Protein Identification for Stroke Progression via Mendelian Randomization in Million Veteran Program and UK Biobank.

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; ncases=51 929; ncontrols=39 980) and subsequent arterial ischemic stroke (AIS; ncases=45 120; ncontrols=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.

Comparison of the Test-negative Design and Cohort Design With Explicit Target Trial Emulation for Evaluating COVID-19 Vaccine Effectiveness.

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.

Modeling the longitudinal changes of ancestry diversity in the Million Veteran Program.

BACKGROUND: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). RESULTS: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen's d < 0.259, p < 7.80 × 10-4). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics. CONCLUSIONS: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies.

Military and occupational exposures among Veterans in the Million Veteran Program by survey self-report: a descriptive study.

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.

Venous thromboembolism risk in cancer patients receiving first-line immune checkpoint inhibitor versus chemotherapy.

It remains unclear if immune checkpoint inhibitor (ICI) therapy is associated with higher rate of venous thromboembolism (VTE) compared with cytotoxic chemotherapy (chemo) in patients with comparable cancer type, staging, and comorbidities. Using the national Veterans Affairs healthcare system database from 2016 to 2021, we performed a propensity score (PS)-weighted retrospective cohort study to compare the incidence of VTE in patients with selected stage III/IV cancer receiving first-line ICI versus chemo. The PS model utilized overlap weights to balance age, sex, race, treatment year, VTE history, paralysis/immobilization, prolonged hospitalization, cancer type, staging, time between diagnosis and treatment, and National Cancer Institute comorbidity index. Weighted Cox regressions with robust standard error were used to assess the hazard ratio (HR) and 95% confidence interval (CI). We found that among comparable advanced cancers, first-line ICI (n = 1823) and first-line chemo (n = 6345) had similar rates of VTE (8.49% for ICI and 8.36% for chemo at 6 months). The weighted HR was 1.06 (95% CI 0.88-1.26) for ICI versus chemo. In a subgroup analysis restricted to lung cancers, first-line ICI/chemo (n = 828), ICI monotherapy (n = 428), and chemo monotherapy (n = 4371) had similar rates of VTE (9.60% for ICI/chemo, 10.04% for ICI, and 8.91% for chemo at 6 months). The weighted HR was 1.05 (95% CI 0.77-1.42) for ICI versus chemo, and 1.08 (95% CI 0.83-1.42) for ICI/chemo versus chemo. In conclusion, ICI as a systemic therapy has a similarly elevated risk as cytotoxic chemo for VTE occurrence in cancer patients. This finding can inform future prospective studies exploring thromboprophylaxis strategies.

Validation of an Electronic Medical Record-Based Algorithm for Identifying Posttraumatic Stress Disorder in U.S. Veterans.

We developed an algorithm for identifying U.S. veterans with a history of posttraumatic stress disorder (PTSD), using the Department of Veterans Affairs (VA) electronic medical record (EMR) system. This work was motivated by the need to create a valid EMR-based phenotype to identify thousands of cases and controls for a genome-wide association study of PTSD in veterans. We used manual chart review (n = 500) as the gold standard. For both the algorithm and chart review, three classifications were possible: likely PTSD, possible PTSD, and likely not PTSD. We used Lasso regression with cross-validation to select statistically significant predictors of PTSD from the EMR and then generate a predicted probability score of being a PTSD case for every participant in the study population (range: 0-1.00). Comparing the performance of our probabilistic approach (Lasso algorithm) to a rule-based approach (International Classification of Diseases [ICD] algorithm), the Lasso algorithm showed modestly higher overall percent agreement with chart review than the ICD algorithm (80% vs. 75%), higher sensitivity (0.95 vs. 0.84), and higher accuracy (AUC = 0.95 vs. 0.90). We applied a 0.7 probability cut-point to the Lasso results to determine final PTSD case-control status for the VA population. The final algorithm had a 0.99 sensitivity, 0.99 specificity, 0.95 positive predictive value, and 1.00 negative predictive value for PTSD classification (grouping possible PTSD and likely not PTSD) as determined by chart review. This algorithm may be useful for other research and quality improvement endeavors within the VA.

Spanish Abstracts by Asociación Chilena de Estrés Traumático (ACET) Validación de un algoritmo basado en registros médicos electrónicos para identificar el trastorno por estrés postraumático en veteranos de los EE. UU. VALIDACIÓN DE ALGORITOMO DE TEPT Desarrollamos un algoritmo para identificar a los veteranos de EE. UU. con historial de trastorno de estrés postraumático (TEPT), utilizando el sistema de registro médico electrónico (RME) del Departamento de Asuntos de Veteranos (AS). Este trabajo fue motivado por la necesidad de crear un fenotipo válido, basado en RME para identificar miles de casos y controles para un estudio de asociación del genoma del TEPT en los veteranos. Utilizamos la revisión manual de tablas (n = 500) como gold estándar. Tanto para el algoritmo como para la revisión de la tabla, fueron posibles tres clasificaciones: PTSD probable, PTSD posible y probablemente no PTSD. Usamos la regresión Lasso con validación cruzada para seleccionar los factores de pronóstico estadísticamente significativos del TEPT a partir de la RME y luego generar una puntuación de probabilidad pronosticada de ser un caso de TEPT para cada participante en la población del estudio (rango: 0-1.00). Comparando el rendimiento de nuestro enfoque probabilístico (algoritmo Lasso) con un enfoque basado en reglas (algoritmo de Clasificación Internacional de Enfermedades [CIE]), el algoritmo Lasso mostró un porcentaje de acuerdo global modestamente más alto con la revisión de tablas que el algoritmo CIE (80% vs. 75). %), mayor sensibilidad (0.95 frente a 0.84) y mayor precisión (AUC = 0.95 frente a 0.90). Aplicamos un punto de corte de probabilidad de 0.7 a los resultados de Lasso para determinar el estado final de control de caso de TEPT para la población de AV. El algoritmo final tuvo una sensibilidad de 0.99, una especificidad de 0.99, un valor predictivo positivo de 0.95 y un valor predictivo negativo de 1.00 para la clasificación de TEPT (agrupación de TEPT posible y probablemente no TEPT) según lo determinado por la revisión de la tabla. Este algoritmo puede ser útil para otros esfuerzos de investigación y mejora de la calidad dentro del AV.

Tobacco, alcohol use and risk of hepatocellular carcinoma and intrahepatic cholangiocarcinoma: The Liver Cancer Pooling Project.

BACKGROUND: While tobacco and alcohol are established risk factors for hepatocellular carcinoma (HCC), the most common type of primary liver cancer, it is unknown whether they also increase the risk of intrahepatic cholangiocarcinoma (ICC). Thus, we examined the association between tobacco and alcohol use by primary liver cancer type. METHODS: The Liver Cancer Pooling Project is a consortium of 14 US-based prospective cohort studies that includes data from 1,518,741 individuals (HCC n = 1423, ICC n = 410). Multivariable-adjusted hazards ratios (HRs) and 95% confidence intervals (CI) were estimated using proportional hazards regression. RESULTS: Current smokers at baseline had an increased risk of HCC (hazard ratio (HR) = 1.86, 95% confidence interval (CI): 1.57-2.20) and ICC (HR = 1.47, 95% CI: 1.07-2.02). Among individuals who quit smoking >30 years ago, HCC risk was almost equivalent to never smokers (HR = 1.09, 95% CI: 0.74-1.61). Compared to non-drinkers, heavy alcohol consumption was associated with an 87% increased HCC risk (HR≥7 drinks/day = 1.87, 95% CI: 1.41-2.47) and a 68% increased ICC risk (HR≥5 drinks/day = 1.68, 95% CI: 0.99-2.86). However, light-to-moderate alcohol consumption of <3 drinks/day appeared to be inversely associated with HCC risk (HR>0-<0.5 drinks/day = 0.77, 95% CI: 0.67-0.89; HR>0.5-<1 drinks/day = 0.57, 95% CI: 0.44-0.73; HR1-<3 drinks/day = 0.71, 95% CI: 0.58-0.87), but not ICC. CONCLUSIONS: These findings suggest that, in this relatively healthy population, smoking cessation and light-to-moderate drinking may reduce the risk of HCC.

Association between class III obesity (BMI of 40-59 kg/m2) and mortality: a pooled analysis of 20 prospective studies.

BACKGROUND: The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity. METHODS AND FINDINGS: In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per 100,000 persons per year) and multivariable-adjusted hazard ratios for adults, aged 19-83 y at baseline, classified as obese class III (BMI 40.0-59.9 kg/m2) compared with those classified as normal weight (BMI 18.5-24.9 kg/m2). Participants reporting ever smoking cigarettes or a history of chronic disease (heart disease, cancer, stroke, or emphysema) on baseline questionnaires were excluded. Among 9,564 class III obesity participants, mortality rates were 856.0 in men and 663.0 in women during the study period (1976-2009). Among 304,011 normal-weight participants, rates were 346.7 and 280.5 in men and women, respectively. Deaths from heart disease contributed largely to the excess rates in the class III obesity group (rate differences = 238.9 and 132.8 in men and women, respectively), followed by deaths from cancer (rate differences = 36.7 and 62.3 in men and women, respectively) and diabetes (rate differences = 51.2 and 29.2 in men and women, respectively). Within the class III obesity range, multivariable-adjusted hazard ratios for total deaths and deaths due to heart disease, cancer, diabetes, nephritis/nephrotic syndrome/nephrosis, chronic lower respiratory disease, and influenza/pneumonia increased with increasing BMI. Compared with normal-weight BMI, a BMI of 40-44.9, 45-49.9, 50-54.9, and 55-59.9 kg/m2 was associated with an estimated 6.5 (95% CI: 5.7-7.3), 8.9 (95% CI: 7.4-10.4), 9.8 (95% CI: 7.4-12.2), and 13.7 (95% CI: 10.5-16.9) y of life lost. A limitation was that BMI was mainly ascertained by self-report. CONCLUSIONS: Class III obesity is associated with substantially elevated rates of total mortality, with most of the excess deaths due to heart disease, cancer, and diabetes, and major reductions in life expectancy compared with normal weight. Please see later in the article for the Editors' Summary.

The Effect of Randomized Beta-Carotene Supplementation on CKD in Men.

Introduction: Beta-carotene (BC) protects the body against free radicals that may damage the kidney and lead to the development of acute kidney injury and chronic kidney disease (CKD). Previous studies in animal models have demonstrated a potential protective effect of 30 mg/kg BC supplementation on renal ischemia or reperfusion injury and subsequently improved kidney function. The extension of these findings to humans, however, remains unclear. Methods: Our study leverages previously collected data from the Physicians' Health Study I (PHS I), a large-scale, long-term, randomized trial of middle-aged and older US male physicians testing 50 mg BC every other day for primary prevention of cardiovascular disease and cancer. We examined the impact of randomized BC supplementation on self-reported incident CKD identified by self-reports stating "yes" to kidney disease from annual follow-up questionnaires from randomization in 1982 through the end of the randomized BC intervention at the end of 1995, and on CKD defined as an estimated glomerular filtration rate (eGFR) < 60 ml/min per 1.73 m2 at the end of 1995. Analyses compared incident CKD between BC supplementation and placebo using Cox proportional hazards regression models and logistic regression. We also examined whether smoking status (current vs. former or never smoker) or other factors modified the effect of randomized BC supplementation on CKD. Results: A total of 10,966 participants were randomized to BC, and 10,952 participants were randomized to a placebo group. Baseline characteristics between randomized BC groups were similar. There was no significant benefit between BC supplementation and self-reported incident CKD after adjusting for age and randomized aspirin treatment (hazard ratio [HR] = 0.97, 95% confidence interval [CI]: 0.86-1.08, P-value = 0.56). Stratified by smoking status, there was no significant benefit of BC supplementation and self-reported incident CKD either among former or never smokers (HR = 0.95, 95% CI: 0.84-1.07, P-value = 0.41) or current smokers (HR = 1.08, 95% CI: 0.78-1.50, P-value = 0.64). Smoking status did not modify the association between BC supplementation and incident CKD (P-interaction = 0.47). In subgroup analysis among those with available serum creatinine at the study end (5480 with BC and 5496 with placebo), there was no significant benefit between BC supplementation and CKD based on eGFR < 60 ml/min per 1.73 m2 (odds ratio [OR] = 0.96, 95% CI: 0.85-1.08, P-value = 0.49). Conclusion: Long-term randomized BC supplementation did not affect the risk of incident CKD in middle-aged and older male physicians.

Impact of 8 lifestyle factors on mortality and life expectancy among United States veterans: The Million Veteran Program.

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.

A Multivariable Mendelian Randomization Study of Systolic and Diastolic Blood Pressure, Lipid Profile, and Heart Failure Subtypes.

Heart failure (HF) is a significant health burden, with two major clinical subtypes: HF with reduced (HFrEF) and preserved ejection fraction (HFpEF). Blood pressure and lipid profile are established risk factors of HF. We performed univariable and multivariable Mendelian randomization (MR) analyses to assess potential causal effects of blood pressures and lipids on HF subtypes. Genetic instruments for blood pressures and lipids were derived from genome-wide association studies (GWASs) among the European participants of the UK Biobank. GWAS summaries of HFrEF and HFpEF were obtained from the meta-analysis of the European participants from the Million Veteran Program and the Vanderbilt University DNA Databank. Systolic blood pressure exhibited a supportive MR association primarily with HFpEF (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.04-1.23), while diastolic blood pressure had an independent MR association with HFrEF (OR, 1.43; 95% CI, 1.13-1.77). MR associations also supported the observation that higher levels of low-density lipoprotein cholesterol increase the risk for both subtypes (HFrEF OR, 1.10 and 95% CI, 1.05-1.17; HFpEF OR, 1.05 and 95% CI, 1.02-1.09). These findings underscore differences in HF subtype-specific risk profiles and mechanisms, which may lead to different interventional strategies for different HF subtypes.

Validation of a Blood-Based Protein Biomarker Panel for a Risk Assessment of Lethal Lung Cancer in the Physicians' Health Study.

This study aimed to assess a four-marker protein panel (4MP)'s performance, including the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19, for predicting lung cancer in a cohort enriched with never- and ever-smokers. Blinded pre-diagnostic plasma samples collected within 2 years prior to a lung cancer diagnosis from 25 cases and 100 sex-, age-, and smoking-matched controls were obtained from the Physicians' Health Study (PHS). The 4MP yielded AUC performance estimates of 0.76 (95% CI: 0.61-0.92) and 0.69 (95% CI: 0.56-0.82) for predicting lung cancer within one year and within two years of diagnosis, respectively. When stratifying into ever-smokers and never-smokers, the 4MP had respective AUCs of 0.77 (95% CI: 0.63-0.92) and 0.72 (95% CI: 0.17-1.00) for a 1-year risk of lung cancer. The AUCs of the 4MP for predicting metastatic lung cancer within one year and two years of the blood draw were 0.95 (95% CI: 0.87-1.00) and 0.78 (95% CI: 0.62-0.94), respectively. Our findings indicate that a blood-based biomarker panel may be useful in identifying ever- and never-smokers at high risk of a diagnosis of lung cancer within one-to-two years.

Association of dietary fatty acids with the risk of atherosclerotic cardiovascular disease in a prospective cohort of United States veterans.

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.

Plant-based diets and the incidence of cardiovascular disease: the Million Veteran Program.

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.

Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure.

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.

Association of Gulf War Illness with Characteristics in Deployed vs. Non-Deployed Gulf War Era Veterans in the Cooperative Studies Program 2006/Million Veteran Program 029 Cohort: A Cross-Sectional Analysis.

Gulf War Illness (GWI), a chronic multisymptom illness with a complex and uncertain etiology and pathophysiology, is highly prevalent among veterans deployed to the 1990-1991 GW. We examined how GWI phenotypes varied by demographic and military characteristics among GW-era veterans. Data were from the VA's Cooperative Studies Program 2006/Million Veteran Program (MVP) 029 cohort, Genomics of GWI. From June 2018 to March 2019, 109,976 MVP enrollees (out of a total of over 676,000) were contacted to participate in the 1990-1991 GW-era Survey. Of 109,976 eligible participants, 45,169 (41.1%) responded to the 2018-2019 survey, 35,902 respondents met study inclusion criteria, 13,107 deployed to the GW theater. GWI phenotypes were derived from Kansas (KS) and Centers for Disease Control and Prevention (CDC) GWI definitions: (a) KS Symptoms (KS Sym+), (b) KS GWI (met symptom criteria and without exclusionary health conditions) [KS GWI: Sym+/Dx-], (c) CDC GWI and (d) CDC GWI Severe. The prevalence of each phenotype was 67.1% KS Sym+, 21.5% KS Sym+/Dx-, 81.1% CDC GWI, and 18.6% CDC GWI severe. These findings affirm the persistent presence of GWI among GW veterans providing a foundation for further exploration of biological and environmental underpinnings of this condition.

Lifestyle changes and 14-year change in high-density lipoprotein cholesterol in a cohort of male physicians.

BACKGROUND: Although cross-sectional studies have identified lifestyle factors associated with high-density lipoprotein cholesterol (HDL-C), no studies have examined the association between changes in lifestyle factors and long-term changes in HDL-C. METHODS: We examined the association between changes in lifestyle factors and changes in HDL-C over a 14-year period in a cohort of 4,168 US male physicians, followed up between 1982 and 1997 and with HDL-C measured at both time points. Using linear regression, we examined the association between HDL-C change and categorized changes in alcohol consumption, physical activity, body mass index (BMI), and smoking, adjusting for age, baseline HDL-C, and other covariates. RESULTS: Stable BMI of <25 kg/m(2) or BMI reduction from ≥25 to <25 kg/m(2) were associated with increases in HDL-C of 3.1 to 4.7 mg/dL over 14 years. Alcohol consumption of ≥1 drink daily or increase in alcohol consumption from <1 to ≥1 drink daily was associated with increases in HDL-C of 2.4 to 3.3 mg/dL over 14 years. Adopting a sedentary lifestyle was associated with decreases in 14-year decreases in HDL-C. CONCLUSION: These findings suggest that reductions in BMI and increases in alcohol consumption are associated with 14-year increases in HDL-C, whereas decreases in physical activity are associated with 14-year decreases in HDL-C.

Racial and Ethnic Disparities in U.S. Veteran Health Characteristics.

Racial/ethnic health disparities persist among veterans despite comparable access and quality of care. We describe racial/ethnic differences in self-reported health characteristics among 437,413 men and women (mean age (SD) = 64.5 (12.6), 91% men, 79% White) within the Million Veteran Program. The Cochran-Mantel-Haenszel test and linear mixed models were used to compare age-standardized frequencies and means across race/ethnicity groups, stratified by gender. Black, Hispanic, and Other race men and women reported worse self-rated health, greater VA healthcare utilization, and more combat exposure than Whites. Compared to White men, Black and Other men reported more circulatory, musculoskeletal, mental health, and infectious disease conditions while Hispanic men reported fewer circulatory and more mental health, infectious disease, kidney, and neurological conditions. Compared to White women, Black women reported more circulatory and infectious disease conditions and Other women reported more infectious disease conditions. Smoking rates were higher among Black men, but lower for other minority groups compared to Whites. Minority groups were less likely to drink alcohol and had lower physical fitness than Whites. By identifying differences in burden of various health conditions and risk factors across different racial/ethnic groups, our findings can inform future studies and ultimately interventions addressing disparities.

The Structure of Relationships between the Human Exposome and Cardiometabolic Health: The Million Veteran Program.

The exposome represents the array of dietary, lifestyle, and demographic factors to which an individual is exposed. Individual components of the exposome, or groups of components, are recognized as influencing many aspects of human physiology, including cardiometabolic health. However, the influence of the whole exposome on health outcomes is poorly understood and may differ substantially from the sum of its individual components. As such, studies of the complete exposome are more biologically representative than fragmented models based on subsets of factors. This study aimed to model the system of relationships underlying the way in which the diet, lifestyle, and demographic components of the overall exposome shapes the cardiometabolic risk profile. The current study included 36,496 US Veterans enrolled in the VA Million Veteran Program (MVP) who had complete assessments of their diet, lifestyle, demography, and markers of cardiometabolic health, including serum lipids, blood pressure, and glycemic control. The cohort was randomly divided into training and validation datasets. In the training dataset, we conducted two separate exploratory factor analyses (EFA) to identify common factors among exposures (diet, demographics, and physical activity) and laboratory measures (lipids, blood pressure, and glycemic control), respectively. In the validation dataset, we used multiple normal regression to examine the combined effects of exposure factors on the clinical factors representing cardiometabolic health. The mean ± SD age of participants was 62.4 ± 13.4 years for both the training and validation datasets. The EFA revealed 19 Exposure Common Factors and 5 Physiology Common Factors that explained the observed (measured) data. Multivariate regression in the validation dataset revealed the structure of associations between the Exposure Common Factors and the Physiology Common Factors. For example, we found that the factor for fruit consumption was inversely associated with the factor summarizing total cholesterol and low-density lipoprotein cholesterol (LDLC, p = 0.008), and the latent construct describing light levels of physical activity was inversely associated with the blood pressure latent construct (p < 0.0001). We also found that a factor summarizing that participants who frequently consume whole milk are less likely to frequently consume skim milk, was positively associated with the latent constructs representing total cholesterol and LDLC as well as systolic and diastolic blood pressure (p = 0.0006 and <0.0001, respectively). Multiple multivariable-adjusted regression analyses of exposome factors allowed us to model the influence of the exposome as a whole. In this metadata-rich, prospective cohort of US Veterans, there was evidence of structural relationships between diet, lifestyle, and demographic exposures and subsequent markers of cardiometabolic health. This methodology could be applied to answer a variety of research questions about human health exposures that utilize electronic health record data and can accommodate continuous, ordinal, and binary data derived from questionnaires. Further work to explore the potential utility of including genetic risk scores and time-varying covariates is warranted.

Genomics of Gulf War Illness in U.S. Veterans Who Served during the 1990-1991 Persian Gulf War: Methods and Rationale for Veterans Affairs Cooperative Study #2006.

BACKGROUND: Approximately 697,000 members of the U.S. Armed Forces were deployed to the Persian Gulf in support of the 1990-1991 Persian Gulf War (GW). Subsequently, many deployed and some non-deployed veterans developed a chronic multi-symptom illness, now named Gulf War Illness (GWI). This manuscript outlines the methods and rationale for studying the genomics of GWI within the Million Veteran Program (MVP), a VA-based national research program that has linked medical records, surveys, and genomic data, enabling genome-wide association studies (GWASs). METHODS: MVP participants who served in the military during the GW era were contacted by mail and invited to participate in the GWI study. A structured health questionnaire, based on a previously tested instrument, was also included in the mailing. Data on deployment locations and exposures, symptoms associated with GWI, clinical diagnoses, personal habits, and health care utilization were collected. Self-reported data will be augmented with chart reviews and structured international classification of disease codes, to classify participants by GWI case status. We will develop a phenotyping algorithm, based on two commonly used case definitions, to determine GWI status, and then conduct a nested case-control GWAS. Genetic variants associated with GWI will be investigated, and gene-gene and gene-environment interactions studied. The genetic overlap of GWI with, and causative mechanisms linking this illness to, other health conditions and the effects of genomic regulatory mechanisms on GWI risk will also be explored. CONCLUSIONS: The proposed initial GWAS described in this report will investigate the genomic underpinnings of GWI with a large sample size and state-of-the-art genomic analyses and phenotyping. The data generated will provide a rich and expansive foundation on which to build additional analyses.