of metabolic syndrome (MetS) traits is currently limited and inconsistent. Therefore, the purpose of this Mendelian randomization (MR) study was to investigate the potential causal relationship between genetically predicted antioxidants, minerals, and vitamins, and MetS.

METHODS

In this study, we utilized genetic variation as instrumental variable (IV) to capture exposure data related to commonly consumed dietary nutrients, including antioxidants (β-carotene, lycopene, and uric acid), minerals (copper, calcium, iron, magnesium, phosphorus, zinc, and selenium), and vitamins (folate, vitamin A, B6, B12, C, D, E, and K1). The outcomes of interest, namely MetS (n = 291,107), waist circumference (n = 462,166), hypertension (n = 463,010), fasting blood glucose (FBG) (n = 281,416), triglycerides (n = 441,016), and high-density lipoprotein cholesterol (HDL-C) (n = 403,943), were assessed using pooled data obtained from the most comprehensive genome-wide association study (GWAS) available. Finally, we applied the inverse variance weighting method as the result and conducted a sensitivity analysis for further validation.

RESULTS

Genetically predicted higher iron (OR = 1.070, 95% CI 1.037-1.105, P = 2.91E-05) and magnesium levels (OR = 1.130, 95% CI 1.058-1.208, P = 2.80E-04) were positively associated with increased risk of MetS. For each component of MetS, higher level of genetically predicted selenium (OR = 0.971, 95% CI 0.957-0.986, P = 1.09E-04) was negatively correlated with HDL-C levels, while vitamin K1 (OR = 1.023, 95% CI 1.012-1.033, P = 2.90E-05) was positively correlated with HDL-C levels. Moreover, genetically predicted vitamin D (OR = 0.985, 95% CI 0.978-0.992, P = 5.51E-5) had a protective effect on FBG levels. Genetically predicted iron level (OR = 1.043, 95% CI 1.022-1.064, P = 4.33E-05) had a risk effect on TG level.

CONCLUSIONS

Our study provides evidence that genetically predicted some specific, but not all, antioxidants, minerals, and vitamins may be causally related to the development of MetS traits.

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.

The Physiological and Pathological Role of Acyl-CoA Oxidation

Fatty acid metabolism, including β-oxidation (βOX), plays an important role in human physiology and pathology. βOX is an essential process in the energy metabolism of most human cells. Moreover, βOX is also the source of acetyl-CoA, the substrate for (a) ketone bodies synthesis, (b) cholesterol synthesis, (c) phase II detoxication, (d) protein acetylation, and (d) the synthesis of many other compounds, including N-acetylglutamate-an important regulator of urea synthesis. This review describes the current knowledge on the importance of the mitochondrial and peroxisomal βOX in various organs, including the liver, heart, kidney, lung, gastrointestinal tract, peripheral white blood cells, and other cells. In addition, the diseases associated with a disturbance of fatty acid oxidation (FAO) in the liver, heart, kidney, lung, alimentary tract, and other organs or cells are presented. Special attention was paid to abnormalities of FAO in cancer cells and the diseases caused by mutations in gene-encoding enzymes involved in FAO. Finally, issues related to α- and ω- fatty acid oxidation are discussed.

The causal effect of metabolic syndrome and its components on benign prostatic hyperplasia: A univariable and multivariable Mendelian randomization study

BACKGROUND

Previous observational studies have indicated that metabolic abnormalities are associated with benign prostatic hyperplasia (BPH). The limitations of the research methodology of observational studies do not allow causal inference to be drawn; however, Mendelian randomization (MR) can clarify this.

METHODS

Using summary-level data from genome-wide association studies, we conducted a two-sample MR study to examine the causality of the metabolic syndrome (MetS) and its components on BPH (26,358 BPH cases and 110,070 controls). The random-effects inverse-variance weighted was employed as the primary method for MR analyses.

RESULTS

We observed that genetically predicted waist circumference (WC) (odds ratio [OR] = 1.236, 95% confidence interval [CI]: 1.034-1.478, p = 0.020) and diastolic blood pressure (DBP) (OR = 1.011, 95% CI: 1.002-1.020, p = 0.020) were significantly positively associated with BPH risk. We did not identify a causal effect of MetS (OR = 0.975, 95% CI: 0.922-1.031, p = 0.375), systolic blood pressure (OR = 1.004, 95% CI: 0.999-1.008, p = 0.115), triglycerides (OR = 1.016, 95% CI: 0.932-1.109, p = 0.712), high-density lipoprotein (OR = 1.005, 95% CI: 0.930-1.086, p = 0.907), and fasting blood glucose (OR = 1.037, 95% CI: 0.874-1.322, p = 0.678) on BPH. In the multivariable MR analysis, we observed that the risk effect of DBP (OR = 1.013, 95% CI: 1.000-1.026, p = 0.047) on BPH persisted after conditioning with WC (OR = 1.132, 95% CI: 0.946-1.356, p = 0.177).

CONCLUSIONS

Our study provides genetic evidence supporting the causal effect of DBP on BPH, although the effect of WC needs to be further validated.

Genes, environment, and African ancestry in cardiometabolic disorders

The past two decades have been characterized by a substantial global increase in cardiometabolic diseases, but the prevalence and incidence of these diseases and related traits differ across populations. African ancestry populations are among the most affected yet least included in research. Populations of African descent manifest significant genetic and environmental diversity and this under-representation is a missed opportunity for discovery and could exacerbate existing health disparities and curtail equitable implementation of precision medicine. Here, we discuss cardiometabolic diseases and traits in the context of African descent populations, including both genetic and environmental contributors and emphasizing novel discoveries. We also review new initiatives to include more individuals of African descent in genomics to address current gaps in the field.

Causal Associations Between Cardiovascular Risk Factors and Venous Thromboembolism

OBJECTIVE

 The aim of the study is to assess the causal effects of cardiovascular risk factors on venous thromboembolism (VTE) and its subtypes including deep vein thrombosis (DVT) and pulmonary embolism (PE).

METHODS

 A summary-level Mendelian randomization (MR) analysis was performed by extracting data from public and large-scale genome-wide association studies for cardiovascular risk factors (hypertension, systolic blood pressure [SBP], diastolic blood pressure [DBP], total cholesterol, triglycerides, high-density lipoprotein [HDL], low-density lipoprotein [LDL], type 2 diabetes, fasting glucose, body mass index [BMI], smoking, alcohol, and physical activity), VTE, DVT, and PE to identify genetic instruments.

RESULTS

 BMI (per standard deviation [SD] increase; odds ratio [OR]: 1.39; 95% confidence interval [CI]: 1.25-1.54; p = 8.02 × 10-10) could increase the VTE risk, whereas SBP (per SD increase; OR: 0.99; 95% CI: 0.98-0.99; p = 0.0005) could decrease the VTE risk. For DVT, BMI (per SD increase; OR: 1.48; 95% CI: 1.28-1.72; p = 1.53 × 10-7) could increase the risk, whereas physical activity (per SD increase; OR: 0.05; 95% CI: 0.01-0.33; p = 0.0020) could decrease the risk. For PE, BMI (per SD increase; OR: 1.29; 95% CI: 1.12-1.49; p = 0.0005) could increase the risk, whereas SBP (per SD increase; OR: 0.99; 95% CI: 0.98-1.00; p = 0.0032) could decrease the risk. Suggestive evidence between smoking and higher risks of VTE and DVT was also observed.

CONCLUSION

 Our study supports that BMI is a causal risk factor for VTE, DVT, and PE. SBP is a protective factor for VTE and PE. Physical activity is a protective factor for DVT. However, the effects of other cardiovascular risk factors are not identified.

Genetic Evidence Strongly Supports Managing Weight and Blood Pressure in Addition to Glycemic Control in Preventing Vascular Complications in People With Type 2 Diabetes

OBJECTIVE

To investigate the causal association of type 2 diabetes and its components with risk of vascular complications independent of shared risk factors obesity and hypertension and to identify the main driver of this risk.

RESEARCH DESIGN AND METHODS

We conducted Mendelian randomization (MR) using independent genetic variants previously associated with type 2 diabetes, fasting glucose, HbA1c, fasting insulin, BMI, and systolic blood pressure as instrumental variables. We obtained summary-level data for 18 vascular diseases (15 for type 2 diabetes) from FinnGen and publicly available genome-wide association studies as our outcomes. We conducted univariable and multivariable MR, in addition to sensitivity tests to detect and minimize pleiotropic effects.

RESULTS

Univariable MR analysis showed that type 2 diabetes was associated with 9 of 15 outcomes; BMI and systolic blood pressure were associated with 13 and 15 of 18 vascular outcomes, respectively; and fasting insulin was associated with 4 and fasting glucose with 2. No robust association was found for HbA1c instruments. With adjustment for correlated traits in the multivariable test, BMI and systolic blood pressure, consistent causal effects were maintained, while five associations with type 2 diabetes (chronic kidney disease, ischemic heart disease, heart failure, subarachnoid hemorrhage, and intracerebral hemorrhage) were attenuated to null.

CONCLUSIONS

Our findings add strong evidence to support the importance of BMI and systolic blood pressure in the development of vascular complications in people with type 2 diabetes. Such findings strongly support the need for better weight and blood pressure management in type 2 diabetes, independent of glucose lowering, to limit important complications.

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort

AIMS/HYPOTHESIS

There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution.

METHODS

Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin.

RESULTS

A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10-8). Two variants associated with low z-insulin (P15, p value <5×10-6) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin.

CONCLUSIONS/INTERPRETATION

The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations.

Efficacy of metformin targets on cardiometabolic health in the general population and non-diabetic individuals: a Mendelian randomization study

BACKGROUND

Metformin shows beneficial effects on cardiometabolic health in diabetic individuals. However, the beneficial effects in the general population, especially in non-diabetic individuals are unclear. We aim to estimate the effects of perturbation of seven metformin targets on cardiometabolic health using Mendelian randomization (MR).

METHODS

Genetic variants close to metformin-targeted genes associated with expression of the corresponding genes and glycated haemoglobin (HbA1c) level were used to proxy therapeutic effects of seven metformin-related drug targets. Eight cardiometabolic phenotypes under metformin trials were selected as outcomes (average N = 466,947). MR estimates representing the weighted average effects of the seven effects of metformin targets on the eight outcomes were generated. One-sample MR was applied to estimate the averaged and target-specific effects in 338,425 non-diabetic individuals in UK Biobank.

FINDINGS

Genetically proxied averaged effects of five metformin targets, equivalent to a 0.62% reduction of HbA1c level, was associated with 37.8% lower risk of coronary artery disease (CAD) (odds ratio [OR] = 0.62, 95% confidence interval [CI] = 0.46-0.84), lower levels of body mass index (BMI) (β = -0.22, 95% CI = -0.35 to -0.09), systolic blood pressure (SBP) (β = -0.19, 95% CI = -0.28 to -0.09) and diastolic blood pressure (DBP) levels (β = -0.29, 95% CI = -0.39 to -0.19). One-sample MR suggested that the seven metformin targets showed averaged and target-specific beneficial effects on BMI, SBP and DBP in non-diabetic individuals.

INTERPRETATION

This study showed that perturbation of seven metformin targets has beneficial effects on BMI and blood pressure in non-diabetic individuals. Clinical trials are needed to investigate whether similar effects can be achieved with metformin medications.

FUNDING

Funding information is provided in the Acknowledgements.

Genetically proxied antidiabetic drugs targets and stroke risk

BACKGROUND

Previous studies have assessed the association between antidiabetic drugs and stroke risk, but the results are inconsistent. Mendelian randomization (MR) was used to assess effects of antidiabetic drugs on stroke risk.

METHODS

We selected blood glucose-lowering variants in genes encoding antidiabetic drugs targets from genome-wide association studies (GWAS). A two-sample MR and Colocalization analyses were applied to examine associations between antidiabetic drugs and the risk of stroke. For antidiabetic agents that had effect on stroke risk, an independent blood glucose GWAS summary data was used for further verification.

RESULTS

Genetic proxies for sulfonylureas targets were associated with reduced risk of any stroke (OR=0.062, 95% CI 0.013-0.295, P=4.65×10－4) and any ischemic stroke (OR=0.055, 95% CI 0.010-0.289, P=6.25×10－4), but not with intracranial hemorrhage. Colocalization supported shared casual variants for blood glucose with any stroke and any ischemic stroke within the encoding genes for sulfonylureas targets (KCNJ11 and ABCC8) (posterior probability>0.7). Furthermore, genetic variants in the targets of insulin/insulin analogues, glucagon-like peptide-1 analogues, thiazolidinediones, and metformin were not associated with the risk of any stroke, any ischemic stroke and intracranial hemorrhage. The association was consistent in the analysis of sulfonylureas with stroke risk using an independent blood glucose GWAS summary data.

CONCLUSIONS

Our findings showed that genetic proxies for sulfonylureas targets by lowering blood glucose were associated with a lower risk of any stroke and any ischemic stroke. The study might be of great significance to guide the selection of glucose-lowering drugs in individuals at high risk of stroke.

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.

Effect of women's fertility and sexual development on epigenetic clock: Mendelian randomization study

BACKGROUND AND OBJECTIVES

In observational studies, women's fertility and sexual development traits may have implications for DNA methylation patterns, and pregnancy-related risk factors can also affect maternal DNA methylation patterns. The aim of our study is to disentangle any potential causal associations between women's fertility and sexual development traits and epigenetic clocks, as well as to search for probable mediators by using the Mendelian randomization (MR) method.

METHODS

Instrumental variables for exposures, mediators, and outcomes were adopted from genome-wide association studies data of European ancestry individuals. The potential causal relationship between women's fertility and sexual development traits and four epigenetic clocks were evaluated by inverse variance weighted method and verified by other two methods. Furthermore, we employed multivariable MR (MVMR) adjusting for hypertension, hyperglycemia, BMI changes, and insomnia. Then, combining the MVMR results and previous research, we performed two-step MR to explore the mediating effects of BMI, AFS, and AFB. Multiple sensitivity analyses were further performed to verify the robustness of our findings.

RESULTS

Leveraging two-sample MR analysis, we observed statistically significant associations between earlier age at first birth (AFB) with a higher HannumAge, PhenoAge and GrimAge acceleration(β = - 0.429, 95% CI [- 0.781 to - 0.077], p = 0.017 for HannumAge; β = - 0.571, 95% CI [- 1.006 to - 0.136], p = 0.010 for PhenoAge, and β = - 1.136, 95% CI [- 1.508 to - 0.765], p = 2.03E-09 for GrimAge respectively) and age at first sexual intercourse (AFS) with a higher HannumAge and GrimAge acceleration(β = - 0.175, 95% CI [- 0.336 to - 0.014], p = 0.033 for HannumAge; β = - 0.210, 95% CI [- 0.350 to - 0.070], p = 0.003 for GrimAge, respectively). Further analyses indicated that BMI, AFB and AFS played mediator roles in the path from women's fertility and sexual development traits to epigenetic aging.

CONCLUSIONS

Our study suggested that AFS and AFB are associated with epigenetic aging. These findings may prove valuable in informing the development of prevention strategies and interventions targeted towards women's fertility and sexual development experiences and their relationship with epigenetic aging-related diseases.

Heterogeneous effects on type 2 diabetes and cardiovascular outcomes of genetic variants and traits associated with fasting insulin

Hyperinsulinemia is a complex and heterogeneous phenotype that characterizes molecular alterations that precede the development of type 2 diabetes (T2D). It results from a complex combination of molecular processes, including insulin secretion and insulin sensitivity, that differ between individuals. To better understand the physiology of hyperinsulinemia and ultimately T2D, we implemented a genetic approach grouping fasting insulin (FI)-associated genetic variants based on their molecular and phenotypic similarities. We identified seven distinctive genetic clusters representing different physiologic mechanisms leading to rising FI levels, ranging from clusters of variants with effects on increased FI, but without increased risk of T2D (non-diabetogenic hyperinsulinemia), to clusters of variants that increase FI and T2D risk with demonstrated strong effects on body fat distribution, liver, lipid, and inflammatory processes (diabetogenic hyperinsulinemia). We generated cluster-specific polygenic scores in 1,104,258 individuals from five multi-ancestry cohorts to show that the clusters differed in associations with cardiometabolic traits. Among clusters characterized by non-diabetogenic hyperinsulinemia, there was both increased and decreased risk of coronary artery disease despite the non-increased risk of T2D. Similarly, the clusters characterized by diabetogenic hyperinsulinemia were associated with an increased risk of T2D, yet had differing risks of cardiovascular conditions, including coronary artery disease, myocardial infarction, and stroke. The strongest cluster-T2D associations were observed with the same direction of effect in non-Hispanic Black, Hispanic, non-Hispanic White, and non-Hispanic East Asian populations. These genetic clusters provide important insights into granular metabolic processes underlying the physiology of hyperinsulinemia, notably highlighting specific processes that decouple increasing FI levels from T2D and cardiovascular risk. Our findings suggest that increasing FI levels are not invariably associated with adverse cardiometabolic outcomes.

Causality of anti-Helicobacter pylori IgG levels on myocardial infarction and potential pathogenesis: a Mendelian randomization study

Background

Previous observational studies have shown that a potential relationship between anti-Helicobacter pylori (H. pylori) IgG levels and Myocardial Infarction (MI). Nevertheless, the evidence for the causal inferences remains disputable. To further clarify the relationship between anti-H. pylori IgG levels and MI and explore its pathogenesis, we conducted a Mendelian randomization (MR) analysis.

Methods

In this study, we used two-sample Mendelian Randomization (MR) to assess the causality of anti-H. pylori IgG levels on MI and potential pathogenesis, 12 single nucleotide polymorphisms (SNPs) related to anti-H. pylori IgG levels were obtained from the European Bioinformatics Institute (EBI). Summary data from a large-scale GWAS meta-analysis of MI was utilized as the outcome dataset. Summary data of mediators was obtained from the FinnGen database, the UK Biobank, the EBI database, MRC-IEU database, the International Consortium of Blood Pressure, the Consortium of Within family GWAS. Inverse variance weighted (IVW) analysis under the fixed effect model was identified as our main method. To ensure the reliability of the findings, many sensitivity analyses were performed.

Results

Our study revealed that increases of anti-H. pylori IgG levels were significantly related to an increased risk of MI (OR, 1.104; 95% CI,1.042-1.169; p = 7.084 × 10-4) and decreases in HDL cholesterol levels (β, -0.016; 95% CI, -0.026 to -0.006; p = 2.02 × 10-3). In addition, there was no heterogeneity or pleiotropy in our findings.

Conclusion

This two-sample MR analysis revealed the causality of anti-H. pylori IgG levels on MI, which might be explained by lower HDL cholesterol levels. Further research is needed to clarify the results.

Assessing the Impact of PCSK9 and HMGCR Inhibition on Liver Function: Drug-Target Mendelian Randomization Analyses in Four Ancestries

BACKGROUND & AIMS

Observational studies have linked lipid-lowering drug targets pro-protein convertase subtilisin/kexin 9 (PCSK9) and HMG-CoA reductase (HMGCR) with adverse liver outcomes; however, liver disease incidence varies across diverse populations, and the long-term hepatic impact of these lipid-lowering drugs among non-white Europeans remains largely unknown.

METHODS

We use single nucleotide polymorphisms (SNPs) in PCSK9 and HMGCR loci from genome-wide association study data of low-density lipoprotein cholesterol in 4 populations (East Asian [EAS], South Asian [SAS], African [AFR], and European [EUR]) to perform drug-target Mendelian randomization investigating relationships between PCSK9 and HMGCR inhibition and alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), and bilirubin.

RESULTS

Analyses of PCSK9 instruments, including functional variants R46L and E670G, failed to find evidence for relationships of low-density lipoprotein cholesterol lowering via PCSK9 variants and adverse effects on ALT, AST, GGT, or ALP among the cohorts. PCSK9 inhibition was associated with increased direct bilirubin levels in EUR (β = 0.089; P value = 5.69 × 10-6) and, nominally, in AFR (β = 0.181; P value = .044). HMGCR inhibition was associated with reduced AST in SAS (β = -0.705; P value = .005) and, nominally, reduced AST in EAS (β = -0.096; P value = .03), reduced ALP in EUR (β = -2.078; P value = .014), and increased direct bilirubin in EUR (β = 0.071; P value = .032). Sensitivity analyses using genetic instruments derived from circulating PCSK9 protein levels, tissue-specific PCSK9 expression, and HMGCR expression were in alignment, strengthening causal inference.

CONCLUSIONS

We did not find ALT, AST, GGT, or ALP associated with genetically proxied PCSK9 and HMGCR inhibition across ancestries. We identified possible relationships in several ancestries between PCSK9 and increased direct and total bilirubin and between HMGCR and reduced AST. These findings support long-term safety profiles and low hepatotoxic risk of PCSK9 and HMGCR inhibition in diverse populations.

Using genetics to examine the overall and sex-specific associations of branch-chain amino acids and the valine metabolite, 3-hydroxyisobutyrate, with ischemic heart disease and diabetes: A two-sample Mendelian randomization study

BACKGROUND AND AIMS

Branch-chain amino acids (BCAAs) are linked to higher risk of diabetes, whilst the evidence on ischemic heart disease (IHD) is limited. Valine metabolite, 3-hydroxyisobutyrate (3-HIB), also plays an important role in metabolism, whilst its effect has been rarely examined. At the situation of no evidence from large trials, we assessed the role of BCAAs and 3-HIB in IHD and diabetes using Mendelian randomization to minimize confounding. Given their potential role in sex hormones, we also examined sex-specific associations.

METHODS

We used genetic variants to predict BCAAs and 3-HIB, and obtained their associations with IHD and diabetes in large consortia and cohorts, as well as sex-specific association in the UK Biobank and DIAGRAM. We obtained and combined the Wald estimates using inverse variance weighting, and different analytic methods robust to pleiotropy.

RESULTS

Genetically predicted BCAAs were associated with higher risk of IHD (odds ratio (OR) 1.19 per standard deviation (SD) increase in BCAAs, 95% confidence interval (CI) 1.05 to 1.35) and diabetes (OR 1.20, 95% CI 1.08 to 1.34). The associations with IHD were stronger in women (OR 1.23, 95% CI 1.03 to 1.48) than men (OR 0.96, 95% CI 0.83 to 1.10). 3-HIB was associated with higher risk of IHD (OR 1.43, 95% CI 1.17 to 1.73) but not diabetes, with no sex disparity.

CONCLUSION

BCAAs and 3-HIB are potential targets for prevention in IHD and/or diabetes. BCAAs may exert a sex-specific role in IHD. Consideration of the sex disparity and exploration of the underlying pathways would be worthwhile.

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers

Background

Previous observational studies have shown that the prevalence of cardiovascular diseases (CVDs) is related to particulate matter (PM). However, given the methodological limitations of conventional observational research, it is difficult to identify causality conclusively. To explore the causality of PM on CVDs and cardiovascular biomarkers, we conducted a Mendelian randomization (MR) analysis.

Method

In this study, we obtained summary-level data for CVDs and cardiovascular biomarkers including atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), ischemic stroke (IS), stroke subtypes, body mass index (BMI), lipid traits, fasting glucose, fasting insulin, and blood pressure from several large genome-wide association studies (GWASs). Then we used two-sample MR to assess the causality of PM on CVDs and cardiovascular biomarkers, 16 single nucleotide polymorphisms (SNPs) for PM2.5 and 6 SNPs for PM10 were obtained from UK Biobank participants. Inverse variance weighting (IVW) analyses under the fixed effects model were used as the main analytical method to calculate MR Estimates, followed by multiple sensitivity analyses to confirm the robustness of the results.

Results

Our study revealed increases in PM2.5 concentration were significantly related to a higher risk of MI (odds ratio (OR), 2.578; 95% confidence interval (CI), 1.611-4.127; p = 7.920 × 10-5). Suggestive evidence was found between PM10 concentration and HF (OR, 2.015; 95% CI, 1.082-3.753; p = 0.027) and IS (OR, 2.279; 95% CI,1.099-4.723; p = 0.027). There was no evidence for an effect of PM concentration on other CVDs. Furthermore, PM2.5 concentration increases were significantly associated with increases in triglyceride (TG) (OR, 1.426; 95% CI, 1.133-1.795; p = 2.469 × 10-3) and decreases in high-density lipoprotein cholesterol (HDL-C) (OR, 0.779; 95% CI, 0.615-0.986; p = 0.038). The PM10 concentration increases were also closely related to the decreases in HDL-C (OR, 0.563; 95% CI, 0.366-0.865; p = 8.756 × 10-3). We observed no causal effect of PM on other cardiovascular biomarkers.

Conclusion

At the genetic level, our study suggested the causality of PM2.5 on MI, TG, as well HDL-C, and revealed the causality of PM10 on HF, IS, and HDL-C. Our findings indicated the need for continued improvements in air pollution abatement for CVDs prevention.

Maternal pre-pregnancy BMI, offspring epigenome-wide DNA methylation, and childhood obesity: findings from the Boston Birth Cohort

BACKGROUND

Maternal pre-pregnancy obesity is an established risk factor for childhood obesity. Investigating epigenetic alterations induced by maternal obesity during fetal development could gain mechanistic insight into the developmental origins of childhood obesity. While obesity disproportionately affects underrepresented racial and ethnic mothers and children in the USA, few studies investigated the role of prenatal epigenetic programming in intergenerational obesity of these high-risk populations.

METHODS

This study included 903 mother-child pairs from the Boston Birth Cohort, a predominantly urban, low-income minority birth cohort. Mother-infant dyads were enrolled at birth and the children were followed prospectively to age 18 years. Infinium Methylation EPIC BeadChip was used to measure epigenome-wide methylation level of cord blood. We performed an epigenome-wide association study of maternal pre-pregnancy body mass index (BMI) and cord blood DNA methylation (DNAm). To quantify the degree to which cord blood DNAm mediates the maternal BMI-childhood obesity, we further investigated whether maternal BMI-associated DNAm sites impact birthweight or childhood overweight or obesity (OWO) from age 1 to age 18 and performed corresponding mediation analyses.

RESULTS

The study sample contained 52.8% maternal pre-pregnancy OWO and 63.2% offspring OWO at age 1-18 years. Maternal BMI was associated with cord blood DNAm at 8 CpG sites (genome-wide false discovery rate [FDR] < 0.05). After accounting for the possible interplay of maternal BMI and smoking, 481 CpG sites were discovered for association with maternal BMI. Among them 123 CpGs were associated with childhood OWO, ranging from 42% decrease to 87% increase in OWO risk for each SD increase in DNAm. A total of 14 identified CpG sites showed a significant mediation effect on the maternal BMI-child OWO association (FDR < 0.05), with mediating proportion ranging from 3.99% to 25.21%. Several of these 14 CpGs were mapped to genes in association with energy balance and metabolism (AKAP7) and adulthood metabolic syndrome (CAMK2B).

CONCLUSIONS

This prospective birth cohort study in a high-risk yet understudied US population found that maternal pre-pregnancy OWO significantly altered DNAm in newborn cord blood and provided suggestive evidence of epigenetic involvement in the intergenerational risk of obesity.

Genetically Predicted Vegetable Intake and Cardiovascular Diseases and Risk Factors: An Investigation with Mendelian Randomization

BACKGROUND

The associations between vegetable intake and cardiovascular diseases have been demonstrated in observational studies, but less sufficiently in randomized trials. Mendelian randomization has been considered a promising alternative in causal inference. The separate effects of cooked and raw vegetable intake remain unclear. This study aimed to investigate the associations between cooked and raw vegetable intake with cardiovascular outcomes using MR.

METHODS

We identified 15 and 28 genetic variants statistically and biologically associated with cooked and raw vegetable intake, respectively, from previous genome-wide association studies, which were used as instrumental variables to estimate associations with coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF). The independent effects of genetically predicted cooked and raw vegetable intake were examined using multivariable MR analysis. We performed one-sample and two-sample MR analyses and combined their results using meta-analysis. Bonferroni correction was applied for multiple comparisons. We performed two-sample MR analysis for cardiometabolic risk factors (serum lipids, blood pressure, body mass index, and glycemic traits) to explore the potential mechanisms.

RESULTS

In the MR meta-analysis of 1.2 million participants, we found null evidence for associations between genetically predicted cooked and raw vegetable intake with CHD, HF, or AF. Raw vegetable intake was nominally associated with stroke (odds ratio [95% confidence interval] 0.82 [0.69-0.98] per 1 daily serving increase, p = 0.03), but this association did not pass the corrected significance level. We found consistently null evidence for associations with serum lipids, blood pressure, body mass index, or glycemic traits.

CONCLUSIONS

We found null evidence for associations between genetically predicted vegetable intake with CHD, AF, HF, or cardiometabolic risk factors in this MR study. Raw vegetable intake may reduce risk of stroke, but this warrants more research. True associations between vegetable intake and CVDs cannot be completely ruled out, and future investigations are required for causal inference in nutritional research.

Pancreatic islet α cell function and proliferation requires the arginine transporter SLC7A2

Interrupting glucagon signaling decreases gluconeogenesis and the fractional extraction of amino acids by liver from blood resulting in lower glycemia. The resulting hyperaminoacidemia stimulates α cell proliferation and glucagon secretion via a liver-α cell axis. We hypothesized that α cells detect and respond to circulating amino acids levels via a unique amino acid transporter repertoire. We found that Slc7a2ISLC7A2 is the most highly expressed cationic amino acid transporter in α cells with its expression being three-fold greater in α than β cells in both mouse and human. Employing cell culture, zebrafish, and knockout mouse models, we found that the cationic amino acid arginine and SLC7A2 are required for α cell proliferation in response to interrupted glucagon signaling. Ex vivo and in vivo assessment of islet function in Slc7a2-/- mice showed decreased arginine-stimulated glucagon and insulin secretion. We found that arginine activation of mTOR signaling and induction of the glutamine transporter SLC38A5 was dependent on SLC7A2, showing that both's role in α cell proliferation is dependent on arginine transport and SLC7A2. Finally, we identified single nucleotide polymorphisms in SLC7A2 associated with HbA1c. Together, these data indicate a central role for SLC7A2 in amino acid-stimulated α cell proliferation and islet hormone secretion.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

DNA methylation studies of incident type 2 diabetes in US populations are limited, and to our knowledge none included individuals of African descent living in the US. We performed an epigenome-wide association analysis of blood-based methylation levels at CpG sites with incident type 2 diabetes using Cox regression in 2,091 Black and 1,029 White individuals from the Atherosclerosis Risk in Communities study. At an epigenome-wide significance threshold of 10-7, we detected 7 novel diabetes-associated CpG sites in C1orf151 (cg05380846: HR= 0.89, p = 8.4 × 10-12), ZNF2 (cg01585592: HR= 0.88, p = 1.6 × 10-9), JPH3 (cg16696007: HR= 0.87, p = 7.8 × 10-9), GPX6 (cg02793507: HR= 0.85, p = 2.7 × 10-8 and cg00647063: HR= 1.20, p = 2.5 × 10-8), chr17q25 (cg16865890: HR= 0.8, p = 6.9 × 10-8), and chr11p15 (cg13738793: HR= 1.11, p = 7.7 × 10-8). The CpG sites at C1orf151, ZNF2, JPH3 and GPX6, were identified in Black adults, chr17q25 was identified in White adults, and chr11p15 was identified upon meta-analyzing the two groups. The CpG sites at JPH3 and GPX6 were likely associated with incident type 2 diabetes independent of BMI. All the CpG sites, except at JPH3, were likely consequences of elevated glucose at baseline. We additionally replicated known type 2 diabetes-associated CpG sites including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLBC2, cg11024682 at SREBF1, cg08857797 at VPS25, and cg06500161 at ABCG1, 3 of which were replicated in Black adults at the epigenome-wide threshold. We observed modest increase in type 2 diabetes variance explained upon addition of the significantly associated CpG sites to a Cox model that included traditional type 2 diabetes risk factors and fasting glucose (increase from 26.2% to 30.5% in Black adults; increase from 36.9% to 39.4% in White adults). We examined if groups of proximal CpG sites were associated with incident type 2 diabetes using a gene-region specific and a gene-region agnostic differentially methylated region (DMR) analysis. Our DMR analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 and promoter regions of TP63 which were differentially methylated across all race groups. This study illustrates improved discovery of CpG sites/regions by leveraging both individual CpG site and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g., GPX6, JPH3, and TP63), and future gene-specific methylation studies could elucidate the link between genes, environment, and methylation in the pathogenesis of type 2 diabetes.

Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E-7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E-14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women's Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.

A whole-genome reference panel of 14,393 individuals for East Asian populations accelerates discovery of rare functional variants

Underrepresentation of non-European (EUR) populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72,298 subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East Asian specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects. We suggest that this dataset will add to the potential value of Asian precision medicine.

High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging

The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.

Comparative Effectiveness of Sodium-Glucose Cotransporter-2 Inhibitors for Recurrent Gout Flares and Gout-Primary Emergency Department Visits and Hospitalizations : A General Population Cohort Study

BACKGROUND

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) decrease serum urate levels, but whether this translates into prevention of recurrent flares among patients with gout and gout-primary emergency department (ED) visits or hospitalizations is unknown.

OBJECTIVE

To compare gout flares and cardiovascular events among patients with gout initiating SGLT2is versus dipeptidyl peptidase 4 inhibitors (DPP-4is), another second-line glucose-lowering agent not associated with serum urate levels or cardiovascular risk.

DESIGN

Propensity score-matched, new-user cohort study.

SETTING

General population database from 1 January 2014 to 30 June 2022.

PARTICIPANTS

Patients with gout and type 2 diabetes.

MEASUREMENTS

The primary outcome was recurrent gout flare counts ascertained by ED, hospitalization, outpatient, and medication dispensing records. Secondary outcomes included myocardial infarction and stroke; genital infection (positive control) and osteoarthritis encounter (negative control) were also assessed. Poisson and Cox proportional hazards regressions were used with 1:1 propensity score matching (primary analysis) and overlap weighting (sensitivity analysis).

RESULTS

After propensity score matching, the flare rate was lower among SGLT2i initiators than DPP-4i initiators (52.4 and 79.7 events per 1000 person-years, respectively), with a rate ratio (RR) of 0.66 (95% CI, 0.57 to 0.75) and a rate difference (RD) of -27.4 (CI, -36.0 to -18.7) per 1000 person-years. The corresponding RR and RD for gout-primary ED visits and hospitalizations were 0.52 (CI, 0.32 to 0.84) and -3.4 (CI, -5.8 to -0.9) per 1000 person-years, respectively. The corresponding hazard ratio (HR) and RD for myocardial infarction were 0.69 (CI, 0.54 to 0.88) and -7.6 (CI, -12.4 to -2.8) per 1000 person-years; the HR for stroke was 0.81 (CI, 0.62 to 1.05). Those who initiated SGLT2is showed higher risk for genital infection (HR, 2.15 [CI, 1.39 to 3.30]) and no altered risk for osteoarthritis encounter (HR, 1.07 [CI, 0.95 to 1.20]). Results were similar when propensity score overlap weighting was applied.

LIMITATION

Participants had concurrent type 2 diabetes.

CONCLUSION

Among patients with gout, SGLT2is may reduce recurrent flares and gout-primary ED visits and hospitalizations and may provide cardiovascular benefits.

PRIMARY FUNDING SOURCE

National Institute of Arthritis and Musculoskeletal and Skin Diseases.

Cross-trait analyses identify shared genetics between migraine, headache, and glycemic traits, and a causal relationship with fasting proinsulin

The co-occurrence of migraine and glycemic traits has long been reported in observational epidemiological studies, but it has remained unknown how they are linked genetically. We used large-scale GWAS summary statistics on migraine, headache, and nine glycemic traits in European populations to perform cross-trait analyses to estimate genetic correlation, identify shared genomic regions, loci, genes, and pathways, and test for causal relationships. Out of the nine glycemic traits, significant genetic correlation was observed for fasting insulin (FI) and glycated haemoglobin (HbA1c) with both migraine and headache, while 2-h glucose was genetically correlated only with migraine. Among 1703 linkage disequilibrium (LD) independent regions of the genome, we found pleiotropic regions between migraine and FI, fasting glucose (FG), and HbA1c, and pleiotropic regions between headache and glucose, FI, HbA1c, and fasting proinsulin. Cross-trait GWAS meta-analysis with glycemic traits, identified six novel genome-wide significant lead SNPs with migraine, and six novel lead SNPs with headache (Pmeta < 5.0 × 10-8 and Psingle-trait < 1 × 10-4), all of which were LD-independent. Genes with a nominal gene-based association (Pgene ≤ 0.05) were significantly enriched (overlapping) across the migraine, headache, and glycemic traits. Mendelian randomisation analyses produced intriguing, but inconsistent, evidence for a causal relationship between migraine and headache with multiple glycemic traits; and consistent evidence suggesting increased fasting proinsulin levels may causally decrease the risk of headache. Our findings indicate that migraine, headache, and glycemic traits share a common genetic etiology and provide genetic insights into the molecular mechanisms contributing to their comorbid relationship.

Genetic liability to multiple factors and uterine leiomyoma risk: a Mendelian randomization study

Background and objective

Uterine leiomyoma is the most common benign tumor in females of reproductive age. However, its causes have never been fully understood. The objective of our study was to analyze the causal association between various factors and uterine leiomyoma using Mendelian randomization (MR).

Methods

Genetic variables associated with risk factors were obtained from genome-wide association studies. Summary-level statistical data for uterine leiomyoma were obtained from FinnGen and the UK Biobank (UKB) consortium. We used inverse variance weighted, MR-Egger, and weighted median methods in univariate analysis. Multivariable MR analysis was used to identify independent risk factors. A fixed-effect model meta-analysis was used to combine the results of the FinnGen and UKB data.

Results

In the FinnGen data, higher genetically predicted age at natural menopause, systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting insulin were associated with an increased risk of uterine leiomyoma, while higher age at menarche was associated with a reduced risk of uterine leiomyoma. Multivariable MR analysis of SBP and DBP showed that higher DBP might be an independent risk factor of uterine leiomyoma. In the UKB data, the results for age at natural menopause, SBP, DBP, and age at menarche were replicated. The result of the meta-analysis suggested that uterine leiomyoma could also be affected by polycystic ovary syndrome (PCOS), endometriosis, and 2-hour glucose level.

Conclusion

Our MR study confirmed that earlier menstrual age, hypertension, obesity, and elevated 2-hour glucose post-challenge were risk factors for uterine leiomyoma, and the causal relationship between smoking and uterine leiomyoma was ruled out. In addition, later age of menopause and endometriosis were found to increase the risk of uterine leiomyoma, while PCOS was found to decrease the risk.

Genetically mimicked effects of ASGR1 inhibitors on all-cause mortality and health outcomes: a drug-target Mendelian randomization study and a phenome-wide association study

BACKGROUND

Asialoglycoprotein receptor 1 (ASGR1) is emerging as a potential drug target to reduce low-density lipoprotein (LDL)-cholesterol and coronary artery disease (CAD) risk. Here, we investigated genetically mimicked ASGR1 inhibitors on all-cause mortality and any possible adverse effects.

METHODS

We conducted a drug-target Mendelian randomization study to assess genetically mimicked effects of ASGR1 inhibitors on all-cause mortality and 25 a priori outcomes relevant to lipid traits, CAD, and possible adverse effects, i.e. liver function, cholelithiasis, adiposity and type 2 diabetes. We also performed a phenome-wide association study of 1951 health-related phenotypes to identify any novel effects. Associations found were compared with those for currently used lipid modifiers, assessed using colocalization, and replicated where possible.

RESULTS

Genetically mimicked ASGR1 inhibitors were associated with a longer lifespan (3.31 years per standard deviation reduction in LDL-cholesterol, 95% confidence interval 1.01 to 5.62). Genetically mimicked ASGR1 inhibitors were inversely associated with apolipoprotein B (apoB), triglycerides (TG) and CAD risk. Genetically mimicked ASGR1 inhibitors were positively associated with alkaline phosphatase, gamma glutamyltransferase, erythrocyte traits, insulin-like growth factor 1 (IGF-1) and C-reactive protein (CRP), but were inversely associated with albumin and calcium. Genetically mimicked ASGR1 inhibitors were not associated with cholelithiasis, adiposity or type 2 diabetes. Associations with apoB and TG were stronger for ASGR1 inhibitors compared with currently used lipid modifiers, and most non-lipid effects were specific to ASGR1 inhibitors. The probabilities for colocalization were > 0.80 for most of these associations, but were 0.42 for lifespan and 0.30 for CAD. These associations were replicated using alternative genetic instruments and other publicly available genetic summary statistics.

CONCLUSIONS

Genetically mimicked ASGR1 inhibitors reduced all-cause mortality. Beyond lipid-lowering, genetically mimicked ASGR1 inhibitors increased liver enzymes, erythrocyte traits, IGF-1 and CRP, but decreased albumin and calcium.

Causal associations between cardiorespiratory fitness and type 2 diabetes

Higher cardiorespiratory fitness is associated with lower risk of type 2 diabetes. However, the causality of this relationship and the biological mechanisms that underlie it are unclear. Here, we examine genetic determinants of cardiorespiratory fitness in 450k European-ancestry individuals in UK Biobank, by leveraging the genetic overlap between fitness measured by an exercise test and resting heart rate. We identified 160 fitness-associated loci which we validated in an independent cohort, the Fenland study. Gene-based analyses prioritised candidate genes, such as CACNA1C, SCN10A, MYH11 and MYH6, that are enriched in biological processes related to cardiac muscle development and muscle contractility. In a Mendelian Randomisation framework, we demonstrate that higher genetically predicted fitness is causally associated with lower risk of type 2 diabetes independent of adiposity. Integration with proteomic data identified N-terminal pro B-type natriuretic peptide, hepatocyte growth factor-like protein and sex hormone-binding globulin as potential mediators of this relationship. Collectively, our findings provide insights into the biological mechanisms underpinning cardiorespiratory fitness and highlight the importance of improving fitness for diabetes prevention.

Physical Activity, Sedentary Behavior, and Type 2 Diabetes: Mendelian Randomization Analysis

Context

The causality and pathways of the associations between physical activity and inactivity and the risk of type 2 diabetes remain inconclusive.

Objective

We conducted an updated mendelian randomization (MR) study to explore the associations of moderate-to-vigorous physical activity (MVPA) and leisure screen time (LST) with type 2 diabetes mellitus (T2DM).

Methods

Genetic variants strongly associated with MVPA or LST with low linkage disequilibrium were selected as instrumental variables from a genome-wide meta-analysis including more than 600 000 individuals. Summary-level data on T2DM were obtained from the DIAbetes Genetics Replication And Meta-analysis consortium including 898 130 individuals. Data on possible intermediates (adiposity indicators, lean mass, glycemic traits, and inflammatory biomarkers) were extracted from large-scale genome-wide association studies (n = 21 758-681 275). Univariable and multivariable MR analyses were performed to estimate the total and direct effects of MVPA and LST on T2DM. Methylation MR analysis was performed for MVPA in relation to diabetes.

Results

The odds ratio of T2DM was 0.70 (95% CI, 0.55-0.88; P = .002) per unit increase in the log-odds ratio of having MVPA and 1.45 (95% CI, 1.30-1.62; P = 7.62 × 10-11) per SD increase in genetically predicted LST. These associations attenuated in multivariable MR analyses adjusted for genetically predicted waist-to-hip ratio, body mass index, lean mass, and circulating C-reactive protein. The association between genetically predicted MVPA and T2DM attenuated after adjusting for genetically predicted fasting insulin levels. Two physical activity-related methylation biomarkers (cg17332422 in ADAMTS2 and cg09531019) were associated with the risk of T2DM (P < .05).

Conclusion

The study suggests causal associations of MVPA and LST with T2DM that appear to be mediated by obesity, lean mass, and chronic low-grade inflammation.

Genetic Association and Potential Mediators between Sarcopenia and Coronary Heart Disease: A Bidirectional Two-Sample, Two-Step Mendelian Randomization Study

OBJECTIVE

To elucidate the bidirectional correlation of sarcopenia with coronary heart disease (CHD), as well as to investigate the mediating role of cardiometabolic factors and inflammatory biomarkers, a bidirectional two-sample, two-step Mendelian randomization (MR) study was conducted.

METHODS

Summary statistics were obtained from genome-wide association studies (GWAS). In our bidirectional two-sample MR, genetic variants associated with sarcopenia-related traits and CHD were instrumented for the estimation of bidirectional correlations. Besides, genetic variants associated with thirteen cardiometabolic factors and six inflammatory biomarkers were selected for further mediation analyses. To confirm the consistency of the results, several sensitivity analyses were carried out.

RESULTS

Genetically predicted higher appendicular lean mass (OR = 0.835, 95% CI: 0.790-0.882), left hand grip strength (OR = 0.703, 95% CI: 0.569-0.869), right hand grip strength (OR = 0.685, 95% CI: 0.555-0.844), and walking pace (OR = 0.321, 95% CI: 0.191-0.539) reduced CHD risk, while genetic predisposition to CHD did not affect any of the sarcopenia-related traits. Seven mediators were identified for the effects of appendicular lean mass on CHD, including waist-to-hip ratio, hip circumference, systolic blood pressure, low-density lipoprotein cholesterol, total cholesterol, triglycerides, and fasting insulin. The mediation proportion ranged from 10.23% for triglycerides to 35.08% for hip circumference. Hip circumference was found to mediate the relationships between both left (mediation proportion: 24.61%) and right-hand grip strength (24.14%) and CHD, and the link between walking pace and CHD was partially mediated by waist-to-hip ratio (31.15%) and body mass index (26.66%).

CONCLUSION

Our results showed that higher appendicular lean mass, hand grip strength, and walking pace reduced CHD risk, but the causal relationship was not bidirectional. Several mediators were found to mediate the causal pathways between sarcopenia-related traits and CHD, and intervention of these factors may be helpful in terms of CHD prevention in sarcopenia patients.

Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH

AIMS/HYPOTHESIS

Characterisation of genetic variation that influences the response to glucose-lowering medications is instrumental to precision medicine for treatment of type 2 diabetes. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH) examined the acute response to metformin and glipizide in order to identify new pharmacogenetic associations for the response to common glucose-lowering medications in individuals at risk of type 2 diabetes.

METHODS

One thousand participants at risk for type 2 diabetes from diverse ancestries underwent sequential glipizide and metformin challenges. A genome-wide association study was performed using the Illumina Multi-Ethnic Genotyping Array. Imputation was performed with the TOPMed reference panel. Multiple linear regression using an additive model tested for association between genetic variants and primary endpoints of drug response. In a more focused analysis, we evaluated the influence of 804 unique type 2 diabetes- and glycaemic trait-associated variants on SUGAR-MGH outcomes and performed colocalisation analyses to identify shared genetic signals.

RESULTS

Five genome-wide significant variants were associated with metformin or glipizide response. The strongest association was between an African ancestry-specific variant (minor allele frequency [MAFAfr]=0.0283) at rs149403252 and lower fasting glucose at Visit 2 following metformin (p=1.9×10-9); carriers were found to have a 0.94 mmol/l larger decrease in fasting glucose. rs111770298, another African ancestry-specific variant (MAFAfr=0.0536), was associated with a reduced response to metformin (p=2.4×10-8), where carriers had a 0.29 mmol/l increase in fasting glucose compared with non-carriers, who experienced a 0.15 mmol/l decrease. This finding was validated in the Diabetes Prevention Program, where rs111770298 was associated with a worse glycaemic response to metformin: heterozygous carriers had an increase in HbA1c of 0.08% and non-carriers had an HbA1c increase of 0.01% after 1 year of treatment (p=3.3×10-3). We also identified associations between type 2 diabetes-associated variants and glycaemic response, including the type 2 diabetes-protective C allele of rs703972 near ZMIZ1 and increased levels of active glucagon-like peptide 1 (GLP-1) (p=1.6×10-5), supporting the role of alterations in incretin levels in type 2 diabetes pathophysiology.

CONCLUSIONS/INTERPRETATION

We present a well-phenotyped, densely genotyped, multi-ancestry resource to study gene-drug interactions, uncover novel variation associated with response to common glucose-lowering medications and provide insight into mechanisms of action of type 2 diabetes-related variation.

DATA AVAILABILITY

The complete summary statistics from this study are available at the Common Metabolic Diseases Knowledge Portal ( https://hugeamp.org ) and the GWAS Catalog ( www.ebi.ac.uk/gwas/ , accession IDs: GCST90269867 to GCST90269899).

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

AIMS/HYPOTHESIS

The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population.

METHODS

We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort.

RESULTS

Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance.

CONCLUSIONS/INTERPRETATION

Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores.

DATA AVAILABILITY

Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

The causal relationship between metabolic factors, drinking, smoking and intrahepatic cholangiocarcinoma: a Mendelian randomization study

Background

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer. While multiple risk factors for iCCA have been established, metabolic diseases (obesity, diabetes, NAFLD, dyslipidemia, and hypertension) and other risk factors, including smoking and drinking, are still controversial due to their potential confounders. Here, Mendelian randomization (MR) analysis was performed to identify the causal relationship between them.

Method

In this study, we obtained GWAS data related to exposures from corresponding large genome-wide association studies. Summary-level statistical data for iCCA were obtained from the UK Biobank (UKB). We performed a univariable MR analysis to identify whether genetic evidence of exposure was significantly associated with iCCA risk. A multivariable MR analysis was conducted to estimate the independent effects of exposures on iCCA.

Results

Univariable and multivariable MR analysis based on the large GWAS data indicated that there is little evidence to support the genetic role of metabolic factors, smoking, drinking, and NAFLD in iCCA development (P >0.05). In contrast to most current studies, their impact on iCCA development, if any, might be smaller than we thought. The previous positive results might be due to the comorbidities between diseases and potentially unavoidable confounding factors.

Conclusion

In this MR study, we found no strong evidence to support causal associations between metabolic factors, NAFLD, smoking, drinking, and iCCA risk.

Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes

The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10^-9 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis improves the fine-mapping precision and the prediction performance of polygenic scores in under-represented populations. These genetic variants are enriched for Wnt signaling and neuron differentiation and affect cognition, emotion and neuropsychiatric disorders. These findings may provide insight into the genetic architectures of hippocampal and subfield volumes.

Genetically proxied impaired GIPR signaling and risk of 6 cancers

Preclinical and genetic studies suggest that impaired glucose-dependent insulinotropic polypeptide receptor (GIPR) signaling worsens glycemic control. The relationship between GIPR signaling and the risk of cancers influenced by impaired glucose homeostasis is unclear. We examined the association of a variant in GIPR, rs1800437 (E354Q), shown to impair long-term GIPR signaling and lower circulating glucose-dependent insulinotropic peptide concentrations, with risk of 6 cancers influenced by impaired glucose homeostasis (breast, colorectal, endometrial, lung, pancreatic, and renal) in up to 235,698 cases and 333,932 controls. Each copy of E354Q was associated with a higher risk of overall and luminal A-like breast cancer and this association was consistent in replication and colocalization analyses. E354Q was also associated with higher postprandial glucose concentrations but diminished insulin secretion and lower testosterone concentrations. Our human genetics analysis suggests an adverse effect of the GIPR E354Q variant on breast cancer risk, supporting further evaluation of GIPR signaling in breast cancer prevention.

Characterizing common and rare variations in non-traditional glycemic biomarkers using multivariate approaches on multi-ancestry ARIC study

Glycated hemoglobin, fasting glucose, glycated albumin, and fructosamine are biomarkers that reflect different aspects of the glycemic process. Genetic studies of these glycemic biomarkers can shed light on unknown aspects of type 2 diabetes genetics and biology. While there exists several GWAS of glycated hemoglobin and fasting glucose, very few GWAS have focused on glycated albumin or fructosamine. We performed a multi-phenotype GWAS of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on the common variants from genotyped/imputed data. We found 2 genome-wide significant loci, one mapping to known type 2 diabetes gene (ARAP1/STARD10, p = 2.8 × 10-8) and another mapping to a novel gene (UGT1A, p = 1.4 × 10-8) using multi-omics gene mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry-specific (e.g., PRKCA from African ancestry individuals, p = 1.7 × 10-8) and sex-specific (TEX29 locus in males only, p = 3.0 × 10-8). Further, we implemented multi-phenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Eleven genes across different rare variant aggregation strategies were exome-wide significant only in multi-ancestry analysis. Four out of 11 genes had notable enrichment of rare predicted loss of function variants in African ancestry participants despite smaller sample size. Overall, 8 out of 15 loci/genes were implicated to influence these biomarkers via glycemic pathways. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across entire allele frequency spectrum in multi-ancestry analyses. Most of the loci/genes we identified have not been previously implicated in studies of type 2 diabetes, and future investigation of the loci/genes potentially acting through glycemic pathways may help us better understand risk of developing type 2 diabetes.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes

BACKGROUND

Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear.

RESULTS

By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection.

CONCLUSIONS

Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.