Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

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

Plasma proteomic associations with genetics and health in the UK Biobank.

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Genetic predisposition to mosaic Y chromosome loss in blood.

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1-5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.

The genetic architecture of type 2 diabetes.

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

Visual deterioration in patients with photoreceptor loss after retinal reattachment surgery.

PURPOSE: Assess the relationship between photoreceptor degeneration and visual function after retinal reattachment surgery (RRS) in a prospective cohort. METHODS: Patients with rhegmatogenous retinal detachment (RRD) were reviewed before and 6 months after vitreoretinal surgery. Optical coherence tomographical thickness of the outer nuclear layer (ONL), outer retinal segment (ORS), retinal pigmented epithelium to ellipsoid zone (RPE-EZ) and external limiting membrane to EZ (ELM-EZ) were recorded 6 months post-operatively. These were compared to best corrected visual acuity (BCVA) and retinal sensitivity (Humphrey visual field). RESULTS: Thirteen macula-off and 8 macula-on RRD patients were included. The mean ONL thickness was higher after macula-on RRD compared to macula-off RRD (97.70 ± 3.62 µm vs. 73.10 ± 4.98 µm). In all RRD eyes, every 1 µm decrease in ONL thickness correlated with a 0.052 dB decrease and in retinal sensitivity and every 1 µm decrease in ORS thickness was associated with a 0.062 dB reduction in retinal sensitivity. ORS, ELM-EZ and RPE-EZ thickness did not correlate with BCVA post-RRS. CONCLUSION: There was greater ONL and ORS thinning following macula-off compared to macula-on RRD. Correlations between ONL and ORS thinning with decreased retinal sensitivity may be explained by RRD-induced photoreceptor death.

MR Measures of Small Bowel Wall T2 Are Associated With Increased Permeability.

BACKGROUND: Increased small bowel permeability leads to bacterial translocation, associated with significant morbidity and mortality. Biomarkers are needed to evaluate these changes in vivo, stratify an individual's risk, and evaluate the efficacy of interventions. MRI is an established biomarker of small bowel inflammation. PURPOSE: To characterize changes in the small bowel with quantitative MRI measures associated with increased permeability induced by indomethacin. STUDY TYPE: Prospective single-center, double-blind, two-way crossover provocation study. SUBJECTS: A provocation cohort (22 healthy volunteers) and intrasubject reproducibility cohort (8 healthy volunteers). FIELD STRENGTH/SEQUENCE: 2D balanced turbo field echo sequences to measure small bowel wall thickness, T2 , and motility acquired at 3T. ASSESSMENT: Participants were randomized to receive indomethacin or placebo prior to assessment. After a minimum 2-week washout, measures were repeated with the alternative allocation. MR measures (wall thickness, T2 , motility) at each study visit were compared to the reference standard 2-hour lactulose/mannitol urinary excretion ratio (LMR) test performed by a lab technician. All analyses were performed blind. STATISTICAL TESTS: Normality was tested (Shapiro-Wilk's test). Paired testing (Student's t-test or Wilcoxon) determined the significance of paired differences with indomethacin provocation. Pearson's correlation coefficient compared significant measures with indomethacin provocation to LMR. Intrasubject (intraclass correlation) and interrater variability (Bland-Altman) were assessed. RESULTS: Indomethacin provocation induced a significant increase in LMR compared to placebo (P < 0.05) and a significant increase in small bowel T2 (0.12 seconds compared to placebo 0.07 seconds, P < 0.05). Small bowel wall thickness (P = 0.17) and motility (P = 0.149) showed no significant change. T2 and LMR were positively correlated (r = 0.68, P < 0.05). T2 measurements were robust to interobserver (intraclass correlation 0.89) and intrasubject variability (Bland-Altman bias of 0.005 seconds, 95% confidence interval [CI] -0.04 to +0.05 seconds, and 0.0006 seconds, 95% CI -0.05 to +0.06 seconds). DATA CONCLUSION: MR measures of small bowel wall T2 were significantly increased following indomethacin provocation and correlated with 2-hour LMR test results. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions.

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann-Whitney = 1.46×10-5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

[This corrects the article DOI: 10.1371/journal.pgen.1006528.].

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.

BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9.

BACKGROUND: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. METHODS: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. RESULTS: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable. CONCLUSIONS: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

Interplay between genetic predisposition, macronutrient intake and type 2 diabetes incidence: analysis within EPIC-InterAct across eight European countries.

AIMS/HYPOTHESIS: Gene-macronutrient interactions may contribute to the development of type 2 diabetes but research evidence to date is inconclusive. We aimed to increase our understanding of the aetiology of type 2 diabetes by investigating potential interactions between genes and macronutrient intake and their association with the incidence of type 2 diabetes. METHODS: We investigated the influence of interactions between genetic risk scores (GRSs) for type 2 diabetes, insulin resistance and BMI and macronutrient intake on the development of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a prospective case-cohort study across eight European countries (N = 21,900 with 9742 incident type 2 diabetes cases). Macronutrient intake was estimated from diets reported in questionnaires, including proportion of energy derived from total carbohydrate, protein, fat, plant and animal protein, saturated, monounsaturated and polyunsaturated fat and dietary fibre. Using multivariable-adjusted Cox regression, we estimated country-specific interaction results on the multiplicative scale, using random-effects meta-analysis. Secondary analysis used isocaloric macronutrient substitution. RESULTS: No interactions were identified between any of the three GRSs and any macronutrient intake, with low-to-moderate heterogeneity between countries (I2 range 0-51.6%). Results were similar using isocaloric macronutrient substitution analyses and when weighted and unweighted GRSs and individual SNPs were examined. CONCLUSIONS/INTERPRETATION: Genetic susceptibility to type 2 diabetes, insulin resistance and BMI did not modify the association between macronutrient intake and incident type 2 diabetes. This suggests that macronutrient intake recommendations to prevent type 2 diabetes do not need to account for differences in genetic predisposition to these three metabolic conditions.

SurR is a master regulator of the primary electron flow pathways in the order Thermococcales.

The sulfur response regulator, SurR, is among a handful of known redox-active transcriptional regulators. First characterized from the hyperthermophile Pyrococcus furiosus, it is unique to the archaeal order Thermococcales. P. furiosus has two modes of electron disposal. Hydrogen gas is produced when the organism is grown in the absence of elemental sulfur (S0 ) and H2 S is produced when grown in its presence. Switching between these metabolic modes requires a rapid transcriptional response and this is orchestrated by SurR. We show here that deletion of SurR causes severely impaired growth in the absence of S0 since genes essential for H2 metabolism are no longer activated. Conversely, a strain containing a constitutively active SurR variant displays a growth phenotype in the presence of S0 due to constitutive repression of S0 -responsive genes. During a metabolic shift initiated by addition of S0 to the growth medium, both strains demonstrate a de-regulation of genes involved in the SurR regulon, including hydrogenase and related S0 -responsive genes. These results demonstrate that SurR is a master regulator of electron flow within P. furiosus, likely affecting the pools of ferredoxin, NADPH and NADH, as well as influencing metabolic pathways and thiol/disulfide redox balance.

Testing the role of predicted gene knockouts in human anthropometric trait variation.

Although the role of complete gene inactivation by two loss-of-function mutations inherited in trans is well-established in recessive Mendelian diseases, we have not yet explored how such gene knockouts (KOs) could influence complex human phenotypes. Here, we developed a statistical framework to test the association between gene KOs and quantitative human traits. Our method is flexible, publicly available, and compatible with common genotype format files (e.g. PLINK and vcf). We characterized gene KOs in 4498 participants from the NHLBI Exome Sequence Project (ESP) sequenced at high coverage (>100×), 1976 French Canadians from the Montreal Heart Institute Biobank sequenced at low coverage (5.7×), and >100 000 participants from the Genetic Investigation of ANthropometric Traits (GIANT) Consortium genotyped on an exome array. We tested associations between gene KOs and three anthropometric traits: body mass index (BMI), height and BMI-adjusted waist-to-hip ratio (WHR). Despite our large sample size and multiple datasets available, we could not detect robust associations between specific gene KOs and quantitative anthropometric traits. Our results highlight several limitations and challenges for future gene KO studies in humans, in particular when there is no prior knowledge on the phenotypes that might be affected by the tested gene KOs. They also suggest that gene KOs identified with current DNA sequencing methodologies probably do not strongly influence normal variation in BMI, height, and WHR in the general human population.

Analysis with the exome array identifies multiple new independent variants in lipid loci.

It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.

Multi-organ assessment of compensated cirrhosis patients using quantitative magnetic resonance imaging.

BACKGROUND & AIMS: Advancing liver disease results in deleterious changes in a number of critical organs. The ability to measure structure, blood flow and tissue perfusion within multiple organs in a single scan has implications for determining the balance of benefit vs. harm for therapies. Our aim was to establish the feasibility of magnetic resonance imaging (MRI) to assess changes in Compensated Cirrhosis (CC), and relate this to disease severity and future liver-related outcomes (LROs). METHODS: A total of 60 patients with CC, 40 healthy volunteers and 7 patients with decompensated cirrhosis were recruited. In a single scan session, MRI measures comprised phase-contrast MRI vessel blood flow, arterial spin labelling tissue perfusion, T1 longitudinal relaxation time, heart rate, cardiac index, and volume assessment of the liver, spleen and kidneys. We explored the association between MRI parameters and disease severity, analysing differences in baseline MRI parameters in the 11 (18%) patients with CC who experienced future LROs. RESULTS: In the liver, compositional changes were reflected by increased T1 in progressive disease (p <0.001) and an increase in liver volume in CC (p = 0.006), with associated progressive reduction in liver (p <0.001) and splenic (p <0.001) perfusion. A significant reduction in renal cortex T1 and increase in cardiac index and superior mesenteric arterial blood flow was seen with increasing disease severity. Baseline liver T1 (p = 0.01), liver perfusion (p <0.01), and renal cortex T1 (p <0.01) were significantly different in patients with CC who subsequently developed negative LROs. CONCLUSIONS: MRI enables the contemporaneous assessment of organs in liver cirrhosis in a single scan without the requirement for a contrast agent. MRI parameters of liver T1, renal T1, hepatic and splenic perfusion, and superior mesenteric arterial blood flow were related to the risk of LROs. LAY SUMMARY: This study assesses the changes to structure, blood flow and perfusion that occur in the key organs (liver, spleen and kidney) associated with severe liver disease (Compensated Cirrhosis), using magnetic resonance imaging. The magnetic resonance imaging measures which changed with disease severity and were related to negative liver-related clinical outcomes are described.

Association of Genetic Variants Related to Gluteofemoral vs Abdominal Fat Distribution With Type 2 Diabetes, Coronary Disease, and Cardiovascular Risk Factors.

Importance: Body fat distribution, usually measured using waist-to-hip ratio (WHR), is an important contributor to cardiometabolic disease independent of body mass index (BMI). Whether mechanisms that increase WHR via lower gluteofemoral (hip) or via higher abdominal (waist) fat distribution affect cardiometabolic risk is unknown. Objective: To identify genetic variants associated with higher WHR specifically via lower gluteofemoral or higher abdominal fat distribution and estimate their association with cardiometabolic risk. Design, Setting, and Participants: Genome-wide association studies (GWAS) for WHR combined data from the UK Biobank cohort and summary statistics from previous GWAS (data collection: 2006-2018). Specific polygenic scores for higher WHR via lower gluteofemoral or via higher abdominal fat distribution were derived using WHR-associated genetic variants showing specific association with hip or waist circumference. Associations of polygenic scores with outcomes were estimated in 3 population-based cohorts, a case-cohort study, and summary statistics from 6 GWAS (data collection: 1991-2018). Exposures: More than 2.4 million common genetic variants (GWAS); polygenic scores for higher WHR (follow-up analyses). Main Outcomes and Measures: BMI-adjusted WHR and unadjusted WHR (GWAS); compartmental fat mass measured by dual-energy x-ray absorptiometry, systolic and diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, fasting glucose, fasting insulin, type 2 diabetes, and coronary disease risk (follow-up analyses). Results: Among 452 302 UK Biobank participants of European ancestry, the mean (SD) age was 57 (8) years and the mean (SD) WHR was 0.87 (0.09). In genome-wide analyses, 202 independent genetic variants were associated with higher BMI-adjusted WHR (n = 660 648) and unadjusted WHR (n = 663 598). In dual-energy x-ray absorptiometry analyses (n = 18 330), the hip- and waist-specific polygenic scores for higher WHR were specifically associated with lower gluteofemoral and higher abdominal fat, respectively. In follow-up analyses (n = 636 607), both polygenic scores were associated with higher blood pressure and triglyceride levels and higher risk of diabetes (waist-specific score: odds ratio [OR], 1.57 [95% CI, 1.34-1.83], absolute risk increase per 1000 participant-years [ARI], 4.4 [95% CI, 2.7-6.5], P < .001; hip-specific score: OR, 2.54 [95% CI, 2.17-2.96], ARI, 12.0 [95% CI, 9.1-15.3], P < .001) and coronary disease (waist-specific score: OR, 1.60 [95% CI, 1.39-1.84], ARI, 2.3 [95% CI, 1.5-3.3], P < .001; hip-specific score: OR, 1.76 [95% CI, 1.53-2.02], ARI, 3.0 [95% CI, 2.1-4.0], P < .001), per 1-SD increase in BMI-adjusted WHR. Conclusions and Relevance: Distinct genetic mechanisms may be linked to gluteofemoral and abdominal fat distribution that are the basis for the calculation of the WHR. These findings may improve risk assessment and treatment of diabetes and coronary disease.

General Framework for Meta-Analysis of Haplotype Association Tests.

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis.

BACKGROUND: Higher circulating levels of the branched-chain amino acids (BCAAs; i.e., isoleucine, leucine, and valine) are strongly associated with higher type 2 diabetes risk, but it is not known whether this association is causal. We undertook large-scale human genetic analyses to address this question. METHODS AND FINDINGS: Genome-wide studies of BCAA levels in 16,596 individuals revealed five genomic regions associated at genome-wide levels of significance (p < 5 × 10-8). The strongest signal was 21 kb upstream of the PPM1K gene (beta in standard deviations [SDs] of leucine per allele = 0.08, p = 3.9 × 10-25), encoding an activator of the mitochondrial branched-chain alpha-ketoacid dehydrogenase (BCKD) responsible for the rate-limiting step in BCAA catabolism. In another analysis, in up to 47,877 cases of type 2 diabetes and 267,694 controls, a genetically predicted difference of 1 SD in amino acid level was associated with an odds ratio for type 2 diabetes of 1.44 (95% CI 1.26-1.65, p = 9.5 × 10-8) for isoleucine, 1.85 (95% CI 1.41-2.42, p = 7.3 × 10-6) for leucine, and 1.54 (95% CI 1.28-1.84, p = 4.2 × 10-6) for valine. Estimates were highly consistent with those from prospective observational studies of the association between BCAA levels and incident type 2 diabetes in a meta-analysis of 1,992 cases and 4,319 non-cases. Metabolome-wide association analyses of BCAA-raising alleles revealed high specificity to the BCAA pathway and an accumulation of metabolites upstream of branched-chain alpha-ketoacid oxidation, consistent with reduced BCKD activity. Limitations of this study are that, while the association of genetic variants appeared highly specific, the possibility of pleiotropic associations cannot be entirely excluded. Similar to other complex phenotypes, genetic scores used in the study captured a limited proportion of the heritability in BCAA levels. Therefore, it is possible that only some of the mechanisms that increase BCAA levels or affect BCAA metabolism are implicated in type 2 diabetes. CONCLUSIONS: Evidence from this large-scale human genetic and metabolomic study is consistent with a causal role of BCAA metabolism in the aetiology of type 2 diabetes.