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Objective: We aimed to characterise self-reported military and occupational exposures including Agent Orange, chemical/biological warfare agents, solvents, fuels, pesticides, metals and burn pits among Veterans in the Department of Veterans Affairs Million Veteran Program (MVP)., Methods: MVP is an ongoing longitudinal cohort and mega-biobank of over one million US Veterans. Over 500 000 MVP participants reported military exposures on the baseline survey, and over 300 000 reported occupational exposures on the lifestyle survey. We determined frequencies of selected self-reported occupational exposures by service era, specific deployment operation (1990-1991 Gulf War, Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF)), service in a combat zone and occupational categories. We also explored differences in self-reported exposures by sex and race., Results: Agent Orange exposure was mainly reported by Vietnam-era Veterans. Gulf War and OEF/OIF Veterans deployed to a combat zone were more likely to report exposures to burn pits, chemical/biological weapons, anthrax vaccination and pyridostigmine bromide pill intake as compared with non-combat deployers and those not deployed. Occupational categories related to combat (infantry, combat engineer and helicopter pilot) often had the highest percentages of self-reported exposures, whereas those in healthcare-related occupations (dentists, physicians and occupational therapists) tended to report exposures much less often. Self-reported exposures also varied by race and sex., Conclusions: Our results demonstrate that the distribution of self-reported exposures varied by service era, demographics, deployment, combat experience and military occupation in MVP. Overall, the pattern of findings was consistent with previous population-based studies of US military Veterans., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: Glucagon-like peptide 1 receptor agonists (GLP-1RAs) may have nephroprotective properties beyond those related to weight loss and glycemic control., Objective: To investigate the association of genetically proxied GLP-1RAs with kidney disease progression., Design, Setting, and Participants: This genetic association study assembled a national retrospective cohort of veterans aged 18 years or older from the US Department of Veterans Affairs Million Veteran Program between January 10, 2011, and December 31, 2021. Data were analyzed from November 2023 to February 2024., Exposures: Genetic risk score for systemic GLP1R gene expression that was calculated for each study participant based on genetic variants associated with GLP1R mRNA levels across all tissue samples within the Genotype-Tissue Expression project., Main Outcomes and Measures: The primary composite outcome was incident end-stage kidney disease or a 40% decline in estimated glomerular filtration rate. Cox proportional hazards regression survival analysis assessed the association between genetically proxied GLP-1RAs and kidney disease progression., Results: Among 353 153 individuals (92.5% men), median age was 66 years (IQR, 58.0-72.0 years) and median follow-up was 5.1 years (IQR, 3.1-7.2 years). Overall, 25.7% had diabetes, and 45.0% had obesity. A total of 4.6% experienced kidney disease progression. Overall, higher genetic GLP1R gene expression was associated with a lower risk of kidney disease progression in the unadjusted model (hazard ratio [HR], 0.96; 95% CI, 0.92-0.99; P = .02) and in the fully adjusted model accounting for baseline patient characteristics, body mass index, and the presence or absence of diabetes (HR, 0.96; 95% CI, 0.92-1.00; P = .04). The results were similar in sensitivity analyses stratified by diabetes or obesity status., Conclusions and Relevance: In this genetic association study, higher GLP1R gene expression was associated with a small reduction in risk of kidney disease progression. These findings support pleiotropic nephroprotective mechanisms of GLP-1RAs independent of their effects on body weight and glycemic control.

Polygenic scores (PGSs) are a promising tool for estimating individual-level genetic risk of disease based on the results of genome-wide association studies (GWASs). However, their promise has yet to be fully realized because most currently available PGSs were built with genetic data from predominantly European-ancestry populations, and PGS performance declines when scores are applied to target populations different from the populations from which they were derived. Thus, there is a great need to improve PGS performance in currently under-studied populations. In this work we leverage data from two large and diverse cohorts the Million Veterans Program (MVP) and All of Us (AoU), providing us the unique opportunity to compare methods for building PGSs for multi-ancestry populations across multiple traits. We build PGSs for five continuous traits and five binary traits using both multi-ancestry and single-ancestry approaches with popular Bayesian PGS methods and both MVP META GWAS results and population-specific GWAS results from the respective African, European, and Hispanic MVP populations. We evaluate these scores in three AoU populations genetically similar to the respective African, Admixed American, and European 1000 Genomes Project superpopulations. Using correlation-based tests, we make formal comparisons of the PGS performance across the multiple AoU populations. We conclude that approaches that combine GWAS data from multiple populations produce PGSs that perform better than approaches that utilize smaller single-population GWAS results matched to the target population, and specifically that multi-ancestry scores built with PRS-CSx outperform the other approaches in the three AoU populations., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Rare coding alleles play crucial roles in the molecular diagnosis of genetic diseases. However, the systemic identification of these alleles has been challenging due to their scarcity in the general population. Here, we discovered and characterized rare coding alleles contributing to genetic dyslipidemia, a principal risk for coronary artery disease, among over a million individuals combining three large contemporary genetic datasets (the Million Veteran Program, n = 634,535, UK Biobank, n = 431,178, and the All of Us Research Program, n = 92,304) totaling 1,158,017 multi-ancestral individuals. Unlike previous rare variant studies in lipids, this study included 238,243 individuals (20.6%) from non-European-like populations. Testing 2,997,401 rare coding variants from diverse backgrounds, we identified 800 exome-wide significant associations across 209 genes including 176 predicted loss of function and 624 missense variants. Among these exome-wide associations, 130 associations were driven by non-European-like populations. Associated alleles are highly enriched in functional variant classes, showed significant additive and recessive associations, exhibited similar effects across populations, and resolved pathogenicity for variants enriched in African or South-Asian populations. Furthermore, we identified 5 lipid-related genes associated with coronary artery disease (RORC, CFAP65, GTF2E2, PLCB3, and ZNF117) . Among them, RORC is a potentially novel therapeutic target through the down regulation of LDLC by its silencing. This study provides resources and insights for understanding causal mechanisms, quantifying the expressivity of rare coding alleles, and identifying novel drug targets across diverse populations., Competing Interests: Competing interest declaration D.K. is a scientific advisor and reports consulting fees from Bitterroot Bio, Inc unrelated to the present work. P.N. reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech / Roche, and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Foresite Labs, Genentech / Roche, GV, HeartFlow, Magnet Biomedicine, Merck, and Novartis, scientific advisory board membership of Esperion Therapeutics, Preciseli, and TenSixteen Bio, scientific co-founder of TenSixteen Bio, equity in MyOme, Preciseli, and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work.

Background: Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments., Methods: We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in the small integral membrane protein 1 (SMIM1) and the general population, leveraging data from five cohorts. Metabolic characterization of SMIM1 -/- individuals was performed using plasma biochemistry, calorimetric chamber, and DXA scan., Findings: We found that individuals homozygous for a loss-of-function genetic variant in SMIM1 gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin to adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure., Conclusion: This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them., Funding: This work was funded by the National Institute of Health Research, British Heart Foundation, and NHS Blood and Transplant., Competing Interests: Declaration of interests J.S. is the deputy CEO and 50% owner of BLUsang AB. He holds patents on Vel genotyping (inventors: Jill Storry, Magnus Jöud, Björn Nilsson, and Martin L. Olsson). J.S. has received speaker fees, royalties, and honoraria from the following companies: Grifols Diagnostic Solutions, QuidelOrtho Inc., and Biorad Laboratories. J.S. receives an honorarium for Section Editor work, Vox Sanguinis from John Wiley & Sons Ltd. J.S. is Vice President of the International Society of Blood Transfusion and married to Professor M.L.O. M.L.O. is CEO and 50% owner of BLUsang AB. M.L.O. holds patents on Vel genotyping (inventors: Jill Storry, Magnus Jöud, Björn Nilsson, and Martin L. Olsson). M.L.O. received speaker fees, royalties, and honoraria from the following companies: Grifols Diagnostic Solutions, QuidelOrtho Inc., and Biorad Laboratories. M.L.O. is married to Adjunct Professor J.S. W.N.E. is chair of the International Council for Standardization in Haematology. W.N.E. works as advisor for Scorpio Labs and is on the editorial board of the Journal of Clinical Pathology. W.H.O. is chair of the Blood Transfusion Genomics Consortium. W.H.O. is in receipt of an educational/research grant from Thermo Fisher Scientific. N.G. offers scientific consulting services to Thermo Fisher Scientific., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Risk for colorectal cancer (CRC) may accumulate through multiple environmental factors. Understanding their effects, along with genetics, age and family history, could allow improvements in clinical decisions for screening protocols. We aimed to extend previous work by recalibrating an environmental risk score (e-Score) for CRC among a sample of US Veteran participants of the Million Veteran Program (MVP)., Methods: Demographic, lifestyle, and CRC data from 2011-2022 were abstracted from survey responses and health records of 227,504 male MVP participants. Weighting for each environmental factor's effect size was recalculated using VA training data to create a recalibrated e-Score. This recalibrated score was compared with the original weighted e-Score in a validation sample of 113,752 (n cases=590). Nested multiple logistic regression models tested associations between quintiles for recalibrated and original e-Scores. Likelihood Ratio Tests were used to compare model performance., Results: Age (p<0.0001), education (p<0.0001), diabetes (p<0.0001), physical activity (p<0.0001), smoking (p<0.0001), NSAID use (p<0.0001), calcium (p=0.015), folate (p=0.020), and fruit consumption (p=0.019) were significantly different between CRC case and control groups. In the validation sample, the recalibrated e-Score model significantly improved the base model performance (p<0.001), but the original e-Score model did not (p=0.07). The recalibrated e-Score model quintile 5 was associated with significantly higher odds for CRC compared with quintile 1 (Q5 vs Q1: 1.79, 95% CI: 1.38-2.33)., Conclusions: Multiple environmental factors, and the recalibrated e-Score quintiles were significantly associated with CRC cases., Impact: A recalibrated, Veteran-specific e-Score could be used to help personalize CRC screening and prevention strategies.

We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10 percentage points higher in African populations. Three signals (SERPINA1, ZFP36L2, and TLR10) contain predicted deleterious missense variants. Two loci, SOCS3 and HPN, each harbor two conditionally distinct, non-coding variants. The gene region encoding the fibrinogen protein chain subunits (FGG;FGB;FGA), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common in African ancestry populations but extremely rare in Europeans (MAFAFR=0.180; MAFEUR=0.008). Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation., (Copyright © 2024 American Society of Hematology.)

Background: Observational studies have reported strongly protective effects of bariatric surgery on cardiovascular disease, but with oversimplified definitions of the intervention, eligibility criteria, and follow-up, which deviate from those in a randomized trial. We describe an attempt to estimate the effect of bariatric surgery on cardiovascular disease without introducing these sources of bias, which may not be entirely possible with existing observational data., Methods: We propose two target trials among persons with diabetes: (1) bariatric operation (vs. no operation) among individuals who have undergone preoperative preparation (lifestyle modifications and screening) and (2) preoperative preparation and a bariatric operation (vs. neither preoperative nor operative component). We emulated both target trials using observational data of US veterans., Results: Comparing bariatric surgery with no surgery (target trial #1; 8,087 individuals), the 7-year cardiovascular risk was 18.0% (95% CI = 6.9, 32.7) in the surgery group and 18.9% (95% CI = 17.7, 20.1) in the no-surgery group (risk difference -0.9, 95% CI = -12.0, 14.0). Comparing preoperative components plus surgery vs. neither (target trial #2; 10,065 individuals), the 7-year cardiovascular risk was 17.4% (95% CI = 13.6, 22.0) in the surgery group and 18.8% (95% CI = 17.8, 19.9) in the no-surgery group (risk difference -1.4, 95% CI = -5.1, 3.2). Body mass index and hemoglobin A1c were reduced with bariatric interventions in both emulations., Conclusions: Within limitations of available observational data, our estimates do not provide evidence that bariatric surgery reduces cardiovascular disease and support equipoise for a randomized trial of bariatric surgery for cardiovascular disease prevention., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Frailty, a syndrome of physiologic vulnerability, increases cardiovascular disease (CVD) risk. Whether in person or automated frailty tools are ideal for identifying CVD risk remains unclear. We calculated 3 distinct frailty scores and examined their associations with mortality and CVD events in the Million Veteran Program, a prospective cohort of nearly 1 million US veterans., Methods and Results: Veterans aged ≥50 years and enrolled from 2011 to 2018 were included. Two frailty indices (FI) based on the deficit accumulation theory were calculated: the questionnaire-based 36-item Million Veteran Program-FI and 31-item Veterans Affairs-FI using claims data. We calculated Fried physical frailty using the self-reported, 3-item Study of Osteoporotic Fractures. Multivariable-adjusted Cox models examined the association of frailty by each score with primary (all-cause and CVD mortality) and secondary (myocardial infarction, stroke, and heart failure) outcomes. In 190 688 veterans (69±9 years, 94% male, 85% White), 33, 233 (17%) all-cause and 10 115 (5%) CVD deaths occurred. Using Million Veteran Program-FI, 29% were robust, 42% pre-frail, and 29% frail. Frailty prevalence increased by age group (27% in 50-59 to 42% in ≥90 years). Using the Million Veteran Program-FI, over 6±2 years, frail veterans had a higher hazard of all-cause (hazard ratio [HR], 3.05 [95% CI, 2.95-3.16]) and CVD mortality (HR, 3.65 [95% CI, 3.43-3.90]). Findings were concordant for the Veterans Affairs-FI and Study of Osteoporotic Fractures frailty definitions, and remained significant even among younger veterans aged 50-59 years., Conclusions: Irrespective of frailty measure, frailty is associated with a higher risk of all-cause mortality and adverse CVD events. Further study of frailty in veterans aged <60 years old is warranted.

Background: Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke., Methods: We performed genome-wide association studies for subsequent major adverse cardiovascular events (MACE; n cases =51 929; n controls =39 980) and subsequent arterial ischemic stroke (AIS; n cases =45 120; n controls =46 789) after the first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (protein quantitative trait loci) to determine the effect of 1463 plasma protein abundances on subsequent MACE using Mendelian randomization., Results: Two variants were significantly associated with subsequent cardiovascular events: rs76472767 near gene RNF220 (odds ratio, 0.75 [95% CI, 0.64-0.85]; P =3.69×10 -8 ) with subsequent AIS and rs13294166 near gene LINC01492 (odds ratio, 1.52 [95% CI, 1.37-1.67]; P =3.77×10 -8 ) with subsequent MACE. Using Mendelian randomization, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 ([C-C motif chemokine 27], effect odds ratio, 0.77 [95% CI, 0.66-0.88]; adjusted P =0.05) and TNFRSF14 ([tumor necrosis factor receptor superfamily member 14], effect odds ratio, 1.42 [95% CI, 1.24-1.60]; adjusted P =0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation., Conclusions: We found evidence that 2 proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets., Competing Interests: Dr Tilling reports grants from the National Institute for Health and Care Research; grants from Wellcome Trust; and grants from Medical Research Council. Dr Gaunt reports grants from the National Institute for Health and Care Research (UK); grants from Biogen; grants from UK Medical Research Council; and grants from GlaxoSmithKline. Dr Gaziano reports grants from the US Department of Veterans Affairs. Dr Davey Smith reports grants from the Medical Research Council. Dr Peloso reports support from Veterans Health Administration; employment by Boston University; compensation from the American Heart Association for consultant services; and grants from the National Institutes of Health. Dr Hartley started working for Novo Nordisk after contributing to this article. The other authors report no conflicts.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third ( n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood., (© 2024. The Author(s).)

Objective: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates., Research Design and Methods: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%)., Results: T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001., Conclusions: Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates., (© 2024 by the American Diabetes Association.)

Background: Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT)., Methods: We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies., Results: Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A , SCN10A , and TTN/CCDC141 . Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals., Conclusions: Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility., Competing Interests: Disclosures Dr Lubitz is a full-time employee of Novartis as of July 2022. Previously, Dr Lubitz received research support from Bristol Myers Squibb/Pfizer, Bayer AG, Boehringer Ingelheim, Fitbit, IBM, Medtronic, and Premier, Inc, and consulted for Bristol Myers Squibb/Pfizer, Bayer AG, Blackstone Life Sciences, and Invitae. Dr Ellinor receives research support from Bayer AG, IBM, and Bristol Myers Squibb/Pfizer and has consulted for Novartis, MyoKardia, and Bayer AG. Dr Damrauer receives research support for RenalytixAI and has consulted for Calico Labs. Dr Svendsen is a member of Medtronic advisory boards and has received speaker honoraria and research grants from Medtronic outside this work. Dr Cutler has consulted for Janssen Scientific. Dr Roselli is supported by a grant from Bayer AG to the Broad Institute focused on the development of therapeutics for cardiovascular disease. The other authors report no conflicts.

The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.

Background: Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear., Objective: This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions., Methods: Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic., Results: Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems., Conclusions: This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code., (©Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024.)

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10 -8 ) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10 -126 ) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10 -44 ) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10 -34 ). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research., (© 2024. The Author(s).)

Objective: Development of clinical phenotypes from electronic health records (EHRs) can be resource intensive. Several phenotype libraries have been created to facilitate reuse of definitions. However, these platforms vary in target audience and utility. We describe the development of the Centralized Interactive Phenomics Resource (CIPHER) knowledgebase, a comprehensive public-facing phenotype library, which aims to facilitate clinical and health services research., Materials and Methods: The platform was designed to collect and catalog EHR-based computable phenotype algorithms from any healthcare system, scale metadata management, facilitate phenotype discovery, and allow for integration of tools and user workflows. Phenomics experts were engaged in the development and testing of the site., Results: The knowledgebase stores phenotype metadata using the CIPHER standard, and definitions are accessible through complex searching. Phenotypes are contributed to the knowledgebase via webform, allowing metadata validation. Data visualization tools linking to the knowledgebase enhance user interaction with content and accelerate phenotype development., Discussion: The CIPHER knowledgebase was developed in the largest healthcare system in the United States and piloted with external partners. The design of the CIPHER website supports a variety of front-end tools and features to facilitate phenotype development and reuse. Health data users are encouraged to contribute their algorithms to the knowledgebase for wider dissemination to the research community, and to use the platform as a springboard for phenotyping., Conclusion: CIPHER is a public resource for all health data users available at https://phenomics.va.ornl.gov/ which facilitates phenotype reuse, development, and dissemination of phenotyping knowledge., (Published by Oxford University Press on behalf of the American Medical Informatics Association 2024.)

Few studies examining the patient outcomes of concurrent neurological manifestations during acute COVID-19 leveraged multinational cohorts of adults and children or distinguished between central and peripheral nervous system (CNS vs. PNS) involvement. Using a federated multinational network in which local clinicians and informatics experts curated the electronic health records data, we evaluated the risk of prolonged hospitalization and mortality in hospitalized COVID-19 patients from 21 healthcare systems across 7 countries. For adults, we used a federated learning approach whereby we ran Cox proportional hazard models locally at each healthcare system and performed a meta-analysis on the aggregated results to estimate the overall risk of adverse outcomes across our geographically diverse populations. For children, we reported descriptive statistics separately due to their low frequency of neurological involvement and poor outcomes. Among the 106,229 hospitalized COVID-19 patients (104,031 patients ≥18 years; 2,198 patients <18 years, January 2020-October 2021), 15,101 (14%) had at least one CNS diagnosis, while 2,788 (3%) had at least one PNS diagnosis. After controlling for demographics and pre-existing conditions, adults with CNS involvement had longer hospital stay (11 versus 6 days) and greater risk of (Hazard Ratio = 1.78) and faster time to death (12 versus 24 days) than patients with no neurological condition (NNC) during acute COVID-19 hospitalization. Adults with PNS involvement also had longer hospital stay but lower risk of mortality than the NNC group. Although children had a low frequency of neurological involvement during COVID-19 hospitalization, a substantially higher proportion of children with CNS involvement died compared to those with NNC (6% vs 1%). Overall, patients with concurrent CNS manifestation during acute COVID-19 hospitalization faced greater risks for adverse clinical outcomes than patients without any neurological diagnosis. Our global informatics framework using a federated approach (versus a centralized data collection approach) has utility for clinical discovery beyond COVID-19., Competing Interests: All authors report no competing interests or conflicts of interest. JGK reports a consulting relationship with the i2b2-tranSMART Foundation through Invocate, Inc. RB reports being a shareholder of Biomeris s.r.l. and Engenome s.r.l. DAH reports entitled to royalties from the University of Michigan for licensing of the EMERSE "synonyms". AM’s work is being funded by the Federal Ministry of Education and Research (BMBF) in Germany in the framework of the MIRACUM Consortium. AM reports being a shareholder of Biomeris s.r.l. BM reports being co-founder and equity owner from DESKI. DLM has received research support from the National Institutes of Health, Department of Veteran Affairs, and the University of Pittsburgh/Pittsburgh Health Data Alliance outside of this work. PA reports consulting for CCHMC and BCH. NG is a co-founder and equity owner of Datavisyn. ZX has served as a Consultant for Genentech/Roche. The institution of ZX has received research support from the National Institute of Health, the National Multiple Sclerosis Society, Food and Drug Administration, the Pittsburgh Foundation, the PNC Charitable Trust, the Ethel Vincent Trust, and Genentech / Roche., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist to efficiently test for differences across subgroups in the thousands of multiple comparisons generated as part of a PheWAS. In this study, we developed an approach that maximizes the power to test for heterogeneous genotype-phenotype associations and applied this approach to an IL6R PheWAS among individuals of African (AFR) and European (EUR) ancestries. We identified 29 traits with differences in IL6R variant-phenotype associations, including a lower risk of type 2 diabetes in AFR (OR 0.96) vs EUR (OR 1.0, p-value for heterogeneity = 8.5 × 10 -3 ), and higher white blood cell count (p-value for heterogeneity = 8.5 × 10 -131 ). These data suggest a more salutary effect of IL6R blockade for T2D among individuals of AFR vs EUR ancestry and provide data to inform ongoing clinical trials targeting IL6 for an expanding number of conditions. Moreover, the method to test for heterogeneity of associations can be applied broadly to other large-scale genotype-phenotype screens in diverse populations., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Importance: Polygenic risk scores (PRSs) have proven to be as strong as or stronger than established clinical risk factors for many cardiovascular phenotypes. Whether this is true for aortic stenosis remains unknown., Objective: To develop a novel aortic stenosis PRS and compare its aortic stenosis risk estimation to established clinical risk factors., Design, Setting, and Participants: This was a longitudinal cohort study using data from the Million Veteran Program (MVP; 2011-2020), UK Biobank (2006-2010), and 6 Thrombolysis in Myocardial Infarction (TIMI) trials, including DECLARE-TIMI 58 (2013-2018), FOURIER (TIMI 59; 2013-2017), PEGASUS-TIMI 54 (2010-2014), SAVOR-TIMI 53 (2010-2013), SOLID-TIMI 52 (2009-2014), and ENGAGE AF-TIMI 48 (2008-2013), which were a mix of population-based and randomized clinical trials. Individuals from UK Biobank and the MVP meeting a previously validated case/control definition for aortic stenosis were included. All individuals from TIMI trials were included unless they had a documented preexisting aortic valve replacement. Analysis took place from January 2022 to December 2023., Exposures: PRS for aortic stenosis (developed using data from MVP and validated in UK Biobank) and other previously validated cardiovascular PRSs, defined either as a continuous variable or as low (bottom 20%), intermediate, and high (top 20%), and clinical risk factors., Main Outcomes: Aortic stenosis (defined using International Classification of Diseases or Current Procedural Terminology codes in UK Biobank and MVP or safety event data in the TIMI trials)., Results: The median (IQR) age in MVP was 67 (57-73) years, and 135 140 of 147 104 participants (92%) were male. The median (IQR) age in the TIMI trials was 66 (54-78) years, and 45 524 of 59 866 participants (71%) were male. The best aortic stenosis PRS incorporated 5 170 041 single-nucleotide variants and was associated with aortic stenosis in both the MVP testing sample (odds ratio, 1.41; 95% CI, 1.37-1.45 per 1 SD PRS; P = 4.6 × 10-116) and TIMI trials (hazard ratio, 1.44; 95% CI, 1.27-1.62 per 1 SD PRS; P = 3.2 × 10-9). Among genetic and clinical risk factors, the aortic stenosis PRS performed comparably to most risk factors besides age, and within a given age range, the combination of clinical and genetic risk factors was additive, providing a 3- to 4-fold increased gradient of risk of aortic stenosis. However, the addition of the aortic stenosis PRS to a model including clinical risk factors only improved risk discrimination of aortic stenosis by 0.01 to 0.02 (C index in MVP: 0.78 with clinical risk factors, 0.79 with risk factors and aortic stenosis PRS; C index in TIMI: 0.71 with clinical risk factors, 0.73 with risk factors and aortic stenosis PRS)., Conclusions: This study developed and validated 1 of the first aortic stenosis PRSs. While aortic stenosis genetic risk was independent from clinical risk factors and performed comparably to all other risk factors besides age, genetic risk resulted in only a small improvement in overall aortic stenosis risk discrimination beyond age and clinical risk factors. This work sets the stage for further development of an aortic stenosis PRS.

Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22-3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76-0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = - 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment., (© 2024. The Author(s).)

Introduction: The Department of Veterans Affairs (VA) Million Veteran Program (MVP) nutrition data is derived from dietary food/beverage intake information collected through a semiquantitative food frequency questionnaire (SFFQ)., Methods: Estimates of dietary energy, nutrient, and non-nutritive food components intakes data were derived from an extensively validated SFFQ, which assessed the habitual frequency of consumption of 61 food items, added sugar, fried food frequency, and 21 nutritional supplements over the 12 months preceding questionnaire administration., Results: Complete nutrition data was available for 353,418 MVP participants as of 30 th September 2021. Overall, 91.5% of MVP participants with nutrition data were male with an average age of 65.7 years at enrollment. Participants who completed the SFFQ were primarily White (82.5%), and Blacks accounted for 13.2% of the responders. Mean ± SD energy intake for 353, 418 MVP participants was 1428 ± 616 kcal/day, which was 1434 ± 617 kcal/day for males and 1364 ± 601 kcal/day for females. Energy intake and information on 322 nutrients and non-nutritive food components is available through contact with MVP for research collaborations at www.research.va.gov/mvp., Conclusions: The energy and nutrient data derived from MVP SFFQ are an invaluable resource for Veteran health and research. In conjunction with the MVP Lifestyle Survey, electronic health records, and genomic data, MVP nutrition data may be used to assess nutritional status and related risk factors, disease prevalence, and determinants of health that can provide scientific support for the development of evidence-based public health policy and health promotion programs and services for Veterans and general population., Competing Interests: Conflict of interest statement: None to declare.

Importance: Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes., Objective: To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts., Design, Setting, and Participants: This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023., Exposure: BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline., Main Outcomes and Measures: The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI., Results: Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11)., Conclusions and Relevance: This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.

Background: Observational studies are used for estimating vaccine effectiveness under real-world conditions. The practical performance of two common approaches-cohort and test-negative designs-need to be compared for COVID-19 vaccines., Methods: We compared the cohort and test-negative designs to estimate the effectiveness of the BNT162b2 vaccine against COVID-19 outcomes using nationwide data from the United States Department of Veterans Affairs. Specifically, we (1) explicitly emulated a target trial using follow-up data and evaluated the potential for confounding using negative controls and benchmarking to a randomized trial, (2) performed case-control sampling of the cohort to confirm empirically that the same estimate is obtained, (3) further restricted the sampling to person-days with a test, and (4) implemented additional features of a test-negative design. We also compared their performance in limited datasets., Results: Estimated BNT162b2 vaccine effectiveness was similar under all four designs. Empirical results suggested limited residual confounding by healthcare-seeking behavior. Analyses in limited datasets showed evidence of residual confounding, with estimates biased downward in the cohort design and upward in the test-negative design., Conclusion: Vaccine effectiveness estimates under a cohort design with explicit target trial emulation and a test-negative design were similar when using rich information from the VA healthcare system, but diverged in opposite directions when using a limited dataset. In settings like ours with sufficient information on confounders and other key variables, the cohort design with explicit target trial emulation may be preferable as a principled approach that allows estimation of absolute risks and facilitates interpretation of effect estimates., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Red meat consumption was associated with an increased risk of cardiovascular disease (CVD) in prospective cohort studies and a profile of biomarkers favoring high CVD risk in short-term controlled trials. However, several recent systematic reviews and meta-analyses concluded with no or weak evidence for limiting red meat intake., Objectives: To prospectively examine the associations between red meat intake and incident CVD in an ongoing cohort study with diverse socioeconomic and racial or ethnic backgrounds., Methods: Our study included 148,506 participants [17,804 female (12.0%)] who were free of cancer, diabetes, and CVD at baseline from the Million Veteran Program. A food frequency questionnaire measured red meat intakes at baseline. Nonfatal myocardial infarction and acute ischemic stroke were identified through a high-throughput phenotyping algorithm, and fatal CVD events were identified by searching the National Death Index., Results: Comparing the extreme categories of intake, the multivariate-adjusted relative risks of CVD was 1.18 (95% CI: 1.01, 1.38; P-trend < 0.0001) for total red meat, 1.14 (95% CI: 0.96, 1.36; P-trend = 0.01) for unprocessed red meat, and 1.29 (95% CI: 1.04, 1.60; P-trend = 0.003) for processed red meat. We observed a more pronounced positive association between red meat intake and CVD in African American participants than in White participants (P-interaction = 0.01). Replacing 0.5 servings/d of red meat with 0.5 servings/d of nuts, whole grains, and skimmed milk was associated with 14% (RR: 0.86; 95% CI: 0.83, 0.90), 7% (RR: 0.93; 95% CI: 0.89, 0.96), and 4% (RR: 0.96; 95% CI: 0.94, 0.99) lower risks of CVD, respectively., Conclusions: Red meat consumption is associated with an increased risk of CVD. Our findings support lowering red meat intake and replacing red meat with plant-based protein sources or low-fat dairy foods as a key dietary recommendation for the prevention of CVD., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Background: Statins are part of long-term medical regimens for many older adults. Whether frailty modifies the protective relationship between statins, mortality, and major adverse cardiovascular events (MACE) is unknown., Methods: This was a retrospective study of US Veterans ≥65, without CVD or prior statin use seen in 2002-2012, followed through 2017. A 31-item frailty index was used. The co-primary endpoint was all-cause mortality or MACE (MI, stroke/TIA, revascularization, or cardiovascular death). Cox proportional hazards models were developed to evaluate the association of statin use with outcomes; propensity score overlap weighting accounted for confounding by indication., Results: We identified 710,313 Veterans (mean age (SD) 75.3(6.5), 98% male, 89% white); 86,327 (12.1%) were frail. Over mean follow-up of 8 (5) years, there were 48.6 and 72.6 deaths per 1000 person-years (PY) among non-frail statin-users vs nonusers (weighted Incidence Rate Difference (wIRD)/1000 person years (PY), -24.0[95% CI, -24.5 to -23.6]), and 90.4 and 130.4 deaths per 1000PY among frail statin-users vs nonusers (wIRD/1000PY, -40.0[95% CI, -41.8 to -38.2]). There were 51.7 and 60.8 MACE per 1000PY among non-frail statin-users vs nonusers (wIRD/1000PY, -9.1[95% CI, -9.7 to -8.5]), and 88.2 and 102.0 MACE per 1000PY among frail statin-users vs nonusers (wIRD/1000PY, -13.8[95% CI, -16.2 to -11.4]). There were no significant interactions by frailty for statin users vs non-users by either mortality or MACE outcomes, p-interaction 0.770 and 0.319, respectively. Statin use was associated with lower risk of all-cause mortality (HR, 0.61 (0.60-0.61)) and MACE (HR 0.86 (0.85-0.87))., Conclusions: New statin use is associated with a lower risk of mortality and MACE, independent of frailty. These findings should be confirmed in a randomized clinical trial., (© 2023 The American Geriatrics Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choices of study design and prediction methodology. Each model used twenty cross-sectional and 190 longitudinal variables observed in eight time intervals covering 7.5 years prior to the time of prediction. Ensembles of seven base models were created and fine-tuned with ten variables expected to change with study design and outcome definition in order to predict suicide and combined outcome in a prospective cohort. The ensemble models achieved c-statistics of 0.73 on 2-year suicide risk and 0.83 on the combined outcome when predicting on a prospective cohort of [Formula: see text] 4.2 M veterans. The ensembles rely on nonlinear base models trained using a matched retrospective nested case-control (Rcc) study cohort and show good calibration across a diversity of subgroups, including risk strata, age, sex, race, and level of healthcare utilization. In addition, a linear Rcc base model provided a rich set of biological predictors, including indicators of suicide, substance use disorder, mental health diagnoses and treatments, hypoxia and vascular damage, and demographics., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Most prior studies on the prognostic significance of newly-diagnosed atrial fibrillation (AF) in COVID-19 did not differentiate newly-diagnosed AF from pre-existing AF. To determine the association between newly-diagnosed AF and in-hospital and 30-day mortality among regular users of Veterans Health Administration using data linked to Medicare. We identified Veterans aged ≥ 65 years who were hospitalized for ≥ 24 h with COVID-19 from 06/01/2020 to 1/31/2022 and had ≥ 2 primary care visits within 24 months prior to the index hospitalization. We performed multivariable logistic regression analyses to estimate adjusted risks, risk differences (RD), and odds ratios (OR) for the association between newly-diagnosed AF and the mortality outcomes adjusting for patient demographics, baseline comorbidities, and presence of acute organ dysfunction on admission. Of 23,299 patients in the study cohort, 5.3% had newly-diagnosed AF, and 29.2% had pre-existing AF. In newly-diagnosed AF adjusted in-hospital and 30-day mortality were 16.5% and 22.7%, respectively. Newly-diagnosed AF was associated with increased mortality compared to pre-existing AF (in-hospital: OR 2.02, 95% confidence interval [CI] 1.72-2.37; RD 7.58%, 95% CI 5.54-9.62) (30-day: OR 1.86; 95% CI 1.60-2.16; RD 9.04%, 95% CI 6.61-11.5) or no AF (in-hospital: OR 2.24, 95% CI 1.93-2.60; RD 8.40%, 95% CI 6.44-10.4) (30-day: 2.07, 95% CI 1.80-2.37; RD 10.2%, 95% CI 7.89-12.6). There was a smaller association between pre-existing AF and the mortality outcomes. Newly-diagnosed AF is an important prognostic marker for patients hospitalized with COVID-19. Whether prevention or treatment of AF improves clinical outcomes in these patients remains unknown., (© 2024. The Author(s).)

To address gaps in understanding the pathophysiology of Gulf War Illness (GWI), the VA Million Veteran Program (MVP) developed and implemented a survey to MVP enrollees who served in the U.S. military during the 1990-1991 Persian Gulf War (GW). Eligible Veterans were invited via mail to complete a survey assessing health conditions as well as GW-specific deployment characteristics and exposures. We evaluated the representativeness of this GW-era cohort relative to the broader population by comparing demographic, military, and health characteristics between respondents and non-respondents, as well as with all GW-era Veterans who have used Veterans Health Administration (VHA) services and the full population of U.S. GW-deployed Veterans. A total of 109,976 MVP GW-era Veterans were invited to participate and 45,270 (41%) returned a completed survey. Respondents were 84% male, 72% White, 8% Hispanic, with a mean age of 61.6 years ( SD = 8.5). Respondents were more likely to be older, White, married, better educated, slightly healthier, and have higher socioeconomic status than non-respondents, but reported similar medical conditions and comparable health status. Although generally similar to all GW-era Veterans using VHA services and the full population of U.S. GW Veterans, respondents included higher proportions of women and military officers, and were slightly older. In conclusion, sample characteristics of the MVP GW-era cohort can be considered generally representative of the broader GW-era Veteran population. The sample represents the largest research cohort of GW-era Veterans established to date and provides a uniquely valuable resource for conducting in-depth studies to evaluate health conditions affecting 1990-1991 GW-era Veterans.

Objective: Idiopathic toe-walking (ITW) is a diagnosis of exclusion. A relationship between ITW and decreased range of motion (ROM) is postulated. Treatments focus on increasing ankle dorsiflexion including serial casting. There is no consensus for duration of serial casting. This study aimed to determine ROM changes with cast change intervals of one vs. two weeks, and the rate of ITW recurrence., Methods: This was a retrospective study of 86 patients, ages 0-9 years with ITW undergoing weekly casting (N = 29) and two-week casting (N = 57) at a children's hospital from 2014-2020. ROM at baseline, two weeks, four weeks, and final cast removal were collected. Statistical analyses included chi-squared tests, two-sample t-tests, and linear mixed regression. Outcome distributions were assessed for normality. P-values < 0.05 were considered statistically significant., Results: After adjusting for baseline ROM, the mean change in ROM from baseline to two weeks was 10.6∘ vs 7.5∘ in the one-week vs. two-week casting interval, respectively (p < 0.001). The baseline to final measurement was 13.4∘ vs 9.8∘ in the one-week vs. two-week casting interval, respectively (p < 0.001). The rate of recurrence of ITW was similar between the two groups., Conclusion: This study suggests greater improvement in ROM in the one-week vs. two-week casting interval group.

Background: Lifestyle medicine has been proposed as a way to address the root causes of chronic disease and their associated health care costs., Objective: This study aimed to estimate mortality risk and longevity associated with individual lifestyle factors and comprehensive lifestyle therapy., Methods: Age- and sex-specific mortality rates were calculated on the basis of 719,147 veterans aged 40-99 y enrolled in the Veteran Affairs Million Veteran Program (2011-2019). Hazard ratios and estimated increase in life expectancy were examined among a subgroup of 276,132 veterans with complete data on 8 lifestyle factors at baseline. The 8 lifestyle factors included never smoking, physical activity, no excessive alcohol consumption, restorative sleep, nutrition, stress management, social connections, and no opioid use disorder., Results: On the basis of 1.12 million person-years of follow-up, 34,247 deaths were recorded. Among veterans who adopted 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, the adjusted hazard ratios for mortality were 0.74 (0.60-0.90), 0.60 (95% CI: 0.49, 0.73), 0.50 (95% CI: 0.41, 0.61), 0.43 (95% CI: 0.35, 0.52), 0.35 (95% CI: 0.29, 0.43), 0.27 (95% CI: 0.22, 0.33), 0.21 (95% CI: 0.17, 0.26), and 0.13 (95% CI: 0.10, 0.16), respectively, as compared with veterans with no adopted lifestyle factors. The estimated life expectancy at age 40 y was 23.0, 26.5, 28.8, 30.8, 32.7, 35.1, 38.3, 41.3, and 47.0 y among males and 27.0, 28.8, 33.1, 38.0, 39.2, 41.4, 43.8, 46.3, and 47.5 y for females who adopted 0, 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, respectively. The difference in life expectancy at age 40 y was 24.0 y for male veterans and 20.5 y for female veterans when comparing adoption of 8-9 lifestyle factors., Conclusions: A combination of 8 lifestyle factors is associated with a significantly lower risk of premature mortality and an estimated prolonged life expectancy., Competing Interests: Conflict of interest The authors report no conflicts of interest., (Published by Elsevier Inc.)

Electronic health record (EHR) data are increasingly used to support real-world evidence studies but are limited by the lack of precise timings of clinical events. Here, we propose a label-efficient incident phenotyping (LATTE) algorithm to accurately annotate the timing of clinical events from longitudinal EHR data. By leveraging the pre-trained semantic embeddings, LATTE selects predictive features and compresses their information into longitudinal visit embeddings through visit attention learning. LATTE models the sequential dependency between the target event and visit embeddings to derive the timings. To improve label efficiency, LATTE constructs longitudinal silver-standard labels from unlabeled patients to perform semi-supervised training. LATTE is evaluated on the onset of type 2 diabetes, heart failure, and relapses of multiple sclerosis. LATTE consistently achieves substantial improvements over benchmark methods while providing high prediction interpretability. The event timings are shown to help discover risk factors of heart failure among patients with rheumatoid arthritis., Competing Interests: The authors declare no competing interests., (© 2023 The Authors.)

Background: There is inconsistent evidence on the association of moderate alcohol consumption and stroke risk in the general population and is not well studied among U.S. Veterans. Furthermore, it is unclear whether primarily drinking beer, wine, or liquor is associated with a difference in stroke risk., Methods: The study included 185,323 Million Veteran Program participants who self-reported alcohol consumption on the Lifestyle Survey. Moderate consumption was defined as 1-2 drinks/day and beverage preference of beer, wine or liquor was defined if ≥ 50% of total drinks consumed were from a single type of beverage. Strokes were defined using ICD-9 and ICD-10 codes from the participants' electronic health record., Results: The mean (sd) age of the sample was 64 (13) years and 11% were women. We observed 4,339 (94% ischemic; 6% hemorrhagic) strokes over a median follow-up of 5.2 years. In Cox models adjusted for age, sex, race, education, income, body mass index, smoking, exercise, diet, cholesterol, prevalent diabetes, prevalent hypertension, lipid-lowering medication, antihypertensive medication, and diabetes medication, moderate alcohol consumption (1-2 drinks/day) was associated with a 22% lower risk of total stroke compared with never drinking [Hazards ratio (HR) 95% confidence interval (CI): 0.78 (0.67, 0.92)]. When stratifying by stroke type, we observed a similar protective association with moderate consumption and ischemic stroke [HR (95% CI): 0.76 (0.65, 0.90)], but a non-statistically significant higher risk of hemorrhagic stroke [HR (95% CI): 1.29 (0.64, 2.61)]. We did not observe a difference in ischemic or hemorrhagic stroke risk among those who preferred beer, liquor or wine vs. no beverage preference. When stratifying by prior number of hospital visits (≤ 15, 16-33, 34-64, ≥ 65) as a proxy for health status, we observed attenuation of the protective association with greater number of visits [HR (95% CI): 0.87 (0.63, 1.19) for ≥ 65 visits vs. 0.80 (0.59, 1.08) for ≤ 15 visits]., Conclusions: We observed a lower risk of ischemic stroke, but not hemorrhagic stroke with moderate alcohol consumption and did not observe substantial differences in risk by beverage preference among a sample of U.S. Veterans. Healthy user bias of moderate alcohol consumption may be driving some of the observed protective association., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Importance: A significant proportion of SARS-CoV-2 infected individuals experience post-COVID-19 condition months after initial infection., Objective: To determine the rates, clinical setting, risk factors, and symptoms associated with the documentation of International Statistical Classification of Diseases Tenth Revision (ICD-10), code U09.9 for post-COVID-19 condition after acute infection., Design, Setting, and Participants: This retrospective cohort study was performed within the US Department of Veterans Affairs (VA) health care system. Veterans with a positive SARS-CoV-2 test result between October 1, 2021, the date ICD-10 code U09.9 was introduced, and January 31, 2023 (n = 388 980), and a randomly selected subsample of patients with the U09.9 code (n = 350) whose symptom prevalence was assessed by systematic medical record review, were included in the analysis., Exposure: Positive SARS-CoV-2 test result., Main Outcomes and Measures: Rates, clinical setting, risk factors, and symptoms associated with ICD-10 code U09.9 in the medical record., Results: Among the 388 980 persons with a positive SARS-CoV-2 test, the mean (SD) age was 61.4 (16.1) years; 87.3% were men. In terms of race and ethnicity, 0.8% were American Indian or Alaska Native, 1.4% were Asian, 20.7% were Black, 9.3% were Hispanic or Latino, 1.0% were Native Hawaiian or Other Pacific Islander; and 67.8% were White. Cumulative incidence of U09.9 documentation was 4.79% (95% CI, 4.73%-4.87%) at 6 months and 5.28% (95% CI, 5.21%-5.36%) at 12 months after infection. Factors independently associated with U09.9 documentation included older age, female sex, Hispanic or Latino ethnicity, comorbidity burden, and severe acute infection manifesting by symptoms, hospitalization, or ventilation. Primary vaccination (adjusted hazard ratio [AHR], 0.80 [95% CI, 0.78-0.83]) and booster vaccination (AHR, 0.66 [95% CI, 0.64-0.69]) were associated with a lower likelihood of U09.9 documentation. Marked differences by geographic region and facility in U09.9 code documentation may reflect local screening and care practices. Among the 350 patients undergoing systematic medical record review, the most common symptoms documented in the medical records among patients with the U09.9 code were shortness of breath (130 [37.1%]), fatigue or exhaustion (78 [22.3%]), cough (63 [18.0%]), reduced cognitive function or brain fog (22 [6.3%]), and change in smell and/or taste (20 [5.7%])., Conclusions and Relevance: In this cohort study of 388 980 veterans, documentation of ICD-10 code U09.9 had marked regional and facility-level variability. Strong risk factors for U09.9 documentation were identified, while vaccination appeared to be protective. Accurate and consistent documentation of U09.9 is needed to maximize its utility in tracking patients for clinical care and research. Future studies should examine the long-term trajectory of individuals with U09.9 documentation.

Background: A healthful plant-based diet was associated with lower risks of coronary heart disease and type 2 diabetes, and a favourable profile of adiposity-associated biomarkers, while an unhealthful plant-based diet was associated with elevated risk of cardiometabolic disease in health professional populations. However, little is known about the associations between plant-based dietary patterns and risk of cardiovascular disease (CVD) in US veterans., Methods: The study population consisted of 148 506 participants who were free of diabetes, CVD and cancer at baseline in the Veterans Affairs (VA) Million Veteran Program. Diet was assessed using a Food Frequency Questionnaire at baseline. We calculated an overall Plant-Based Diet Index (PDI), a healthful PDI (hPDI) and an unhealthful PDI (uPDI). The CVD endpoints included non-fatal myocardial infarction (MI) and acute ischaemic stroke (AIS) identified through high-throughput phenotyping algorithms approach and fatal CVD events identified by searching the National Death Index., Results: With up to 8 years of follow-up, we documented 5025 CVD cases. After adjustment for confounding factors, a higher PDI was significantly associated with a lower risk of CVD (HR comparing extreme quintiles=0.75, 95% CI 0.68 to 0.82, P trend <0.0001). We observed an inverse association between hPDI and the risk of CVD (HR comparing extreme quintiles=0.71, 95% CI 0.64 to 0.78, P trend <0.001), whereas uPDI was positively associated with the risk of CVD (HR comparing extreme quintiles=1.12, 95% CI 1.02 to 1.24, P trend <0.001). We found similar associations of hPDI with subtypes of CVD; a 10-unit increment in hPDI was associated with HRs (95% CI) of 0.81 (0.75 to 0.87) for fatal CVD, 0.86 (0.79 to 0.94) for non-fatal MI and 0.86 (0.78 to 0.95) for non-fatal AIS., Conclusions: Plant-based dietary pattern enriched with healthier plant foods was associated with a substantially lower CVD risk in US veterans., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background The lipid hypothesis postulates that lower blood cholesterol is associated with reduced coronary heart disease (CHD) risk, which has been challenged by reports of a U-shaped relation between cholesterol and death in recent studies. We sought to examine whether the U-shaped relationship is true and to assess the impact of age on this association. Method and Results We conducted a prospective cohort study of 4 467 942 veterans aged >18 years, with baseline outpatient visits from 2002 to 2007 and follow-up to December 30, 2018, in the Veterans Health Administration electronic health record system. We observed a J-shaped relation between total cholesterol (TC) and CHD mortality after a comprehensive adjustment of confounding factors: flat for TC <180 mg/dL, and greater risk was present at higher cholesterol levels. Compared with veterans with TC between 180 and 199 mg/dL, the multiadjusted hazard ratios (HRs) for CHD death were 1.03 (95% CI, 1.02-1.04), 1.07 (95% CI, 1.06-1.09), 1.15 (95% CI, 1.13-1.18), 1.25 (95% CI, 1.22-1.28), and 1.45 (95% CI, 1.42-1.49) times greater among veterans with TC (mg/dL) of 200 to 219, 220 to 239, 140 to 259, 260 to 279 and ≥280, respectively. Similar J-shaped TC-CHD mortality patterns were observed among veterans with and without statin use at or before baseline. Conclusions The cholesterol paradox, for example, higher CHD death in patients with a low cholesterol level, was a reflection of reverse causality, especially among older participants. Our results support the lipid hypothesis that lower blood cholesterol is associated with reduced CHD. Furthermore, the hypothesis remained true when TC was low due to use of statins or other lipid-lowering medication.

Background: The Veterans Health Administration Office of Research and Development (ORD) played a key role in the federal government's response to the COVID-19 pandemic. The ORD effectively leveraged existing resources to answer questions related to the SARS-CoV-2 virus and COVID-19., Observations: When the COVID-19 pandemic hit in 2020, the Million Veteran Program (MVP), one of the largest genomic cohorts in the world, extended the centralized recruitment and enrollment infrastructure to develop a COVID-19 research volunteer registry to assist enrollment in the vaccine and treatment trials in which the US Department of Veterans Affairs (VA) participated. In addition, the MVP allowed for new data collection and a large genomic cohort to understand host contributions to COVID-19. This article describes ways the MVP contributed to the VA's rapid research response to COVID-19. Several host genetic factors believed to play a role in the development and severity of COVID-19 were identified. Furthermore, existing MVP partnerships with other federal agencies, particularly with the Department of Energy, were leveraged to improve understanding and management of COVID-19., Conclusions: A previously established enterprise approach and research infrastructure were essential to the VA's successful and timely COVID-19 research response. This infrastructure not only supported rapid recruitment in vaccine and treatment trials, but also leveraged the unique MVP and VA electronic health record data to drive rapid scientific discovery and inform clinical operations. Extending the models that VA research applied to the federal government at large and establishing centralized resources for shared or federated data analyses across federal agencies will better equip the nation to respond to future public health crises., Competing Interests: Author disclosures: The authors report no actual or potential conflicts of interest or outside sources of funding with regard to this article., (Copyright © 2023 Frontline Medical Communications Inc., Parsippany, NJ, USA.)

Background: Atherosclerotic cardiovascular diseases (ASCVDs) are the leading cause of worldwide adult mortality. Although broad classes of dietary fats have been shown to alter ASCVD risk, the roles that individual dietary fatty acids play in influencing ASCVD risk are unclear., Objectives: The aim of this prospective cohort study was to examine the relationships of the total fat classes and individual fatty acids with the risk of ASCVD., Methods: The Million Veteran Program is a prospective cohort whereby dietary intake of fatty acids was assessed in 158,198 participants that had enrolled between January 2011 and November 2018 and were free of ASCVD at baseline. Incident ASCVD was ascertained from the Veterans Affairs electronic health records and the National Death Index. Multivariable-adjusted hazard ratios (HRs) for the relationship between fat intake and ASCVD risk were computed using Cox regression models., Results: The mean age was 61 years, 88% were males. A total of 11,771 ASCVD events were identified during the follow-up. When compared with the lowest quintile, participants in the highest quintile of dietary trans-monounsaturated fats and conjugated linoleic acids had an increased risk (HR [95% CI]) of ASCVD events: 1.10 (1.04, 1.17) and 1.11 (1.05, 1.18), respectively. When compared with low consumers, participants in the highest quintile of total cis-polyunsaturated fatty acid intake had a lower risk of experiencing an ASCVD event 0.93 (0.87, 0.99)., Conclusion: Although higher intakes of specific trans-fatty acids and conjugated linoleic were associated with an increased risk of ASCVD, the same cannot be said for all other fat classes. This work suggests that care must be taken when drawing general conclusions regarding the health effects of dietary individual fatty acids., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Importance: The US Food and Drug Administration (FDA) is building a national postmarketing surveillance system for medical devices, moving to a "total product life cycle" approach whereby more limited premarketing data are balanced with postmarketing surveillance to capture rare adverse events and long-term safety issues., Objective: To assess the methodological requirements and feasibility of postmarketing device surveillance using endovascular aneurysm repair devices (EVARs), which have been the subject of safety concerns, using clinical data from a large health care system., Design, Setting, and Participants: This retrospective cohort study included patients with electronic health record (EHR) data in the Veterans Affairs Corporate Data Warehouse., Exposure: Implantation of an AFX Endovascular AAA System (AFX) device (any of 3 iterations) or a non-AFX comparator EVAR device from January 1, 2011, to December 21, 2021., Main Outcomes and Measures: The primary outcomes were rates of type III endoleaks and all-cause mortality; and rates of these outcomes associated with AFX devices compared with non-AFX devices, assessed using Cox proportional hazards regression models and doubly robust causal modeling. Information on type III endoleaks was available only as free-text mentions in clinical notes, while all-cause mortality data could be extracted using structured data. Device-specific information required by the FDA is ascertained using unique device identifiers (UDIs), which include factors such as model numbers, catalog numbers, and manufacturer-specific product codes. The availability of UDIs in EHRs was assessed., Results: In total, 13 941 patients (mean [SD] age, 71.8 [7.4] years) received 1 of the devices of interest (AFX with Strata [AFX-S]: 718 patients [5.2%]; AFX with Duraply [AFX-D]: 404 patients [2.9%]; or AFX2: 682 patients [4.9%]), and 12 137 (87.1%) received non-AFX devices. The UDIs were not recorded in the EHR for any patient with an AFX device, and partial UDIs were available for 19 patients (0.1%) with a non-AFX device. This necessitated the development of advanced natural language processing tools to define the cohort of patients for analysis. The study identified a significantly higher risk of type III endoleaks at 5 years among patients receiving any of the AFX device iterations, including the most recent version, AFX2 (11.6%; 95% CI, 8.1%-15.1%) compared with that among patients with non-AFX devices (5.7%; 95% CI, 2.2%-9.2%; absolute risk difference, 5.9%; 95% CI, 2.3%-9.4%). However, there was no significantly higher all-cause mortality for any of the AFX device iterations, including for AFX2 (19.0%; 95% CI, 16.0%-22.0%) compared with non-AFX devices (18.0%; 95% CI, 15.0%-21.0%; absolute risk difference, 1.0%; 95% CI, -2.1% to 4.1%)., Conclusions and Relevance: The findings of this cohort study suggest that clinical data can be used for the postmarketing device surveillance required by the FDA. The study also highlights ongoing challenges to performing larger-scale surveillance, including lack of consistent use of UDIs and insufficient relevant structured data to efficiently capture certain outcomes of interest.

Background: Morbidity and mortality following COVID-19 infection may be influenced by baseline atherosclerotic cardiovascular disease (ASCVD) risk, yet limited data are available to identify those at highest risk. We examined the association between baseline ASCVD risk with mortality and major adverse cardiovascular events (MACE) in the year following COVID-19 infection., Methods: We evaluated a nationwide retrospective cohort of US Veterans free of ASCVD who were tested for COVID-19. The primary outcome was absolute risk of all-cause mortality in the year following a COVID-19 test among those hospitalized vs. not stratified by baseline VA-ASCVD risk scores. Secondarily, risk of MACE was examined., Results: There were 393,683 Veterans tested for COVID-19 and 72,840 tested positive. Mean age was 57 years, 86% were male, and 68% were white. Within 30 days following infection, hospitalized Veterans with VA-ASCVD scores >20% had an absolute risk of death of 24.6% vs. 9.7% (P ≤0.0001) for those who tested positive and negative for COVID-19 respectively. In the year following infection, risk of mortality attenuated with no difference in risk after 60 days. The absolute risk of MACE was similar for Veterans who tested positive or negative for COVID-19., Conclusions: Veterans without clinical ASCVD experienced an increased absolute risk of death within 30 days of a COVID-19 infection compared to Veterans with the same VA-ASCVD risk score who tested negative, but this risk attenuated after 60 days. Whether cardiovascular preventive medications can lower the risk of mortality and MACE in the acute period following COVID-19 infection should be evaluated., Competing Interests: Declaration of Competing Interest No authors have any conflicts of interest for this work., (Published by Elsevier B.V.)

Background: Although recent large randomized clinical trials have reported an increased risk of atrial fibrillation (AF) with marine ω-3 fatty acid supplements, it is unclear whether dietary marine ω-3 fatty acids assessed through food frequency questionnaires are associated with AF risk., Objectives: We sought to test the hypothesis that dietary eicosapentaenoic acid/docosahexaenoic acid/docosapentaecnoic acid (EPA/DHA/DPA) is associated with a higher risk of AF in a large prospective cohort of US Veterans., Methods: We analyzed data from Million Veteran Program participants who completed self-reported food frequency questionnaires. We used multivariable Cox regression to estimate the HRs of AF across quintiles of ω-3 fatty acid consumption and a cubic spline analysis to assess the dose-response relations between ω-3 fatty acids and AF., Results: Of the 301,294 veterans studied, the median intake of ω-3 fatty acids (EPA/DHA/DPA) was 219 mg/d (IQR: 144-575), and the mean age was 64.9 y (SD: 12.0); 91% were men, and 84% were White. Consumption of EPA/DHA/DPA exhibited a nonlinear inverse relation with incident AF characterized by an initial decline to 11% at 750 mg/d of marine ω-3 fatty acid intake followed by a plateau., Conclusions: Contrary to our hypothesis, dietary EPA/DHA/DPA was not associated with a higher risk of AF but was inversely related to AF risk in a nonlinear manner., (Published by Elsevier Inc.)

Objective: Electronic health records (EHR), containing detailed longitudinal clinical information on a large number of patients and covering broad patient populations, open opportunities for comprehensive predictive modeling of disease progression and treatment response. However, since EHRs were originally constructed for administrative purposes not for research, in the EHR-linked studies, it is often not feasible to capture reliable information for analytical variables, especially in the survival setting, when both accurate event status and event times are needed for model building. For example, progression-free survival (PFS), a commonly used survival outcome for cancer patients, often involves complex information embedded in free-text clinical notes and cannot be extracted reliably. Proxies of PFS time such as time to the first mention of progression in the notes are at best good approximations to the true event time. This leads to difficulty in efficiently estimating event rates for an EHR patient cohort. Estimating survival rates based on error-prone outcome definitions can lead to biased results and hamper the power in the downstream analysis. On the other hand, extracting accurate event time information via manual annotation is time and resource intensive. The objective of this study is to develop a calibrated survival rate estimator using noisy outcomes from EHR data., Materials and Methods: In this paper, we propose a two-stage semi-supervised calibration of noisy event rate (SCANER) estimator that can effectively overcome censoring induced dependency and attains more robust performance (i.e., not sensitive to misspecification of the imputation model) by fully utilizing both a small-labeled set of gold-standard survival outcomes annotated via manual chart review and a set of proxy features automatically captured via EHR in the unlabeled set. We validate the SCANER estimator by estimating the PFS rates for a virtual cohort of lung cancer patients from one large tertiary care center and the ICU-free survival rates for COVID patients from two large tertiary care centers., Results: In terms of survival rate estimates, the SCANER had very similar point estimates compared to the complete-case Kaplan Meier estimator. On the other hand, other benchmark methods for comparison, which fail to account for the induced dependency between event time and the censoring time conditioning on surrogate outcomes, produced biased results across all three case studies. In terms of standard errors, the SCANER estimator was more efficient than the KM estimator, with up to 50% efficiency gain., Conclusion: The SCANER estimator achieves more efficient, robust, and accurate survival rate estimates compared to existing approaches. This promising new approach can also improve the resolution (i.e., granularity of event time) by using labels conditioning on multiple surrogates, particularly among less common or poorly coded conditions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure., (© 2023. The Author(s).)

Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPS Mult , that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPS Mult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPS Mult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPS Mult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPS Mult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction., (© 2023. The Author(s).)

Background: Genetic factors play an important role in prostate cancer (PCa) susceptibility., Objective: To discover common genetic variants contributing to the risk of PCa in men of African ancestry., Design, Setting, and Participants: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry., Outcome Measurements and Statistical Analysis: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness., Results and Limitations: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10 -4 )., Conclusions: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry., Patient Summary: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease., (Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.)