Genetics and Epigenetics of Cardiovascular Disease

National Human Genome Research Institute

Investigators

Linked publications, trials & patents

Abstract

The Cardiovascular Disease Section (CDS) has hired an experienced molecular biologist to extend its ability to pursue functional analyses that builds upon its statistical findings and provide plausible biological explanations for the signals uncovered so far. CDS has also strengthened its Bioinformatics analytical capacity by hiring a bioinformatician to process, maintain and analyze the large datasets generated by its ongoing sequencing and genotyping of GENE-FORECAST, MH-GRID samples and to maintain data acquired through collaborations. Given the multiple ongoing omics assays (Multi-ethnic array genotyping, whole-genome sequencing, mRNA and microRNA sequencing, methylation sequencing, metabolome, microbiome and telomere assay), CDS has developed robust computer infrastructure and sequencing pipelines to support analyses through actively computing, imputing, and simulating genomic and phenotypic models developed by dimensionality reduction techniques to gain useful insights from large genomic data sets. This computational infrastructure is now being transferred to a cloud-based platform to benefit from storage and computing elasticity in the cloud and integrate standardized pipelines and algorithms developed by the scientific community for cloud computing. CDS has also developed an analytical framework which uses both conventional statistical and Machine Learning techniques to integrates those various data sources and provide a more comprehensive picture of the traits of interest and the interplay between the underlying determinants. The framework makes use of data already collected or projected to be collected by CDS as part of MH-GRID, GENE-FORECAST. This analytical framework is being used in the current projects listed below. (1) Transcriptome and genetic study of Metabolic Healthy Obesity Building on its previous published findings and in collaboration with Dr Rotimi group, CDS is now undertaking functional analyses to investigate micro-RNA regulating the genes identified in the earlier project. (2) Social Disadvantage, Gene Expression and Depressive Symptoms in African American from MH-GRID This project expands earlier published work and is an effort to combine several proxies of socioeconomic status, into one score, for a more comprehensive look into the influence of psycho-social factors on the blood transcriptome. (3) Exome-wide association study (EWAS) of 8 cardiometabolic traits Findings from the MH-GRID whole-exome sequencing data have now been replicated in an African descent subset of the UK Biobank cohort. (4) Transcriptome-informed polygenic risk score of reduced kidney function in African American with hypertension Using a novel approach that leverages gene expression data to identify eQTL to include in the SNP-set of score, CDS was able to develop a score that predicts eGFR in the MHGRID data. The score was validated in a sample set from the REGARDS study. (5) Transcriptome-informed polygenic risk score of hypertension in African American Following the same approach that worked to develop a polygenic risk score for kidney function, CDS developed a score that predicts hypertension status in MHGRID and REGARDS.