Background The Veterans Affairs Frailty Index (VA-FI) is an electronic frailty index developed to measure frailty using administrative claims and electronic health records data in Veterans. An update to ICD-10 coding is needed to enable contemporary measurement of frailty. Methods ICD-9 codes from the original VA-FI were mapped to ICD-10 first using the Centers for Medicaid and Medicare Services (CMS) General Equivalence Mappings. The resulting ICD-10 codes were reviewed by two geriatricians. Using nationals cohort of Veterans ≥65 years old, the prevalence of deficits contributing to the VA-FI and associations between the VA-FI and mortality over years 2012-2018 were examined. Results The updated VA-FI-10 includes 6422 codes representing 31 health deficits. Annual cohorts defined on October 1 of each year included 2 266 191 to 2 428 115 Veterans, for which the mean age was 76 years, 97-98% were male, 78-79% were white, and the mean VA-FI was 0.20-0.22. The VA-FI-10 deficits showed stability before and after the transition to ICD-10 in 2015, and maintained strong associations with mortality. Patients classified as frail (VA-FI ≥0.2) consistently had a hazard of death more than two-times higher than non-frail patients (VA-FI <0.1). Distributions of frailty and associations with mortality varied with and without linkage to CMS data and with different assessment periods for capturing deficits. Conclusions The updated VA-FI-10 maintains content validity, stability, and predictive validity for mortality in a contemporary cohort of Veterans ≥65 years old, and may be applied to ICD-9 and ICD-10 claims data to measure frailty.

Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Pharmacologic clinical trials for heart failure with preserved ejection fraction have been largely unsuccessful as compared to those for heart failure with reduced ejection fraction. Whether differences in the genetic underpinnings of these major heart failure subtypes may provide insights into the disparate outcomes of clinical trials remains unknown. We utilize a large, uniformly phenotyped, single cohort of heart failure sub-classified into heart failure with reduced and with preserved ejection fractions based on current clinical definitions, to conduct detailed genetic analyses of the two heart failure sub-types. We find different genetic architectures and distinct genetic association profiles between heart failure with reduced and with preserved ejection fraction suggesting differences in underlying pathobiology. The modest genetic discovery for heart failure with preserved ejection fraction (one locus) compared to heart failure with reduced ejection fraction (13 loci) despite comparable sample sizes indicates that clinically defined heart failure with preserved ejection fraction likely represents the amalgamation of several, distinct pathobiological entities. Development of consensus sub-phenotyping of heart failure with preserved ejection fraction is paramount to better dissect the underlying genetic signals and contributors to this highly prevalent condition.

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

OBJECTIVE Diabetes and dementia are diseases of high health care burden worldwide, and studies have shown that diabetes is associated with an increased relative risk of dementia. We set out to examine whether type 2 diabetes–associated genetic variants were associated with dementia and whether they differed by race/ethnicity or clinical dementia diagnosis. RESEARCH DESIGN AND METHODS We evaluated associations of two type 2 diabetes genetic risk scores (GRS and GRS-nonAPOE: a score without rs429358, a variant associated with Alzheimer disease [AD]) with three classifications of clinical dementia diagnoses in the Million Veteran Program (MVP): all-cause dementia, vascular dementia (VaD), and AD. We conducted our analysis stratified by European (EUR), African (AFR), and Hispanic (HIS) races/ethnicities. RESULTS In EUR, we found associations of the GRS with all-cause dementia (odds ratio [OR] 1.06, P = 1.60e−07) and clinically diagnosed VaD (OR 1.12, P = 5.2e−05) but not with clinically diagnosed AD (OR 1.02, P = 0.43). The GRS was not associated with any dementia outcome in AFR or HIS. When testing with GRS-nonAPOE, we found that effect size estimates in EUR increased and P values decreased for all-cause dementia (OR 1.08, P = 2.6e−12), for VaD (OR 1.14, P = 7.2e−07), and for AD (OR 1.06, P = 0.018). For AFR, the association of GRS-nonAPOE and clinically diagnosed VaD (OR 1.15, P = 0.016) was statistically significant. There were no significant findings for HIS. CONCLUSIONS We found evidence suggesting shared genetic pathogenesis of diabetes with all-cause dementia and clinically diagnosed VaD.