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For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer's disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer's disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer's disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.

BackgroundDNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach.MethodsThe study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses.ResultsWe identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development.ConclusionsWe uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common precursor state for blood cancers that most frequently occurs due to mutations in the DNA-methylation modifying enzymes DNMT3A or TET2. We used DNA-methylation array and whole-genome sequencing data from four cohorts together comprising 5522 persons to study the association between CHIP, epigenetic clocks, and health outcomes. CHIP was strongly associated with epigenetic age acceleration, defined as the residual after regressing epigenetic clock age on chronological age, in several clocks, ranging from 1.31 years (GrimAge, p 0 in both Hannum and GrimAge (referred to as AgeAccelHG+). This group was at high risk of all-cause mortality (hazard ratio 2.90, p

Background. When added to age, CD4 count and human immunodeficiency virus type 1 (HIV-1) RNA alone (Restricted Index), hemoglobin, FIB-4 Index, hepatitis C virus (HCV), and estimated glomerular filtration rate improve prediction of mortality. Weighted and combined, these 7 routine clinical variables constitute the Veterans Aging Cohort Study (VACS) Index. Because nonroutine biomarkers of inflammation (interleukin 6 [IL-6]), coagulation (D-dimer), and monocyte activation (sCD14) also predict mortality, we test the association of these indices and biomarkers with each other and with mortality. Methods. Samples from 1302 HIV-infected veterans on antiretroviral therapy were analyzed. Indices were calculated closest to date of collection. We calculated Spearman correlations stratified by HIV-1 RNA and HCV status and measured association with mortality using C statistics and net reclassification improvement (NRI). Results. Of 1302 subjects, 915 had HIV-1 RNA <500 copies/mL and 154 died. The VACS Index was more correlated with IL-6, D-dimer, and sCD14 than the Restricted Index (P < .001). It was also more predictive of mortality (C statistic, 0.76; 95% confidence interval [CI], .72-.80) than any biomarker (C statistic, 0.66-0.70) or the Restricted Index (C statistic, 0.71; 95% CI, .67-.75). Compared to the Restricted Index alone, NRI resulted from incremental addition of VACS Index components (10%), D-dimer (7%), and sCD14 (4%), but not from IL-6 (0%). Conclusions. Among HIV-infected individuals, independent of CD4, HIV-1 RNA, and age, hemoglobin and markers of liver and renal injury are associated with inflammation. Addition of D-dimer and sCD14, but not IL-6, improves the predictive accuracy of the VACS Index for mortality. [ABSTRACT FROM AUTHOR]