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Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

BackgroundRare pathogenic variants in cardiomyopathy (CM) genes can predispose to cardiac remodeling or fibrosis. We studied the carrier status for such variants in adults without clinical cardiovascular disease (CVD) in whom cardiac MRI (CMR)-derived measures of myocardial fibrosis were obtained in the Multi-Ethnic Study of Atherosclerosis (MESA).ObjectivesTo identify CM-associated pathogenic variants and assess their relative prevalence in participants with extensive myocardial fibrosis by CMR.MethodsMESA whole-genome sequencing data was evaluated to capture variants in CM-associated genes (n = 82). Coding variants with a frequency of

We present new models and methods for the posterior drift problem where the regression function in the target domain is modelled as a linear adjustment, on an appropriate scale, of that in the source domain, and study the theoretical properties of our proposed estimators in the binary classification problem. The core idea of our model inherits the simplicity and the usefulness of generalized linear models and accelerated failure time models from the classical statistics literature. Our approach is shown to be flexible and applicable in a variety of statistical settings, and can be adopted for transfer learning problems in various domains including epidemiology, genetics and biomedicine. As concrete applications, we illustrate the power of our approach (i) through mortality prediction for British Asians by borrowing strength from similar data from the larger pool of British Caucasians, using the UK Biobank data, and (ii) in overcoming a spurious correlation present in the source domain of the Waterbirds dataset. [ABSTRACT FROM AUTHOR]

Background: Copy number aberrations (CNAs) in cancer affect disease outcomes by regulating molecular phenotypes, such as gene expressions, that drive important biological processes. To gain comprehensive insights into molecular biomarkers for cancer, it is critical to identify key groups of CNAs, the associated gene modules, regulatory modules, and their downstream effect on outcomes. Methods: In this paper, we demonstrate an innovative use of sparse canonical correlation analysis (sCCA) to effectively identify the ensemble of CNAs, and gene modules in the context of binary and censored disease endpoints. Our approach detects potentially orthogonal gene expression modules which are highly correlated with sets of CNA and then identifies the genes within these modules that are associated with the outcome. Results: Analyzing clinical and genomic data on 1,904 breast cancer patients from the METABRIC study, we found 14 gene modules to be regulated by groups of proximally located CNA sites. We validated this finding using an independent set of 1,077 breast invasive carcinoma samples from The Cancer Genome Atlas (TCGA). Our analysis of 7 clinical endpoints identified several novel and interpretable regulatory associations, highlighting the role of CNAs in key biological pathways and processes for breast cancer. Genes significantly associated with the outcomes were enriched for early estrogen response pathway, DNA repair pathways as well as targets of transcription factors such as E2F4, MYC, and ETS1 that have recognized roles in tumor characteristics and survival. Subsequent meta-analysis across the endpoints further identified several genes through the aggregation of weaker associations. Conclusions: Our findings suggest that sCCA analysis can aggregate weaker associations to identify interpretable and important genes, modules, and clinically consequential pathways. [ABSTRACT FROM AUTHOR]

Objective: Many studies suggest a strong familial component to fibromyalgia (FM). However, those studies have nearly all been confined to individuals with primary FM, i.e., FM without any other accompanying disorder. The current 2011 and 2016 criteria for diagnosing FM construct a score using a combination of the number of painful body sites and the severity of somatic symptoms (FM score). This study was undertaken to estimate the genetic heritability of the FM score across sex and age groups to identify subgroups of individuals with greater heritability, which may help in the design of future genetic studies. Methods: We collected data on 26,749 individuals of European ancestry undergoing elective surgery at the University of Michigan (Michigan Genomics Initiative study). We estimated the single‐nucleotide polymorphism–based heritability of FM score by age and sex categories using genome‐wide association study data and a linear mixed‐effects model. Results: Overall, the FM score had an estimated heritability of 13.9% (SE 2.9%) (P = 1.6 × 10−7). Estimated FM score heritability was highest in individuals ≤50 years of age (23.5%; SE 7.9%) (P = 3.0 ×10−4) and lowest in individuals >60 years of age (7.5%; SE 8.1%) (P = 0.41). These patterns remained the same when we analyzed FM as a case–control phenotype. Even though women had an ~30% higher average FM score than men across age categories, FM score heritability did not differ significantly by sex. Conclusion: Younger individuals appear to have a much stronger genetic component to the FM score than older individuals. Older individuals may be more likely to have what was previously called "secondary FM." Regardless of the cause, these results have implications for future genetic studies of FM and associated conditions. [ABSTRACT FROM AUTHOR]

Heart failure is a major public health problem affecting over 23 million people worldwide. In this study, we present the results of a large scale meta-analysis of heart failure GWAS and replication in a comparable sized cohort to identify one known and two novel loci associated with heart failure. Heart failure sub-phenotyping shows that a new locus in chromosome 1 is associated with left ventricular adverse remodeling and clinical heart failure, in response to different initial cardiac muscle insults. Functional characterization and fine-mapping of that locus reveal a putative causal variant in a cardiac muscle specific regulatory region activated during cardiomyocyte differentiation that binds to the ACTN2 gene, a crucial structural protein inside the cardiac sarcolemma (Hi-C interaction p-value = 0.00002). Genomeediting in human embryonic stem cell-derived cardiomyocytes confirms the influence of the identified regulatory region in the expression of ACTN2. Our findings extend our understanding of biological mechanisms underlying heart failure. [ABSTRACT FROM AUTHOR]

Background: Rare pathogenic variants in cardiomyopathy (CM) genes can predispose to cardiac remodeling or fibrosis. We studied the carrier status for such variants in adults without clinical cardiovascular disease (CVD) in whom cardiac MRI (CMR)-derived measures of myocardial fibrosis were obtained in the Multi-Ethnic Study of Atherosclerosis (MESA)., Objectives: To identify CM-associated pathogenic variants and assess their relative prevalence in participants with extensive myocardial fibrosis by CMR., Methods: MESA whole-genome sequencing data was evaluated to capture variants in CM-associated genes ( n = 82). Coding variants with a frequency of <0.1% in gnomAD and 1,000 Genomes Project databases and damaging/deleterious effects based on in-silico scoring tools were assessed by ClinVar database and ACMG curation guidelines for evidence of pathogenicity. Cases were participants with high myocardial fibrosis defined as highest quartile of extracellular volume (ECV) or native T1 time in T1-mapping CMR and controls were the remainder of participants., Results: A total of 1,135 MESA participants had available genetic data and phenotypic measures and were free of clinical CVD at the time of CMR. We identified 6,349 rare variants in CM-associated genes in the overall MESA population, of which six pathogenic/likely pathogenic (P/LP) variants were present in the phenotyped subpopulation. The genes harboring P/LP variants in the case group were MYH7, CRYAB , and SCN5A . The prevalence of P/LP rare variants in cases was higher than controls (5 in 420 [1.1%] vs. 1 in 715 [0.1%], p = 0.03). We identified two MYBPC3 Variants of Unknown Significance (VUS)s with borderline pathogenicity in the case group. The left ventricle (LV) volume, mass, ejection fraction (EF), and longitudinal and circumferential strain in participants with the variants were not different compared to the overall cohort., Conclusions: We observed a higher prevalence of rare potentially pathogenic CM associated genetic variants in participants with significant myocardial fibrosis quantified in CMR as compared to controls without significant fibrosis. No cardiac structural or functional differences were found between participants with or without P/LP variants., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with one of the authors with the authors WP, KT, SR, JR, and JL., (Copyright © 2022 Shabani, Dutta, Ambale-Venkatesh, Post, Taylor, Rich, Wu, Pereira, Shah, Chatterjee, Rotter, Arking and Lima.)

Background: Proteomic profiling may allow identification of plasma proteins that associate with subsequent changesin kidney function, elucidating biologic processes underlying the development and progression of CKD., Methods: We quantified the association between 4877 plasma proteins and a composite outcome of ESKD or decline in eGFR by ≥50% among 9406 participants in the Atherosclerosis Risk in Communities (ARIC) Study (visit 3; mean age, 60 years) who were followed for a median of 14.4 years. We performed separate analyses for these proteins in a subset of 4378 participants (visit 5), who were followed at a later time point, for a median of 4.4 years. For validation, we evaluated proteins with significant associations (false discovery rate <5%) in both time periods in 3249 participants in the Chronic Renal Insufficiency Cohort (CRIC) and 703 participants in the African American Study of Kidney Disease and Hypertension (AASK). We also compared the genetic determinants of protein levels with those from a meta-analysis genome-wide association study of eGFR., Results: In models adjusted for multiple covariates, including baseline eGFR and albuminuria, we identified 13 distinct proteins that were significantly associated with the composite end point in both time periods, including TNF receptor superfamily members 1A and 1B, trefoil factor 3, and β -trace protein. Of these proteins, 12 were also significantly associated in CRIC, and nine were significantly associated in AASK. Higher levels of each protein associated with higher risk of 50% eGFR decline or ESKD. We found genetic evidence for a causal role for one protein, lectin mannose-binding 2 protein (LMAN2)., Conclusions: Large-scale proteomic analysis identified both known and novel proteomic risk factors for eGFR decline., (Copyright © 2021 by the American Society of Nephrology.)