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BACKGROUND: It remains unclear whether there is a racial disparity in the response to angiotensin inhibitors in patients with heart failure with reduced ejection fraction (HFrEF) and whether the role of genomic ancestry plays a part. Therefore, we compared survival rates associated with angiotensin inhibitors in patients with HFrEF by self-identified race and proportion of West African genomic ancestry. METHODS: Three datasets totaling 1153 and 1480 self-identified Black and White patients, respectively, with HFrEF were meta-analyzed (random effects model) for race-based analyses. One dataset had genomic data for ancestry analyses (416 and 369 self-identified Black and White patients, respectively). Cox proportional hazards regression, adjusted for propensity scores, assessed the association of angiotensin inhibitor exposure with all-cause mortality by self-identified race or proportion of West African genomic ancestry. RESULTS: In meta-analysis of self-identified race, adjusted hazard ratios (95% CI) for exposure to angiotensin inhibitors were similar in self-identified Black and White patients with HFrEF: 0.52 (0.31–0.85) P = 0.006 and 0.54 (0.42–0.71) P = 0.001, respectively. Results were similar when the proportion of West African genomic ancestry was > 80% or < 5%: 0.66 (0.34–1.25) P = 0.200 and 0.56 (0.26–1.23) P = 0.147, respectively. CONCLUSIONS: Among self-identified Black and White patients with HFrEF, reduction in all-cause mortality associated with exposure to angiotensin inhibitors was similar regardless of self-identified race or proportion of West African genomic ancestry.

Background: Recent advances in multi-marker platforms offer faster data generation, but the fidelity of these methods compared to the ELISA is not established. We tested the correlation and predictive performance of SOMAscan vs. ELISA methods for NTproBNP and ST2. Methods: Patients ≥ 18 years with heart failure and ejection fraction < 50% were enrolled. We tested the correlation between SOMA and ELISA for each biomarker and their association with outcomes. Results: There was good correlation of SOMA vs. ELISA for ST2 (ρ = 0.71) and excellent correlation for NTproBNP (ρ = 0.94). The two versions of both markers were not significantly different regarding survival association. The two ST2 assays and NTproBNP assays were similarly associated with all-cause mortality and cardiovascular mortality. These associations remained statistically significant when adjusted for MAGGIC risk score (all p < 0.05). Conclusion: SOMAscan quantifications of ST2 and NTproBNP correlate to ELISA versions and carry similar prognosis. Graphical abstract: [Figure not available: see fulltext.]

IMPORTANCEClinical epidemiological studies have found high rates of comorbidity between suicide attempts (SA) and opioid use disorder (OUD). However, the patterns of correlation and causation between them are still not clear due to psychiatric confounding.OBJECTIVETo investigate the pairwise associations and interrogate the potential bidirectional relationship between OUD and SA using genetically based methods.DESIGN, SETTING, AND PARTICIPANTSWe utilized raw phenotypes and genotypes from UK Biobank, and summary statistics from Million Veteran Program, Psychiatric Genomic Consortium, iPSYCH, and International Suicide Genetics Consortium. Statistical genetics tools were used to perform epidemiological association, genetic correlation, polygenic risk score prediction, and Mendelian randomizations (MR). Analyses were conducted to examine the OUD-SA relationship with and without controlling for psychiatric disease status (e.g., major depressive disorder [MDD]).MAIN OUTCOMES AND MEASURESOUD and SA with or without major psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, and alcohol use disorder).RESULTSStrong correlations between OUD and SA were observed at both phenotypic level (overall samples [OR=2.94,P=1.59 ×10−14]; non-psychiatric subgroup [OR=2.15,P=1.07 ×10−3]) and genetic level (r2=0.4 and 0.5 with or without conditioning on MDD). The higher genetic susceptibility to SA can increase the polygenic risk of OUD (OR=1.08, false discovery rate [FDR] =1.71 ×10−3), while the higher susceptibility to OUD can also increase the risk of SA (OR=1.09, FDR =1.73 ×10−6). However, predictive abilities for both were much weakened after controlling for influence of psychiatric diseases. A combination of different MR analyses suggested a possible causal association from SA to OUD (2-sample univariable MR: OR=1.14,P= 0.001; multivariable MR: OR=1.08,P= 0.001).CONCLUSIONS AND RELEVANCEThis study provided new genetic evidence underlying the strong OUD-SA comorbidity. While controlling for the influence of psychiatric diseases, there is still some clue on possible causal association between SA genetic liability and the risk for OUD. Future prevention strategy for each phenotype needs to take into consideration of screening for the other one.Key PointsQuestionDoes opioid use disorder (OUD) have a potentially causal role in the risk for suicide attempts (SA), or vice versa?FindingsIn this observational study with raw data from >150,000 UK Biobank samples and genome-wide association summary statistics from >600,000 individuals, positive phenotypic and genetic associations were observed between OUD and SA, whether or not controlling for major psychiatric disorders. Comprehensive Mendelian randomization analyses (one-sample and two-sample) suggested the genetic liability for SA was associated with increased risk for OUD. However, they were still underpowered to reveal the putative causal association from OUD to SA.MeaningThis genomics-based study supports a strong genetic association underlying the OUD-SA comorbidity. Though both phenotypes are intertwined with other psychiatric disorders, there also exists an independent bidirectional relationship between OUD and SA.

Background: Suppressor of tumorigenicity 2 (ST2) is a powerful marker of prognosis and treatment response in heart failure (HF), however, it is an enzyme-linked immunosorbent assay (ELISA) which may be cumbersome and costly. A turbidimetric immunoassay (TIA) that can run on common chemistry analyzers could overcome this. We studied a novel TIA for ST2, comparing it to commercial ST2 (ELISA). Methods: Patients age ≥ 18 years meeting Framingham definition for HF were enrolled in a prospective registry (Oct 2007 – March 2015) at Henry Ford Hospital and donated blood samples. Participants with reduced ejection fraction (

Baseline lung function is a standard diagnostic criterion used by clinicians to detect lung diseases. It is a complex trait significantly influenced by both genetics and environmental factors..., Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV1), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV1 on chromosome 12 in 867 African American children with asthma (P = 1.26 × 10−8, β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV1. Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with KITLG (KIT ligand, also known as SCF), and their minor alleles were associated with increased expression of the KITLG gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure (P = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV1, possibly mediated through KITLG, in African American children with asthma. This is the first study that has identified a genetic association between lung function and KITLG, which has established a role in orchestrating allergic inflammation in asthma.

BACKGROUND: Asthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma. METHODS: WGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician’s diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes. RESULTS: A genome-wide significant association was identified between baseline FEV(1)/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10(−8) in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10(−6)). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV(1) (P = 3.3 × 10(−3)), postbronchodilator (PB) FEV(1) (7.3 × 10(−3)), and PB FEV(1)/FVC ratio (P = 2.7 × 10(−3)). The identified baseline FEV(1)/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR. CONCLUSIONS: These findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

The lack of a reliable and easy-to-operate screening pipeline for disease-related noncoding RNA regulatory axis is a problem that needs to be solved urgently. To address this, we designed a hybrid pipeline, disease-related lncRNA–miRNA–mRNA regulatory axis prediction from multiomics (DLRAPom), to identify risk biomarkers and disease-related lncRNA–miRNA–mRNA regulatory axes by adding a novel machine learning model on the basis of conventional analysis and combining experimental validation. The pipeline consists of four parts, including selecting hub biomarkers by conventional bioinformatics analysis, discovering the most essential protein-coding biomarkers by a novel machine learning model, extracting the key lncRNA–miRNA–mRNA axis and validating experimentally. Our study is the first one to propose a new pipeline predicting the interactions between lncRNA and miRNA and mRNA by combining WGCNA and XGBoost. Compared with the methods reported previously, we developed an Optimized XGBoost model to reduce the degree of overfitting in multiomics data, thereby improving the generalization ability of the overall model for the integrated analysis of multiomics data. With applications to gestational diabetes mellitus (GDM), we predicted nine risk protein-coding biomarkers and some potential lncRNA–miRNA–mRNA regulatory axes, which all correlated with GDM. In those regulatory axes, the MALAT1/hsa-miR-144-3p/IRS1 axis was predicted to be the key axis and was identified as being associated with GDM for the first time. In short, as a flexible pipeline, DLRAPom can contribute to molecular pathogenesis research of diseases, effectively predicting potential disease-related noncoding RNA regulatory networks and providing promising candidates for functional research on disease pathogenesis.

Aims The HERMES (HEart failure Molecular Epidemiology for Therapeutic targets) consortium aims to identify the genomic and molecular basis of heart failure.Methods and results The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of >1.10 for common variants (allele frequency > 0.05) and >1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 x 10(-8) under an additive genetic model.Conclusions HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

We analyzed whole genome and RNA sequencing data from 2,733 African American and Hispanic/Latino children to explore ancestry- and heterozygosity-related differences in the genetic architecture of whole blood gene expression. We found that heritability of gene expression significantly increases with greater proportion of African genetic ancestry and decreases with higher levels of Indigenous American ancestry, consistent with a relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of statistically significant ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most of the anc-eQTLs (89%) were driven by population differences in allele frequency, demonstrating the importance of measuring gene expression across multiple populations. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait pairs using models trained in our admixed population than models trained in GTEx. Our study highlights the importance of large and ancestrally diverse genomic studies for enabling new discoveries of complex trait architecture and reducing disparities.

Background Elevated resting heart rate (HR) is a risk factor and therapeutic target in patients with heart failure (HF) and reduced ejection fraction (HFrEF). Previous studies indicate a genetic contribution to HR in population samples but there is little data in patients with HFrEF. Methods Patients who met Framingham criteria for HF and had an ejection fraction

Background: It remains unclear whether the plasma proteome adds value to established predictors in heart failure (HF) with reduced ejection fraction (HFrEF). We sought to derive and validate a plasma proteomic risk score (PRS) for survival in patients with HFrEF (HFrEF-PRS). Methods: Patients meeting Framingham criteria for HF with EF Results: Participants’ mean age was 68 years, 48% identified as Black, 35% were female, and 296 deaths occurred. In derivation (n=681), 128 proteins associated with mortality, 8 comprising the optimized HFrEF-PRS. In validation (n=336) the HFrEF-PRS associated with mortality (hazard ratio, 2.27 [95% CI, 1.84–2.82], P =6.3×10 -14 ), Kaplan-Meier curves differed significantly between HFrEF-PRS quartiles ( P =2.2×10 -6 ), and it remained significant after adjustment for clinical score and NT-proBNP (hazard ratio, 1.37 [95% CI, 1.05–1.79], P =0.021). The HFrEF-PRS improved metrics of risk stratification (C statistic change, 0.009, P =0.612; integrated discrimination index, 0.041, P =0.010; net reclassification index=0.391, P =0.078; median improvement in risk score=0.039, P =0.016) and associated with cardiovascular death and HF phenotypes (eg, 6-minute walk distance, EF change). Most HFrEF-PRS proteins had little known connection to HFrEF. Conclusions: A plasma multiprotein score improved risk stratification in patients with HFrEF and identified novel candidates.

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Background: β-Blockers (BBs) are mainstay therapy for heart failure with reduced ejection fraction. However, individual patient responses to BB vary, which may be partially due to genetic variation. The goal of this study was to derive and validate the first polygenic response predictor (PRP) for BB survival benefit in heart failure with reduced ejection fraction patients. Methods: Derivation and validation analyses were performed in n=1436 total HF patients of European descent and with ejection fraction Results: Five-fold cross-validation summaries out to 1000 single-nucleotide polymorphisms identified optimal prediction with a 44 single-nucleotide polymorphism score and cutoff at the 30th percentile. In validation testing (n=1188), greater BB exposure was associated with reduced all-cause mortality in patients with low PRP score (n=251; hazard ratio, 0.19 [95% CI, 0.04–0.51]; P =0.0075) but not high PRP score (n=937; hazard ratio, 0.84 [95% CI, 0.53–1.3]; P =0.448)—a difference that was statistically significant ( P interaction, 0.0235). Results were consistent regardless of atrial fibrillation, ejection fraction (≤40% versus 41%–50%), or when examining cardiovascular death. Conclusions: Among patients of European ancestry with heart failure with reduced ejection fraction, a PRP distinguished patients who derived substantial survival benefit from BB exposure from a larger group that did not. Additional work is needed to prospectively test clinical utility and to develop PRPs for other population groups and other medications.

Background: Exercise has shown benefit in patients with systolic heart failure, including in the clinical trial Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION). There is heterogeneity in who derives benefit from exercise, and the biologic mechanisms of favorable response to exercise in systolic heart failure are not well understood. Hypothesis: Genetic variation is an underlying factor influencing heterogeneity in response to exercise in patients with systolic heart failure. Methods: The HF-ACTION trial randomized individuals with systolic heart failure (left ventricular ejection fraction Results: Five loci met genome-wide significance in the European ancestry analyses, 5 loci in the African ancestry, and 8 in the meta-analyses. The two most significantly associated loci across both additive and dominant meta-analysis models were rs111577308 located in the histone acetylation for transcription elongator complex 3 gene ( ELP3, p=1.212x10 -9 ) and rs75444785 located in the phosphodiesterase 4D gene ( PDE4D , p=1.565x10 -9 ). ELP3 is responsible for histone modifications related to DNA transcription factor complexes, and PDE4D is involved in cyclic AMP cell signaling. In silico analysis of these loci showed that they are in linkage with regions associated with skeletal muscle and peripheral vascular disease phenotypes. Conclusions: Using a genome-wide association study in a well-phenotyped clinical trial of exercise in systolic heart failure, we found common genetic variants in genes involved in DNA transcription histone modification and cyclic AMP cell signaling that are associated with a more favorable response to exercise.

Introduction: Definitive evidence for the efficacy of angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) in Black Americans with heart failure and reduced ejection fraction (HFrEF) is deficient. It is based on retrospective data, and there were very few Black patients enrolled in the landmark ACEI/ARB trials. Moreover, self-reported race does not reliably reflect genomic ancestry, particularly in Black Americans. Therefore, the objective of this study was to assess ACEI/ARB associated survival benefit in a prospective cohort of HFrEF patients, by both self-reported race and proportion of African genomic ancestry. Methods: Insured HFrEF patients (n=989) were enrolled in a prospective genomic registry from 2007-2015. ACEI/ARB exposure (ACEI/ARBexp) was calculated from pharmacy claims as % target exposure, and the proportion of African ancestry was determined from genome-wide array data. Cox proportional hazards regression with time-dependent ACEI/ARBexp and adjusted for established risk factors tested the association with all-cause mortality by self-reported race and proportion of African ancestry (≤5% vs. ≥80%). Results: Overall, 36% of patients were female, 52% self-identified as Black, average age was 68±12 years, and the mean follow-up was 3.0 years. Self-reported Black patients were significantly younger, more were women, more often had hypertension and non-ischemic etiology, had lower LVEF, and mean proportion African genomic ancestry of 84%. ACEI/ARBexp was similar among self-reported Blacks and Whites (52% and 55%; p=0.228), as was mortality (121 [24%] and 121 [25%]; p=0.526). ACEI/ARBexp was associated with similar survival benefit in all groups (Table 1). Conclusions: In this prospective registry, estimates of survival benefit associated with ACEI/ARB use in HFrEF patients appear similar regardless of self-reported race or African genomic ancestry.

Rationale: The 17q12-21.1 locus is one of the most highly replicated genetic associations with asthma. Individuals of African descent have lower linkage disequilibrium in this region, which could facilitate identifying causal variants.Objectives: To identify functional variants at 17q12-21.1 associated with early-onset asthma among African American individuals.Methods: We evaluated African American participants from SAPPHIRE (Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity) (n = 1,940), SAGE II (Study of African Americans, Asthma, Genes and Environment) (n = 885), and GCPD-A (Study of the Genetic Causes of Complex Pediatric Disorders-Asthma) (n = 2,805). Associations with asthma onset at ages under 5 years were meta-analyzed across cohorts. The lead signal was reevaluated considering haplotypes informed by genetic ancestry (i.e., African vs. European). Both an expression-quantitative trait locus analysis and a phenome-wide association study were performed on the lead variant.Measurements and Main Results: The meta-analyzed results from SAPPHIRE, SAGE II, and the GCPD-A identified rs11078928 as the top association for early-onset asthma. A haplotype analysis suggested that the asthma association partitioned most closely with the rs11078928 genotype. Genetic ancestry did not appear to influence the effect of this variant. In the expression-quantitative trait locus analysis, rs11078928 was related to alternative splicing of GSDMB (gasdermin-B) transcripts. The phenome-wide association study of rs11078928 suggested that this variant was predominantly associated with asthma and asthma-associated symptoms.Conclusions: A splice-acceptor polymorphism appears to be a causal variant for asthma at the 17q12-21.1 locus. This variant appears to have the same magnitude of effect in individuals of African and European descent.

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins. ispartof: NEUROBIOLOGY OF AGING vol:92 ispartof: location:United States status: published

Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV1), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole genome sequencing data from the National Heart, Lung, and Blood Institute TOPMed project, we identified a novel genetic association with FEV1on chromosome 12 in 867 African American children with asthma (p = 1.26 × 10−8, β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded 9 variants as the most likely candidates responsible for the association with FEV1. Hi-C data and eQTL analysis demonstrated that these variants physically interacted withKITLG (aka SCF)and their minor alleles were associated with increased expression ofKITLGgene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year SO2exposure (p = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV1, possibly mediated throughKITLG, in African American children with asthma.

Author(s): Cocco, Maxwell P; White, Evan; Xiao, Shujie; Hu, Donglei; Mak, Angel; Sleiman, Patrick; Yang, Mao; Bobbitt, Kevin R; Gui, Hongsheng; Levin, Albert M; Hochstadt, Samantha; Whitehouse, Kyle; Rynkowski, Dean; Barczak, Andrea J; Abecasis, Goncalo; Blackwell, Thomas W; Kang, Hyun Min; Nickerson, Deborah A; Germer, Soren; Ding, Jun; Lanfear, David E; Gilliland, Frank; Gauderman, W James; Kumar, Rajesh; Erle, David J; Martinez, Fernando; Hakonarson, Hakon; Burchard, Esteban G; Williams, L Keoki | Abstract: BackgroundMitochondria support critical cellular functions, such as energy production through oxidative phosphorylation, regulation of reactive oxygen species, apoptosis, and calcium homeostasis.ObjectiveGiven the heightened level of cellular activity in patients with asthma, we sought to determine whether mitochondrial DNA (mtDNA) copy number measured in peripheral blood differed between individuals with and without asthma.MethodsWhole genome sequence data was generated as part of the Trans-Omics for Precision Medicine (TOPMed) Program on participants from the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) and the Study of African Americans, Asthma, Genes, a Environment II (SAGE II). We restricted our analysis to individuals who self-identified as African American (3,651 asthma cases and 1,344 controls). Mitochondrial copy number was estimated using the sequencing read depth ratio for the mitochondrial and nuclear genomes. Respiratory complex expression was assessed using RNA-sequencing.ResultsAverage mitochondrial copy number was significantly higher among individuals with asthma when compared with controls (SAPPHIRE: 218.60 vs. 200.47, Pl0.001; SAGE II: 235.99 vs. 223.07, Pl0.001). Asthma status was significantly associated with mitochondrial copy number after accounting for potential explanatory variables, such as participant age, sex, leukocyte counts, and mitochondrial haplogroup. Despite the consistent relationship between asthma status and mitochondrial copy number, the latter was not associated with time-to-exacerbation or patient-reported asthma control. Mitochondrial respiratory complex gene expression was disproportionately lower in individuals with asthma when compared with individuals without asthma and other protein-encoding genes.ConclusionsWe observed a robust association between asthma and higher mitochondrial copy number. Asthma having an effect on mitochondria function was also supported by lower respiratory complex gene expression in this group.

PURPOSE: Protein kinase C alpha (gene:PRKCA) is a key regulator of cardiac contractility. Two genetic variants have recently been discovered to regulate PRKCA expression in failing human heart tissue (rs9909004 [T→C] and rs9303504 [C→G]). The association of those variants with clinical outcomes in patients with heart failure (HF), and their interaction with HF drug efficacy, is unknown. METHODS: Patients with HF in a prospective registry starting in 2007 were genotyped by whole genome array (n=951). The primary outcome was all-cause mortality. Cox proportional hazards models adjusted for established clinical risk factors and genomic ancestry tested the independent association of rs9909004 or rs9303504 and the variant interactions with cornerstone HF pharmacotherapies (beta-blockers or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers) in additive genetic models. RESULTS: The minor allele of rs9909004, but not rs9303504, was independently associated with decreased risk for all-cause mortality: adjusted HR = 0.81 (95% CI = 0.67 – 0.98) p = 0.032. The variants did not significantly interact with mortality benefit associated with cornerstone HF pharmacotherapies (p > 0.1 for all). CONCLUSIONS: A recently discovered cardiac-specific regulatory variant for PRKCA (rs9909004) was independently associated with decreased risk for all-cause mortality in patients with HF. The variant did not interact with mortality benefit associated with cornerstone HF pharmacotherapies.

Background Whether the plasma proteome can predict the course of heart failure (HF) and has incremental value to established predictors is uncertain. Methods Patients meeting Framingham HF criteria with history of reduced ejection fraction (n=1017) were prospectively enrolled in a registry and donated fasting blood samples. Plasma underwent analysis on the SOMAscan proteomic discovery platform, quantifying 4789 proteins using standard assay and quality controls. Patients were randomly divided into derivation (n=681) and validation (n=336) cohorts. We derived a proteomic risk score (PRS) in the derivation cohort using Lasso-penalized Cox regression and then tested it in the validation cohort. Both models were adjusted for an establish HF clinical risk score (MAGGIC) and NTproBNP. We assessed risk stratification improvement in the validation cohort by comparing models with and without PRS using the model C statistic, continuous net reclassification index (NRI), integrated discrimination index (IDI), and the median improvement in risk score (MIRS). Results Overall 47.5% of patients were African American, 35.2% were female, mean ejection fraction was 34.8%, and average age was 67.9 years. After median follow-up of 3.6 years, there were 296 deaths (194 in derivation and 102 in validation). Optimized modeling defined a 32 protein PRS (hazard ratio [HR] 2.33, p Methods Variables Estimate 95% CI P Validation Testing MAGGIC 1.06 1.027, 1.092 2.84E-04 NTproBNP 1.84 1.430, 2.359 1.88E-06 PRS 1.19 1.001, 1.408 4.87E-02 Risk Stratification Assessment C-statistic improvement 0.012 −0.076, 0.101 8.30E-01 IDI 0.034 0.007, 0.095 Conclusion A plasma multi-protein predictive score can improve risk stratification in HF patients on top of a validated clinical score and NTproBNP. Additional investigation is warranted to define mechanisms underlying individual proteins and explore proteomic clinical applications.

Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown.1 Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations was associated with both hematologic cancer incidence2–4 and coronary heart disease prevalence.5 Somatic mutations with leukemogenic potential may confer selective cellular advantages leading to clonal expansion, a phenomenon termed ‘Clonal Hematopoiesis of Indeterminate Potential’ (CHIP).6 Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico-informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer. Aggregates of rare germline loss-of-function variants in CHEK2, a DNA damage repair gene, predisposed to CHIP acquisition. Overall, we observe that germline genetic variation altering hematopoietic stem cell function and the fidelity of DNA-damage repair increase the likelihood of somatic mutations leading to CHIP.

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2–4 and coronary heart disease5—this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

Background: Risk stratification is critical in heart failure (HF) and the Meta-Analysis Global Group in Chronic HF (MAGGIC) score is a validated tool derived from ~40,000 patients. However, few of these patients self-identified as black, raising uncertainty regarding performance in blacks with HF. Methods and Results: This study analyzed a racially diverse group of 4046 patients (1646 black and 2400 white) from a single center from 2007 to 2015. Baseline characteristics were collected to tabulate MAGGIC score and test its discrimination and calibration within race groups. The primary end point was all-cause mortality. Death was detected using system records and the social security death master file. Discrimination was tested using Cox models of MAGGIC score stratified by race, and combined analysis including MAGGIC, race, and MAGGIC×race. Calibration was assessed using linear regression models and plots of observed versus predicted data. Overall, 901 (21%) patients died during 1-year follow-up. MAGGIC score discrimination was similar in both race groups in terms of C statistic (0.707±0.027 versus 0.725±0.014, for black versus white; P =0.556) and the hazard ratio (HR) per MAGGIC point was 1.12 in black patients (95% CI, 1.10–1.14) and 1.13 in white patients (95% CI, 1.12–1.14). Race was a significant correlate of survival, with better survival in black patients compared with white (HR, 0.66; 95% CI, 0.56–0.78), but the interaction of MAGGIC×race was not significant (β=−0.013; P =0.16), and adding race to the model did not improve discrimination (C statistic for MAGGIC versus MAGGIC+race, 0.721 versus 0.722; P =0.79). In calibration testing, the slope was not significantly different from 1 in either group, but the groups differed from each other, and it was closer to unity among black patients (0.94 versus 1.4; P =0.004). Conclusions: These data support the use of the MAGGIC score to risk stratify black patients with HF.