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Identifying Potential Therapeutic Targets for Calcific Aortic Valve Disease Through Multi-Omics Approaches

GSE267580 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2026/05/01 Platform GPL20795
Summary
Calcific aortic valve disease (CAVD) is a degenerative disease characterized by aortic valve fibrosis and calcification with no medications available for treatment. We conducted the Mendelian randomization (MR) and summary data-based Mendelian randomization (SMR) combined with transcriptomic analysis to identify potential therapeutic targets for CAVD.Protein quantitative trait loci (pQTL) from two whole plasma protein databases (deCODE and UKBppp) were utilized as the exposure. Three large CAVD cohorts from Finland (9,870 cases and 402,311 controls), the UK (3,552 cases and 425,855 controls) and France (3,163 cases and 6,531 controls) served as the outcome. Colocalization analysis was performed to determine whether CAVD and target proteins shared common causal SNPs. Single-cell and bulk RNA sequencing was further used to detect the cell-type specific and differential expression of target proteins. Drug prediction and molecular docking was applied to discover potential medications. 15 plasma proteins were identified via MR and SMR analysis with 6 strongly supported via colocalization analysis. Among them, ANGPTL4 and ITGAV was validated in the replication CAVD cohorts from the UK or France. Meanwhile, the protein levels of ANGPTL4 and ITGAV was upregulated in valvular interstitial cells (VICs). Molecular docking suggested a stable binding between the target proteins and medications.The proteome-wide MR analysis discovered 6 proteins associated with the progression of CAVD and provided novel perspective in the etiology and drug target screening strategy.
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Direct links to NCBI, no account and no request form: the whole study as GSE267580_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1111889 and SRA study SRP507955. Searching any of these in the dataset finder brings you back here.

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