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The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Aims Sleep duration has been associated with cardiovascular disease, however the effect of sleep on peripheral artery disease (PAD) specifically remains unestablished. We conducted observational and Mendelian randomization (MR) analyses to assess the associations of sleep duration and daytime napping with PAD risk. Methods and results Sleep traits were assessed for associations with incident PAD using cohort analysis among 53 416 Swedish adults. Replicated was sought in a case-control study of 28 123 PAD cases and 128 459 controls from the veterans affairs Million Veteran Program (MVP) and a cohort study of 452 028 individuals from the UK Biobank study (UKB). Two-sample Mendelian randomization (MR) was used for casual inference-based analyses of sleep-related traits and PAD (31 307 PAD cases 211 753 controls). Observational analyses demonstrated a U-shaped association between sleep duration and PAD risk. In Swedish adults, incident PAD risk was higher in those with short sleep [ Conclusion Short sleep duration was associated with an increased risk of PAD.

BackgroundChronic age-related dizziness can arise from dysfunction of the vestibulocochlear system, an elegant neuroanatomical group of pathways that mediates human perception of linear acceleration, gravity, and angular head motion. Studies indicates that 27-46% of chronic imbalance is genetically inherited, nevertheless, underlying genes leading to chronic imbalance remain unknown.MethodsThe Million Veteran Program comprises over 900,000 diverse-ancestry participants. Cases required two diagnoses of dizziness at least six months apart, excluding acute vertiginous syndromes, ataxias, syncope, and traumatic brain injury. Genome-wide association studies (GWAS’) were performed as separate logistic regressions on Europeans, African Americans, and those of Hispanic ancestry, followed by trans-ancestry meta-analysis. Downstream analysis included case-case-GWAS, fine-mapping, probabilistic colocalization of significant variants and genes with eQTLs, and functional analysis of significant hits.ResultsThe final cohort consisted of 50,339 cases and 366,900 controls. Two significant loci were identified in Europeans, another in the Hispanic population, and two additional loci in trans-ancestry meta-analysis. Fine mapping revealed credible sets of intronic single nucleotide polymorphisms in genes includingMLLT10- a histone methyl transferase cofactor,BPTF- a subunit of a nucleosome remodeling complex implicated in neurodevelopment,LINC01224- affecting transcription ofZNF91, a repressor of retrotransposons, andROS1– a proto-oncogene receptor tyrosine kinase.ConclusionBalance dysfunction can lead to catastrophic outcomes, including falls, injury, and death in the elderly. By removing acute vertiginous syndromes and non-cochlear disorders to focus on vestibulocochlear age-related dizziness, findings suggest genomic candidates for further study and ultimate treatment of this common neurologic disease.KEY MESSAGESWhat is already known on this topicThe vestibule of the cochlea is a neuroanatomic structure mediating balance, and chronic imbalance in the elderly is a large predictor of falls and their associated morbidities and mortalities. Chronic vestibular balance is 27% - 46% heritable, however, underlying genes are unknown.What this study addsIn a genome-wide association study, we identified novel single nucleotide polymorphisms and genes associated with chronic dizziness in the elderly.How this study might affect research, practice or policyAscertaining the physiologic/genetic architecture in the cochleovestibular system will aid in future treatment where drug development can target specifically genes related to imbalance. Individuals at higher genetic risk for imbalance can be provided more focused preventive vestibular therapy.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries. A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

Genome-wide association studies (GWAS) provide an unbiased first look at genetic loci involved in aging and noise-induced sensorineural hearing loss and tinnitus. The hearing phenotype, whether audiogram-based or self-report, is regressed against genotyped information at representative single nucleotide polymorphisms (SNPs) across the genome. Findings include the fact that both hearing loss and tinnitus are polygenic disorders, with up to thousands of genes, each of effect size of < 0.02. Smaller human GWAS’ were able to use objective measures and identified a few loci, however, hundreds of thousands of participants have been required for the statistical power to identify significant variants, and GWAS is unable to assess rare variants with mean allele frequency < 1%. Animal studies are required as well because of inability to access the human cochlea. Mouse GWAS builds on linkage techniques and the known phenotypic differences in auditory function between inbred strains. With the advantage that the laboratory environment can be controlled for noise and aging, the Hybrid Mouse Diversity Panel (HDMP) combines 100 strains sequenced at high resolution. Lift-over regions between mice and humans have identified over 17,000 homologous genes. Since most significant SNPs are either intergenic or in introns, and binding sites between species are poorly preserved between species, expression quantitative trait locus information is required to bring humans and mice into agreement. Transcriptome-wide analysis studies (TWAS) can prioritize putative causal genes and tissues. Diverse species, each making a distinct contribution, carry a synergistic advantage in the quest for treatment and ultimate cure of sensorineural hearing difficulties.

Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up., Identifying causal variants and genes in genome-wide association studies remains a challenge, an issue that is ameliorated with larger sample sizes. Here the authors meta-analyze kidney function genome-wide association studies to identify new loci and fine-map loci to home in on variants and genes involved in kidney function.

Objective: Diabetes and dementia are diseases of high healthcare burden worldwide, and studies have shown that diabetes is associated with increased relative risk of dementia. We set out to examine whether type 2 diabetes-associated genetic variants were associated with dementia and if they differed by race/ethnicity or clinical dementia diagnosis. Research Design and Methods: We evaluated associations of two type 2 diabetes genetic risk scores (GRS and GRS-NonAPOE: a score without rs429358, a variant associated with Alzheimer’s disease [AD]) with three classifications of clinical dementia diagnoses in the Million Veteran Program (MVP): all-cause-dementia, vascular dementia (VaD), and AD. We conducted our analysis stratified by European (EUR), African (AFR), and Hispanic (HIS) race/ethnicities. Results: In EUR, we found associations of the GRS with all-cause-dementia (OR = 1.06, P = 1.60e-07), and clinically diagnosed VaD (OR = 1.12, P = 5.2e-05) but not clinically diagnosed AD (OR = 1.02, P = .43). The GRS was not associated with any dementia outcome in AFR or HIS. When testing with GRS-NonAPOE, we found that effect size estimates in EUR increased and P values decreased (for all-cause-dementia OR = 1.08, P = 2.6e-12; for VaD OR = 1.14, P = 7.2e-07and for AD OR = 1.06, P = .018). For AFR, the association of GRS-NonAPOE and clinically diagnosed VaD (OR = 1.15, P = .016) was statistically significant. There were no significant findings for HIS. Conclusions: We found evidence suggesting shared genetic pathogenesis of diabetes with all-cause-dementia and clinically diagnosed VaD.

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

The purpose of this study was to examine subjective cognitive and psychiatric functioning in post-deployed military Veterans who underwent the Veterans Health Administration's Traumatic Brain Injury (TBI) Screening and Evaluation Program and enrolled in the VA's Million Veteran Program (MVP). Veterans (N=7483) were classified into three groups based on outcomes from the TBI Screening and Evaluation Program: (1) negative TBI screen ('Screen-'), (2) positive TBI screen but no TBI diagnosis ('Screen+/TBI-'), or (3) positive TBI screen and TBI diagnosis ('Screen+/TBI+'). Chi-square analyses revealed significant group differences across all self-reported cognitive and psychiatric health conditions (e.g., memory loss, depression), and ANCOVAs similarly showed a significant association between group and subjective symptom reporting. Specifically, the relationship between TBI group and clinical outcome (i.e., health conditions and symptoms) was such that the Screen+/TBI+group fared the worst, followed by the Screen+/TBI- group, and finally the Screen- group. However, evaluation of effect sizes suggested that Veterans in the two Screen+groups (Screen+/TBI+ and Screen+/TBI-) are faring similarly to one another on subjective cognitive and psychiatric functioning, but that both Screen+groups are faring significantly worse than the Screen- group. Our results have meaningful clinical implications and suggest that Veterans who screen positive for TBI, regardless of ultimate TBI diagnosis, be eligible for similar clinical services so that both groups can benefit from valuable treatments and therapeutics. Finally, this research sets the stage for follow-up work to be conducted within MVP that will address the neurobiological underpinnings of cognitive and psychiatric distress in this population.

Plasma levels of liver enzymes provide insights into hepatic function and related diseases. Here, the authors perform a genome-wide association study on three liver enzymes, identifying genetic variants associated with their plasma concentration as well as links to metabolic and cardiovascular diseases.Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease.

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10−6; IFNAR2, P = 9.8 × 10−11 and IL-10RB, P = 2.3 × 10−14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P

We conducted genome-wide association analyses of over 250,000 participants of European (EUR) and African (AFR) ancestry from the Million Veteran Program using electronic health record-validated post-traumatic stress disorder (PTSD) diagnosis and quantitative symptom phenotypes. Applying genome-wide multiple testing correction, we identified three significant loci in European case-control analyses and 15 loci in quantitative symptom analyses. Genomic structural equation modeling indicated tight coherence of a PTSD symptom factor that shares genetic variance with a distinct internalizing (mood–anxiety–neuroticism) factor. Partitioned heritability indicated enrichment in several cortical and subcortical regions, and imputed genetically regulated gene expression in these regions was used to identify potential drug repositioning candidates. These results validate the biological coherence of the PTSD syndrome, inform its relationship to comorbid anxiety and depressive disorders and provide new considerations for treatment. Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in individuals of European and African ancestry provide insights into its relationship with anxiety and depressive disorders and identify potential candidates for drug repositioning.

Objective: To examine the association between intakes of sodium and potassium and the ratio of sodium to potassium and incident myocardial infarction and stroke. Design, Setting and Participants: Prospective cohort study of 180,156 Veterans aged 19 to 107 years with plausible dietary intake measured by food frequency questionnaire (FFQ) who were free of cardiovascular disease (CVD) and cancer at baseline in the VA Million Veteran Program (MVP). Main outcome measures: CVD defined as non-fatal myocardial infarction (MI) or acute ischemic stroke (AIS) ascertained using high-throughput phenotyping algorithms applied to electronic health records. Results: During up to 8 years of follow-up, we documented 4090 CVD cases (2499 MI and 1712 AIS). After adjustment for confounding factors, a higher sodium intake was associated with a higher risk of CVD, whereas potassium intake was inversely associated with the risk of CVD [hazard ratio (HR) comparing extreme quintiles, 95% confidence interval (CI): 1.09 (95% CI: 0.99–1.21, p trend = 0.01) for sodium and 0.87 (95% CI: 0.79–0.96, p trend = 0.005) for potassium]. In addition, the ratio of sodium to potassium (Na/K ratio) was positively associated with the risk of CVD (HR comparing extreme quintiles = 1.26, 95% CI: 1.14–1.39, p trend < 0.0001). The associations of Na/K ratio were consistent for two subtypes of CVD; one standard deviation increment in the ratio was associated with HRs (95% CI) of 1.12 (1.06–1.19) for MI and 1.11 (1.03–1.19) for AIS. In secondary analyses, the observed associations were consistent across race and status for diabetes, hypertension, and high cholesterol at baseline. Associations appeared to be more pronounced among participants with poor dietary quality. Conclusions: A high sodium intake and a low potassium intake were associated with a higher risk of CVD in this large population of US veterans.

The onset and persistence of life events (LE) such as housing instability, job instability, and reduced social connection have been shown to increase risk of suicide. Predictive models for suicide risk have low sensitivity to many of these factors due to under-reporting in structured electronic health records (EHR) data. In this study, we show how natural language processing (NLP) can help identify LE in clinical notes at higher rates than reported medical codes. We compare domain-specific lexicons formulated from Unified Medical Language System (UMLS) selection, content analysis by subject matter experts (SME) and the Gravity Project, to datadriven expansion through contextual word embedding using Word2Vec. Our analysis covers EHR from the VA Corporate Data Warehouse (CDW) and measures the prevalence of LE across time for patients with known underlying cause of death in the National Death Index (NDI). We found that NLP methods had higher sensitivity of detecting LE relative to structured EHR variables. We observed that, on average, suicide cases had higher rates of LE over time when compared to patients who died of non-suicide related causes with no previous history of diagnosed mental illness. When used to discriminate these outcomes, the inclusion of NLP derived variables increased the concentration of LE along the top 0.1%, 0.5% and 1% of predicted risk. LE were less informative when discriminating suicide death from non suicide related death for patients with diagnosed mental illness.

To examine the association between intakes of sodium and potassium and the ratio of sodium to potassium and incident myocardial infarction and stroke.Prospective cohort study of 180,156 Veterans aged 19 to 107 years with plausible dietary intake measured by food frequency questionnaire (FFQ) who were free of cardiovascular disease (CVD) and cancer at baseline in the VA Million Veteran Program (MVP).CVD defined as non-fatal myocardial infarction (MI) or acute ischemic stroke (AIS) ascertained using high-throughput phenotyping algorithms applied to electronic health records.During up to 8 years of follow-up, we documented 4090 CVD cases (2499 MI and 1712 AIS). After adjustment for confounding factors, a higher sodium intake was associated with a higher risk of CVD, whereas potassium intake was inversely associated with the risk of CVD [hazard ratio (HR) comparing extreme quintiles, 95% confidence interval (CI): 1.09 (95% CI: 0.99-1.21,A high sodium intake and a low potassium intake were associated with a higher risk of CVD in this large population of US veterans.

Spontaneous coronary artery dissection (SCAD) is a non-atherosclerotic cause of myocardial infarction (MI), typically in young women. We undertook a genome-wide association study of SCAD (Ncases = 270/Ncontrols = 5,263) and identified and replicated an association of rs12740679 at chromosome 1q21.2 (Pdiscovery+replication = 2.19 × 10−12, OR = 1.8) influencing ADAMTSL4 expression. Meta-analysis of discovery and replication samples identified associations with P, Spontaneous coronary artery dissection (SCAD) is a cause of myocardial infarction Here, the authors present a genome-wide association study of SCAD, finding an association at 1q21.2 which potentially affects expression of ADAMTSL4.

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

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect biosamples with consent from at least one million veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records, make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide a genome-wide scan of the entire cohort, in parallel with whole-genome sequencing, methylation, and other ‘omics assays. Here, we present the design and performance of the MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality-control analysis was developed and conducted on an initial tranche of 485,856 individuals, leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high-quality genotypes not only on common variants but also on rare variants. We confirmed that, with non-European individuals making up nearly 30%, MVP’s substantial ancestral diversity surpasses that of other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current dataset has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

BACKGROUND AND AIMS: Observational and clinical trial evidence suggests an inverse association of omega-3 polyunsaturated fatty acid with coronary artery disease (CAD) mortality, although relationships with non-fatal CAD and stroke are less clear. We investigated whether omega-3 fatty acid supplement use and fish intake were associated with incident non-fatal CAD and ischemic stroke among US Veterans. METHODS: The Million Veteran Program (MVP) is an ongoing nation-wide longitudinal cohort study of US Veterans with self-reported survey, biospecimen, and electronic health record data. Regular use of omega-3 supplements (yes/no) and frequency of fish intake within the past year were assessed using a food frequency questionnaire. Cox proportional hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the associations of omega-3 supplement use and fish intake with incident non-fatal CAD and ischemic stroke, defined from electronic health records using validated algorithms. Multivariable models included demographics, body mass index, education, smoking status, alcohol intake, and exercise frequency. RESULTS: Among 197,761 participants with food frequency data (mean age: 66 ± 12 years, 92% men), 21% regularly took omega-3 supplements and median fish intake was 1 (3–5 ounce) serving/week. Over a median follow-up of 2.9 years for non-fatal CAD and 3.3 years for non-fatal ischemic stroke, we observed 6,265 and 4,042 incident cases of non-fatal CAD and non-fatal ischemic stroke, respectively. Omega-3 fatty acid supplement use was independently associated with a lower risk of non-fatal ischemic stroke [HR (95% CI): 0.88 (0.81, 0.95)] but not non-fatal CAD [0.99 (0.93, 1.06)]. Fish intake was not independently associated with non-fatal CAD [1.01 (0.94, 1.09) for 1–3 servings/month, 1.03 (0.98, 1.11) for 1 serving/week, 1.02 (0.93, 1.11) for 2–4 servings/week, and 1.15 (0.98, 1.35) for ≥5 servings/week, reference =

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 in vivo and IL-7 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 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.

The purpose of this study was to examine neurobehavioral symptom reporting in a large sample of military veterans (N=12,144) who completed the Comprehensive Traumatic Brain Injury Evaluation (CTBIE) and enrolled in the VA's Million Veteran Program (MVP). The CTBIE is a clinician-administered interview that assesses for historical, deployment-related traumatic brain injury (TBI) and evaluates symptoms using the Neurobehavioral Symptom Inventory (NSI). Clinicians completing the CTBIE made clinical determinations about participants' (1) TBI diagnostic status (i.e., CTBIE+or CTBIE-) and (2) current symptom etiology (i.e., Symptom Resolution, TBI, Behavioral Health, Comorbid TBI+Behavioral Health [Comorbid], or Other). We evaluated the association of TBI diagnostic status and symptom etiology group with neurobehavioral symptoms. Results showed a significant association between TBI diagnostic status and all NSI variables, with CTBIE+veterans endorsing greater symptoms than CTBIE- veterans. There was also a significant association between symptom etiology group and all NSI variables; specifically, the Comorbid and Behavioral Health groups generally endorsed significantly greater symptoms compared to the other groups. Follow-up analyses showed that relative to the Symptom Resolution group, the Comorbid and Behavioral Health groups had increased odds of severe/very severe cognitive and affective symptoms, whereas the TBI and Other groups did not. Finally, presence of psychiatric symptoms, pain, post-traumatic amnesia, loss of consciousness, and blast exposure significantly predicted Comorbid symptom etiology group membership. Findings from this large epidemiologic MVP study have relevant clinical implications and further highlight the importance of prioritizing integrated behavioral health interventions for this vulnerable population.

The increasing availability of electronic health record (EHR) systems has created enormous potential for translational research. However, it is difficult to know all the relevant codes related to a phenotype due to the large number of codes available. Traditional data mining approaches often require the use of patient-level data, which hinders the ability to share data across institutions. In this project, we demonstrate that multi-center large-scale code embeddings can be used to efficiently identify relevant features related to a disease of interest. We constructed large-scale code embeddings for a wide range of codified concepts from EHRs from two large medical centers. We developed knowledge extraction via sparse embedding regression (KESER) for feature selection and integrative network analysis. We evaluated the quality of the code embeddings and assessed the performance of KESER in feature selection for eight diseases. Besides, we developed an integrated clinical knowledge map combining embedding data from both institutions. The features selected by KESER were comprehensive compared to lists of codified data generated by domain experts. Features identified via KESER resulted in comparable performance to those built upon features selected manually or with patient-level data. The knowledge map created using an integrative analysis identified disease-disease and disease-drug pairs more accurately compared to those identified using single institution data. Analysis of code embeddings via KESER can effectively reveal clinical knowledge and infer relatedness among codified concepts. KESER bypasses the need for patient-level data in individual analyses providing a significant advance in enabling multi-center studies using EHR data.

Although affecting different arterial territories, the related atherosclerotic vascular diseases coronary artery disease (CAD) and peripheral artery disease (PAD) share similar risk factors and have shared pathobiology. To identify novel pleiotropic loci associated with atherosclerosis, we performed a joint analysis of their shared genetic architecture, along with that of common risk factors. Using summary statistics from genome-wide association studies of nine known atherosclerotic (CAD, PAD) and atherosclerosis risk factors (body mass index, smoking initiation, type 2 diabetes, low density lipoprotein, high density lipoprotein, total cholesterol, and triglycerides), we perform 15 separate multi-trait genetic association scans which resulted in 25 novel pleiotropic loci not yet reported as genome-wide significant for their respective traits. Colocalization with single-tissue eQTLs identified candidate causal genes at 14 of the detected signals. Notably, the signal between PAD and LDL-C at the PCSK6 locus affects PCSK6 splicing in human liver tissue and induced pluripotent derived hepatocyte-like cells. These results show that joint analysis of related atherosclerotic disease traits and their risk factors allowed identification of unified biology that may offer the opportunity for therapeutic manipulation. The signal at PCSK6 represent possible shared causal biology where existing inhibitors may be able to be leveraged for novel therapies.

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.

The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and provides novel insights into the molecular mechanisms of severe disease, leading to new therapeutic targets and sensitive detection of at-risk individuals.

Apparent treatment-resistant hypertension (ATRH) has been linked to end-stage kidney disease (ESKD) and cardiovascular disease. We tested the hypothesis that the effect of ATRH on ESKD is greater in Black patients than in White patients and investigated the effect of ATRH on ESKD independent of APOL1 genotype. In a retrospective cohort of 139 685 hypertensive veterans (22% Black, 5% women) in the Million Veteran Program, ATRH was defined as failure to achieve outpatient blood pressure P -interactionAPOL1 genotype. Patients with ATRH experienced excess ESKD and cardiovascular disease risk. This excess ATRH-related ESKD risk was magnified among Black patients independently of APOL1 genotype. Targeted treatment of ATRH could curtail ESKD and cardiovascular disease incidence.

BackgroundPosttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD.MethodsGenetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals.ResultsGenetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01-1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001).ConclusionsOur findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.