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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.
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Bancos de Espécimes Biológicos , Estudo de Associação Genômica Ampla , Análise da Randomização Mendeliana , Acidente Vascular Cerebral , Veteranos , Humanos , Masculino , Acidente Vascular Cerebral/genética , Acidente Vascular Cerebral/epidemiologia , Feminino , Reino Unido/epidemiologia , Pessoa de Meia-Idade , Idoso , Progressão da Doença , Polimorfismo de Nucleotídeo Único/genética , AVC Isquêmico/genética , AVC Isquêmico/epidemiologia , Fatores de Risco , Locos de Características Quantitativas , Biobanco do Reino UnidoRESUMO
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.
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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.
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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.
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Veteranos , Humanos , Masculino , Feminino , Estados Unidos/epidemiologia , Adulto , Expectativa de Vida , Fumar , Estilo de Vida , Exercício Físico , Fatores de Risco , MortalidadeRESUMO
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.
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COVID-19 , Vacinas , Estados Unidos/epidemiologia , Humanos , Vacinas contra COVID-19/uso terapêutico , Vacina BNT162 , Eficácia de Vacinas , COVID-19/epidemiologia , COVID-19/prevenção & controleRESUMO
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.
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Aterosclerose , Doenças Cardiovasculares , Ácidos Graxos trans , Veteranos , Masculino , Adulto , Humanos , Estados Unidos/epidemiologia , Pessoa de Meia-Idade , Feminino , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/etiologia , Estudos Prospectivos , Ácidos Graxos , Gorduras na Dieta/efeitos adversos , Aterosclerose/etiologia , Aterosclerose/induzido quimicamente , Ácidos Graxos trans/efeitos adversos , Fatores de RiscoRESUMO
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.
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Estudo de Associação Genômica Ampla , Insuficiência Cardíaca , Humanos , Análise da Randomização Mendeliana , Proteômica , Insuficiência Cardíaca/tratamento farmacológico , Insuficiência Cardíaca/genéticaRESUMO
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.
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Etnicidade , Grupos Raciais , Veteranos , Humanos , Etnicidade/genética , Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único/genética , Grupos Raciais/genéticaRESUMO
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.
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Antineoplásicos , Inibidores de Checkpoint Imunológico , Tromboembolia Venosa , Humanos , Tromboembolia Venosa/epidemiologia , Tromboembolia Venosa/etiologia , Neoplasias/terapia , Antineoplásicos/uso terapêutico , Estudos Retrospectivos , Incidência , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou maisRESUMO
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.
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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.
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Militares , Síndrome do Golfo Pérsico , Veteranos , Humanos , Estudos Transversais , Síndrome do Golfo Pérsico/epidemiologia , Síndrome do Golfo Pérsico/etiologia , Guerra do GolfoRESUMO
AIMS: This study aims to develop the first race-specific and sex-specific risk prediction models for heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF). METHODS AND RESULTS: We created a cohort of 1.8 million individuals who had an outpatient clinic visit between 2002 and 2007 within the Veterans Affairs (VA) Healthcare System and obtained information on HFpEF, HFrEF, and several risk factors from electronic health records (EHR). Variables were selected for the risk prediction models in a 'derivation cohort' that consisted of individuals with baseline date in 2002, 2003, or 2004 using a forward stepwise selection based on a change in C-index threshold. Discrimination and calibration were assessed in the remaining participants (internal 'validation cohort'). A total of 66 831 individuals developed HFpEF, and 92 233 developed HFrEF (52 679 and 71 463 in the derivation cohort) over a median of 11.1 years of follow-up. The HFpEF risk prediction model included age, diabetes, BMI, COPD, previous MI, antihypertensive treatment, SBP, smoking status, atrial fibrillation, and estimated glomerular filtration rate (eGFR), while the HFrEF model additionally included previous CAD. For the HFpEF model, C-indices were 0.74 (SE = 0.002) for white men, 0.76 (0.005) for black men, 0.79 (0.015) for white women, and 0.77 (0.026) for black women, compared with 0.72 (0.002), 0.72 (0.004), 0.77 (0.017), and 0.75 (0.028), respectively, for the HFrEF model. These risk prediction models were generally well calibrated in each race-specific and sex-specific stratum of the validation cohort. CONCLUSIONS: Our race-specific and sex-specific risk prediction models, which used easily obtainable clinical variables, can be a useful tool to implement preventive strategies or subtype-specific prevention trials in the nine million users of the VA healthcare system and the general population after external validation.
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Insuficiência Cardíaca , Disfunção Ventricular Esquerda , Feminino , Humanos , Masculino , Fatores de Risco , Volume Sistólico , Função Ventricular EsquerdaRESUMO
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.
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Electronic frailty indices based on data from administrative claims and electronic health records can be used to estimate frailty in large populations of older adults with cancer where direct frailty measures are lacking. The objective of this study was to use the electronic Veterans Affairs Frailty Index (VA-FI-10)-developed and validated to measure frailty in the national United States (US) VA Healthcare System-to estimate the prevalence and impact of frailty in older US veterans newly treated for multiple myeloma (MM) with contemporary therapies. We designed a retrospective cohort study of 4924 transplant-ineligible veterans aged ≥ 65 years initiating MM therapy within VA from 2004 to 2017. Initial MM therapy was measured using inpatient and outpatient treatment codes from pharmacy data in the VA Corporate Data Warehouse. In total, 3477 veterans (70.6%) were classified as frail (VA-FI-10 > 0.2), with 1510 (30.7%) mildly frail (VA-FI-10 > 0.2-0.3), 1105 (22.4%) moderately frail (VA-FI-10 > 0.3-0.4), and 862 (17.5%) severely frail (VA-FI-10 > 0.4). Survival and time to hospitalization decreased with increasing VA-FI-10 severity (log-rank p-value < 0.001); the VA-FI-10 predicted mortality and hospitalizations independently of age, sociodemographic variables, and measures of disease risk. Varying data sources and assessment periods reclassified frailty severity for a substantial portion of veterans but did not substantially affect VA-FI-10's association with mortality. Our study supports use of the VA-FI-10 in future research involving older veterans with MM and provides insights into its potential use in identifying frailty in clinical practice.
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BACKGROUND: The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death. METHODS AND RESULTS: We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality. CONCLUSIONS: Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.
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COVID-19/epidemiologia , Saúde dos Veteranos , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Índice de Massa Corporal , COVID-19/mortalidade , Progressão da Doença , Feminino , Hospitalização , Humanos , Unidades de Terapia Intensiva , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Fatores de Risco , SARS-CoV-2/isolamento & purificação , Fatores Sexuais , Estados Unidos/epidemiologia , VeteranosRESUMO
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.
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Exposição Ambiental/estatística & dados numéricos , Expossoma , Síndrome Metabólica/epidemiologia , Medição de Risco/métodos , Veteranos/estatística & dados numéricos , Idoso , Biomarcadores/análise , Pressão Sanguínea , Fatores de Risco Cardiometabólico , Dieta/efeitos adversos , Dieta/estatística & dados numéricos , Exposição Dietética/efeitos adversos , Exposição Dietética/estatística & dados numéricos , Exposição Ambiental/efeitos adversos , Análise Fatorial , Feminino , Controle Glicêmico/estatística & dados numéricos , Humanos , Estilo de Vida , Lipídeos/sangue , Masculino , Síndrome Metabólica/etiologia , Pessoa de Meia-Idade , Análise Multivariada , Exposição Ocupacional/efeitos adversos , Exposição Ocupacional/estatística & dados numéricos , Análise de Regressão , Estados Unidos/epidemiologiaRESUMO
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.
Assuntos
Etnicidade , Veteranos , Negro ou Afro-Americano , Feminino , Disparidades em Assistência à Saúde , Hispânico ou Latino , Humanos , Masculino , Estados Unidos/epidemiologia , População BrancaRESUMO
Purpose: To evaluate the association between dietary fat intake and the presence of AMD. Methods: Cross-sectional, observational study with cohorts prospectively recruited from the United States and Portugal. AMD was diagnosed based on color fundus photographs with the AREDS classification. A validated food frequency questionnaire was used to calculate the percent energy intake of trans fat, saturated fat, monounsaturated fatty acid (MUFA), and polyunsaturated fatty acid (PUFA). Odds ratio (OR) and 95% confidence intervals for quintile of amount of FA were calculated. Multiple logistic regression was used to estimate the OR. Results: We included 483 participants, 386 patients with AMD and 97 controls. Higher intake of trans fat was associated with a 2.3-fold higher odds of presence of AMD (P for trend = 0.0156), whereas a higher intake of PUFA (OR, 0.25; P for trend = 0.006) and MUFA (OR, 0.24; P for trend < 0.0001) presented an inverse association. Subgroup analysis showed that higher quintile of trans fat was associated with increased odds of having intermediate AMD (OR, 2.26; P for trend = 0.02); and higher quintile of PUFA and MUFA were inversely associated with intermediate AMD (OR, 0.2 [P for trend = 0.0013]; OR, 0.17 [P for trend < 0.0001]) and advanced AMD (OR, 0.13 [P for trend = 0.02]; OR, 0.26 [P for trend = 0.004]). Additionally, a statistically significant effect modification by country was noted with inverse association between MUFA and AMD being significant (OR, 0.04; P for trend < 0.0001) for the Portugal population only. Conclusions: Our study shows that higher dietary intake of trans fat is associated with the presence of AMD, and a higher intake of PUFA and MUFA is inversely associated with AMD.
Assuntos
Ácidos Graxos Monoinsaturados/efeitos adversos , Ácidos Graxos Insaturados/efeitos adversos , Degeneração Macular/etiologia , Idoso , Estudos Transversais , Dieta/efeitos adversos , Gorduras na Dieta/administração & dosagem , Gorduras na Dieta/efeitos adversos , Gorduras Insaturadas na Dieta/administração & dosagem , Gorduras Insaturadas na Dieta/efeitos adversos , Ingestão de Energia , Ácidos Graxos Monoinsaturados/administração & dosagem , Ácidos Graxos Insaturados/administração & dosagem , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Portugal , Estudos Prospectivos , Estados UnidosRESUMO
BACKGROUND: The Department of Veterans Affairs Million Veteran Program (MVP) is the largest ongoing cohort program of its kind, with 654,903 enrollees as of June 2018. The objectives of this study were to examine gender differences in the MVP cohort with respect to response and enrollment rates; demographic, health, and health care characteristics; and prevalence of self-reported health conditions. METHODS: The MVP Baseline Survey was completed by 415,694 veterans (8% women), providing self-report measures of demographic characteristics, health status, and medical history. RESULTS: Relative to men, women demonstrated a higher positive responder rate (23.0% vs. 16.0%), slightly higher enrollment rate (13.5% vs. 12.9%), and, among enrollees, a lower survey completion rate (59.7% vs. 63.8%). Women were younger, more racially diverse, had higher educational attainment, and were less likely to be married or cohabitating with a partner than men. Women were more likely to report good to excellent health status but poorer physical fitness, and less likely to report lifetime smoking and drinking than men. Compared with men, women veterans showed an increased prevalence of musculoskeletal conditions, thyroid problems, gastrointestinal conditions, migraine headaches, and mental health disorders, as well as a decreased prevalence of gout, cardiovascular diseases, high cholesterol, diabetes, and hearing problems. CONCLUSIONS: These results revealed some substantial gender differences in the research participation rates, demographic profile, health characteristics, and prevalence of health conditions for veterans in the MVP cohort. Findings highlight the need for tailoring recruitment efforts to ensure representation of the increasing women veteran population receiving care through the Veterans Health Administration.
Assuntos
Nível de Saúde , Transtornos Mentais/epidemiologia , Aptidão Física , Saúde dos Veteranos , Veteranos/estatística & dados numéricos , Adulto , Idoso , Doenças Cardiovasculares/epidemiologia , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos de Enxaqueca/epidemiologia , Doenças Musculoesqueléticas/epidemiologia , Prevalência , Distribuição por Sexo , Fatores Sexuais , Fumar/epidemiologia , Inquéritos e Questionários , Estados Unidos/epidemiologia , United States Department of Veterans Affairs , Veteranos/psicologia , Saúde dos Veteranos/estatística & dados numéricos , Adulto JovemRESUMO
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.