Identification and correction for collider bias in a genome-wide association study of diabetes-related heart failure.

Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) and has elevated incidence among individuals with HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted a genome-wide association study (GWAS) of diabetes-related HF with correction for collider bias. We first performed a GWAS of HF to identify genetic instrumental variables (GIVs) for HF and to enable bidirectional Mendelian randomization (MR) analysis between T2D and HF. We identified 61 genomic loci, significantly associated with all-cause HF in 114,275 individuals with HF and over 1.5 million controls of European ancestry. Using a two-sample bidirectional MR approach with 59 and 82 GIVs for HF and T2D, respectively, we estimated that T2D increased HF risk (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to the study design of index cases. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program and replicated the associations in the UK Biobank. Our MR findings provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci.

GWAS of longitudinal trajectories at biobank scale.

Biobanks linked to massive, longitudinal electronic health record (EHR) data make numerous new genetic research questions feasible. One among these is the study of biomarker trajectories. For example, high blood pressure measurements over visits strongly predict stroke onset, and consistently high fasting glucose and Hb1Ac levels define diabetes. Recent research reveals that not only the mean level of biomarker trajectories but also their fluctuations, or within-subject (WS) variability, are risk factors for many diseases. Glycemic variation, for instance, is recently considered an important clinical metric in diabetes management. It is crucial to identify the genetic factors that shift the mean or alter the WS variability of a biomarker trajectory. Compared to traditional cross-sectional studies, trajectory analysis utilizes more data points and captures a complete picture of the impact of time-varying factors, including medication history and lifestyle. Currently, there are no efficient tools for genome-wide association studies (GWASs) of biomarker trajectories at the biobank scale, even for just mean effects. We propose TrajGWAS, a linear mixed effect model-based method for testing genetic effects that shift the mean or alter the WS variability of a biomarker trajectory. It is scalable to biobank data with 100,000 to 1,000,000 individuals and many longitudinal measurements and robust to distributional assumptions. Simulation studies corroborate that TrajGWAS controls the type I error rate and is powerful. Analysis of eleven biomarkers measured longitudinally and extracted from UK Biobank primary care data for more than 150,000 participants with 1,800,000 observations reveals loci that significantly alter the mean or WS variability.

Integration of rare expression outlier-associated variants improves polygenic risk prediction.

Polygenic risk scores (PRSs) quantify the contribution of multiple genetic loci to an individual's likelihood of a complex trait or disease. However, existing PRSs estimate this likelihood with common genetic variants, excluding the impact of rare variants. Here, we report on a method to identify rare variants associated with outlier gene expression and integrate their impact into PRS predictions for body mass index (BMI), obesity, and bariatric surgery. Between the top and bottom 10%, we observed a 20.8% increase in risk for obesity (p = 3 × 10-14), 62.3% increase in risk for severe obesity (p = 1 × 10-6), and median 5.29 years earlier onset for bariatric surgery (p = 0.008), as a function of expression outlier-associated rare variant burden when controlling for common variant PRS. We show that these predictions were more significant than integrating the effects of rare protein-truncating variants (PTVs), observing a mean 19% increase in phenotypic variance explained with expression outlier-associated rare variants when compared with PTVs (p = 2 × 10-15). We replicated these findings by using data from the Million Veteran Program and demonstrated that PRSs across multiple traits and diseases can benefit from the inclusion of expression outlier-associated rare variants identified through population-scale transcriptome sequencing.

A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program.

BACKGROUND: Height has been associated with many clinical traits but whether such associations are causal versus secondary to confounding remains unclear in many cases. To systematically examine this question, we performed a Mendelian Randomization-Phenome-wide association study (MR-PheWAS) using clinical and genetic data from a national healthcare system biobank. METHODS AND FINDINGS: Analyses were performed using data from the US Veterans Affairs (VA) Million Veteran Program in non-Hispanic White (EA, n = 222,300) and non-Hispanic Black (AA, n = 58,151) adults in the US. We estimated height genetic risk based on 3290 height-associated variants from a recent European-ancestry genome-wide meta-analysis. We compared associations of measured and genetically-predicted height with phenome-wide traits derived from the VA electronic health record, adjusting for age, sex, and genetic principal components. We found 345 clinical traits associated with measured height in EA and an additional 17 in AA. Of these, 127 were associated with genetically-predicted height at phenome-wide significance in EA and 2 in AA. These associations were largely independent from body mass index. We confirmed several previously described MR associations between height and cardiovascular disease traits such as hypertension, hyperlipidemia, coronary heart disease (CHD), and atrial fibrillation, and further uncovered MR associations with venous circulatory disorders and peripheral neuropathy in the presence and absence of diabetes. As a number of traits associated with genetically-predicted height frequently co-occur with CHD, we evaluated effect modification by CHD status of genetically-predicted height associations with risk factors for and complications of CHD. We found modification of effects of MR associations by CHD status for atrial fibrillation/flutter but not for hypertension, hyperlipidemia, or venous circulatory disorders. CONCLUSIONS: We conclude that height may be an unrecognized but biologically plausible risk factor for several common conditions in adults. However, more studies are needed to reliably exclude horizontal pleiotropy as a driving force behind at least some of the MR associations observed in this study.

Design and pilot results from the Million Veteran Program Return Of Actionable Results (MVP-ROAR) Study.

BACKGROUND: As a mega-biobank linked to a national healthcare system, the Million Veteran Program (MVP) can directly improve the health care of participants. To determine the feasibility and outcomes of returning medically actionable genetic results to MVP participants, the program launched the MVP Return of Actionable Results (MVP-ROAR) Study, with familial hypercholesterolemia (FH) as an exemplar actionable condition. METHODS: The MVP-ROAR Study consists of a completed single-arm pilot phase and an ongoing randomized clinical trial (RCT), in which MVP participants are recontacted and invited to receive clinical confirmatory gene sequencing testing and a telegenetic counseling intervention. The primary outcome of the RCT is 6-month change in low-density lipoprotein cholesterol (LDL-C) between participants receiving results at baseline and those receiving results after 6 months. RESULTS: The pilot developed processes to identify and recontact participants nationally with probable pathogenic variants in low-density lipoprotein receptor (LDLR) on the MVP genotype array, invite them to clinical confirmatory gene sequencing, and deliver a telegenetic counseling intervention. Among participants in the pilot phase, 8 (100%) had active statin prescriptions after 6 months. Results were shared with 16 first-degree family members. Six-month ΔLDL-C (low-density lipoprotein cholesterol) after the genetic counseling intervention was -37 mg/dL (95% CI: -12 to -61; P = .03). The ongoing RCT will determine between-arm differences in this primary outcome. CONCLUSION: While underscoring the importance of clinical confirmation of research results, the pilot phase of the MVP-ROAR Study marks a turning point in MVP and demonstrates the feasibility of returning genetic results to participants and their providers. The ongoing RCT will contribute to understanding how such a program might improve patient health care and outcomes. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov ID NCT04178122.

Maternal and Offspring Fatty Acid Desaturase Variants, Prenatal DHA Supplementation, and Dietary n-6:n-3 Fatty Acid Ratio in Relation to Cardiometabolic Health in Mexican Children.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) in fatty acid desaturase (FADS) genes may modify dietary fatty acid requirements and influence cardiometabolic health (CMH). OBJECTIVES: We evaluated the role of selected variants in maternal and offspring FADS genes on offspring CMH at the age of 11 y and assessed interactions of genotype with diet quality and prenatal docosahexaenoic acid (DHA) supplementation. METHODS: We used data from offspring (n = 203) born to females who participated in a randomized controlled trial of DHA supplementation (400 mg/d) from midgestation to delivery. We generated a metabolic syndrome (MetS) score from body mass index, high-density lipoprotein cholesterol, triglycerides, systolic blood pressure, and fasting glucose and identified 6 distinct haplotypes from 5 offspring FADS SNPs. Dietary n-6 (ω-6):n-3 fatty acid ratios were derived from 24-h recall data (n = 141). We used generalized linear models to test associations of offspring diet and FADS haplotypes with MetS score and interactions of maternal and offspring FADS SNP rs174602 with prenatal treatment group and dietary n-6:n-3 ratio on MetS score. RESULTS: Associations between FADS haplotypes and MetS score were null. Offspring SNP rs174602 did not modify the association of prenatal DHA supplementation with MetS score. Among children with TT or TC genotype for SNP rs174602 (n = 88), those in the highest n-6:n-3 ratio tertile (>8.61) had higher MetS score relative to the lowest tertile [<6.67) (Δ= 0.36; 95% confidence interval (CI): 0.03, 0.69]. Among children with CC genotype (n = 53), those in the highest n-6:n-3 ratio tertile had a lower MetS score relative to the lowest tertile (Δ= -0.23; 95% CI: -0.61, 0.16). CONCLUSIONS: There was evidence of an interaction of offspring FADS SNP rs174602 with current dietary polyunsaturated fatty acid intake, but not with prenatal DHA supplementation, on MetS score. Further studies may help to determine the utility of targeted supplementation strategies and dietary recommendations based on genetic profile.

Epigenetic associations with kidney disease in individuals of African ancestry with APOL1 high-risk genotypes and Human Immunodeficiency Virus.

BACKGROUND: Apolipoprotein L1 (APOL1) high-risk variants are major determinants of chronic kidney disease (CKD) in people of African ancestry. Previous studies have identified epigenetic changes in relation to kidney function and CKD, but not in individuals with APOL1 high-risk genotypes. We conducted an epigenome-wide analysis of CKD and estimated glomerular filtration rate (eGFR) in in people of African ancestry and APOL1 high-risk genotypes with HIV. METHODS: DNA methylation profiles from peripheral blood mononuclear cells of 119 individuals with APOL1 high-risk genotypes (mean age 48 years, 49% female, median CD4 count 515 cells/mm3, 90% HIV-1 RNA <200 copies/mL, 23% with CKD) were obtained by Illumina MethylationEPIC BeadChip. Differential methylation analysis of CKD considered technical and biological covariates. We also assessed associations with eGFR. Replication was pursued in three independent multi-ancestry cohorts with and without HIV. RESULTS: DNA methylation levels at 14 regions were associated with CKD. The strongest signals were located in SCARB1, DNAJC5B and C4orf50. Seven of the 14 signals also associated with eGFR, and most showed evidence for a genetic basis. Four signals (in SCARB1, FRMD4A, CSRNP1 and RAB38) replicated in other cohorts, and 11 previously reported epigenetic signals for kidney function or CKD replicated in our cohort. We found no significant DNA methylation signals in, or near, the APOL1 promoter region. CONCLUSIONS: We report several novel as well as previously reported epigenetic associations with CKD and eGFR in individuals with HIV having APOL1 high-risk genotypes. Further investigation of pathways linking DNA methylation to APOL1 nephropathies is warranted.

Interaction between genetics and smoking in determining risk of coronary artery diseases.

Coronary artery disease (CAD) is a preeminent cause of death, and smoking is a strong risk factor for CAD. Genetic factors contribute to the development of CAD, but the interplay between genetic predisposition and smoking history in CAD remains unclear. Using data from the UK Biobank, we constructed several genetic risk scores (GRSs) based on known CAD loci and assessed their interactions with smoking for the development of incident CAD in 307,147 participants of European ancestry who were free of CAD. We fitted Cox proportional hazard models and assessed gene-smoking interaction on both multiplicative and additive scales. Overall, we found no multiplicative interactions, but observed a synergistic additive interaction of GRS with both smoking status and pack-years of smoking, finding that the absolute CAD risk due to smoking was higher for those with high genetic risk. Trait-based sub-GRSs suggested smoking status and smoking intensity measured by pack-years might confer gene-smoking interaction effects with different intermediate risk factors for CAD. Our study results suggest that genetics could modify the effects of smoking on CAD and highlight the value of addressing gene-lifestyle interactions on both additive and multiplicative scales.

Epigenetic Age Acceleration Markers Are Associated With Physiologic Frailty and All-Cause Mortality in People With Human Immunodeficiency Virus.

BACKGROUND: Biomarkers that provide insight into drivers of aging are needed for people with human immunodeficiency virus (PWH). The study objective was to determine if epigenetic age acceleration (EAA) markers are associated with physiologic frailty measured by the Veterans Aging Cohort Study (VACS) Index and predict all-cause mortality for PWH. METHODS: Epigenome-wide DNA methylation was profiled in VACS total white blood cell samples collected during 2005-2007 from 531 PWH to generate 6 established markers of EAA. The association of each EAA marker was tested with VACS Index 2.0. All-cause mortality was assessed over 10 years. For each EAA marker, the hazard ratio per increased year was determined using Cox regression. To evaluate mortality discrimination, C-statistics were derived. RESULTS: Participants were mostly men (98.5%) and non-Hispanic Black (84.4%), with a mean age of 52.4 years (standard deviation [SD], 7.8 years). Mean VACS Index score was 59.3 (SD, 16.4) and 136 deaths occurred over a median follow-up of 8.7 years. Grim age acceleration (AA), PhenoAA, HannumAA, and extrinsic epigenetic AA were associated with the VACS Index and mortality. HorvathAA and intrinsic epigenetic AA were not associated with either outcome. GrimAA had the greatest mortality discrimination among EAA markers and predicted mortality independently of the VACS Index. One-year increase in GrimAA was associated with a 1-point increase in VACS Index and a 10% increased hazard for mortality. CONCLUSIONS: The observed associations between EAA markers with physiologic frailty and mortality support future research to provide mechanistic insight into the accelerated aging process and inform interventions tailored to PWH for promoting increased healthspan.

A MUC5B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality.

Rationale: A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). Methods: The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post-COVID-19 pneumonia were performed in MVP subjects. Measurements and Main Results: The rs35705950-T allele was associated with fewer COVID-19 hospitalizations in transancestry meta-analyses within the MVP (Ncases = 4,325; Ncontrols = 507,640; OR = 0.89 [0.82-0.97]; P = 6.86 × 10-3) and joint meta-analyses with the HGI (Ncases = 13,320; Ncontrols = 1,508,841; OR, 0.90 [0.86-0.95]; P = 8.99 × 10-5). The rs35705950-T allele was not associated with reduced COVID-19 positivity in transancestry meta-analysis within the MVP (Ncases = 19,168/Ncontrols = 492,854; OR, 0.98 [0.95-1.01]; P = 0.06) but was nominally significant (P < 0.05) in the joint meta-analysis with the HGI (Ncases = 44,820; Ncontrols = 1,775,827; OR, 0.97 [0.95-1.00]; P = 0.03). Associations were not observed with severe outcomes or mortality. Among individuals of European ancestry in the MVP, rs35705950-T was associated with fewer post-COVID-19 pneumonia events (OR, 0.82 [0.72-0.93]; P = 0.001). Conclusions: The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

Latent Class Analysis of Depressive Symptom Phenotypes Among Black/African American Mothers.

BACKGROUND: Depression is a growing global problem with significant individual and societal costs. Despite their consequences, depressive symptoms are poorly recognized and undertreated because wide variation in symptom presentation limits clinical identification-particularly among African American (AA) women-an understudied population at an increased risk of health inequity. OBJECTIVES: The aims of this study were to explore depressive symptom phenotypes among AA women and examine associations with epigenetic, cardiometabolic, and psychosocial factors. METHODS: This cross-sectional, retrospective analysis included self-reported Black/AA mothers from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure study (data collected in 2015-2020). Clinical phenotypes were identified using latent class analysis. Bivariate logistic regression examined epigenetic age, cardiometabolic traits (i.e., body mass index ≥ 30 kg/m 2 , hypertension, or diabetes), and psychosocial variables as predictors of class membership. RESULTS: All participants were Black/AA and predominantly non-Hispanic. Over half of the sample had one or more cardiometabolic traits. Two latent classes were identified (low vs. moderate depressive symptoms). Somatic and self-critical symptoms characterized the moderate symptom class. Higher stress overload scores significantly predicted moderate-symptom class membership. DISCUSSION: In this sample of AA women with increased cardiometabolic burden, increased stress was associated with depressive symptoms that standard screening tools may not capture. Research examining the effect of specific stressors and the efficacy of tools to identify at-risk AA women are urgently needed to address disparities and mental health burdens.

Genetic determinants of increased body mass index mediate the effect of smoking on increased risk for type 2 diabetes but not coronary artery disease.

Clinical observations have linked tobacco smoking with increased type 2 diabetes risk. Mendelian randomization analysis has recently suggested smoking may be a causal risk factor for type 2 diabetes. However, this association could be mediated by additional risk factors correlated with smoking behavior, which have not been investigated. We hypothesized that body mass index (BMI) could help to explain the association between smoking and diabetes risk. First, we confirmed that genetic determinants of smoking initiation increased risk for type 2 diabetes (OR 1.21, 95% CI: 1.15-1.27, P = 1 × 10-12) and coronary artery disease (CAD; OR 1.21, 95% CI: 1.16-1.26, P = 2 × 10-20). Additionally, 2-fold increased smoking risk was positively associated with increased BMI (~0.8 kg/m2, 95% CI: 0.54-0.98 kg/m2, P = 1.8 × 10-11). Multivariable Mendelian randomization analyses showed that BMI accounted for nearly all the risk smoking exerted on type 2 diabetes (OR 1.06, 95% CI: 1.01-1.11, P = 0.03). In contrast, the independent effect of smoking on increased CAD risk persisted (OR 1.12, 95% CI: 1.08-1.17, P = 3 × 10-8). Causal mediation analyses agreed with these estimates. Furthermore, analysis using individual-level data from the Million Veteran Program independently replicated the association of smoking behavior with CAD (OR 1.24, 95% CI: 1.12-1.37, P = 2 × 10-5), but not type 2 diabetes (OR 0.98, 95% CI: 0.89-1.08, P = 0.69), after controlling for BMI. Our findings support a model whereby genetic determinants of smoking increase type 2 diabetes risk indirectly through their relationship with obesity. Smokers should be advised to stop smoking to limit type 2 diabetes and CAD risk. Therapeutic efforts should consider pathophysiology relating smoking and obesity.

Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies.

Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs.

GEM: scalable and flexible gene-environment interaction analysis in millions of samples.

MOTIVATION: Gene-environment interaction (GEI) studies are a general framework that can be used to identify genetic variants that modify the effects of environmental, physiological, lifestyle or treatment effects on complex traits. Moreover, accounting for GEIs can enhance our understanding of the genetic architecture of complex diseases and traits. However, commonly used statistical software programs for GEI studies are either not applicable to testing certain types of GEI hypotheses or have not been optimized for use in large samples. RESULTS: Here, we develop a new software program, GEM (Gene-Environment interaction analysis in Millions of samples), which supports the inclusion of multiple GEI terms, adjustment for GEI covariates and robust inference, while allowing multi-threading to reduce computation time. GEM can conduct GEI tests as well as joint tests of genetic main and interaction effects for both continuous and binary phenotypes. Through simulations, we demonstrate that GEM scales to millions of samples while addressing limitations of existing software programs. We additionally conduct a gene-sex interaction analysis on waist-hip ratio in 352 768 unrelated individuals from the UK Biobank, identifying 24 novel loci in the joint test that have not previously been reported in combined or sex-specific analyses. Our results demonstrate that GEM can facilitate the next generation of large-scale GEI studies and help advance our understanding of the genetic architecture of complex diseases and traits. AVAILABILITY AND IMPLEMENTATION: GEM is freely available as an open source project at https://github.com/large-scale-gxe-methods/GEM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Association Between Posttraumatic Stress Disorder and Epigenetic Age Acceleration in a Sample of Twins.

OBJECTIVE: Posttraumatic stress disorder (PTSD) has been related to accelerated biological aging processes, but objective evidence for this association is limited. DNA methylation (DNAm) age acceleration is a novel measure of biological aging that may help clarify if PTSD is related to biological aging processes. We aim to examine whether PTSD is associated with biological aging using a comprehensive set of DNAm age acceleration markers and to what extent the unshared environment contributes to the association. METHODS: Using a cross-sectional co-twin control study design, we investigated the association of the clinical diagnosis and symptom severity of PTSD with six measurements of DNAm age acceleration based on epigenome-wide data derived from peripheral blood lymphocytes of 296 male twins from the Vietnam Era Twin Registry. RESULTS: Twins with current PTSD had significantly advanced DNAm age acceleration compared with twins without PTSD for five of six measures of DNAm age acceleration. Across almost all measures of DNAm age acceleration, twins with current PTSD were "epigenetically older" than their twin brothers without PTSD: estimated differences ranged between 1.6 (95% confidence interval = 0.0-3.1) and 2.7 (95% confidence interval = 0.5-4.8) biological age year-equivalents. A higher Clinician-Administered PTSD Scale score was also associated with a higher within-pair DNAm age acceleration. Results remained consistent after adjustment for behavioral and cardiovascular risk factors. CONCLUSIONS: PTSD is associated with epigenetic age acceleration, primarily through unshared environmental mechanisms as opposed to genetic or familial factors. These results suggest that PTSD is related to systemic processes relevant to biological aging.

Obesity-associated metabolites in relation to type 2 diabetes risk: A prospective nested case-control study of the CARRS cohort.

AIMS: To determine whether obesity-associated metabolites are associated with type 2 diabetes (T2DM) risk among South Asians. MATERIALS AND METHODS: Serum-based nuclear magnetic resonance imaging metabolomics data were generated from two South Asian population-based prospective cohorts from Karachi, Pakistan: CARRS1 (N = 4017) and CARRS2 (N = 4802). Participants in both cohorts were followed up for 5 years and incident T2DM was ascertained. A nested case-control study approach was developed to select participants from CARRS1 (Ncases  = 197 and Ncontrols  = 195) and CARRS2 (Ncases  = 194 and Ncontrols  = 200), respectively. First, we investigated the association of 224 metabolites with general obesity based on body mass index and with central obesity based on waist-hip ratio, and then the top obesity-associated metabolites were studied in relation to incident T2DM. RESULTS: In a combined sample of the CARRS1 and CARRS2 cohorts, out of 224 metabolites, 12 were associated with general obesity and, of these, one was associated with incident T2DM. Fifteen out of 224 metabolites were associated with central obesity and, of these, 10 were associated with incident T2DM. The higher level of total cholesterol in high-density lipoprotein (HDL) was associated with reduced T2DM risk (odds ratio [OR] 0.68, 95% confidence interval [CI] 0.53, 0.86; P = 1.2 × 10-3 ), while higher cholesterol esters in large very-low-density lipoprotein (VLDL) particles were associated with increased T2DM risk (OR 1.90, 95% CI 1.40, 2.58; P = 3.5 × 10-5 ). CONCLUSION: Total cholesterol in HDL and cholesterol esters in large VLDL particles may be an important biomarker in the identification of early development of obesity-associated T2DM risk among South Asian adults.

Mendelian Randomization Analysis of Hemostatic Factors and Their Contribution to Peripheral Artery Disease-Brief Report.

BACKGROUND AND OBJECTIVE: Peripheral artery disease (PAD) is the third most common form of atherosclerotic vascular disease and is characterized by significant functional disability and increased cardiovascular mortality. Recent genetic data support a role for a procoagulation protein variant, the factor V Leiden mutation, in PAD. The role of other hemostatic factors in PAD remains unknown. We evaluated the role of hemostatic factors in PAD using Mendelian randomization. Approach and Results: Two-sample Mendelian randomization to evaluate the roles of FVII (factor VII), FVIII (factor VIII), FXI (factor XI), VWF (von Willebrand factor), and fibrinogen in PAD was performed using summary statistics from GWAS for hemostatic factors performed within the Cohorts for Heart and Aging Research in the Genome Epidemiology Consortium and from GWAS performed for PAD within the Million Veteran Program. Genetically determined FVIII and VWF, but not FVII, FXI, or fibrinogen, were associated with PAD in Mendelian randomization experiments (FVIII: odds ratio, 1.41 [95% CI, 1.23-1.62], P=6.0×10-7, VWF: odds ratio, 1.28 [95% CI, 1.07-1.52], P=0.0073). In single variant sensitivity analysis, the ABO locus was the strongest genetic instrument for both FVIII and VWF. CONCLUSIONS: Our results suggest a role for hemostasis, and by extension, thrombosis in PAD. Further study is warranted to determine whether VWF and FVIII independently affect the biology of PAD.

Association between depression and epigenetic age acceleration: A co-twin control study.

INTRODUCTION: Prior studies have shown inconsistent findings of an association between depression and epigenetic aging. DNA methylation (DNAm) age acceleration can measure biological aging. We adopted a robust co-twin control study design to examine whether depression is associated with DNAm age acceleration after accounting for the potential confounding influences of genetics and family environment. METHODS: We analyzed data on a sub-cohort of the Vietnam Era Twin Registry. A total of 291 twins participated at baseline and 177 at follow-up visit after a mean of 11.7 years, with 111 participants having DNA samples for both time points. Depression was measured using the Beck Depression Inventory II (BDI-II). Six measures of DNAm age acceleration were computed at each time point, including Horvath's DNAm age acceleration (HorvathAA), intrinsic epigenetic age acceleration (IEAA), Hannum's DNAm age acceleration (HannumAA), extrinsic epigenetic age acceleration (EEAA), GrimAge acceleration (GrimAA), and PhenoAge acceleration (PhenoAA). Mixed-effects modeling was used to assess the within-pair association between depression and DNAm age acceleration. RESULTS: At baseline, a 10-unit higher BDI-II total score was associated with HannumAA (0.73 years, 95% confidence interval [CI] 0.13-1.33, p = .019) and EEAA (0.94 years, 95% CI 0.22-1.66, p = .012). At follow-up, 10-unit higher BDI-II score was associated with PhenoAA (1.32 years, 95% CI 0.18-2.47, p = .027). CONCLUSION: We identified that depression is associated with higher levels of DNAm age acceleration. Further investigation is warranted to better understand the underlying mechanisms for the potential causal relationship between depression and accelerated aging.

Genome-wide analysis identifies novel susceptibility loci for myocardial infarction.

AIMS: While most patients with myocardial infarction (MI) have underlying coronary atherosclerosis, not all patients with coronary artery disease (CAD) develop MI. We sought to address the hypothesis that some of the genetic factors which establish atherosclerosis may be distinct from those that predispose to vulnerable plaques and thrombus formation. METHODS AND RESULTS: We carried out a genome-wide association study for MI in the UK Biobank (n∼472 000), followed by a meta-analysis with summary statistics from the CARDIoGRAMplusC4D Consortium (n∼167 000). Multiple independent replication analyses and functional approaches were used to prioritize loci and evaluate positional candidate genes. Eight novel regions were identified for MI at the genome wide significance level, of which effect sizes at six loci were more robust for MI than for CAD without the presence of MI. Confirmatory evidence for association of a locus on chromosome 1p21.3 harbouring choline-like transporter 3 (SLC44A3) with MI in the context of CAD, but not with coronary atherosclerosis itself, was obtained in Biobank Japan (n∼165 000) and 16 independent angiography-based cohorts (n∼27 000). Follow-up analyses did not reveal association of the SLC44A3 locus with CAD risk factors, biomarkers of coagulation, other thrombotic diseases, or plasma levels of a broad array of metabolites, including choline, trimethylamine N-oxide, and betaine. However, aortic expression of SLC44A3 was increased in carriers of the MI risk allele at chromosome 1p21.3, increased in ischaemic (vs. non-diseased) coronary arteries, up-regulated in human aortic endothelial cells treated with interleukin-1ß (vs. vehicle), and associated with smooth muscle cell migration in vitro. CONCLUSIONS: A large-scale analysis comprising ∼831 000 subjects revealed novel genetic determinants of MI and implicated SLC44A3 in the pathophysiology of vulnerable plaques.

Depressive Symptoms and Blood Pressure in African American Women: A Secondary Analysis From the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure Study.

BACKGROUND: Depression is a risk factor for hypertension, yet few studies have been conducted in African American women. OBJECTIVE: We conducted a secondary analysis of depressive symptoms and high blood pressure among African American women from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure longitudinal study (N = 250). METHODS: Logistic regression was used to examine depressive symptoms and blood pressure, adjusting for education, employment, and racism/discrimination. Growth curve modeling was used to investigate longitudinal associations between depressive symptoms and systolic (SBP) and diastolic (DBP) blood pressures at 4 time points (T1-T4). RESULTS: Depressive symptoms at baseline were not prospectively associated with hypertension prevalence. Participants with Beck Depression Inventory scores higher than 10 had higher estimated marginal SBP and DBP over time compared with participants with lower scores. CONCLUSION: Depressive symptoms were not associated with hypertension prevalence at T4, but they were associated with higher estimated marginal SBP and DBP. Future research is needed to elucidate mechanisms and implications for clinical care and prevention.