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Updated: Jan 16, 2026

In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Identification of therapeutic targets for rheumatic heart valve disease based on systematic druggable genome wide
Wei-Hua Shi1, Jing-Chang Zhang, Zhi-Tao Xie
1Department of Cardiology, Third Affiliated Hospital of Guangxi Medical University, Nanning, China.
Abstract:
Rheumatic heart valve disease (RHD) is a chronic immune valvular heart disease caused by rheumatic fever, primarily affecting the mitral and aortic valves. It often leads to atrial fibrillation, heart failure, and even premature death. Currently, there are no effective therapeutic drugs available, partially due to the lack of appropriate therapeutic targets. To identify therapeutic targets for RHD, we employed a 2-sample Mendelian randomization approach integrating identified druggable genomics to assess the causal effect of expression quantitative trait loci of druggable genes in the blood on RHD. Subsequently, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses on the druggable genes. We used colocalization analysis to test whether the risk of RHD and gene expression are driven by common single nucleotide polymorphisms. Additionally, the Comparative Toxicogenomics Database was utilized to evaluate the impact of environmental exposures on druggable genes, and molecular docking was conducted to identify potential small molecule interactions. A total of 6888 druggable genes were collected. After conducting various Mendelian randomization analyses and applying false discovery rate correction, we identified 13 drug targets for RHD: TFRC, FMO4, CA2, HLA-DPB2, OXTR, GRAMD1B, PNP, HLA-DPB1, leukocyte immunoglobulin-like receptor B1 (LILRB1), TUBB, LGR6, F13A1, and LPL. These targets were found to be closely related to immune regulation and inflammatory response in Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Bayesian colocalization analysis established an interaction between LILRB1 and RHD, with a PP.H4 >0.5, LILRB1 demonstrated a protective effect in RHD (OR = 0.833, 95% confidence interval, 0.699-0.993). Comparative Toxicogenomics Database analysis identified several small molecules influencing LILRB1 mRNA expression, with lipopolysaccharide showing excellent binding affinity in molecular docking with LILRB1 against available structural data for drugs and proteins. Based on a cohort of European ancestry, this study reveals 13 potential therapeutic targets for RHD, with LILRB1 showing particularly promising prospects as a future therapeutic target for RHD.
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