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Elevated plasma levels of sCD14 predict all-cause mortality in people with HIV (PWH). Epigenetic regulation plays a key role in infection and inflammation. To reveal the epigenetic relationships between sCD14, immune function and disease progression among PWH, we conducted an epigenome-wide association study (EWAS) of sCD14 and investigated the relationship with mortality.DNA methylation (DNAm) levels of peripheral blood samples from PWH in the Veterans Aging Cohort Study (VACS) were measured using the Illumina Infinium Methylation 450K (n = 549) and EPIC (850K) BeadChip (n = 526). Adjusted for covariates and multiple testing, we conducted an epigenome-wide discovery, replication, and meta-analysis to identify significant associations with sCD14. We then examined and replicated the relationship between the principal epigenetic sites and survival using Cox regression models.We identified 118 DNAm sites significantly associated with sCD14 in the meta-analysis of 1075 PWH. The principal associated DNAm sites mapped to genes (e.g. STAT1, PARP9, IFITM1, MX1, and IFIT1) related to inflammation and antiviral response. Adjusting for multiple testing, 10 of 118 sCD14-associated DNAm sites significantly predicted survival time conditional on sCD14 levels.The identification of DNAm sites independently predicting survival may improve our understanding of prognosis and potential therapeutic targets among PWH.

Obesity is a significant public health concern across the globe. Research investigating epigenetic mechanisms related to obesity and obesity-associated conditions has identified differences that may contribute to cellular dysregulation that accelerates the development of disease. However, few studies include Black women, who experience the highest incidence of obesity and early onset of cardiometabolic disorders.The association of BMI with epigenome-wide DNA methylation (DNAm) was examined using the 850K Illumina EPIC BeadChip in two Black populations (Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure [InterGEN], n = 239; and The Genetic Epidemiology Network of Arteriopathy [GENOA] study, n = 961) using linear mixed-effects regression models adjusted for batch effects, cell type heterogeneity, population stratification, and confounding factors.Cross-sectional analysis of the InterGEN discovery cohort identified 28 DNAm sites significantly associated with BMI, 24 of which had not been previously reported. Of these, 17 were replicated using the GENOA study. In addition, a meta-analysis, including both the InterGEN and GENOA cohorts, identified 658 DNAm sites associated with BMI with false discovery rate 0.05. In a meta-analysis of Black women, we identified 628 DNAm sites significantly associated with BMI. Using a more stringent significance threshold of Bonferroni-corrected p value 0.05, 65 and 61 DNAm sites associated with BMI were identified from the combined sex and female-only meta-analyses, respectively.This study suggests that BMI is associated with differences in DNAm among women that can be identified with DNA extracted from salivary (discovery) and peripheral blood (replication) samples among Black populations across two cohorts.

Background Biomarkers that provide insight into drivers of aging are needed for people with human immunodeficiency virus (PWH). The study objective was to determine if epigenetic age acceleration (EAA) markers are associated with physiologic frailty measured by the Veterans Aging Cohort Study (VACS) Index and predict all-cause mortality for PWH. Methods Epigenome-wide DNA methylation was profiled in VACS total white blood cell samples collected during 2005–2007 from 531 PWH to generate 6 established markers of EAA. The association of each EAA marker was tested with VACS Index 2.0. All-cause mortality was assessed over 10 years. For each EAA marker, the hazard ratio per increased year was determined using Cox regression. To evaluate mortality discrimination, C-statistics were derived. Results Participants were mostly men (98.5%) and non-Hispanic Black (84.4%), with a mean age of 52.4 years (standard deviation [SD], 7.8 years). Mean VACS Index score was 59.3 (SD, 16.4) and 136 deaths occurred over a median follow-up of 8.7 years. Grim age acceleration (AA), PhenoAA, HannumAA, and extrinsic epigenetic AA were associated with the VACS Index and mortality. HorvathAA and intrinsic epigenetic AA were not associated with either outcome. GrimAA had the greatest mortality discrimination among EAA markers and predicted mortality independently of the VACS Index. One-year increase in GrimAA was associated with a 1-point increase in VACS Index and a 10% increased hazard for mortality. Conclusions The observed associations between EAA markers with physiologic frailty and mortality support future research to provide mechanistic insight into the accelerated aging process and inform interventions tailored to PWH for promoting increased healthspan.

ImportancePrimary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation.ObjectiveTo determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population.Design, Setting, and ParticipantsThis was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023.ExposuresPRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status.Main Outcomes and MeasuresIncident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events.ResultsA total of 79 151 participants (mean [SD] age, 57.8 [13.7] years; 68 503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18 505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53 861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk >3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, −0.07% to 3.30%).Conclusions and RelevanceStudy results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.

BackgroundHeart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for cardiovascular diseases, including HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF.MethodsIn the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99,368 White (British, Irish, and any other white background) participants with ≥ 3 BMI measures during > 2 years preceding enrollment were included, with a median follow-up of 12.5 years. The within-participant variability of BMI was evaluated using standardized standard deviation (SD) and coefficient of variation (CV). The association of BMI variability with incident HF was assessed using Fine and Gray’s competing risk model, and adjusted for age, sex, smoking history, alcohol consumption, diabetes, hypertension, history of heart attack, stroke, atrial fibrillation, lipids, estimated glomerular filtration rate and mean BMI per individual.ResultsIn the fully adjusted model, higher BMI variability measured in both SD and CV were significantly associated with higher risk in HF incidence (SD: Hazard Ratio [HR] 1.05, 95% Confidence Interval [CI] 1.02 - 1.07, p = 0.0002; CV: HR 1.06, 95% CI 1.04 - 1.09, p < 0.0001).ConclusionsLongitudinal health records capture BMI fluctuation, which independently predicts HF incidence. Integration of long-term BMI and other routinely measured health factors may improve risk prediction of HF and other cardiovascular outcomes.

Major Depressive Disorder (MDD) is a complex neuropsychiatric disease with known genetic associations, but without known links to rare variation in the human genome. Here we aim to identify rare genetic variants associated with MDD using deep whole-genome sequencing data in an independent population.We report the sequencing of 1,688 whole genomes in a large sample of male-male Veteran twins. Depression status was classified based on a structured diagnostic interview according toOur analysis identified one gene associated with severe depression, basic helix loop helix e22 (The gene

Although people with HIV are living longer, as they age they remain disproportionately burdened with multimorbidity that is exacerbated in resource-poor settings. The geroscience hypothesis postulates that a discrete set of between five and ten hallmarks of biological ageing drive multimorbidity, but these processes have not been systematically examined in the context of people with HIV. We examine four major hallmarks of ageing (macromolecular damage, senescence, inflammation, and stem-cell dysfunction) as gerodrivers in the context of people with HIV. As a counterbalance, we introduce healthy ageing, physiological reserve, intrinsic capacity, and resilience as promoters of geroprotection that counteract gerodrivers. We discuss emerging geroscience-based diagnostic biomarkers and therapeutic strategies, and provide examples based on recent advances in cellular senescence, and other, non-pharmacological approaches. Finally, we present a conceptual model of biological ageing in the general population and in people with HIV that integrates gerodrivers and geroprotectors as modulators of homoeostatic reserves and organ function over the lifecourse.

Objective Modern healthcare data reflect massive multi-level and multi-scale information collected over many years. The majority of the existing phenotyping algorithms use case–control definitions of disease. This paper aims to study the time to disease onset and progression and identify the time-varying risk factors that drive them. Materials and Methods We developed an algorithmic approach to phenotyping the incidence of diseases by consolidating data sources from the UK Biobank (UKB), including primary care electronic health records (EHRs). We focused on defining events, event dates, and their censoring time, including relevant terms and existing phenotypes, excluding generic, rare, or semantically distant terms, forward-mapping terminology terms, and expert review. We applied our approach to phenotyping diabetes complications, including a composite cardiovascular disease (CVD) outcome, diabetic kidney disease (DKD), and diabetic retinopathy (DR), in the UKB study. Results We identified 49 049 participants with diabetes. Among them, 1023 had type 1 diabetes (T1D), and 40 193 had type 2 diabetes (T2D). A total of 23 833 diabetes subjects had linked primary care records. There were 3237, 3113, and 4922 patients with CVD, DKD, and DR events, respectively. The risk prediction performance for each outcome was assessed, and our results are consistent with the prediction area under the ROC (receiver operating characteristic) curve (AUC) of standard risk prediction models using cohort studies. Discussion and Conclusion Our publicly available pipeline and platform enable streamlined curation of incidence events, identification of time-varying risk factors underlying disease progression, and the definition of a relevant cohort for time-to-event analyses. These important steps need to be considered simultaneously to study disease progression.

Elevated levels of inflammation associated with HIV infection are considered one of the primary causes for the excess burden of age-related morbidity and mortality among people with HIV (PWH). Circulating protein levels can be used to investigate biological pathways contributing to persistent inflammation among PWH. In this study, we profiled 73 inflammation-related protein markers and assessed their associations with chronological age, sex and CD4+ cell count among 87 black South African PWH prior to initiating ART. We identified 1, 1 and 14 inflammatory proteins significantly associated with sex, CD4+ T-cell count, and age respectively among PWH. Twelve out of 14 age-associated proteins have been reported to be associated with age in the general population, and 4 have previously shown significant associations with age for PWH. Furthermore, many of the age-associated proteins such as CST5, CCL23, SLAMF1, MMP-1, MCP-1, and CDCP1 have been linked to chronic diseases such as cardiovascular disease and neurocognitive decline in the general population. We also found a synergistic interaction between male sex and older age accounting for excessive expression of CST5. In conclusion, we found that age may lead to the elevation of multiple inflammatory proteins among PWH. We also demonstrated the potential utility of proteomics for evaluating and characterizing the inflammatory status among PWH.

OBJECTIVES Major Depressive Disorder (MDD) is a complex neuropsychiatric disease with known genetic associations, but without known links to rare variation in the human genome. Here we aim to identify rare genetic variants associated with MDD using deep whole-genome sequencing data in an independent population. METHODS We report the sequencing of 1,688 whole genomes in a large sample of male-male Veteran twins. Depression status was classified based on a structured diagnostic interview according to DSM-III-R diagnostic criteria. Searching only rare variants in genomic regions from recent GWAS on MDD, we used the optimised sequence kernel association test and Fisher's Exact test to fine map loci associated with severe depression. RESULTS Our analysis identified one gene associated with severe depression, basic helix loop helix e22 (PAdjusted = 0.03) via SKAT-O test between unrelated severely depressed cases compared to unrelated non-depressed controls. The same gene BHLHE22 had a non-silent variant rs13279074 (PAdjusted = 0.032) based on a single variant Fisher's Exact test between unrelated severely depressed cases compared to unrelated non-depressed controls. CONCLUSION The gene BHLHE22 shows compelling genetic evidence of directly impacting the severe depression phenotype. Together these results advance understanding of the genetic contribution to major depressive disorder in a new cohort and link a rare variant to severe forms of the disorder.

High dimensional predictive models of Major Adverse Cardiac Events (MACE), which includes heart attack (AMI), stroke, and death caused by cardiovascular disease (CVD), were built using four longitudinal cohorts of Veterans Administration (VA) patients created from VA medical records. We considered 247 variables / risk factors measured across 7.5 years for millions of patients in order to compare predictions for the first reported MACE event using six distinct modelling methodologies. The best-performing methodology varied across the four cohorts. Model coefficients related to disease pathophysiology and treatment were relatively constant across cohorts, while coefficients dependent upon the confounding variables of age and healthcare utilization varied considerably across cohorts. In particular, models trained on a retrospective case-control (Rcc) cohort (where controls are matched to cases by date of birth cohort and overall level of healthcare utilization) emphasize variables describing pathophysiology and treatment, while predictions based on the cohort of all active patients at the start of 2017 (C-17) rely much more on age and variables reflecting healthcare utilization. In consequence, directly using an Rcc-trained model to evaluate the C-17 cohort resulted in poor performance (C-statistic = 0.65). However, a simple reoptimization of model dependence on age, demographics, and five other variables improved the C-statistic to 0.74, nearly matching the 0.76 obtained on C-17 by a C-17-trained model. Dependence of MACE risk on biomarkers for hypertension, cholesterol, diabetes, body mass index, and renal function in our models was consistent with the literature. At the same time, including medications and procedures provided important indications of both disease severity and the level of treatment. More detailed study designs will be required to disentangle these effects.

Previous studies have shown reduced cardiovascular risk with increasing high-density lipoprotein cholesterol (HDL-C) levels. However, recent data in the general population have shown increased risk of adverse outcomes at very high concentrations of HDL-C. Thus, we aimed to study the gender-specific relation between very high HDL-C levels (80,100 mg/100 ml) and adverse cardiovascular outcomes and the genetic basis in the general population enrolled in the United Kingdom Biobank. A total of 415,416 participants enrolled in the United Kingdom Biobank without coronary artery disease were included in this prospective cohort study, with a median follow-up of 9 years. A high HDL-C level80 mg/100 ml was associated with increased risk of all-cause death (Hazard ratio [HR] 1.11, confidence interval [CI] 1.03 to 1.20, p = 0.005) and cardiovascular death (HR 1.24, CI 1.05 to 1.46, p = 0.01) after adjustment for age, gender, race, body mass index, hypertension, smoking, triglycerides, LDL-C, stroke history, heart attack history, diabetes, eGFR, and frequent alcohol use (defined as ≥3 times/week) using Cox proportional hazard and Fine and Gray's subdistribution hazard models, respectively. In gender-stratified analyses, such associations were only observed in men (all-cause death HR 1.79, CI 1.59 to 2.02, p0.0001; cardiovascular death HR 1.92, CI 1.52 to 2.42, p0.0001), but not in women (all-cause death HR 0.97, CI 0.88 to 1.06, p = 0.50; cardiovascular death HR 1.04, CI 0.83 to 1.31, p = 0.70). The findings persisted after adjusting for the genetic risk score comprised of known HDL-C-associated single nucleotide polymorphisms. Very high HDL-C levels are associated with an increased risk of all-cause death and cardiovascular death among men but not in women in the general population free of coronary artery disease.

Objective: Despite evidence that trauma exposure is linked to higher risk of hypertension, epigenetic mechanisms (such as DNA methylation) by which trauma potentially influences hypertension risk among Black adults remain understudied. Methods: Data from a longitudinal study of Black mothers were used to test the hypothesis that direct childhood trauma (ie, personal exposure) and vicarious trauma (ie, childhood trauma experienced by their children) would interact with DNA methylation to increase blood pressure (BP). Separate linear mixed effects models were fitted at each CpG site with the DNA methylation beta-value and direct and vicarious trauma as predictors and systolic and diastolic BP modeled as dependent variables adjusted for age, cigarette smoking, and body mass index. Interaction terms between DNA methylation beta-values with direct and vicarious trauma were added. Results: The sample included 244 Black mothers with a mean age of 31.2 years (SD = ±5.8). Approximately 45% of participants reported at least one form of direct childhood trauma and 49% reported at least one form of vicarious trauma. Epigenome-wide interaction analyses found that no CpG sites passed the epigenome-wide significance level indicating the interaction between direct or vicarious trauma with DNAm did not influence systolic or diastolic BP. Conclusions: This is one of the first studies to simultaneously examine whether direct or vicarious exposure to trauma interact with DNAm to influence BP. Although findings were null, this study highlights directions for future research that investigates epigenetic mechanisms that may link trauma exposure with hypertension risk in Black women.

BackgroundApolipoprotein A1 (ApoA1) is the principal protein component of high-density lipoprotein (HDL). Although low HDL cholesterol (HDL-C) levels are known to be associated with greater cardiovascular risk, recent studies have also shown heightened mortality risk at very high HDL-C levels.AimsTo investigate the sex-specific association between elevated ApoA1 levels and adverse outcomes, and their genetic basis.MethodsA prospective cohort study of United Kingdom Biobank participants without coronary artery disease at enrollment was performed. The primary exposure was serum ApoA1 levels. The primary and secondary outcome measures were cardiovascular and all-cause death, respectively.ResultsIn 402 783 participants followed for a median of 12.1 years, there was a U-shaped relationship between ApoA1 levels and both cardiovascular as well as all-cause mortality, after adjustment for traditional cardiovascular risk factors. Individuals in the highest decile of ApoA1 levels (1.91–2.50 g/L) demonstrated higher cardiovascular (HR 1.21, 95% CI 1.07–1.37, P < 0.0022) and all-cause mortality (HR 1.14, 95% CI 1.07–1.21, P < 0.0001) compared with those within the lowest risk eighth decile (1.67–1.75 g/L). The U-shaped relationship was present in both sexes, though more pronounced in men. Sensitivity analyses showed that cardiovascular mortality rates were higher in those with greater alcohol intake (P < 0.004). Adjustment for polygenic variation associated with higher ApoA1 levels did not attenuate the effect of very high ApoA1 levels on mortality. In the sub-group with very elevated HDL-C levels (> 80 mg/dL in men, > 100 mg/dL in women), there was no association between ApoA1 levels and mortality.ConclusionBoth very low and very elevated ApoA1 levels are associated with higher cardiovascular and all-cause mortality.

Prior studies have shown inconsistent findings of an association between depression and epigenetic aging. DNA methylation (DNAm) age acceleration can measure biological aging. We adopted a robust co-twin control study design to examine whether depression is associated with DNAm age acceleration after accounting for the potential confounding influences of genetics and family environment.We analyzed data on a sub-cohort of the Vietnam Era Twin Registry. A total of 291 twins participated at baseline and 177 at follow-up visit after a mean of 11.7 years, with 111 participants having DNA samples for both time points. Depression was measured using the Beck Depression Inventory II (BDI-II). Six measures of DNAm age acceleration were computed at each time point, including Horvath's DNAm age acceleration (HorvathAA), intrinsic epigenetic age acceleration (IEAA), Hannum's DNAm age acceleration (HannumAA), extrinsic epigenetic age acceleration (EEAA), GrimAge acceleration (GrimAA), and PhenoAge acceleration (PhenoAA). Mixed-effects modeling was used to assess the within-pair association between depression and DNAm age acceleration.At baseline, a 10-unit higher BDI-II total score was associated with HannumAA (0.73 years, 95% confidence interval [CI] 0.13-1.33, p = .019) and EEAA (0.94 years, 95% CI 0.22-1.66, p = .012). At follow-up, 10-unit higher BDI-II score was associated with PhenoAA (1.32 years, 95% CI 0.18-2.47, p = .027).We identified that depression is associated with higher levels of DNAm age acceleration. Further investigation is warranted to better understand the underlying mechanisms for the potential causal relationship between depression and accelerated aging.

To determine whether obesity-associated metabolites are associated with type 2 diabetes (T2DM) risk among South Asians.Serum-based nuclear magnetic resonance imaging metabolomics data were generated from two South Asian population-based prospective cohorts from Karachi, Pakistan: CARRS1 (N = 4017) and CARRS2 (N = 4802). Participants in both cohorts were followed up for 5 years and incident T2DM was ascertained. A nested case-control study approach was developed to select participants from CARRS1 (NIn a combined sample of the CARRS1 and CARRS2 cohorts, out of 224 metabolites, 12 were associated with general obesity and, of these, one was associated with incident T2DM. Fifteen out of 224 metabolites were associated with central obesity and, of these, 10 were associated with incident T2DM. The higher level of total cholesterol in high-density lipoprotein (HDL) was associated with reduced T2DM risk (odds ratio [OR] 0.68, 95% confidence interval [CI] 0.53, 0.86; P = 1.2 × 10Total cholesterol in HDL and cholesterol esters in large VLDL particles may be an important biomarker in the identification of early development of obesity-associated T2DM risk among South Asian adults.

Background: Coronary revascularization is recommended to treat ischemic cardiomyopathy. However, the relations of revascularization-associated ejection fraction (EF) change to subsequent outcomes have not been elucidated. Methods: In 10 071 veterans (mean age 67 years; 1% women; 15% non-White) who underwent a first percutaneous coronary intervention (PCI) or coronary artery bypass grafting between January 1, 1995, and December 31, 2010, and had prerevascularization and postrevascularization EF measured, we calculated delta-EF (postprocedure EF–preprocedure EF). We related delta-EF as a continuous measure and as categories (≤−5, −5 Results: Over follow-up (mean/maximum 5/14 years) 56% died. Each 5% improvement in delta-EF was associated with statistically significant reductions in death and heart failure hospitalization days of 5% (95% CI, 3%–7%) and 10% (95% CI, 5%–15%), respectively, in the total sample and 6% (95% CI, 4%–8%) and 10% (95% CI, 5%–16%), respectively, in the PCI subgroup. Patients in the highest delta-EF category had 27% (95% CI, 19%–34%) lower mortality (30% [95% CI, 21%–37%] lower in PCI stratum) and ≈40% lower heart failure hospitalization days in total sample and PCI stratum, compared with those in the lowest category. Relations of delta-EF and outcomes in coronary artery bypass grafting subgroup did not reach statistical significance. Conclusions: Revascularization-associated EF improvement was associated with significant reductions in mortality and heart failure hospitalization burden, particularly in the PCI subgroup.

Background: African American women (AAW) have a high risk of both cardiometabolic (CM) illness and depressive symptoms. Depressive symptoms co-occur in individuals with CM illness at higher rates than the general population, and accelerated aging may explain this. In this secondary analysis, we examined associations between age acceleration; depressive symptoms; and CM traits (hypertension, diabetes mellitus [DM], and obesity) in a cohort of AAW. Methods: Genomic and clinical data from the InterGEN cohort (n = 227) were used. Age acceleration was based on the Horvath method of DNA methylation (DNAm) age estimation. Accordingly, DNAm age acceleration (DNAm AA) was defined as the residuals from a linear regression of DNAm age on chronological age. Spearman’s correlations, linear and logistic regression examined associations between DNAm AA, depressive symptoms, and CM traits. Results: DNAm AA did not associate with total depressive symptom scores. DNAm AA correlated with specific symptoms including self-disgust/self-hate (−0.13, 95% CI −0.26, −0.01); difficulty with making decisions (−0.15, 95% CI −0.28, −0.02); and worry over physical health (0.15, 95% CI 0.02, 0.28), but were not statistically significant after multiple comparison correction. DNAm AA associated with obesity (0.08, 95% CI 1.02, 1.16), hypertension (0.08, 95% CI 1.01, 1.17), and DM (0.20, 95% CI 1.09, 1.40), after adjustment for potential confounders. Conclusions: Associations between age acceleration and depressive symptoms may be highly nuanced and dependent on study design contexts. Factors other than age acceleration may explain the connection between depressive symptoms and CM traits. AAW with CM traits may be at increased risk of accelerated aging.

Biobanks linked to massive, longitudinal electronic health record (EHR) data make numerous new genetic research questions feasible. One among these is the study of biomarker trajectories. For example, high blood pressure measurements over visits strongly predict stroke onset, and consistently high fasting glucose and Hb1Ac levels define diabetes. Recent research reveals that not only the mean level of biomarker trajectories but also their fluctuations, or within-subject (WS) variability, are risk factors for many diseases. Glycemic variation, for instance, is recently considered an important clinical metric in diabetes management. It is crucial to identify the genetic factors that shift the mean or alter the WS variability of a biomarker trajectory. Compared to traditional cross-sectional studies, trajectory analysis utilizes more data points and captures a complete picture of the impact of time-varying factors, including medication history and lifestyle. Currently, there are no efficient tools for genome-wide association studies (GWASs) of biomarker trajectories at the biobank scale, even for just mean effects. We propose TrajGWAS, a linear mixed effect model-based method for testing genetic effects that shift the mean or alter the WS variability of a biomarker trajectory. It is scalable to biobank data with 100,000 to 1,000,000 individuals and many longitudinal measurements and robust to distributional assumptions. Simulation studies corroborate that TrajGWAS controls the type I error rate and is powerful. Analysis of eleven biomarkers measured longitudinally and extracted from UK Biobank primary care data for more than 150,000 participants with 1,800,000 observations reveals loci that significantly alter the mean or WS variability.

BACKGROUND: Coronary artery disease (CAD) is a preeminent cause of death and smoking is a strong risk factor for CAD. Genetic factors contribute to the development of CAD but the interplay between genetic predisposition and smoking history in CAD remains unclear. METHODS AND RESULTS: Using data from the UK Biobank, we constructed several genetic risk scores (GRSs) based on known CAD loci and assessed their interactions with smoking for development of incident CAD in 307,147 participants of European ancestry who were free of CAD. We fitted Cox proportional hazard models and assessed gene-smoking interaction on both multiplicative and additive scales. Overall, we found no multiplicative interactions but observed a synergistic additive interaction of GRS with both smoking status and pack-years of smoking, finding that the absolute CAD risk due to smoking was higher for those with high genetic risk. Trait-based sub-GRSs suggested smoking status and smoking intensity measured by pack-years might confer gene-smoking interaction effects with different intermediate risk factors for CAD. CONCLUSIONS: Our study results suggest that genetics could modify the effects of smoking on CAD and highlight the value of addressing gene-lifestyle interactions on both additive and multiplicative scales.

Background: Familial hypercholesterolemia (FH) genetic variants confer risk for coronary artery disease independent of LDL-C (low-density lipoprotein cholesterol) when considering a single measurement. In real clinical settings, longitudinal LDL-C data are often available through the electronic health record. It is unknown whether genetic testing for FH variants provides additional risk-stratifying information once longitudinal LDL-C is considered. Methods: We used the extensive electronic health record data available through the Million Veteran Program to conduct a nested case-control study. The primary outcome was coronary artery disease, derived from electronic health record codes for acute myocardial infarction and coronary revascularization. Incidence density sampling was used to match case/control exposure windows, defined by the date of the first LDL-C measurement to the date of the first coronary artery disease code of the index case. Adjustments for the first, maximum, or mean LDL-C were analyzed. FH variants in LDLR , APOB , and PCSK9 (Proprotein convertase subtilisin/kexin type 9) were assessed by custom genotype array. Results: In a cohort of 23 091 predominantly prevalent cases at enrollment and 230 910 matched controls, FH variant carriers had an increased risk for coronary artery disease (odds ratio [OR], 1.53 [95% CI, 1.24–1.89]). Adjusting for mean LDL-C led to the greatest attenuation of the risk estimate, but significant risk remained (odds ratio, 1.33 [95% CI, 1.08–1.64]). The degree of attenuation was not affected by the number and the spread of LDL-C measures available. Conclusions: The risk associated with carrying an FH variant cannot be fully captured by the LDL-C data available in the electronic health record, even when considering multiple LDL-C measurements spanning more than a decade.

BACKGROUND: Accelerated biological aging, as indicated by telomere shortening, is associated with CAD pathogenesis. In a cross-sectional study, we investigated neural correlates of acute psychological stress and short telomeres in patients with CAD. METHODS: Individuals with CAD (N = 168) underwent a validated mental stress protocol including public speaking and mental arithmetic. Imaging of the brain with [O-15] water and high-resolution positron emission tomography (HR-PET) was performed during mental stress and control conditions. Blood flow during stressful tasks (average of speech and arithmetic) and control tasks were assessed. Telomere length in peripheral leucocytes was measured by quantitative polymerase chain reaction and expressed as Telomere/Single Copy Gene (T/S) ratio. Voxel-wise regression models were constructed to assess the association between brain areas and activity during rest and mental stress after adjustments for demographic factors and clinical characteristics. RESULTS: The mean (SD) age of the sample was 62 (8) years, and 69% were men. Increased activation with mental stress in the lingual gyrus, cerebellum and superior and inferior frontal gyri were associated with reduced telomere length; 1.6 higher voxel activation of these areas was associated with 0.1 T/S-units reduction in telomere length (P < 0.005). Additionally, during neutral counting and speaking tasks, brain activity in the precentral, middle and superior frontal and middle temporal gyri was inversely associated with telomere length. Results remained consistent after adjustment for demographic and clinical risk factors. CONCLUSION: Increased stress-induced activity in brain areas mediating the stress response was associated with shortened telomere length in CAD patients.

Objective Posttraumatic stress disorder (PTSD) has been related to accelerated biological aging processes, but objective evidence for this association is limited. DNA methylation (DNAm) age acceleration is a novel measure of biological aging which may help clarify if PTSD is related to biological aging processes. We aim to examine whether PTSD is associated with biological aging using a comprehensive set of DNAm age acceleration markers, and to what extent the unshared environment contributes to the association. Methods Using a cross-sectional co-twin control study design, we investigated the association of the clinical diagnosis and symptom severity of posttraumatic stress disorder with six measurements of DNAm age acceleration based on epigenome-wide data derived from peripheral blood lymphocytes of 296 male twins from the Vietnam Era Twin Registry. Results Twins with current PTSD had significantly advanced DNAm age acceleration compared with twins without PTSD for five out of six measures of DNAm age acceleration. Across almost all measures of DNAm age acceleration, twins with current PTSD were "epigenetically older" than their twin brothers without PTSD: estimated differences ranged between 1.6 (95% confidence interval 0.0 to 3.1) to 2.7 (95% confidence interval 0.5 to 4.8) biological age year-equivalents. A higher CAPS score was also associated with a higher within-pair DNAm age acceleration. Results remained consistent after adjustment for behavioral and cardiovascular risk factors. Conclusions PTSD is associated with epigenetic age acceleration, primarily through unshared environmental mechanisms as opposed to genetic or familial factors. These results suggest that PTSD is related to systemic processes relevant to biological aging.

Polygenic risk scores (PRSs) quantify the contribution of multiple genetic loci to an individual’s likelihood of a complex trait or disease. However, existing PRSs estimate this likelihood with common genetic variants, excluding the impact of rare variants. Here, we report on a method to identify rare variants associated with outlier gene expression and integrate their impact into PRS predictions for body mass index (BMI), obesity, and bariatric surgery. Between the top and bottom 10%, we observed a 20.8% increase in risk for obesity (p = 3 × 10(−14)), 62.3% increase in risk for severe obesity (p = 1 × 10(−6)), and median 5.29 years earlier onset for bariatric surgery (p = 0.008), as a function of expression outlier-associated rare variant burden when controlling for common variant PRS. We show that these predictions were more significant than integrating the effects of rare protein-truncating variants (PTVs), observing a mean 19% increase in phenotypic variance explained with expression outlier-associated rare variants when compared with PTVs (p = 2 × 10(−15)). We replicated these findings by using data from the Million Veteran Program and demonstrated that PRSs across multiple traits and diseases can benefit from the inclusion of expression outlier-associated rare variants identified through population-scale transcriptome sequencing.

Introduction: Heart failure (HF) increases morbidity, mortality, and costs, with complex pathogenic mechanisms. Interleukin-6 (IL-6) is a key cytokine and immune regulator with broad impact on inflammation – a critical component of HF pathophysiology. Circulating levels of IL-6 receptor (IL-6R) determines the activity of the IL-6 signaling pathway. We aim to estimate the causal effect of the IL-6R on HF and two clinical subtypes: HF with reduced (HFrEF) and preserved ejection fraction (HFpEF) in a Mendelian Randomization (MR) framework including mediators. Hypothesis: Plausible causal associations between IL-6R and HF, HFrEF and HFpEF are mediated by body mass index (BMI) or coronary artery disease (CAD). Methods: Two-sample MR analyses were conducted using genetic association results for composite HF, HFrEF and HFpEF among >300,000 MVP participants of European ancestry. Thirty-four independent genetic variants within 250 kb from the IL6R gene associated with plasma IL-6R levels were used as genetic instrumental variables. We estimated the direct effect of IL-6R levels on HF and subtypes, and the indirect effect mediated through BMI and CAD. Results: Causal effects of IL-6R on composite HF, HFrEF and HFpEF were estimated as odds ratios (OR): 0.97 (CI 0.96-0.99, p=0.02), 0.96 (CI 0.93-0.98, p=0.003) and 1.00 (CI 0.97-1.03, p=0.89), respectively. Mediation analyses for composite HF and HFrEF showed significant mediation effects by CAD, with ORs 0.98 (CI 0.97-0.99) and 0.98 (CI 0.96-1.00), respectively. No mediation effect of BMI was identified. Conclusions: These findings support a causal role of IL-6 signaling in composite HF and HFrEF, but not HFpEF. Although the IL-6 signaling pathway plays a role in both BMI and CAD, the effect of IL-6 signaling on composite HF and HFrEF may be mediated through by CAD. Our findings demonstrate the role of IL-6 signaling in HF and its difference between HF subtypes, which may lead to more specific therapeutic targets for HF.

The prediction of myocardial infarction (MI), acute ischemic stroke (AIS), cardiovascular (CVD) death, and 3-point MACE (MI, AIS, or CVD death) in Million Veteran Program (MVP) participants over 8 years of follow up was evaluated using environmental/traditional risk factors (“E”), polygenic risk scores (“G”), and a combination of both approaches (“GxE”). Individuals free of atherosclerotic cardiovascular disease (ASCVD) at baseline were included. Risk factor levels for the participants close to the time of MVP enrollment for age, sex, systolic blood pressure, cholesterol, HDL cholesterol, smoking status, and diabetes status were analyzed. Outcomes were determined from VA electronic record data, Medicare/Medicaid data, and the National Death Index. Analyses were undertaken separately for non-Hispanic European (EUR), African American (AFR), and Hispanic (HIS) participants. There were 157,941 veterans at risk with 8,157 MI events, 2,024 AIS events, 1,778 CVD deaths, and 9,350 3-pt MACE events over 8 years of follow-up. The overall results showed good performance with the environmental model for all three racial-ethnic groups, with C-statistics ranging from 0.69 to 0.77. The G models showed very modest prediction capabilities and similarly modest improvement in the combined GxE models. In conclusion, traditional risk factor modeling has been shown to be highly effective and, in the MVP experience, the additional impact of genetic or genetic interaction information was small.

Despite significant advances in the treatment and care of people with HIV (PWH), several challenges remain in our understanding of disease pathogenesis to improve patient care. HIV infection can modify the host epigenome and as such can impact disease progression, as well as the molecular processes driving non-AIDS comorbidities in PWH. Epigenetic epidemiologic studies including epigenome-wide association studies (EWAS) offer a unique set of tools to expand our understanding of HIV disease and to identify novel strategies applicable to treatment and diagnosis in this patient population. In this review, we summarize the current state of knowledge from epigenetic epidemiologic studies of PWH, identify the main challenges of this approach, and highlight future directions for the field. Emerging epigenetic epidemiologic studies of PWH can expand our understanding of HIV infection and health outcomes, improve scientific validity through collaboration and replication, and increase the coverage of diverse populations affected by the global HIV pandemic. Through this review, we hope to highlight the potential of EWAS as a tool for HIV research and to engage more investigators to explore its application to important research questions.