| Title: | Systematic identification of therapeutic targets for coronary artery calcification: an integrated transcriptomic and proteomic Mendelian randomization |
| Journal: | Frontiers in Cardiovascular Medicine |
| Published: | 25 Oct 2024 |
| DOI: | https://doi.org/10.3389/fcvm.2024.1419440 |
| URL: | http://dx.doi.org/10.3389/fcvm.2024.1419440 |
Publication 13375
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Abstract
Coronary artery calcification (CAC) is associated with an increased risk of mortality and cardiovascular events. However, none therapeutic drugs have been proven effective for CAC treatment. The objective of this study was to identify potential therapeutic targets for CAC through the utilization of Mendelian randomization (MR) and colocalization analysis. The expression quantitative trait loci (eQTLs) of 16,943 genes from the eQTLGen consortium and protein quantitative trait loci (pQTLs) of 4,412 proteins from a plasma proteome were utilized as genetic instruments. Genetic associations with CAC were derived from a GWAS meta-analysis of 26,909 individuals. The MR and colocalization analysis were utilized to identify potential target genes. A total of 671 genes were found to be significantly associated with the risk of CAC based on transcriptomic MR analysis at a false discovery rate <0.05, while proteomic MR analysis identified 15 genes with significant associations with CAC at the same threshold. With robust evidence from colocalization analysis, we observed positive associations between CWF19L2, JARID2, and MANBA and the risk of CAC, while KLB exhibited an inverse association. In summary, our study identified 23 potential therapeutic targets for CAC. Further downstream analysis revealed IGFBP3, ABCC6, ULK3, DOT1L, KLB and AMH as promising candidates for repurposing in the treatment of CAC. The integrated MR analysis of transcriptomic and proteomic data identified multiple potential drug targets for the treatment of CAC. ULK3, DOT1L, and AMH were recognized as novel targets for drug repurposing for CAC and deserve further investigation.</p>
4 Authors
- Lihong Chen
- Xiaoqi Ye
- Yan Li
- Xingwu Ran
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