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Updated: Sep 13, 2025

Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
Published on: January 31, 2025
Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular
Jia-Hao Wang1, Shan-Shan Dong1, Wei Huang2
1Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, People's Republic of China.
Insights
This study identified 72 proteins causally linked to cardiovascular diseases (CVD) risk using proteome-wide association studies. These findings offer new insights into CVD mechanisms and potential therapeutic targets.
Area of Science:
- Genetics
- Proteomics
- Cardiovascular Medicine
Background:
- Cardiovascular diseases (CVD) are a leading global cause of death.
- Current CVD treatments are effective for only a limited number of patients.
- New therapeutic targets are needed to address the unmet needs in CVD treatment.
Purpose of the Study:
- To conduct the first proteome-wide association study (PWAS) for 26 CVDs.
- To identify novel protein targets for CVD treatment.
- To leverage a large-scale plasma proteomics dataset from the UK Biobank Pharma Proteomics Project (UKB-PPP).
Main Methods:
- Calculated SNP-protein weights using UKB-PPP data.
- Integrated weights with GWAS summary statistics for 26 CVDs (cardiac, venous, cerebrovascular).
- Employed the FUSION framework for PWAS and conducted replication in independent datasets.
Main Results:
- Identified 155 proteins associated with CVDs, with 72 showing causal association via Mendelian randomization.
- Discovered 33 novel proteins not previously implicated in CVD GWAS, including PROC for venous thromboembolism.
- Developed diagnostic models for 18 diseases, with 14 achieving AUC > 0.8, indicating strong diagnostic potential.
Conclusions:
- Identified 72 proteins with a causal influence on CVD risk.
- Provided new mechanistic insights into CVD pathogenesis.
- Highlighted promising protein targets for future CVD therapeutics.
Background:
Cardiovascular diseases (CVD) are the leading cause of global mortality, yet current treatments benefit only a subset of patients. To identify new potential treatment targets, we conducted the first proteome wide association study (PWAS) for 26 CVDs using plasma proteomics data from the largest cohort to date (53,022 individuals in the UK Biobank Pharma Proteomics Project (UKB-PPP)).
Methods And Results:
We calculated single nucleotide polymorphism (SNP)-protein weights using the UKB-PPP dataset and integrated these weights with genome-wide association study (GWAS) summary statistics for 26 CVDs across three categories (16 cardiac, 5 venous, and 5 cerebrovascular diseases) in up to 1,308,460 individuals. PWAS was performed using the Functional Summary-based Imputation (FUSION) framework to identify protein-disease associations. Replication was conducted in two independent human plasma proteomic datasets (comprising 7213 and 3301 participants, respectively). We identified 155 proteins associated with CVDs and further Mendelian randomization analysis revealed 72 proteins with evidence of a causal association. Of these, 26 out of 35 available proteins were validated. Notably, 33 of the 72 proteins were not previously implicated in GWAS of CVDs. For example, PROC was found to be associated with venous thromboembolism (P = 6.32 × 10-7). We further conducted longitudinal analyses using plasma proteomics data and peripheral blood mononuclear cells single cell RNA-seq data. The results showed that 90.63% (29/32) of the detected proteins exhibited stable plasma expression, and 18 genes displayed stable expression in at least one cell type, particularly in CD14+ monocytes. We also utilized these proteins to construct disease diagnostic models, and notably, models for 14 out of 18 diseases achieved an area under the curve (AUC) exceeding 0.8, indicating promising diagnostic potential.
Conclusions:
We identified 72 proteins that causally influence CVD risk, providing new mechanistic insights into CVD and may prove to be promising targets as CVD therapeutics.
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