Potential drug targets for multiple sclerosis identified through Mendelian randomization analysis

Abstract

Multiple sclerosis is a complex autoimmune disease, and several therapies for multiple sclerosis have been developed and widely used. However, existing medications for multiple sclerosis were far from satisfactory due to their failure to suppress relapses and alleviate disease progression. Novel drug targets for multiple sclerosis prevention are still needed. We performed Mendelian randomization to explore potential drug targets for multiple sclerosis using summary statistics from the International Multiple Sclerosis Genetics Consortium (nCase = 47 429, nControl = 68 374) and further replicated in UK Biobank (nCase = 1356, nControl = 395 209) and FinnGen cohorts (nCase = 1326, nControl = 359 815). Genetic instruments for 734 plasma and 154 CSF proteins were obtained from recently published genome-wide association studies. The reverse causality detection using bidirectional Mendelian randomization analysis and Steiger filtering, Bayesian co-localization, and phenotype scanning that searched previously reported genetic variant-trait associations were implemented to consolidate the Mendelian randomization findings further. In addition, the protein-protein interaction network was performed to reveal potential associations among proteins and/or present multiple sclerosis medications. At Bonferroni significance (P < 5.63 × 10-5), Mendelian randomization analysis revealed six protein-multiple sclerosis pairs. In plasma, per standard deviation increase in FCRL3, TYMP and AHSG had a protective effect. Odds ratios for the proteins above were 0.83 (95% CI, 0.79-0.89), 0.59 (95% CI, 0.48-0.71) and 0.88 (95% CI, 0.83-0.94), respectively. In CSF, per 10-fold increase in MMEL1 (OR, 5.03; 95% CI, 3.42-7.41) increased the risk of multiple sclerosis, while SLAMF7 (OR, 0.42; 95% CI, 0.29-0.60) and CD5L (OR, 0.30; 95%CI, 0.18-0.52) decreased the risk. None of the six proteins had reverse causality. Bayesian co-localization suggested that FCRL3 [coloc.abf-posterior probability of hypothesis 4 (PPH4) = 0.889], TYMP (coloc.susie-PPH4 = 0.896), AHSG (coloc.abf-PPH4 = 0.957, coloc.susie-PPH4 = 0.973), MMEL1 (coloc.abf-PPH4 = 0.930) and SLAMF7 (coloc.abf-PPH4 = 0.947) shared the same variant with multiple sclerosis. FCRL3, TYMP and SLAMF7 interacted with target proteins of current multiple sclerosis medications. MMEL1 was replicated in both UK Biobank and FinnGen cohorts. Our integrative analysis suggested that genetically determined levels of circulating FCRL3, TYMP, AHSG, CSF MMEL1 and SLAMF7 had causal effects on multiple sclerosis risk. These findings suggested those five proteins might be promising drug targets for multiple sclerosis and warrant further clinical investigation, especially FCRL3 and SLAMF7.

Keywords: Mendelian randomization; drug target; multiple sclerosis.

Figure 1

Study design for identification of plasma and CSF proteins causally associated with MS.

Figure 2

MR results for plasma and CSF proteins and the risk of MS. Volcano plots of the MR results for (A) 734 plasma and (B) 154 CSF proteins on the risk of MS. A and B show MR analysis with Wald ratio or inverse variance weighted method on plasma and CSF proteins on the risk of MS, respectively. OR for increased risk of MS were expressed as per SD increase in plasma protein levels and per 10-fold increase in CSF protein levels. Dashed horizontal black line corresponded to P = 5.63 × 10⁻⁵ (0.05/888). ln = natural logarithm; PVE = proportion of variance explained.

Figure 3

Interaction between current MS medications targets and identified potential drug targets.

Figure 4

External validation of the causal relationship between six potential causal proteins and MS MR analysis on the causal relationship of six potential causal proteins on MS using data from (A) the UK Biobank and (B) the FinnGen cohort. OR for increased risk of MS were expressed as per SD increase in plasma protein levels and per 10-fold increase in CSF protein levels.