Clinical and Translational DiscoveryGenomicsPeer-reviewed journal article
Investigating variant and expression of CVD genes associated phenotypes among high-risk Heart Failure patients
Zeeshan AhmediD, Saman ZeeshaniD, Nicholas Persaud, William DeGroatiD, Habiba AbdelhalimiD, Bruce T. LiangiD
Abstract
Cardiovascular disease (CVD) is a leading cause of premature mortality in the US and the world. CVD comprises of several complex and mostly heritable conditions, which range from myocardial infarction to congenital heart disease. Here, we report our findings from an integrative analysis of gene expression, disease-causing gene variants, and associated phenotypes among CVD populations, with a focus on high-risk Heart Failure (HF) patients. We built a cohort using electronic health records (EHR) of consented patients with available samples, and then performed high-throughput whole-genome and RNA sequencing (RNA-seq) of key genes responsible for HF and other CVD pathologies. We also incorporated a translational aspect to our study by integrating genomics findings with patient medical records. This involved linking ICD-10 codes with our gene expression and variant data to identify associations with HF and other CVDs. Our in-depth gene expression analysis revealed differentially expressed genes associated with HF (41 genes) and other CVDs (23 genes). Furthermore, a variant analysis of whole-genome sequence data of CVD patients identified genes with altered gene expression (FLNA, CST3, LGALS3, and HBA1) with functional and nonfunctional mutations in these genes. Our study highlights the importance of an integrative approach that leverages gene expression, genetic mutations, and clinical data that will allow the prioritization of key driver genes for complex diseases to improve personalized healthcare.
- organism: human
- assay: whole-genome sequencing
- assay: bulk RNA-seq
- research focus: variant calling
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 7
- FWCI
- 1.16
- Field percentile
- top 23%
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