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Proteome-wide Mendelian Randomization and Colocalization Nominate CD58, PARP1, and Immune Co-stimulatory Pathways as
Zheyi Wang1,2, Yize Sun3, Zetai Bai1,2
1Department of Neurology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
Introduction:
Multiple sclerosis (MS) is a chronic inflammatory disorder characterized by demyelination within the central nervous system. Emerging evidence suggests that plasma proteins may serve as genetically supported candidate targets, yet their underlying mechanisms in MS remain poorly understood. In this study, we applied proteome-wide Mendelian randomization (MR) to systematically identify plasma proteins that are causally associated with MS risk and to explore their potential biological roles and treatment implications.
Methods:
We performed a comprehensive proteome-wide MR analysis using cis-prioritized protein quantitative trait loci (pQTLs) as instruments. Plasma protein data came from two large-scale resources: the Icelandic deCODE study (4,907 proteins measured in 35,559 individuals with the SomaScan v4 platform) and the UK Biobank Pharma Proteomics Project (UKB-PPP, 2,940 proteins measured in 54,219 European-ancestry participants with the Olink platform). MS genomewide association study (GWAS) summary statistics were obtained from the International Multiple Sclerosis Genetics Consortium (IMSGC), UK Biobank, and FinnGen releases R9 and R10. After applying a stringent false discovery rate threshold (FDR < 0.05), we conducted meta-analysis, Bayesian colocalization, protein-protein interaction (PPI) network construction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also evaluated potential adverse effects of druggable proteins through a phenome-wide association study (PheWAS) across 2,409 phenotypes in FinnGen R10.
Results:
In the deCODE dataset, MR identified five plasma proteins causally linked to MS: PARP1, DNAJC27, and TNXB increased risk, whereas CD58 and STAT3 were protective. In the UKB-PPP dataset, ten proteins showed significant associations: CD58, AGER, TNF, and AIF1 as risk factors and CD40, FCRL1, GIMAP7, CD59, EVI5, and TNFRSF14 as protective. Colocalization analysis provided strong support for CD58 across multiple datasets and moderate-to-strong support for PGLYRP1, PARP1, CD40, FCRL1, and EVI5. GO and KEGG analyses indicated that these proteins are enriched in neuroinflammation, immune regulation, and metabolic pathways. The PPI network highlighted TNF, STAT3, CD40, CD58, and PARP1 as central hubs. PheWAS revealed eight significant phenotype associations, pointing to both therapeutic opportunities and possible off-target effects.
Discussion:
Our findings underscore the central importance of immune regulation and neuroinflammatory pathways in MS pathogenesis and nominate several genetically supported candidate targets that could guide future precision-medicine approaches. Nevertheless, these associations require rigorous functional validation and clinical trials before they can be translated into new therapies.
Conclusions:
This proteome-wide MR study identifies genetically supported plasma protein targets for MS, offering fresh mechanistic insights and potential therapeutic directions while emphasizing the need for further research to move from genetic association to clinical benefit.
