Browsing by Author "Hauser, Elizabeth R"
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Item Open Access A functional polymorphism in the 5HTR2C gene associated with stress responses also predicts incident cardiovascular events.(PLoS One, 2013) Brummett, Beverly H; Babyak, Michael A; Jiang, Rong; Shah, Svati H; Becker, Richard C; Haynes, Carol; Chryst-Ladd, Megan; Craig, Damian M; Hauser, Elizabeth R; Siegler, Ilene C; Kuhn, Cynthia M; Singh, Abanish; Williams, Redford BPreviously we have shown that a functional nonsynonymous single nucleotide polymorphism (rs6318) of the 5HTR2C gene located on the X-chromosome is associated with hypothalamic-pituitary-adrenal axis response to a stress recall task, and with endophenotypes associated with cardiovascular disease (CVD). These findings suggest that individuals carrying the rs6318 Ser23 C allele will be at higher risk for CVD compared to Cys23 G allele carriers. The present study examined allelic variation in rs6318 as a predictor of coronary artery disease (CAD) severity and a composite endpoint of all-cause mortality or myocardial infarction (MI) among Caucasian participants consecutively recruited through the cardiac catheterization laboratory at Duke University Hospital (Durham, NC) as part of the CATHGEN biorepository. Study population consisted of 6,126 Caucasian participants (4,036 [65.9%] males and 2,090 [34.1%] females). A total of 1,769 events occurred (1,544 deaths and 225 MIs; median follow-up time = 5.3 years, interquartile range = 3.3-8.2). Unadjusted Cox time-to-event regression models showed, compared to Cys23 G carriers, males hemizygous for Ser23 C and females homozygous for Ser23C were at increased risk for the composite endpoint of all-cause death or MI: Hazard Ratio (HR) = 1.47, 95% confidence interval (CI) = 1.17, 1.84, p = .0008. Adjusting for age, rs6318 genotype was not related to body mass index, diabetes, hypertension, dyslipidemia, smoking history, number of diseased coronary arteries, or left ventricular ejection fraction in either males or females. After adjustment for these covariates the estimate for the two Ser23 C groups was modestly attenuated, but remained statistically significant: HR = 1.38, 95% CI = 1.10, 1.73, p = .005. These findings suggest that this functional polymorphism of the 5HTR2C gene is associated with increased risk for CVD mortality and morbidity, but this association is apparently not explained by the association of rs6318 with traditional risk factors or conventional markers of atherosclerotic disease.Item Open Access Accelerated epigenetic age as a biomarker of cardiovascular sensitivity to traffic-related air pollution.(Aging, 2020-12) Ward-Caviness, Cavin K; Russell, Armistead G; Weaver, Anne M; Slawsky, Erik; Dhingra, Radhika; Kwee, Lydia Coulter; Jiang, Rong; Neas, Lucas M; Diaz-Sanchez, David; Devlin, Robert B; Cascio, Wayne E; Olden, Kenneth; Hauser, Elizabeth R; Shah, Svati H; Kraus, William EBackground
Accelerated epigenetic age has been proposed as a biomarker of increased aging, which may indicate disruptions in cellular and organ system homeostasis and thus contribute to sensitivity to environmental exposures.Methods
Using 497 participants from the CATHGEN cohort, we evaluated whether accelerated epigenetic aging increases cardiovascular sensitivity to traffic-related air pollution (TRAP) exposure. We used residential proximity to major roadways and source apportioned air pollution models as measures of TRAP exposure, and chose peripheral arterial disease (PAD) and blood pressure as outcomes based on previous associations with TRAP. We used Horvath epigenetic age acceleration (AAD) and phenotypic age acceleration (PhenoAAD) as measures of age acceleration, and adjusted all models for chronological age, race, sex, smoking, and socioeconomic status.Results
We observed significant interactions between TRAP and both AAD and PhenoAAD. Interactions indicated that increased epigenetic age acceleration elevated associations between proximity to roadways and PAD. Interactions were also observed between AAD and gasoline and diesel source apportioned PM2.5.Conclusion
Epigenetic age acceleration may be a biomarker of sensitivity to air pollution, particularly for TRAP in urban cohorts. This presents a novel means by which to understand sensitivity to air pollution and provides a molecular measure of environmental sensitivity.Item Open Access An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.(Genome medicine, 2021-05) Wang, Liuyang; Balmat, Thomas J; Antonia, Alejandro L; Constantine, Florica J; Henao, Ricardo; Burke, Thomas W; Ingham, Andy; McClain, Micah T; Tsalik, Ephraim L; Ko, Emily R; Ginsburg, Geoffrey S; DeLong, Mark R; Shen, Xiling; Woods, Christopher W; Hauser, Elizabeth R; Ko, Dennis CBackground
While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.Results
Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.Conclusions
Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .Item Open Access Assessment of LD matrix measures for the analysis of biological pathway association.(Stat Appl Genet Mol Biol, 2010) Crosslin, David R; Qin, Xuejun; Hauser, Elizabeth RComplex diseases will have multiple functional sites, and it will be invaluable to understand the cross-locus interaction in terms of linkage disequilibrium (LD) between those sites (epistasis) in addition to the haplotype-LD effects. We investigated the statistical properties of a class of matrix-based statistics to assess this epistasis. These statistical methods include two LD contrast tests (Zaykin et al., 2006) and partial least squares regression (Wang et al., 2008). To estimate Type 1 error rates and power, we simulated multiple two-variant disease models using the SIMLA software package. SIMLA allows for the joint action of up to two disease genes in the simulated data with all possible multiplicative interaction effects between them. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequilibrium (LD) patterns with other markers. We measured the effects of marginal disease effect size, haplotype LD, disease prevalence and minor allele frequency have on cross-locus interaction (epistasis). In the setting of strong allele effects and strong interaction, the correlation between the two disease genes was weak (r=0.2). In a complex system with multiple correlations (both marginal and interaction), it was difficult to determine the source of a significant result. Despite these complications, the partial least squares and modified LD contrast methods maintained adequate power to detect the epistatic effects; however, for many of the analyses we often could not separate interaction from a strong marginal effect. While we did not exhaust the entire parameter space of possible models, we do provide guidance on the effects that population parameters have on cross-locus interaction.Item Open Access Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events.(Circ Cardiovasc Genet, 2010-04) Shah, Svati H; Bain, James R; Muehlbauer, Michael J; Stevens, Robert D; Crosslin, David R; Haynes, Carol; Dungan, Jennifer; Newby, L Kristin; Hauser, Elizabeth R; Ginsburg, Geoffrey S; Newgard, Christopher B; Kraus, William EBACKGROUND: Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. METHODS AND RESULTS: We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("event-replication" group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). CONCLUSIONS: Metabolite profiles are associated with CAD and subsequent cardiovascular events.Item Open Access Characterization of Gene-by-Age Interaction and Gene-by-Gene Interaction In Coronary Artery Disease(2012) Zhao, YiThe success of genome-wide association studies (GWAS) has been limited by missing heritability and lack of biological relevance of identified variants. We sought to address these issues by characterizing interaction among genotypes and environment using case-control samples enrolled at Duke University Medical Center. First, we studied the impact of age on coronary artery disease (CAD). Gene-by-age (GxAGE) interactions were tested at genome-wide scale, along with genes' marginal effects in age-stratified groups. Based on the interaction model, age plays the role as a modifier of the age-CAD relationship. SNPs associated with CAD in both young and old demonstrate consistency in effect sizes and directions. In spite of these SNPs, vastly different CAD associated genes were discovered across age and race groups, suggesting age-dependent mechanisms of CAD onset. Second, we explored gene-by-gene interaction (GxG) using a statistical model and compared results to biological evidence. Specifically, we investigated GATA2 as a candidate gene transcription factor, and modeled the interaction with genome-wide SNPs. The genetic effects at interacting loci were modified by GATA2 genotype. Without taking GATA2 variants into account , no marginal main effects were detected. Open access ChIP-seq data was available for comparison with the statistical model, and to relate GWAS findings with biological mechanisms. The agreement between the statistical and biological models was very limited.
Item Open Access Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.(Scientific reports, 2021-04-14) Hong, Julian C; Hauser, Elizabeth R; Redding, Thomas S; Sims, Kellie J; Gellad, Ziad F; O'Leary, Meghan C; Hyslop, Terry; Madison, Ashton N; Qin, Xuejun; Weiss, David; Bullard, A Jasmine; Williams, Christina D; Sullivan, Brian A; Lieberman, David; Provenzale, DawnUnderstanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care.Item Open Access Clinical utility of a Web-enabled risk-assessment and clinical decision support program.(Genet Med, 2016-10) Orlando, Lori A; Wu, R Ryanne; Myers, Rachel A; Buchanan, Adam H; Henrich, Vincent C; Hauser, Elizabeth R; Ginsburg, Geoffrey SPURPOSE: Risk-stratified guidelines can improve quality of care and cost-effectiveness, but their uptake in primary care has been limited. MeTree, a Web-based, patient-facing risk-assessment and clinical decision support tool, is designed to facilitate uptake of risk-stratified guidelines. METHODS: A hybrid implementation-effectiveness trial of three clinics (two intervention, one control). PARTICIPANTS: consentable nonadopted adults with upcoming appointments. PRIMARY OUTCOME: agreement between patient risk level and risk management for those meeting evidence-based criteria for increased-risk risk-management strategies (increased risk) and those who do not (average risk) before MeTree and after. MEASURES: chart abstraction was used to identify risk management related to colon, breast, and ovarian cancer, hereditary cancer, and thrombosis. RESULTS: Participants = 488, female = 284 (58.2%), white = 411 (85.7%), mean age = 58.7 (SD = 12.3). Agreement between risk management and risk level for all conditions for each participant, except for colon cancer, which was limited to those <50 years of age, was (i) 1.1% (N = 2/174) for the increased-risk group before MeTree and 16.1% (N = 28/174) after and (ii) 99.2% (N = 2,125/2,142) for the average-risk group before MeTree and 99.5% (N = 2,131/2,142) after. Of those receiving increased-risk risk-management strategies at baseline, 10.5% (N = 2/19) met criteria for increased risk. After MeTree, 80.7% (N = 46/57) met criteria. CONCLUSION: MeTree integration into primary care can improve uptake of risk-stratified guidelines and potentially reduce "overuse" and "underuse" of increased-risk services.Genet Med 18 10, 1020-1028.Item Open Access Determinants of Dropout from and Variation in Adherence to an Exercise Intervention: The STRRIDE Randomized Trials.(Translational journal of the American College of Sports Medicine, 2022-01) Collins, Katherine A; Huffman, Kim M; Wolever, Ruth Q; Smith, Patrick J; Siegler, Ilene C; Ross, Leanna M; Hauser, Elizabeth R; Jiang, Rong; Jakicic, John M; Costa, Paul T; Kraus, William EPurpose
This study aimed to characterize the timing and self-reported determinants of exercise dropout among sedentary adults with overweight or obesity. We also sought to explore variations in adherence among individuals who completed a 6- to 8-month structured exercise intervention.Methods
A total of 947 adults with dyslipidemia [STRRIDE I, STRRIDE AT/RT] or prediabetes [STRRIDE-PD] were enrolled to either control or to one of 10 exercise interventions, ranging from doses of 8-23 kcal/kg/week; intensities of 50%-75% V̇O2 peak; and durations of 6-8 months. Two groups included resistance training and one included dietary intervention (7% weight loss goal). Dropout was defined as an individual who withdrew from the study due a variety of determinants. Timing of intervention dropout was defined as the last session attended and categorized into phases. Exercise training adherence was calculated by dividing weekly minutes or total sets of exercise completed by weekly minutes or total sets of exercise prescribed. General linear models were used to characterize the associations between timing of dropout and determinant category.Results
Compared to exercise intervention completers (n=652), participants who dropped out (n=295) were on average non-white (98% vs. 80%, p<0.01), had higher body mass index (31.0 kg/m2 vs. 30.2 kg/m2; p<0.01), and were less fit at baseline (25.0 mg/kg/min vs. 26.7 ml/kg/min, p<0.01). Of those who dropped out, 67% did so prior to the start of or while ramping up to the prescribed exercise volume and intensity. The most commonly reported reason for dropout was lack of time (40%). Notably, among individuals who completed the ramp training period, subsequent exercise intervention adherence did not waiver over the ensuing 6-8 months of training.Conclusion
These findings are some of the first to delineate associations between the timing of dropout and dropout determinants, providing guidance to future exercise interventions to better support individuals at-risk for dropout.Item Open Access Drebrin attenuates atherosclerosis by limiting smooth muscle cell transdifferentiation.(Cardiovascular research, 2021-04-29) Wu, Jiao-Hui; Zhang, Lisheng; Nepliouev, Igor; Brian, Leigh; Huang, Taiqin; Snow, Kamie P; Schickling, Brandon M; Hauser, Elizabeth R; Miller, Francis J; Freedman, Neil J; Stiber, Jonathan AAims
The F-actin-binding protein Drebrin inhibits smooth muscle cell (SMC) migration, proliferation and pro-inflammatory signaling. Therefore, we tested the hypothesis that Drebrin constrains atherosclerosis.Methods and results
SM22-Cre+/Dbnflox/flox/Ldlr-/- (SMC-Dbn-/-/Ldlr-/-) and control mice (SM22-Cre+/Ldlr-/-, Dbnflox/flox/Ldlr-/-, and Ldlr-/-) were fed a Western diet for 14-20 weeks. Brachiocephalic arteries of SMC-Dbn-/-/Ldlr-/- mice exhibited 1.5- or 1.8-fold greater cross-sectional lesion area than control mice at 14 or 20 wk, respectively. Aortic atherosclerotic lesion surface area was 1.2-fold greater in SMC-Dbn-/-/Ldlr-/- mice. SMC-Dbn-/-/Ldlr-/- lesions comprised necrotic cores that were two-fold greater in size than those of control mice. Consistent with their bigger necrotic core size, lesions in SMC-Dbn-/- arteries also showed more transdifferentiation of SMCs to macrophage-like cells: 1.5- to 2.5-fold greater, assessed with BODIPY or with CD68, respectively. In vitro data were concordant: Dbn-/- SMCs had 1.7-fold higher levels of KLF4 and transdifferentiated to macrophage-like cells more readily than Dbnflox/flox SMCs upon cholesterol loading, as evidenced by greater up-regulation of CD68 and galectin-3. Adenovirally mediated Drebrin rescue produced equivalent levels of macrophage-like transdifferentiation in Dbn-/- and Dbnflox/flox SMCs. During early atherogenesis, SMC-Dbn-/-/Ldlr-/- aortas demonstrated 1.6-fold higher levels of reactive oxygen species than control mouse aortas. The 1.8-fold higher levels of Nox1 in Dbn-/- SMCs was reduced to WT levels with KLF4 silencing. Inhibition of Nox1 chemically or with siRNA produced equivalent levels of macrophage-like transdifferentiation in Dbn-/- and Dbnflox/flox SMCs.Conclusions
We conclude that SMC Drebrin limits atherosclerosis by constraining SMC Nox1 activity and SMC transdifferentiation to macrophage-like cells.Translational perspective
Drebrin is abundantly expressed in vascular smooth muscle cells (SMCs) and is up-regulated in human atherosclerosis. A hallmark of atherosclerosis is the accumulation of foam cells that secrete pro-inflammatory cytokines and contribute to plaque instability. A large proportion of these foam cells in humans derive from SMCs. We found that SMC Drebrin limits atherosclerosis by reducing SMC transdifferentiation to macrophage-like foam cells in a manner dependent on Nox1 and KLF4. For this reason, strategies aimed at augmenting SMC Drebrin expression in atherosclerotic plaques may limit atherosclerosis progression and enhance plaque stability by bridling SMC-to-foam-cell transdifferentiation.Item Open Access Effect of behavioral weight-loss program on biomarkers of cardiometabolic disease risk: Heart Health Study randomized trial.(Obesity (Silver Spring, Md.), 2023-02) Collins, Katherine A; Kraus, William E; Rogers, Renee J; Hauser, Elizabeth R; Lang, Wei; Jiang, Rong; Schelbert, Erik B; Huffman, Kim M; Jakicic, John MObjective
This study aimed to determine whether novel biomarkers of cardiometabolic health improve in response to a 12-month behavioral weight-loss intervention and to compare benefits of diet alone with diet plus physical activity for these biomarkers.Methods
Participants (N = 374) were randomized to either diet alone (DIET), diet plus 150 min/wk of prescribed moderate-intensity physical activity (DIET + PA150), or diet plus 250 min/wk of prescribed moderate-intensity physical activity (DIET + PA250). Biomarker concentrations were determined using nuclear magnetic resonance spectroscopy. Mixed models assessed for a time effect, group effect, or group by time interaction.Results
All groups significantly improved body weight (time: p < 0.0001), Lipoprotein Insulin Resistance Index score (time: p < 0.0001), Diabetes Risk Index score (time: p < 0.0001), branched-chain amino acid concentration (time: p < 0.0001), and GlycA concentration (time: p < 0.0001), with no group effect or group by time interactions.Conclusions
All intervention groups prompted a notable beneficial change among biomarkers of insulin resistance and cardiometabolic health. However, the addition of at least moderate-intensity physical activity to a diet-only intervention did not provide any additional benefit. These findings highlight that an average weight loss of approximately 10% profoundly impacts biomarkers of insulin resistance and cardiometabolic disease in adults with overweight or obesity.Item Open Access Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci.(Genome medicine, 2021-04-30) Breeze, Charles E; Batorsky, Anna; Lee, Mi Kyeong; Szeto, Mindy D; Xu, Xiaoguang; McCartney, Daniel L; Jiang, Rong; Patki, Amit; Kramer, Holly J; Eales, James M; Raffield, Laura; Lange, Leslie; Lange, Ethan; Durda, Peter; Liu, Yongmei; Tracy, Russ P; Van Den Berg, David; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed MESA Multi-Omics Working Group; Evans, Kathryn L; Kraus, William E; Shah, Svati; Tiwari, Hermant K; Hou, Lifang; Whitsel, Eric A; Jiang, Xiao; Charchar, Fadi J; Baccarelli, Andrea A; Rich, Stephen S; Morris, Andrew P; Irvin, Marguerite R; Arnett, Donna K; Hauser, Elizabeth R; Rotter, Jerome I; Correa, Adolfo; Hayward, Caroline; Horvath, Steve; Marioni, Riccardo E; Tomaszewski, Maciej; Beck, Stephan; Berndt, Sonja I; London, Stephanie J; Mychaleckyj, Josyf C; Franceschini, NoraBackground
DNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach.Methods
The study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses.Results
We identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development.Conclusions
We uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.Item Open Access Evaluating the precision of EBF1 SNP x stress interaction association: sex, race, and age differences in a big harmonized data set of 28,026 participants.(Translational psychiatry, 2020-10-20) Singh, Abanish; Babyak, Michael A; Sims, Mario; Musani, Solomon K; Brummett, Beverly H; Jiang, Rong; Kraus, William E; Shah, Svati H; Siegler, Ilene C; Hauser, Elizabeth R; Williams, Redford BIn prior work, we identified a novel gene-by-stress association of EBF1's common variation (SNP rs4704963) with obesity (i.e., hip, waist) in Whites, which was further strengthened through multiple replications using our synthetic stress measure. We now extend this prior work in a precision medicine framework to find the risk group using harmonized data from 28,026 participants by evaluating the following: (a) EBF1 SNPxSTRESS interaction in Blacks; (b) 3-way interaction of EBF1 SNPxSTRESS with sex, race, and age; and (c) a race and sex-specific path linking EBF1 and stress to obesity to fasting glucose to the development of cardiometabolic disease risk. Our findings provided additional confirmation that genetic variation in EBF1 may contribute to stress-induced human obesity, including in Blacks (P = 0.022) that mainly resulted from race-specific stress due to "racism/discrimination" (P = 0.036) and "not meeting basic needs" (P = 0.053). The EBF1 gene-by-stress interaction differed significantly (P = 1.01e-03) depending on the sex of participants in Whites. Race and age also showed tentative associations (Ps = 0.103, 0.093, respectively) with this interaction. There was a significant and substantially larger path linking EBF1 and stress to obesity to fasting glucose to type 2 diabetes for the EBF1 minor allele group (coefficient = 0.28, P = 0.009, 95% CI = 0.07-0.49) compared with the same path for the EBF1 major allele homozygotes in White females and also a similar pattern of the path in Black females. Underscoring the race-specific key life-stress indicators (e.g., racism/discrimination) and also the utility of our synthetic stress, we identified the potential risk group of EBF1 and stress-induced human obesity and cardiometabolic disease.Item Open Access Gene by stress genome-wide interaction analysis and path analysis identify EBF1 as a cardiovascular and metabolic risk gene.(European journal of human genetics : EJHG, 2015-06) Singh, Abanish; Babyak, Michael A; Nolan, Daniel K; Brummett, Beverly H; Jiang, Rong; Siegler, Ilene C; Kraus, William E; Shah, Svati H; Williams, Redford B; Hauser, Elizabeth RWe performed gene-environment interaction genome-wide association analysis (G × E GWAS) to identify SNPs whose effects on metabolic traits are modified by chronic psychosocial stress in the Multi-Ethnic Study of Atherosclerosis (MESA). In Whites, the G × E GWAS for hip circumference identified five SNPs within the Early B-cell Factor 1 (EBF1) gene, all of which were in strong linkage disequilibrium. The gene-by-stress interaction (SNP × STRESS) term P-values were genome-wide significant (Ps = 7.14E-09 to 2.33E-08, uncorrected; Ps = 1.99E-07 to 5.18E-07, corrected for genomic control). The SNP-only (without interaction) model P-values (Ps = 0.011-0.022) were not significant at the conventional genome-wide significance level. Further analysis of related phenotypes identified gene-by-stress interaction effects for waist circumference, body mass index (BMI), fasting glucose, type II diabetes status, and common carotid intimal-medial thickness (CCIMT), supporting a proposed model of gene-by-stress interaction that connects cardiovascular disease (CVD) risk factor endophenotypes such as central obesity and increased blood glucose or diabetes to CVD itself. Structural equation path analysis suggested that the path from chronic psychosocial stress to CCIMT via hip circumference and fasting glucose was larger (estimate = 0.26, P = 0.033, 95% CI = 0.02-0.49) in the EBF1 rs4704963 CT/CC genotypes group than the same path in the TT group (estimate = 0.004, P = 0.34, 95% CI = -0.004-0.012). We replicated the association of the EBF1 SNPs and hip circumference in the Framingham Offspring Cohort (gene-by-stress term P-values = 0.007-0.012) as well as identified similar path relationships. This observed and replicated interaction between psychosocial stress and variation in the EBF1 gene may provide a biological hypothesis for the complex relationship between psychosocial stress, central obesity, diabetes, and cardiovascular disease.Item Open Access Gene-Environment Interactions in Cardiovascular Disease(2014) WardCaviness, Cavin KeithIn this manuscript I seek to demonstrate the importance of gene-environment interactions in cardiovascular disease. This manuscript contains five studies each of which contributes to our understanding of the joint impact of genetic variation and environmental exposures to cardiovascular disease: a candidate gene study for gene-smoking interactions associated with early-onset coronary artery disease, an epidemiology study of the association between traffic-related air pollution and cardiovascular disease, a Genome-Wide Interaction Study for gene-by-traffic related air pollution interactions associated with peripheral arterial disease, a Genome-Wide Interaction Study for gene-by-traffic related air pollution interactions on coronary atherosclerosis burden, and a method for analyzing associations between high-dimensional genomics datasets.
Smoking is a strong risk factors for coronary artery disease, and may play a causative role in the incidence of coronary artery disease. Smoking had been implicated as a reason for heterogeneity observed in associations between genetic variants on chromosome three and coronary artery disease. I used a family-based early-onset coronary artery disease cohort (GENECARD) to study gene-smoking interactions. I also used data from the three independent cohorts to perform a meta-analysis of gene-smoking interactions focusing on the KALRN gene and Rho-GTPase pathway. I found significant evidence for gene-smoking interactions associations involving variants in KALRN and other Rho-GTPase pathway genes on chromosome 3.
Though the estimated increase in incident cardiovascular disease or cardiovascular events due to air pollution exposure is modest at 3-5%, the ubiquitous nature of air pollution exposures means it has a substantial population-level impact on cardiovascular disease. Historically genome-wide interaction studies with air pollution have not yielded genome-wide significant interactions, however by implementing statistical tools novel to this field I have discovered significant interactions between genetic variants and traffic-related air pollution that are associated with cardiovascular diseases.
I studied interactions associated with peripheral arterial disease and the number of diseased coronary vessels (an indicator for coronary artery disease burden) using race-stratified cohort study designs. With peripheral arterial disease I observed that variants in both BMP8A and BMP2 showed evidence for interactions in both European-American and African-American cohorts. In BMP8A I uncovered the first genome-wide significant interaction with air pollution associated with cardiovascular disease. BMP2 gene expression is upregulated after exposure to black carbon, a major component of diesel exhaust, and coding variants within this gene showed evidence for interaction. With the number of diseased coronary vessels I observed that variants in PIGR showed significant evidence for involvement in gene-traffic related air pollution interactions. I observed that coding variation within PIGR was associated with coronary artery disease burden in a gene-by-traffic related air pollution interaction model. As PIGR is involved in the immune response it represents a strong candidate gene discovered via an unbiased genome-wide scan.
The use of high dimensional data to study chronic disease is becoming commonplace. In order to properly analyze high-dimensional data without suffering from high false-discovery rate penalties, the data is often summarized in a way that takes advantage of the correlation structure. Two common approaches for this are principal components analysis and canonical correlation analysis. However neither of these approaches are appropriate when one preferentially desires to preserve structure within the data. To address this shortcoming I developed constrained canonical correlation analysis (cCCA). With cCCA one can evaluate the correlation between two high dimensional datasets while preferentially preserving structure in one of the datasets. This has uses when studying multi-variate outcomes such as cardiovascular disease using multi-variate predictors such as air pollution. Additionally cCCA can be used to create endophenotype factors that specifically explain the variation within a high-dimensional set of predictors (such as gene expression or metabolomics data) with respect to potential endophenotypes for cardiovascular disease, such as cholesterol measures.
Item Open Access Genetic Analysis of Gulf War illness: Phenotype Development, GWAS, and Gene-Environment Interaction(2022) Vahey, JacquelineVeterans who served in the 1990-1991 Gulf War experience debilitating chronic symptoms at extremely high rates. In the 30 years since the Gulf War, many researchers have worked to identify the cause and biological pathway of Gulf War illness (GWI). There is, however, no biomarker, ICD code, or other standardized way to identify veterans with GWI; veterans are told they have GWI based on a clinician’s assessment of their unexplained chronic symptoms. There is also little agreement on the causes and potential biological pathways of GWI. This dissertation describes phenotyping efforts, the first genome-wide association study (GWAS) of GWI, and a candidate gene-environment interaction study. First, I describe methods for developing well-documented indicators for complex phenotypes, which have generated GWI indicators that are used for the MVP and GWECB datasets. This is the only tested and published algorithm for defining GWI. This work required extensive exploratory analysis and data cleaning, as it was the first major analysis of the GWECB dataset. The variables generated through both the data cleaning and GWI algorithm have been incorporated into the GWECB. Then, I performed the first GWAS of GWI, which supports prior work in the field and suggests further candidate analyses. Top gene-set associations include response to cadmium ion, regulation of response to interferon gamma, and regulation of autophagosome maturation. Among other top associations, these results indicate association with a neuroimmune response to exposure. GWAS summary statistics will be made available. Finally, I developed a hypothesis-driven candidate gene-environment interaction study, which replicated a previously published statistically significant association of rs662/PB pill exposure with GWI. Future research building off my contributions could help identify the underlying biological pathways and causes of GWI, allowing better treatment of the underlying disease for hundreds of thousands of Gulf War Veterans.
Item Open Access Genetic and epigenetic signatures associated with plasma oxytocin levels in children and adolescents with autism spectrum disorder(Autism Research) Siecinski, Stephen K; Giamberardino, Stephanie N; Spanos, Marina; Hauser, Annalise C; Gibson, Jason R; Chandrasekhar, Tara; Trelles, Maria Del Pilar; Rockhill, Carol M; Palumbo, Michelle L; Cundiff, Allyson Witters; Montgomery, Alicia; Siper, Paige; Minjarez, Mendy; Nowinski, Lisa A; Marler, Sarah; Kwee, Lydia C; Shuffrey, Lauren C; Alderman, Cheryl; Weissman, Jordana; Zappone, Brooke; Mullett, Jennifer E; Crosson, Hope; Hong, Natalie; Luo, Sheng; She, Lilin; Bhapkar, Manjushri; Dean, Russell; Scheer, Abby; Johnson, Jacqueline L; King, Bryan H; McDougle, Christopher J; Sanders, Kevin B; Kim, Soo-Jeong; Kolevzon, Alexander; Veenstra-VanderWeele, Jeremy; Hauser, Elizabeth R; Sikich, Linmarie; Gregory, Simon GItem Open Access Genome-wide analysis identifies novel susceptibility loci for myocardial infarction.(European heart journal, 2021-03) Hartiala, Jaana A; Han, Yi; Jia, Qiong; Hilser, James R; Huang, Pin; Gukasyan, Janet; Schwartzman, William S; Cai, Zhiheng; Biswas, Subarna; Trégouët, David-Alexandre; Smith, Nicholas L; INVENT Consortium; CHARGE Consortium Hemostasis Working Group; GENIUS-CHD Consortium; Seldin, Marcus; Pan, Calvin; Mehrabian, Margarete; Lusis, Aldons J; Bazeley, Peter; Sun, Yan V; Liu, Chang; Quyyumi, Arshed A; Scholz, Markus; Thiery, Joachim; Delgado, Graciela E; Kleber, Marcus E; März, Winfried; Howe, Laurence J; Asselbergs, Folkert W; van Vugt, Marion; Vlachojannis, Georgios J; Patel, Riyaz S; Lyytikäinen, Leo-Pekka; Kähönen, Mika; Lehtimäki, Terho; Nieminen, Tuomo VM; Kuukasjärvi, Pekka; Laurikka, Jari O; Chang, Xuling; Heng, Chew-Kiat; Jiang, Rong; Kraus, William E; Hauser, Elizabeth R; Ferguson, Jane F; Reilly, Muredach P; Ito, Kaoru; Koyama, Satoshi; Kamatani, Yoichiro; Komuro, Issei; Biobank Japan; Stolze, Lindsey K; Romanoski, Casey E; Khan, Mohammad Daud; Turner, Adam W; Miller, Clint L; Aherrahrou, Redouane; Civelek, Mete; Ma, Lijiang; Björkegren, Johan LM; Kumar, S Ram; Tang, WH Wilson; Hazen, Stanley L; Allayee, HoomanAims
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-1β (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.Item Open Access Genome-Wide Genetic Analysis of Dropout in a Controlled Exercise Intervention in Sedentary Adults With Overweight or Obesity and Cardiometabolic Disease(Annals of Behavioral Medicine) Jiang, Rong; Collins, Katherine A; Huffman, Kim M; Hauser, Elizabeth R; Hubal, Monica J; Johnson, Johanna L; Williams, Redford B; Siegler, Ilene C; Kraus, William EAbstract Background Despite the benefits of exercise, many individuals are unable or unwilling to adopt an exercise intervention. Purpose The purpose of this analysis was to identify putative genetic variants associated with dropout from exercise training interventions among individuals in the STRRIDE trials. Methods We used a genome-wide association study approach to identify genetic variants in 603 participants initiating a supervised exercise intervention. Exercise intervention dropout occurred when a subject withdrew from further participation in the study or was otherwise lost to follow-up. Results Exercise intervention dropout was associated with a cluster of single-nucleotide polymorphisms with the top candidate being rs722069 (T/C, risk allele = C) (unadjusted p = 2.2 × 10−7, odds ratio = 2.23) contained within a linkage disequilibrium block on chromosome 16. In Genotype-Tissue Expression, rs722069 is an expression quantitative trait locus of the EARS2, COG7, and DCTN5 genes in skeletal muscle tissue. In subsets of the STRRIDE genetic cohort with available muscle gene expression (n = 37) and metabolic data (n = 82), at baseline the C allele was associated with lesser muscle expression of EARS2 (p < .002) and COG7 (p = .074) as well as lesser muscle concentrations of C2- and C3-acylcarnitines (p = .026). Conclusions Our observations imply that exercise intervention dropout is genetically moderated through alterations in gene expression and metabolic pathways in skeletal muscle. Individual genetic traits may allow the development of a biomarker-based approach for identifying individuals who may benefit from more intensive counseling and other interventions to optimize exercise intervention adoption. Clinical Trial information STRRIDE I = NCT00200993; STRRIDE AT/RT = NCT00275145; STRRIDE-PD = NCT00962962.Item Open Access GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.(The American journal of psychiatry, 2023-10) Docherty, Anna R; Mullins, Niamh; Ashley-Koch, Allison E; Qin, Xuejun; Coleman, Jonathan RI; Shabalin, Andrey; Kang, JooEun; Murnyak, Balasz; Wendt, Frank; Adams, Mark; Campos, Adrian I; DiBlasi, Emily; Fullerton, Janice M; Kranzler, Henry R; Bakian, Amanda V; Monson, Eric T; Rentería, Miguel E; Walss-Bass, Consuelo; Andreassen, Ole A; Behera, Chittaranjan; Bulik, Cynthia M; Edenberg, Howard J; Kessler, Ronald C; Mann, J John; Nurnberger, John I; Pistis, Giorgio; Streit, Fabian; Ursano, Robert J; Polimanti, Renato; Dennis, Michelle; Garrett, Melanie; Hair, Lauren; Harvey, Philip; Hauser, Elizabeth R; Hauser, Michael A; Huffman, Jennifer; Jacobson, Daniel; Madduri, Ravi; McMahon, Benjamin; Oslin, David W; Trafton, Jodie; Awasthi, Swapnil; Berrettini, Wade H; Bohus, Martin; Chang, Xiao; Chen, Hsi-Chung; Chen, Wei J; Christensen, Erik D; Crow, Scott; Duriez, Philibert; Edwards, Alexis C; Fernández-Aranda, Fernando; Galfalvy, Hanga; Gandal, Michael; Gorwood, Philip; Guo, Yiran; Hafferty, Jonathan D; Hakonarson, Hakon; Halmi, Katherine A; Hishimoto, Akitoyo; Jain, Sonia; Jamain, Stéphane; Jiménez-Murcia, Susana; Johnson, Craig; Kaplan, Allan S; Kaye, Walter H; Keel, Pamela K; Kennedy, James L; Kim, Minsoo; Klump, Kelly L; Levey, Daniel F; Li, Dong; Liao, Shih-Cheng; Lieb, Klaus; Lilenfeld, Lisa; Marshall, Christian R; Mitchell, James E; Okazaki, Satoshi; Otsuka, Ikuo; Pinto, Dalila; Powers, Abigail; Ramoz, Nicolas; Ripke, Stephan; Roepke, Stefan; Rozanov, Vsevolod; Scherer, Stephen W; Schmahl, Christian; Sokolowski, Marcus; Starnawska, Anna; Strober, Michael; Su, Mei-Hsin; Thornton, Laura M; Treasure, Janet; Ware, Erin B; Watson, Hunna J; Witt, Stephanie H; Woodside, D Blake; Yilmaz, Zeynep; Zillich, Lea; Adolfsson, Rolf; Agartz, Ingrid; Alda, Martin; Alfredsson, Lars; Appadurai, Vivek; Artigas, María Soler; Van der Auwera, Sandra; Azevedo, M Helena; Bass, Nicholas; Bau, Claiton HD; Baune, Bernhard T; Bellivier, Frank; Berger, Klaus; Biernacka, Joanna M; Bigdeli, Tim B; Binder, Elisabeth B; Boehnke, Michael; Boks, Marco P; Braff, David L; Bryant, Richard; Budde, Monika; Byrne, Enda M; Cahn, Wiepke; Castelao, Enrique; Cervilla, Jorge A; Chaumette, Boris; Corvin, Aiden; Craddock, Nicholas; Djurovic, Srdjan; Foo, Jerome C; Forstner, Andreas J; Frye, Mark; Gatt, Justine M; Giegling, Ina; Grabe, Hans J; Green, Melissa J; Grevet, Eugenio H; Grigoroiu-Serbanescu, Maria; Gutierrez, Blanca; Guzman-Parra, Jose; Hamshere, Marian L; Hartmann, Annette M; Hauser, Joanna; Heilmann-Heimbach, Stefanie; Hoffmann, Per; Ising, Marcus; Jones, Ian; Jones, Lisa A; Jonsson, Lina; Kahn, René S; Kelsoe, John R; Kendler, Kenneth S; Kloiber, Stefan; Koenen, Karestan C; Kogevinas, Manolis; Krebs, Marie-Odile; Landén, Mikael; Leboyer, Marion; Lee, Phil H; Levinson, Douglas F; Liao, Calwing; Lissowska, Jolanta; Mayoral, Fermin; McElroy, Susan L; McGrath, Patrick; McGuffin, Peter; McQuillin, Andrew; Mehta, Divya; Melle, Ingrid; Mitchell, Philip B; Molina, Esther; Morken, Gunnar; Nievergelt, Caroline; Nöthen, Markus M; O'Donovan, Michael C; Ophoff, Roel A; Owen, Michael J; Pato, Carlos; Pato, Michele T; Penninx, Brenda WJH; Potash, James B; Power, Robert A; Preisig, Martin; Quested, Digby; Ramos-Quiroga, Josep Antoni; Reif, Andreas; Ribasés, Marta; Richarte, Vanesa; Rietschel, Marcella; Rivera, Margarita; Roberts, Andrea; Roberts, Gloria; Rouleau, Guy A; Rovaris, Diego L; Sanders, Alan R; Schofield, Peter R; Schulze, Thomas G; Scott, Laura J; Serretti, Alessandro; Shi, Jianxin; Sirignano, Lea; Sklar, Pamela; Smeland, Olav B; Smoller, Jordan W; Sonuga-Barke, Edmund JS; Trzaskowski, Maciej; Tsuang, Ming T; Turecki, Gustavo; Vilar-Ribó, Laura; Vincent, John B; Völzke, Henry; Walters, James TR; Weickert, Cynthia Shannon; Weickert, Thomas W; Weissman, Myrna M; Williams, Leanne M; Wray, Naomi R; Zai, Clement C; Agerbo, Esben; Børglum, Anders D; Breen, Gerome; Demontis, Ditte; Erlangsen, Annette; Gelernter, Joel; Glatt, Stephen J; Hougaard, David M; Hwu, Hai-Gwo; Kuo, Po-Hsiu; Lewis, Cathryn M; Li, Qingqin S; Liu, Chih-Min; Martin, Nicholas G; McIntosh, Andrew M; Medland, Sarah E; Mors, Ole; Nordentoft, Merete; Olsen, Catherine M; Porteous, David; Smith, Daniel J; Stahl, Eli A; Stein, Murray B; Wasserman, Danuta; Werge, Thomas; Whiteman, David C; Willour, Virginia; VA Million Veteran Program (MVP); MVP Suicide Exemplar Workgroup; Suicide Working Group of the Psychiatric Genomics Consortium; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium; Bipolar Disorder Working Group of the Psychiatric Genomics Consortium; Schizophrenia Working Group of the Psychiatric Genomics Consortium; Eating Disorder Working Group of the Psychiatric Genomics Consortium; German Borderline Genomics Consortium; Coon, Hilary; Beckham, Jean C; Kimbrel, Nathan A; Ruderfer, Douglas MObjective
Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures.Methods
This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses.Results
Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors.Conclusions
This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.