Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases
Abstract 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 f...
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BMC
2025-08-01
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| Series: | Cardiovascular Diabetology |
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| Online Access: | https://doi.org/10.1186/s12933-025-02847-w |
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| author | Jia-Hao Wang Shan-Shan Dong Wei Huang Hao-An Wang Shao-Shan Liu Xiaoyi Ma Ren-Jie Zhu Wei Shi Hao Wu Ke Yu Tian-Pei Zhang Cong-Ru Wang Yan Guo Hanzhong Xue Tie-Lin Yang |
| author_facet | Jia-Hao Wang Shan-Shan Dong Wei Huang Hao-An Wang Shao-Shan Liu Xiaoyi Ma Ren-Jie Zhu Wei Shi Hao Wu Ke Yu Tian-Pei Zhang Cong-Ru Wang Yan Guo Hanzhong Xue Tie-Lin Yang |
| author_sort | Jia-Hao Wang |
| collection | DOAJ |
| description | Abstract 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. Graphical abstract |
| format | Article |
| id | doaj-art-8d1dd8d18f084ff9868a9b34e7651943 |
| institution | DOAJ |
| issn | 1475-2840 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMC |
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| series | Cardiovascular Diabetology |
| spelling | doaj-art-8d1dd8d18f084ff9868a9b34e76519432025-08-20T03:04:14ZengBMCCardiovascular Diabetology1475-28402025-08-0124111510.1186/s12933-025-02847-wBlood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseasesJia-Hao Wang0Shan-Shan Dong1Wei Huang2Hao-An Wang3Shao-Shan Liu4Xiaoyi Ma5Ren-Jie Zhu6Wei Shi7Hao Wu8Ke Yu9Tian-Pei Zhang10Cong-Ru Wang11Yan Guo12Hanzhong Xue13Tie-Lin Yang14Key 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 UniversityKey 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 UniversityDepartment of Trauma Surgery, Honghui Hospital, Xi’an Jiaotong UniversityKey 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 UniversityKey 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 UniversityDepartment of Biostatistics, School of Public Health and Health Professions, The State University of New York at BuffaloKey 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 UniversityKey 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 UniversityKey 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 UniversityKey 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 UniversityKey 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 UniversityKey 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 UniversityKey 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 UniversityDepartment of Trauma Surgery, Honghui Hospital, Xi’an Jiaotong UniversityKey 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 UniversityAbstract 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. Graphical abstracthttps://doi.org/10.1186/s12933-025-02847-wCVDHuman blood plasma proteomesCausal proteinsPWAS |
| spellingShingle | Jia-Hao Wang Shan-Shan Dong Wei Huang Hao-An Wang Shao-Shan Liu Xiaoyi Ma Ren-Jie Zhu Wei Shi Hao Wu Ke Yu Tian-Pei Zhang Cong-Ru Wang Yan Guo Hanzhong Xue Tie-Lin Yang Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases Cardiovascular Diabetology CVD Human blood plasma proteomes Causal proteins PWAS |
| title | Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases |
| title_full | Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases |
| title_fullStr | Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases |
| title_full_unstemmed | Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases |
| title_short | Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases |
| title_sort | blood plasma proteome wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases |
| topic | CVD Human blood plasma proteomes Causal proteins PWAS |
| url | https://doi.org/10.1186/s12933-025-02847-w |
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