Genetic-Proteomic Integration Identifies Predictive Plasma Proteins for Multiple Sclerosis - Summary - MDSpire
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Integration of Genetic and Proteomic Data Reveals Predictive Plasma Biomarkers for Multiple Sclerosis

  • By

  • Yuan Ding

  • Dylan Hamitouche

  • Simon Thebault

  • Patrick Kearns

  • Ahmed Abdelhak

  • Adil Harroud

  • May 22, 2026

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Objective:

To identify plasma proteins causally implicated in multiple sclerosis (MS) using an integrated genetic-proteomic approach.

Approach:
  • Methodology: Utilized Mendelian randomization and colocalization to analyze 2,545 protein measurements from 3 cohorts, totaling 80,824 individuals, and assessed their association with MS in an independent set of 14,802 cases and 26,703 controls.
Key Findings:
  • Nominated 39 causal proteins associated with MS risk.
  • Validated predictive value of these proteins in individuals diagnosed with MS up to 15 years prior.
  • Identified DKKL1 as a candidate with protective effects on MS risk and severity.
  • Improved fine-mapping resolution by over 10-fold and identified novel MS risk loci.
Interpretation:

The findings refine genetic factors and pathways involved in MS onset and highlight protein biomarkers that may enhance early risk stratification and inform targeted therapies.

Limitations:
  • Discordance across proteomic platforms remains unresolved.
  • Prediagnostic validation has not been performed.
  • Relevance of identified proteins to disease severity is unclear.
Conclusion:

The integrated approach provides insights into causal proteins and genetic factors related to MS, potentially aiding in early detection and therapeutic strategies.

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