Excel · study · 2026
Identifying Potential Therapeutic Targets for Calcific Aortic Valve Disease Through Multi-Omics Approaches
Listed in NCBI GEO
Calcific aortic valve disease (CAVD) is a degenerative disease characterized by aortic valve fibrosis and calcification with no medications available for treatment.
Description
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.
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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.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE267nnn/GSE267580 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267580 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1111889 ncbi.nlm.nih.gov/bioproject/PRJNA1111889 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Disease 75% · RNA sequencing 75% · Sequencing 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE267580 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:rna-seq | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:sequencing | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |