Plasma proteomics reveals the potential causal impact of extracellular matrix proteins on abdominal aortic aneurysm.

Background: Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous associated loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAA have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAA. Methods: Causal inference was performed using two-sample Mendelian randomization (MR). For AAA, we utilized recently published summary statistics from a multi-population genome-wide association (GWAS) meta-analysis including 39,221 individuals with, and 1,086,107 individuals without AAA from 14 cohorts. We used protein quantitative trait loci (pQTLs) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2,783 plasma proteins for possible causal effects on AAA using two-sample MR with inverse variance weighting and common sensitivity analyses to evaluate the MR assumptions. Bayesian colocalization and gene ontology (GO) enrichment analyses provided additional insights. Results: MR identified 90 plasma proteins associated with AAA at FDR<0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were previously experimentally validated proteins such as PCSK9 (OR 1.3; 95%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). GO analysis revealed enrichment of proteins found in extracellular matrix (ECM, 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. We then investigated whether variants responsible for expression changes in the aorta also influenced plasma levels and AAA risk. Colocalization analysis showed that an aortic expression quantitative trait locus (eQTL) for COL6A3, and a splicing quantitative trait locus (sQTL) for LTBP4 colocalized with their respective plasma pQTLs and AAA signals (posterior probabilities 0.84 and 0.89, respectively). Conclusions: Our results highlight proteins and pathways with potential causal effects on AAA, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting ECM proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAA.