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Post-traumatic stress disorder (PTSD) is a major problem among military veterans and civilians alike, yet its pathophysiology remains poorly understood. We performed a genome-wide association study and bioinformatic analyses, which included 146,660 European Americans and 19,983 African Americans in the US Million Veteran Program, to identify genetic risk factors relevant to intrusive reexperiencing of trauma, which is the most characteristic symptom cluster of PTSD. In European Americans, eight distinct significant regions were identified. Three regions had values of P

Peripheral artery disease (PAD) is a leading cause of cardiovascular morbidity and mortality; however, the extent to which genetic factors increase risk for PAD is largely unknown. Using electronic health record data, we performed a genome-wide association study in the Million Veteran Program testing ~32 million DNA sequence variants with PAD (31,307 cases and 211,753 controls) across veterans of European, African and Hispanic ancestry. The results were replicated in an independent sample of 5,117 PAD cases and 389,291 controls from the UK Biobank. We identified 19 PAD loci, 18 of which have not been previously reported. Eleven of the 19 loci were associated with disease in three vascular beds (coronary, cerebral, peripheral), including LDLR, LPL and LPA, suggesting that therapeutic modulation of low-density lipoprotein cholesterol, the lipoprotein lipase pathway or circulating lipoprotein(a) may be efficacious for multiple atherosclerotic disease phenotypes. Conversely, four of the variants appeared to be specific for PAD, including F5 p.R506Q, highlighting the pathogenic role of thrombosis in the peripheral vascular bed and providing genetic support for Factor Xa inhibition as a therapeutic strategy for PAD. Our results highlight mechanistic similarities and differences among coronary, cerebral and peripheral atherosclerosis and provide therapeutic insights.

Summary Thoracic aortic aneurysm (TAA) is characterized by dilation of the aortic root or ascending/descending aorta. TAA is a heritable disease that can be potentially life threatening. While 10%–20% of TAA cases are caused by rare, pathogenic variants in single genes, the origin of the majority of TAA cases remains unknown. A previous study implicated common variants in FBN1 with TAA disease risk. Here, we report a genome-wide scan of 1,351 TAA-affected individuals and 18,295 control individuals from the Cardiovascular Health Improvement Project and Michigan Genomics Initiative at the University of Michigan. We identified a genome-wide significant association with TAA for variants within the third intron of TCF7L2 following replication with meta-analysis of four additional independent cohorts. Common variants in this locus are the strongest known genetic risk factor for type 2 diabetes. Although evidence indicates the presence of different causal variants for TAA and type 2 diabetes at this locus, we observed an opposite direction of effect. The genetic association for TAA colocalizes with an aortic eQTL of TCF7L2, suggesting a functional relationship. These analyses predict an association of higher expression of TCF7L2 with TAA disease risk. In vitro, we show that upregulation of TCF7L2 is associated with BCL2 repression promoting vascular smooth muscle cell apoptosis, a key driver of TAA disease.

OBJECTIVES: Ethnic disparities in hypertension prevalence are well documented, though the influence of genetic ancestry is unclear. The aim of this study was to evaluate associations of geographic genetic ancestry with hypertension and underlying blood pressure traits. METHODS: We tested genetically inferred ancestry proportions from five 1000 Genomes reference populations (GBR, PEL, YRI, CHB, and LWK) for association with four continuous blood pressure (BP) traits (SBP, DBP, PP, MAP) and the dichotomous outcomes hypertension and apparent treatment-resistant hypertension in 220 495 European American, 59 927 African American, and 21 273 Hispanic American individuals from the Million Veteran Program. Ethnicity stratified results were meta-analyzed to report effect estimates per 10% difference for a given ancestry proportion in all samples. RESULTS: Percentage GBR was negatively associated with BP (P = 2.13 × 10(−19), 7.92 × 10(−8), 4.41 × 10(−11), and 3.57 × 10(−13) for SBP, DBP, PP, and MAP, respectively; coefficient range −0.10 to −0.21 mmHg per 10% increase in ancestry proportion) and was protective against hypertension [P = 2.59 × 10(−5), odds ratio (OR) = 0.98] relative to other ancestries. YRI percentage was positively associated with BP (P = 1.63 × 10(−23), 1.94 × 10(−26), 0.012, and 3.26 × 10(−29) for SBP, DBP, PP, and MAP, respectively; coefficient range 0.06–0.32 mmHg per 10% increase in ancestry proportion) and was positively associated with hypertension risk (P = 3.10 × 10(−11), OR = 1.04) and apparent treatment-resistant hypertension risk (P = 1.86 × 10(−4), OR = 1.04) compared with other ancestries. Percentage PEL was inversely associated with DBP (P = 2.84 × 10(−5), beta = −0.11 mmHg per 10% increase in ancestry proportion). CONCLUSION: These results demonstrate that risk for BP traits varies significantly by genetic ancestry. Our findings provide insight into the geographic origin of genetic factors underlying hypertension risk and establish that a portion of BP trait ethnic disparities are because of genetic differences between ancestries.

SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations.

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=6.0x10(-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.

Supplemental Digital Content is available in the text., Serum urate has been implicated in hypertension and cardiovascular disease, but it is not known whether it is exerting a causal effect. To investigate this, we performed Mendelian randomization analysis using data from UK Biobank, Million Veterans Program and genome-wide association study consortia, and meta-analysis of randomized controlled trials. The main Mendelian randomization analyses showed that every 1-SD increase in genetically predicted serum urate was associated with an increased risk of coronary heart disease (odds ratio, 1.19 [95% CI, 1.10–1.30]; P=4×10−5), peripheral artery disease (1.12 [95% CI, 1.03–1.21]; P=9×10−3), and stroke (1.11 [95% CI, 1.05–1.18]; P=2×10−4). In Mendelian randomization mediation analyses, elevated blood pressure was estimated to mediate approximately one-third of the effect of urate on cardiovascular disease risk. Systematic review and meta-analysis of randomized controlled trials showed a favorable effect of urate-lowering treatment on systolic blood pressure (mean difference, −2.55 mm Hg [95% CI, −4.06 to −1.05]; P=1×10−3) and major adverse cardiovascular events in those with previous cardiovascular disease (odds ratio, 0.40 [95% CI, 0.22–0.73]; P=3×10−3) but no significant effect on major adverse cardiovascular events in all individuals (odds ratio, 0.67 [95% CI, 0.44–1.03]; P=0.07). In summary, these Mendelian randomization and clinical trial data support an effect of higher serum urate on increasing blood pressure, which may mediate a consequent effect on cardiovascular disease risk. High-quality trials are necessary to provide definitive evidence on the specific clinical contexts where urate lowering may be of cardiovascular benefit.

Background Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world’s population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. Methods We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. Results Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P < 10–30) and African American (P < .0005) participants in CSP #572. Conclusions We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

AIMS: The aim of this study was to use Mendelian randomization (MR) to determine the causality of the association between smoking and 14 different cardiovascular diseases (CVDs). METHODS AND RESULTS: Our primary genetic instrument comprised 361 single-nucleotide polymorphisms (SNPs) associated with smoking initiation (ever smoked regularly) at genome-wide significance. Data on the associations between the SNPs and 14 CVDs were obtained from the UK Biobank study (N = 367 643 individuals), CARDIoGRAMplusC4D consortium (N = 184 305 individuals), Atrial Fibrillation Consortium (2017 dataset; N = 154 432 individuals), and Million Veteran Program (MVP; N = 190 266 individuals). The main analyses were conducted using the random-effects inverse-variance weighted method and complemented with multivariable MR analyses and the weighted median and MR-Egger approaches. Genetic predisposition to smoking initiation was most strongly and consistently associated with higher odds of coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension. Genetic predisposition to smoking initiation was additionally associated with higher odds of deep vein thrombosis and pulmonary embolism in the UK Biobank but not with venous thromboembolism in the MVP. There was limited evidence of causal associations of smoking initiation with atrial fibrillation, aortic valve stenosis, thoracic aortic aneurysm, and intracerebral and subarachnoid haemorrhage. CONCLUSION: This MR study supports a causal association between smoking and a broad range of CVDs, in particular, coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p< 5× 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count invivo and IL-7 secretion levels invitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Importance: With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). Objectives: To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. Design, Setting, and Participants: A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. Main Outcomes and Measures: Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). Results: A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (μ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: β = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. Conclusions and Relevance: This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci.

Hypoglycemia is a preventable adverse effect of treatment in diabetes patients, but actionable pharmacogenetic evidence to minimize hypoglycemia risk is lacking. We used the MVP biospecimen and clinical biobank to perform a case/control GWAS of hypoglycemia in 96,406 diabetes patients receiving care in the U.S. Veterans Health Administration. Cases had an outpatient random plasma glucose (RPG) 1%. GWAS were conducted in 72,244 participants (22,045 cases) of European ancestry [EUR] and 24,162 (10,441 cases) of African ancestry [AFR]), adjusted for age at MVP enrollment, sex, and 10 genetic principal components. We identified a single locus associated with hypoglycemia in EUR individuals (rs1064173, HLA-DQB1 locus, odds ratio [OR] 1.15, p=5.6E-19, MAF 0.20) and in AFR individuals (rs12712928, SIX3 locus, OR 0.87, p=2.7E-8, MAF 0.17). In a phenomewide association study (PheWAS) in MVP EUR diabetes patients, rs1064173 was associated with type 1 diabetes (T1D, OR 1.41, p=7.8E-25) and diabetes complications (retinopathy, OR 1.24, p=9E-24; neuropathy, OR 1.16, p=1.3E-5). To address the known association of the HLA locus with T1D, we performed a sensitivity analysis excluding patients with any use of T1D diagnosis codes. In this sample enriched for type 2 diabetes, rs1064173 remained nominally associated with hypoglycemia (OR 1.23, p=0.02) and retinopathy (OR 1.10, p=0.003). Rs12712928 - previously associated with glucose and hemoglobin A1c in an East Asian sample - was not associated with any diagnoses in a PheWAS of MVP AFR diabetes patients. In conclusion, a GWAS of hypoglycemia in a clinical biobank found ancestry-specific genetic associations that may have treatment implications. Disclosure S. Raghavan: None. Z. Wang: None. A.M. Hung: None. B.R. Charest: None. L. Costa: None. E.M. Litkowski: None. A. Leong: None. J.B. Meigs: Consultant; Self; Quest Diagnostics. P.W. Wilson: None. P. Reaven: Consultant; Self; Boston Heart Diagnostics, Intercept Pharmaceuticals, Inc. Research Support; Self; Bristol-Myers Squibb, Lysulin. M.K. Rhee: Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc. Y.V. Sun: None. L.S. Phillips: Research Support; Self; AbbVie Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, GlaxoSmithKline plc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Pfizer Inc., Sanofi-Aventis. Other Relationship; Self; Diasyst, Janssen Pharmaceuticals, Inc. Funding U.S. Department of Veterans Affairs (I01-CX001737, IK2-CX001907-01)

Major depressive disorder is the most common neuropsychiatric disorder, affecting 11% of veterans. Here we report results of a large meta-analysis of depression using data from the Million Veteran Program, 23andMe, UK Biobank and FinnGen, including individuals of European ancestry (n = 1,154,267; 340,591 cases) and African ancestry (n = 59,600; 25,843 cases). Transcriptome-wide association study analyses revealed significant associations with expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others. We fine-mapped 178 genomic risk loci, and we identified likely pathogenicity in these variants and overlapping gene expression for 17 genes from our transcriptome-wide association study, including TRAF3. Finally, we were able to show substantial replications of our findings in a large independent cohort (n = 1,342,778) provided by 23andMe. This study sheds light on the genetic architecture of depression and provides new insight into the interrelatedness of complex psychiatric traits. This bi-ancestral genome-wide association study of major depressive disorder (MDD) identified 178 risk variants. The results advance understanding of the biology of MDD and hint at new treatment possibilities.

SummaryBlood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including 563,946 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering the full allele frequency spectrum of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood cell traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell GWAS to interrogate clinically meaningful variants across the full allelic spectrum of human variation.

SUMMARYMost loci identified by GWAS have been found in populations of European ancestry (EA). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EA individuals, we identified 5,552 trait-variant associations at P−9, including 71 novel loci not found in EA populations. We also identified novel ancestry-specific variants not found in EA, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional, and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EA-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations, and compared genetic architecture and the impact of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Aims The aim of this study was to use Mendelian randomization (MR) to determine the causality of the association between smoking and 14 different cardiovascular diseases (CVDs). Methods and results Our primary genetic instrument comprised 361 single-nucleotide polymorphisms (SNPs) associated with smoking initiation (ever smoked regularly) at genome-wide significance. Data on the associations between the SNPs and 14 CVDs were obtained from the UK Biobank study (N = 367 643 individuals), CARDIoGRAMplusC4D consortium (N = 184 305 individuals), Atrial Fibrillation Consortium (2017 dataset; N = 154 432 individuals), and Million Veteran Program (MVP; N = 190 266 individuals). The main analyses were conducted using the random-effects inverse-variance weighted method and complemented with multivariable MR analyses and the weighted median and MR-Egger approaches. Genetic predisposition to smoking initiation was most strongly and consistently associated with higher odds of coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension. Genetic predisposition to smoking initiation was additionally associated with higher odds of deep vein thrombosis and pulmonary embolism in the UK Biobank but not with venous thromboembolism in the MVP. There was limited evidence of causal associations of smoking initiation with atrial fibrillation, aortic valve stenosis, thoracic aortic aneurysm, and intracerebral and subarachnoid haemorrhage. Conclusion This MR study supports a causal association between smoking and a broad range of CVDs, in particular, coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension.

Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.91, p = 2.3*10−11). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.025 SD, 3.7*10−43), alkaline phosphatase (-0.025 SD, 1.2*10−37), total cholesterol (-0.030 SD, p = 1.9*10−36) and LDL cholesterol (-0.027 SD, p = 5.1*10−30) levels. We identified a series of additional MARC1 alleles (low-frequency missense p.M187K and rare protein-truncating p.R200Ter) that also associated with lower cholesterol levels, liver enzyme levels and reduced risk of cirrhosis (0 cirrhosis cases for 238 R200Ter carriers versus 17,046 cases of cirrhosis among 759,027 non-carriers, p = 0.04) suggesting that deficiency of the MARC1 enzyme may lower blood cholesterol levels and protect against cirrhosis., Author summary Cirrhosis is a leading cause of death worldwide. However, the genetic underpinnings of cirrhosis remain poorly understood. In this study, we analyze twelve thousand individuals with cirrhosis and identify a common missense variant in a gene called MARC1 that protects against cirrhosis. Carriers of this missense variant also have lower blood cholesterol levels, lower liver enzyme levels and reduced liver fat. We identify an additional two low-frequency coding variants in MARC1 that are also associated with lower cholesterol levels, lower liver enzyme levels and protection from cirrhosis. Finally, we identify an individual homozygous for a predicted loss-of-function variant in MARC1 who exhibits very low blood LDL cholesterol levels. These genetic findings suggest that MARC1 deficiency may lower blood cholesterol levels and protect against cirrhosis, pointing to MARC1 as a potential therapeutic target for liver disease.

Summary Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation., Graphical Abstract, Highlights • Largest genome-wide association study of blood cell traits to date • Empiric assessments of omnigenic and infinitesimal models of polygenic variation • Functional insights into how genetic variants impact human hematopoiesis • Assessment of the effect of polygenic trait scores upon blood diseases, Analysis of blood cell traits in the UK Biobank and other cohorts illuminates the full genetic architecture of hematopoietic phenotypes, with evidence supporting the omnigenic model for complex traits and linking polygenic burden with monogenic blood diseases.

BackgroundTherapeutic inhibition of PCSK9 protects against coronary artery disease (CAD) and ischemic stroke (IS). The impact on other diseases remains less well characterized.MethodsWe created a genetic risk score (GRS) forPCSK9using four single nucleotide polymorphisms (SNPs) at or near thePCSK9locus known to impact lower LDL-Cholesterol (LDL-C): rs11583680, rs11591147, rs2479409, and rs11206510. We then used our GRS to calculate weighted odds ratios reflecting the impact of a genetically determined 10 mg/dL decrease in LDL-C on several pre-specified phenotypes including CAD, IS, peripheral artery disease (PAD), abdominal aortic aneurysm (AAA), type 2 diabetes, dementia, chronic obstructive pulmonary disease, and cancer. Finally, we used our weighted GRS to perform a phenome-wide association study.ResultsGenetic and electronic health record data that passed quality control was available in 312,097 individuals, (227,490 White participants, 58,907 Black participants, and 25,700 Hispanic participants).PCSK9mediated reduction in LDL-C was associated with a reduced risk of CAD and AAA in trans-ethnic meta-analysis (CAD OR 0.83 [95% CI 0.80–0.87], p = 6.0 x 10−21; AAA OR 0.76 [95% CI 0.68–0.86], p = 2.9 x 10−06). Significant protective effects were noted for PAD in White individuals (OR 0.83 [95% CI 0.71–0.97], p = 2.3 x 10−04) but not in other genetic ancestries. Genetically reduced PCSK9 function associated with a reduced risk of dementia in trans-ethnic meta-analysis (OR 0.86 [95% CI 0.78–0.93], p = 5.0 x 10−04).ConclusionsGenetically reduced PCSK9 function results in a reduction in risk of several important extra-coronary atherosclerotic phenotypes in addition to known effects on CAD and IS, including PAD and AAA. We also highlight a novel reduction in risk of dementia, supporting a well-recognized vascular component to cognitive impairment and an opportunity for therapeutic repositioning.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. We meta-analyzed GWAS data from 18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes.

Myeloproliferative neoplasms (MPNs) are blood cancers characterized by excessive production of mature myeloid cells that result from the acquisition of somatic driver mutations in hematopoietic stem cells (HSCs)1. While substantial progress has been made to define the causal somatic mutation profile for MPNs2, epidemiologic studies indicate a significant heritable component for the disease that is among the highest known for all cancers3. However, only a limited set of genetic risk loci have been identified, and the underlying biological mechanisms leading to MPN acquisition remain unexplained. Here, to define the inherited risk profile, we conducted the largest genome-wide association study of MPNs to date (978,913 individuals with 3,224 cases) and identified 14 genome-wide significant loci, as well as a polygenic signature that increases the odds for disease acquisition by nearly 3-fold between the top and median deciles. Interestingly, we find a shared genetic architecture between MPN risk and several hematopoietic traits spanning distinct lineages, as well as an association between increased MPN risk and longer leukocyte telomere length, collectively implicating HSC function and self-renewal. Strikingly, we find a significant enrichment for risk variants mapping to accessible chromatin in HSCs compared with other hematopoietic populations. Finally, gene mapping identifies modulators of HSC biology and targeted variant-to-function analyses suggest likely roles for CHEK2 and GFI1B in altering HSC function to confer disease risk. Overall, we demonstrate the power of human genetic studies to illuminate a previously unappreciated mechanism for MPN risk through modulation of HSC function.

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.

Objective Traumatic brain injury (TBI) research in Veterans is based primarily on non-Hispanic White samples, which does not reflect the diversity of the current military population. We examined the relationship between race/ethnicity and clinical outcomes in a large sample of Iraq/Afghanistan-era Veterans within the Million Veteran Program. Method Primary outcomes included injury characteristics, neurobehavioral-related symptoms, and employment status gleaned from the Comprehensive TBI Evaluation (CTBIE) for 7006 Veterans with a clinician-confirmed history of TBI. Logistic regressions adjusting for age, sex, and education examined the effect of race/ethnicity on CTBIE outcomes. Results Racial/ethnic groups included non-Hispanic White (n = 4203), Hispanic (¬n = 1302), non-Hispanic Black (n = 951), Asian (¬n = 205), Multiracial (¬n = 157), Native Hawaiian/Pacific Islander (−n = 91), and American Indian/Alaska Native (¬n = 79). Race/ethnicity was significantly associated with 5/10 CTBIE variables after applying Bonferroni-correction: blast exposure, loss of consciousness, post-traumatic amnesia (PTA), affective neurobehavioral symptoms, and unemployment (p’s Conclusions Results highlight that certain TBI outcomes—particularly those related to injury characteristics and affective symptoms—vary by race/ethnicity. An enhanced understanding of how outcomes are modified by race/ethnicity is vital so that clinical care can be appropriately tailored to the unique needs of racially and ethnically diverse Veterans. Future studies should further elucidate the relationship between race/ethnicity and TBI outcomes.

In search for common genetic variants contributing to the risk of prostate cancer in men of African ancestry, we conducted a meta-analysis of GWAS summary statistics from the African Ancestry Prostate Cancer Consortium (AAPC; 12,643 cases and 16,627 controls) and the VA Million Veteran Program (6,107 cases and 47,412 controls). A total of 29,896,808 common (minor allele frequency (MAF) > 0.01) genotyped and imputed variants (r2 > 0.3) were meta-analyzed in a total of 18,750 prostate cancer cases and 64,039 controls. Of the 269 established risk variants for prostate cancer, 265 were polymorphic and 168 were nominally (P Citation Format: Fei Chen, Ravi K. Madduri, Xin Sheng, Alex Rodriguez, Alisha Chou, Todd L. Edwards, Stephen K. Van Den Eeden, Rosalind A. Eeles, John S. Witte, Michael B. Cook, William J. Blot, David V. Conti, John M. Gaziano, Amy C. Justice, Christopher A. Haiman, VA Million Veteran Program and PRACTICAL/ELLIPSE Consortium. Meta-analysis in more than 80,000 men of African ancestry identified nine novel variants associated with prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB011.

Individuals vary in their liability to develop Posttraumatic Stress Disorder (PTSD), the symptoms of which are highly heterogeneous, following exposure to life-threatening trauma. Understanding genetic factors that contribute to the biology of PTSD is critical for refining diagnosis and developing new treatments. Using genetic data from more than 250,000 participants in the Million Veteran Program, genomewide association analyses were conducted using a validated electronic health record-based algorithmically-defined PTSD diagnosis phenotype (48,221 cases and 217,223 controls), and PTSD quantitative symptom phenotypes (212,007 individuals). We identified several genome-wide significant loci in the case-control analyses, and numerous such loci in the quantitative trait analyses, including some (e.g., MAD1L1; TCF4; CRHR1) that were associated with multiple symptom sub-domains and total symptom score, and others that were more specific to certain symptom sub-domains (e.g., CAMKV to re-experiencing; SOX6 to hyperarousal). Genetic correlations between all pairs of symptom sub-domains and their total were very high (rg 0.93 – 0.98) supporting validity of the PTSD diagnostic construct. We also demonstrate strong shared heritability with a range of traits, show that heritability persists when conditioned on other major psychiatric disorders, present independent replication results, provide support for one of the implicated genes in postmortem brain of individuals with PTSD, and use this information to identify potential drug repositioning candidates. These results point to the utility of genetics to inform and validate the biological coherence of the PTSD syndrome despite considerable heterogeneity at the symptom level, and to provide new directions for treatment development.

INTRODUCTION: Previous studies of the relationship between fried food consumption and coronary artery disease (CAD) have yielded conflicting results. We tested the hypothesis that frequent fried food consumption is associated with a higher risk of incident CAD events in Million Veteran Program (MVP) participants. METHODS: Veterans Health Administration electronic health record data were linked to questionnaires completed at MVP enrollment. Self-reported fried food consumption at baseline was categorized: (

BackgroundThe Department of Veterans Affairs Million Veteran Program (MVP) is the largest ongoing cohort program of its kind, with 654,903 enrollees as of June 2018. The objectives of this study were to examine gender differences in the MVP cohort with respect to response and enrollment rates; demographic, health, and health care characteristics; and prevalence of self-reported health conditions.MethodsThe MVP Baseline Survey was completed by 415,694 veterans (8% women), providing self-report measures of demographic characteristics, health status, and medical history.ResultsRelative to men, women demonstrated a higher positive responder rate (23.0% vs. 16.0%), slightly higher enrollment rate (13.5% vs. 12.9%), and, among enrollees, a lower survey completion rate (59.7% vs. 63.8%). Women were younger, more racially diverse, had higher educational attainment, and were less likely to be married or cohabitating with a partner than men. Women were more likely to report good to excellent health status but poorer physical fitness, and less likely to report lifetime smoking and drinking than men. Compared with men, women veterans showed an increased prevalence of musculoskeletal conditions, thyroid problems, gastrointestinal conditions, migraine headaches, and mental health disorders, as well as a decreased prevalence of gout, cardiovascular diseases, high cholesterol, diabetes, and hearing problems.ConclusionsThese results revealed some substantial gender differences in the research participation rates, demographic profile, health characteristics, and prevalence of health conditions for veterans in the MVP cohort. Findings highlight the need for tailoring recruitment efforts to ensure representation of the increasing women veteran population receiving care through the Veterans Health Administration.

Here we report a large genome-wide association study (GWAS) for longitudinal smoking phenotypes in 286,118 individuals from the Million Veteran Program (MVP) where we identified 18 loci for smoking trajectory of current versus never in European Americans, one locus in African Americans, and one in Hispanic Americans. Functional annotations prioritized several dozen genes where significant loci co-localized with either expression quantitative trait loci or chromatin interactions. The smoking trajectories were genetically correlated with 209 complex traits, for 33 of which smoking was either a causal or a consequential factor. We also performed European-ancestry meta-analyses for smoking status in the MVP and GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN) (Ntotal = 842,717) and identified 99 loci for smoking initiation and 13 loci for smoking cessation. Overall, this large GWAS of longitudinal smoking phenotype in multiple populations, combined with a meta-GWAS for smoking status, adds new insights into the genetic vulnerability for smoking behavior., Genome-wide association studies (GWASs) for cigarette smoking have identified several hundred loci that account for a small proportion of the overall genetic risk. Here, the authors report a large GWAS for smoking trajectories and meta-analysis for smoking status, finding multiple plausible loci.

We developed an algorithm for identifying U.S. veterans with a history of posttraumatic stress disorder (PTSD), using the Department of Veterans Affairs (VA) electronic medical record (EMR) system. This work was motivated by the need to create a valid EMR-based phenotype to identify thousands of cases and controls for a genome-wide association study of PTSD in veterans. We used manual chart review (n = 500) as the gold standard. For both the algorithm and chart review, three classifications were possible: likely PTSD, possible PTSD, and likely not PTSD. We used Lasso regression with cross-validation to select statistically significant predictors of PTSD from the EMR and then generate a predicted probability score of being a PTSD case for every participant in the study population (range: 0-1.00). Comparing the performance of our probabilistic approach (Lasso algorithm) to a rule-based approach (International Classification of Diseases [ICD] algorithm), the Lasso algorithm showed modestly higher overall percent agreement with chart review than the ICD algorithm (80% vs. 75%), higher sensitivity (0.95 vs. 0.84), and higher accuracy (AUC = 0.95 vs. 0.90). We applied a 0.7 probability cut-point to the Lasso results to determine final PTSD case-control status for the VA population. The final algorithm had a 0.99 sensitivity, 0.99 specificity, 0.95 positive predictive value, and 1.00 negative predictive value for PTSD classification (grouping possible PTSD and likely not PTSD) as determined by chart review. This algorithm may be useful for other research and quality improvement endeavors within the VA.Spanish Abstracts by Asociación Chilena de Estrés Traumático (ACET) Validación de un algoritmo basado en registros médicos electrónicos para identificar el trastorno por estrés postraumático en veteranos de los EE. UU. VALIDACIÓN DE ALGORITOMO DE TEPT Desarrollamos un algoritmo para identificar a los veteranos de EE. UU. con historial de trastorno de estrés postraumático (TEPT), utilizando el sistema de registro médico electrónico (RME) del Departamento de Asuntos de Veteranos (AS). Este trabajo fue motivado por la necesidad de crear un fenotipo válido, basado en RME para identificar miles de casos y controles para un estudio de asociación del genoma del TEPT en los veteranos. Utilizamos la revisión manual de tablas (n = 500) como gold estándar. Tanto para el algoritmo como para la revisión de la tabla, fueron posibles tres clasificaciones: PTSD probable, PTSD posible y probablemente no PTSD. Usamos la regresión Lasso con validación cruzada para seleccionar los factores de pronóstico estadísticamente significativos del TEPT a partir de la RME y luego generar una puntuación de probabilidad pronosticada de ser un caso de TEPT para cada participante en la población del estudio (rango: 0-1.00). Comparando el rendimiento de nuestro enfoque probabilístico (algoritmo Lasso) con un enfoque basado en reglas (algoritmo de Clasificación Internacional de Enfermedades [CIE]), el algoritmo Lasso mostró un porcentaje de acuerdo global modestamente más alto con la revisión de tablas que el algoritmo CIE (80% vs. 75). %), mayor sensibilidad (0.95 frente a 0.84) y mayor precisión (AUC = 0.95 frente a 0.90). Aplicamos un punto de corte de probabilidad de 0.7 a los resultados de Lasso para determinar el estado final de control de caso de TEPT para la población de AV. El algoritmo final tuvo una sensibilidad de 0.99, una especificidad de 0.99, un valor predictivo positivo de 0.95 y un valor predictivo negativo de 1.00 para la clasificación de TEPT (agrupación de TEPT posible y probablemente no TEPT) según lo determinado por la revisión de la tabla. Este algoritmo puede ser útil para otros esfuerzos de investigación y mejora de la calidad dentro del AV.Traditional and Simplified Chinese Abstracts by the Asian Society for Traumatic Stress Studies (AsianSTSS) 簡體及繁體中文撮要由亞洲創傷心理研究學會翻譯 Validation of an Electronic Medical Record-Based Algorithm for Identifying Posttraumatic Stress Disorder in U.S. Veterans Traditional Chinese 標題: 用以找出患創傷後壓力症美國退役軍人的電子健康紀錄為本演算法的效度驗證 撮要: 我們採用美國退伍軍人事務部(VA)電子健康紀錄(EMR)系統, 建立用以找出曾患創傷後壓力症(PTSD)的美國退役軍人的演算法。我們有見針對退役軍人患PTSD的基因組關連研究需有一個有效的EMR為本表型, 以找出數以千計的個案和對照, 因而作此研究。我們以人手進行圖表回顧作為黃金標準 (n = 500)。在演算法和圖表回顧中的分類法都有三種有可能:很大機會患PTSD、有可能患PTSD、 很大機會沒有患PTSD。我們採用Lasso迴歸法並進行交叉驗證, 從EMR選取具統計顯著性的PTSD預測變量, 然後對每個研究樣本作出患PTSD的概率分數預測(值域: 0-1.00)。我們採用的概率分析法(Lasso 演算法) 相比規條為本的分析法 (國際疾病分類 [ICD] 演算法), 在圖表回顧方面反映稍為較高的整體吻合百分比 (80% vs. 75%), 並有較高敏感度(0.95 vs. 0.84)和準確度(AUC = 0.95 vs. 0.90)。針對Lasso的分析結果, 我們以0.7概率作為取錄點以最後定義VA人口的PTSD個案對照狀態。圖表回顧對於PTSD 分類 (把有可能患 PTSD 及很大機會沒患PTSD結合 ) , 最後的演算法敏感度為 0.99、特殊度 0.99、正向預測值 0.95、負向預測值1.00。此演算法對VA的其他研究和非量化改善計劃可能有所幫助。 Simplified Chinese 标题: 用以找出患创伤后压力症美国退役军人的电子健康纪录为本算法的效度验证 撮要: 我们采用美国退伍军人事务部(VA)电子健康纪录(EMR)系统, 建立用以找出曾患创伤后压力症(PTSD)的美国退役军人的算法。我们有见针对退役军人患PTSD的基因组关连研究需有一个有效的EMR为本表型, 以找出数以千计的个案和对照, 因而作此研究。我们以人手进行图表回顾作为黄金标准 (n = 500)。在算法和图表回顾中的分类法都有三种有可能:很大机会患PTSD、有可能患PTSD、 很大机会没有患PTSD。我们采用Lasso回归法并进行交叉验证, 从EMR选取具统计显著性的PTSD预测变量, 然后对每个研究样本作出患PTSD的概率分数预测(值域: 0-1.00)。我们采用的概率分析法(Lasso 算法) 相比规条为本的分析法 (国际疾病分类 [ICD] 算法), 在图表回顾方面反映稍为较高的整体吻合百分比 (80% vs. 75%), 并有较高敏感度(0.95 vs. 0.84)和准确度(AUC = 0.95 vs. 0.90)。针对Lasso的分析结果, 我们以0.7概率作为取录点以最后定义VA人口的PTSD个案对照状态。图表回顾对于PTSD 分类 (把有可能患 PTSD 及很大机会没患PTSD结合 ) , 最后的算法敏感度为 0.99、特殊度 0.99、正向预测值 0.95、负向预测值1.00。此算法对VA的其他研究和非量化改善计划可能有所帮助。.

We used GWAS in the Million Veteran Program sample (nearly 200,000 informative individuals) using a continuous trait for anxiety (GAD-2) to identify 5 genome-wide significant (GWS) signals for European Americans (EA) and 1 for African Americans. The strongest findings were on chromosome 3 (rs4603973, p=7.40×10−11) near the SATB1 locus, a global regulator of gene expression and on chromosome 6 (rs6557168, p=1.04×10−9) near ESR1 which encodes estrogen receptor α. A locus identified on chromosome 7 near MADIL1 (p=1.62×10−8) has been previously identified in GWAS of bipolar disorder and of schizophrenia and may represent a risk factor for psychiatric disorders broadly. SNP-based heritability was estimated to be ~6% for GAD-2. We also GWASed for self-reported anxiety disorder diagnoses (N=224,330) and identified two GWS loci, one (rs35546597, MAF=0.42, p=1.88×10−8) near the AURKB locus, and the other (rsl0534613, MAF=0.41, p=4.92×10−8) near the IQCHE and MADIL1 locus identified in the GAD-2 analysis. We demonstrate reproducibility by replicating our top findings in the summary statistics from the Anxiety NeuroGenetics Study (ANGST) and a UK Biobank neuroticism GWAS. We also replicated top findings from a large UK Biobank preprint, demonstrating stability of GWAS findings in complex traits once sufficient power is attained. Finally, we found evidence of significant genetic overlap between anxiety and major depression using polygenic risk scores, but also found that the main anxiety signals are independent of those for MDD. This work presents novel insights into the neurobiological risk underpinning anxiety and related psychiatric disorders.SignificanceAnxiety disorders are common and often disabling. They are also frequently co-morbid with other mental disorders such as major depressive disorder (MDD); these disorders may share commonalities in their underlying genetic architecture. Using one of the largest homogenously phenotyped cohorts available, the Million Veteran Program sample, we investigated common variants associated with anxiety in genome-wide association studies (GWASes), using survey results from the GAD-2 anxiety scale (as a continuous trait, n=199,611), and self-reported anxiety disorder diagnosis (as a binary trait, n=224,330). This largest GWAS to date for anxiety and related traits identified numerous novel significant associations, several of which are replicated in other datasets, and allows inference of underlying biology.

The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total n > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease).

BackgroundAccurate breast cancer risk assessment allows personalized approach in breast cancer screening and/or prevention. Breast cancer risk prediction models have been developed. Independent prospective validation however was needed before broad clinical applications. The Department of Veterans Affairs (VA) Million Veteran Program (MVP) is one of the largest biobanks in the world. Important attributes include: large sample size (>830,000, April 20), national coverage, multi-ethnic representation, access to bio-specimens from which multi-omics measurements have been conducted, thousands of biomedical phenotypes derived from our baseline and life style surveys and electronic health records (EHR). About 9% of MVP registrants are women. Breast cancer risk prediction models were evaluated in a prospective cohort of women in MVP. MethodologyMore than 350000 MVP participants completed genotyping to date. Breast cancer diagnoses were captured from the EHR. Ethnicity was determined by a supervised learning algorithm, Harmonized Ancestry and Race/Ethnicity (HARE), that used genetically inferred ancestry to refine self-identified race/ethnicity. Clinical breast cancer risk prediction instruments were based on personal health, lifestyle, demographics, family history, and environmental exposure. Polygenic Risk Score used in this study is comprised of 313 single nucleotide polymorphisms (PRS313). Clinical risk models tested were: BPC3, Lit and Breast Cancer Risk Assessment Tool (BCRAT, a version of the Gail’s model). The BPC3 and Lit models were tested by deploying the iCARE (Individualized Cancer Absolute Risk Estimator) with or without incorporation of PRS313. The BCRAT was deployed in the R package “BCRA” (Breast Cancer Risk Assessment v. 2.1 by F. Zhang). The performance of the risk prediction models was assessed by Area under the Receiver Operating Characteristic Curve (AUC-ROC). The observed absolute risk over expected absolute risk was compared for each decile. Results35133 genetic females were identified without a prior breast cancer diagnosis. By HARE definition, 10717 were African Americans (AA), 317 non-Hispanic Asians (ASIAN), 19941 non-Hispanic whites (EU), 1803 Hispanic (HIS) and 1355 unassigned. The median age of this cohort at MVP entry was 55. 369 subjects developed incident breast cancers with a median follow up of 4 years. These new cases were identified from Cancer Registry (292 cases) and EHR search for compatible ICD plus CPT codes (77 cases). The breast cancer incidence rate was 2.6/1000/year. iCARE-lit model was tested in 2731 AA women (38 incident breast cancers), 9027 EU women (111 incident breast cancers), and 10254 non-AA women (122 incident breast cancers) that had comprehensive risk factor evaluation (20%. The iCARE-BPC3 had similar performance as iCARE-lit. The AUC of BCRAT alone was 0.648 for EU (20550 with 179 incident breast cancers) and 0.661 for AA (10462 with 96 incident breast cancers). Incorporation of PRS313 to BCRAT improved the AUC to 0.682 (EU) and 0.658 (AA). BCRAT plus PRS313 estimated that 5.6% (AA) and 4.4% (EU) of the women would have a lifetime risk of >20%. DiscussionWe prospectively evaluated and validated the performance of breast cancer risk prediction models as reported from case control studies. Longer follow up of more women in MVP will provide better assessment esp. for AA women. Prospective validation of these risk prediction models provides strong rationale for further development of these models in the clinical setting. Citation Format: Shiuh-Wen Luoh, Cynthia Brandt, Sally Haskell, Lina Gao, Byung Park, Paul Spellman, Saiju Pyarajan, Million Veteran Program, Nallakkandi Rajeevan, Jessica Minnier. Predicting breast cancer risk for women veterans [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-07.

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine., Author summary Blood lipid levels are closely linked to cardio-metabolic diseases, and genetic factors play an important role in their metabolism and regulation. Although over 400 loci have been identified through genetic association studies, the genetic architecture of lipid levels is not fully characterized. The lack of representation of diverse populations in previous studies resulted in a large gap in understanding the genetic background of lipid traits between European and minority populations, including African Americans, Hispanics, Hawaiians, and Native Americans. In our current analyses which included ancestrally diverse populations, we identified nine novel loci, one novel gene, and minority-specific independent signals at eight known loci, and pinpointed potential functional variants at two known loci. We further observed smaller effect sizes of reported lipids-associated loci in African Americans and Hispanics than those in Europeans, and better performance of polygenic risk scores using minority-specific instead of European-derived effect sizes when estimating genetic predisposition in minority populations. Our findings showed the benefits of including multi-ethnic studies in identification and refinement of lipids-associated loci, which will help to reduce the existing disparities and to pave the road to precision medicine.

BackgroundHabitual alcohol use can be an indicator of alcohol dependence, which is associated with a wide range of serious health problems.MethodsWe completed a genome-wide association study in 126,936 European American and 17,029 African American subjects in the Veterans Affairs Million Veteran Program for a quantitative phenotype based on maximum habitual alcohol consumption.ResultsADH1B, on chromosome 4, was the lead locus for both populations: for the European American sample, rs1229984 (p= 4.9× 10-47); for African American, rs2066702 (p= 2.3× 10-12). In the European American sample, we identified three additional genome-wide-significant maximum habitual alcohol consumption loci: on chromosome 17, rs77804065 (p= 1.5× 10-12), at CRHR1 (corticotropin-releasing hormone receptor 1); the protein product of this gene is involved in stress and immune responses; and on chromosomes 8 and 10. European American and African American samples were then meta-analyzed; the associated region at CRHR1 increased in significance to 1.02× 10-13, and we identified two additional genome-wide significant loci, FGF14 (p= 9.86× 10-9) (chromosome 13) and a locus on chromosome 11. Besides ADH1B, none of the five loci have prior genome-wide significant support. Post-genome-wide association study analysis identified genetic correlation to other alcohol-related traits, smoking-related traits, and many others. Replications were observed in UK Biobank data. Genetic correlation between maximum habitual alcohol consumption and alcohol dependence was 0.87 (p= 4.78× 10-9). Enrichment for cell types included dopaminergic and gamma-aminobutyric acidergic neurons in midbrain, and pancreatic delta cells.ConclusionsThe present study supports five novel alcohol-use risk loci, with particularly strong statistical support for CRHR1. Additionally, we provide novel insight regarding the biology of harmful alcohol use.

Moderate alcohol consumption has been associated with a lower risk of coronary artery disease (CAD) in the general population but has not been well studied in US veterans. We obtained self-reported alcohol consumption from Million Veteran Program participants. Using electronic health records, CAD events were defined as 1 inpatient or 2 outpatient diagnosis codes for CAD, or 1 code for a coronary procedure. We excluded participants with prevalent CAD (n = 69,995) or incomplete alcohol information (n = 8,449). We used a Cox proportional hazards model to estimate hazard ratios and 95% confidence intervals for CAD, adjusting for age, gender, body mass index, race, smoking, education, and exercise. Among 156,728 participants, the mean age was 65.3 years (standard deviation = 12.1) and 91% were men. There were 6,153 CAD events during a mean follow-up of 2.9 years. Adjusted hazard ratios (95% confidence intervals) for CAD were 1.00 (reference), 1.02 (0.92 to 1.13), 0.83 (0.74 to 0.93), 0.77 (0.67 to 0.87), 0.71 (0.62 to 0.81), 0.62 (0.51 to 0.76), 0.58 (0.46 to 0.74), and 0.95 (0.85 to 1.06) for categories of never drinker; former drinker; current drinkers of ≤0.5 drink/day, >0.5 to 1 drink/day, >1 to 2 drinks/day, >2 to 3 drinks/day, and >3 to 4 drinks/day; and heavy drinkers (>4 drinks/day) or alcohol use disorder, respectively. For a fixed amount of ethanol, intake at ≥3 days/week was associated with lower CAD risk compared with ≤1 day/week. Beverage preference (beer, wine, or liquor) did not influence the alcohol-CAD relation. Our data show a lower risk of CAD with light-to-moderate alcohol consumption among US veterans, and drinking frequency may provide a further reduction in risk.

Introduction: PAD is a leading cause of cardiovascular morbidity and mortality. Previously published GWAS have been limited by small sample sizes and have only identified 3 genome-wide significant (P-8 ) risk loci to date. Hypothesis: DNA sequence variants affecting multiple biological pathways are associated with PAD risk. Methods: Using electronic health record data, we identified individuals with and without clinical PAD from the 353,323 Million Veteran Program (MVP) participants genotyped on a customized Affymetrix Biobank array. We tested 32 million genotyped and imputed DNA variants for association with clinical PAD separately in participants of European (EUR), African (AFR), and Hispanic (HIS) ancestry using logistic regression models controlling for age, sex and population structure, and then performed trans-ethnic meta-analysis. The results were replicated with data from the UK Biobank. Results: We identified 31,307 individuals (24,009 EUR, 5,373 AFR, 1,925 HIS) with, and 211,753 individuals without, PAD. Following meta-analysis and replication, there were 19 genome-wide significant risk loci associated with PAD. We replicated a known association at 9p21 (P=4.3 x10 -39 ), and identified several novel loci associated with PAD that were previously known to be associated with atherosclerosis ( LPA , HDAC9 ), diabetes ( TCF7L2 ), lipid levels ( LPL , CELSR2 ), and tobacco use ( CHRNA3 ). We also identified a novel association with PAD for the Factor V Leiden (FVL) mutation (OR 1.20, P=1.6x10 -12 ), which remained significant after controlling for venous thromboembolism (OR 1.10, P=8.7x10 -4 ). Sensitivity analysis demonstrated FVL is associated with increasing risk estimates for PAD severity (claudication OR 1.19, P=0.0012; rest pain OR 1.41, P=0.004; tissue loss OR 1.57, P=7x10 -9 ). Conclusions: Using the MVP, we assembled the largest reported cohort of individuals with clinical PAD and genetic data worldwide. Our data replicate known causal risk factors and identify a novel association for FVL and its putative role for thrombosis in the development of clinical PAD.

No data exist on the prevalence of ideal cardiovascular health metrics in a national sample of U.S. veterans. We assessed the prevalence of ideal Life's Simple Seven (LSS) metrics in a cross-sectional study of 554,855 U.S. veterans enrolled in the Million Veteran Program (MVP) from 2011 to 2017. We used the American Heart Association's established criteria to categorize each LSS metric as either poor, intermediate, or ideal for a veteran at time of MVP enrollment. Information on adiposity/body mass index, smoking status, diet, and physical activity was obtained from self-reported survey data, and clinical measurements for total cholesterol, blood pressure, and plasma glucose were obtained from electronic health records. Complete data on all LSS health factors were available for 201,745 veterans. The prevalence of having 0, 1, 2, 3, 4, 5, 6, and 7 ideal cardiovascular health metrics was 29.2%, 34.6%, 22.6%, 10.0%, 3.0%, 0.6%