Plasma proteome-wide Mendelian randomization reveals the association of extracellular matrix proteins with abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAAs have not been thoroughly studied. We used genetic causal inference...

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Published inJVS-vascular science Vol. 6; p. 100290
Main Authors Khodursky, Samuel, Yuan, Shuai, Spin, Joshua M., Tsao, Philip S., Levin, Michael G., Damrauer, Scott M.
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LanguageEnglish
Published United States Elsevier Inc 01.01.2025
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Abstract Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAAs have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAAs. Causal inference was performed using two-sample Mendelian randomization (MR). For AAAs, we utilized recently published summary statistics from a multi-population genome-wide association meta-analysis including 39,221 individuals with and 1,086,107 individuals without AAAs from 14 cohorts. We used protein quantitative trait loci (protein quantitative trait loci) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2783 plasma proteins for possible causal effects on AAAs using two-sample MR with inverse variance weighting with common sensitivity analyses. MR identified 90 plasma proteins associated with AAAs at a false discovery rate <0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were proteins such as PCSK9 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.2-1.4; P < 1e-10), LTBP4 (OR, 3.4; 95% CI, 2.6-4.6; P < 1e-10), and COL6A3 (OR, 0.6; 95% CI, 0.5-0.7; P < 1e-6). Gene Ontology analysis revealed enrichment of proteins (extracellular matrix; OR, 7.8; P < 1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. Colocalization analysis showed that an aortic expression quantitative trait locus for COL6A3, and a splicing quantitative trait locus for LTBP4 colocalized with their respective plasma pQTLs and AAA signals. Our results highlight proteins and pathways with potential causal effects on AAAs, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting extracellular matrix proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAAs. Here, we used plasma proteome-wide Mendelian randomization to identify 90 proteins with possible causal associations with abdominal aortic aneurysms. We found that these proteins were enriched for proteins typically found in extracellular matrix and the aorta. Finally, we linked aortic expression changes in LTBP4 and COL6A3 to changes in their plasma levels, and increased liability for abdominal aortic aneurysms. These findings lay the groundwork for potential clinical applications, including new therapeutic targets and blood-based biomarker screening tests.
AbstractList Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAAs have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAAs. Causal inference was performed using two-sample Mendelian randomization (MR). For AAAs, we utilized recently published summary statistics from a multi-population genome-wide association meta-analysis including 39,221 individuals with and 1,086,107 individuals without AAAs from 14 cohorts. We used protein quantitative trait loci (protein quantitative trait loci) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2783 plasma proteins for possible causal effects on AAAs using two-sample MR with inverse variance weighting with common sensitivity analyses. MR identified 90 plasma proteins associated with AAAs at a false discovery rate <0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were proteins such as PCSK9 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.2-1.4; P < 1e-10), LTBP4 (OR, 3.4; 95% CI, 2.6-4.6; P < 1e-10), and COL6A3 (OR, 0.6; 95% CI, 0.5-0.7; P < 1e-6). Gene Ontology analysis revealed enrichment of proteins (extracellular matrix; OR, 7.8; P < 1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. Colocalization analysis showed that an aortic expression quantitative trait locus for COL6A3, and a splicing quantitative trait locus for LTBP4 colocalized with their respective plasma pQTLs and AAA signals. Our results highlight proteins and pathways with potential causal effects on AAAs, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting extracellular matrix proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAAs. Here, we used plasma proteome-wide Mendelian randomization to identify 90 proteins with possible causal associations with abdominal aortic aneurysms. We found that these proteins were enriched for proteins typically found in extracellular matrix and the aorta. Finally, we linked aortic expression changes in LTBP4 and COL6A3 to changes in their plasma levels, and increased liability for abdominal aortic aneurysms. These findings lay the groundwork for potential clinical applications, including new therapeutic targets and blood-based biomarker screening tests.
Here, we used plasma proteome-wide Mendelian randomization to identify 90 proteins with possible causal associations with abdominal aortic aneurysms. We found that these proteins were enriched for proteins typically found in extracellular matrix and the aorta. Finally, we linked aortic expression changes in LTBP4 and COL6A3 to changes in their plasma levels, and increased liability for abdominal aortic aneurysms. These findings lay the groundwork for potential clinical applications, including new therapeutic targets and blood-based biomarker screening tests.
Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAAs have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAAs. Causal inference was performed using two-sample Mendelian randomization (MR). For AAAs, we utilized recently published summary statistics from a multi-population genome-wide association meta-analysis including 39,221 individuals with and 1,086,107 individuals without AAAs from 14 cohorts. We used protein quantitative trait loci (protein quantitative trait loci) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2783 plasma proteins for possible causal effects on AAAs using two-sample MR with inverse variance weighting with common sensitivity analyses. MR identified 90 plasma proteins associated with AAAs at a false discovery rate <0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were proteins such as PCSK9 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.2-1.4; < 1e-10), LTBP4 (OR, 3.4; 95% CI, 2.6-4.6; < 1e-10), and COL6A3 (OR, 0.6; 95% CI, 0.5-0.7; < 1e-6). Gene Ontology analysis revealed enrichment of proteins (extracellular matrix; OR, 7.8; < 1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. Colocalization analysis showed that an aortic expression quantitative trait locus for COL6A3, and a splicing quantitative trait locus for LTBP4 colocalized with their respective plasma pQTLs and AAA signals. Our results highlight proteins and pathways with potential causal effects on AAAs, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting extracellular matrix proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAAs.
Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAAs have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAAs.ObjectiveAbdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAAs have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAAs.Causal inference was performed using two-sample Mendelian randomization (MR). For AAAs, we utilized recently published summary statistics from a multi-population genome-wide association meta-analysis including 39,221 individuals with and 1,086,107 individuals without AAAs from 14 cohorts. We used protein quantitative trait loci (protein quantitative trait loci) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2783 plasma proteins for possible causal effects on AAAs using two-sample MR with inverse variance weighting with common sensitivity analyses.MethodsCausal inference was performed using two-sample Mendelian randomization (MR). For AAAs, we utilized recently published summary statistics from a multi-population genome-wide association meta-analysis including 39,221 individuals with and 1,086,107 individuals without AAAs from 14 cohorts. We used protein quantitative trait loci (protein quantitative trait loci) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2783 plasma proteins for possible causal effects on AAAs using two-sample MR with inverse variance weighting with common sensitivity analyses.MR identified 90 plasma proteins associated with AAAs at a false discovery rate <0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were proteins such as PCSK9 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.2-1.4; P < 1e-10), LTBP4 (OR, 3.4; 95% CI, 2.6-4.6; P < 1e-10), and COL6A3 (OR, 0.6; 95% CI, 0.5-0.7; P < 1e-6). Gene Ontology analysis revealed enrichment of proteins (extracellular matrix; OR, 7.8; P < 1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. Colocalization analysis showed that an aortic expression quantitative trait locus for COL6A3, and a splicing quantitative trait locus for LTBP4 colocalized with their respective plasma pQTLs and AAA signals.ResultsMR identified 90 plasma proteins associated with AAAs at a false discovery rate <0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were proteins such as PCSK9 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.2-1.4; P < 1e-10), LTBP4 (OR, 3.4; 95% CI, 2.6-4.6; P < 1e-10), and COL6A3 (OR, 0.6; 95% CI, 0.5-0.7; P < 1e-6). Gene Ontology analysis revealed enrichment of proteins (extracellular matrix; OR, 7.8; P < 1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. Colocalization analysis showed that an aortic expression quantitative trait locus for COL6A3, and a splicing quantitative trait locus for LTBP4 colocalized with their respective plasma pQTLs and AAA signals.Our results highlight proteins and pathways with potential causal effects on AAAs, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting extracellular matrix proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAAs.ConclusionsOur results highlight proteins and pathways with potential causal effects on AAAs, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting extracellular matrix proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAAs.
ArticleNumber 100290
Author Yuan, Shuai
Damrauer, Scott M.
Spin, Joshua M.
Levin, Michael G.
Tsao, Philip S.
Khodursky, Samuel
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Keywords LTBP4
AAA
COL6A3
Mendelian randomization
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Snippet Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous risk loci, many potentially...
Here, we used plasma proteome-wide Mendelian randomization to identify 90 proteins with possible causal associations with abdominal aortic aneurysms. We found...
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SourceType Open Access Repository
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StartPage 100290
SubjectTerms AAA
COL6A3
ECM
LTBP4
Mendelian randomization
Title Plasma proteome-wide Mendelian randomization reveals the association of extracellular matrix proteins with abdominal aortic aneurysm
URI https://dx.doi.org/10.1016/j.jvssci.2025.100290
https://www.ncbi.nlm.nih.gov/pubmed/40607238
https://www.proquest.com/docview/3226718753
https://pubmed.ncbi.nlm.nih.gov/PMC12221610
Volume 6
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