Potential drug targets for Neuromyelitis optica spectrum disorders (NMOSD): A Mendelian randomization analysis

Abstract

Background Certain peripheral proteins are involved in the development of Neuromyelitis optica spectrum disorders (NMOSD), such as IL-6, complement proteins, and MHC class II molecules. However, the roles of other new protein biomarkers are unclear. Current NMOSD treatments (e.g., intravenous pulse methylprednisolone, or satralizumab for IL-6 receptor inhibition) can only manage symptoms, necessitating the identification of new drug targets to treat NMOSD. The objective of this study is to identify potential drug targets for NMOSD through Mendelian randomization (MR) analysis, thereby addressing the limitations of current treatments and providing better clinical options for patients. Methods NMOSD potential drug targets were evaluated via MR. Data was obtained from a genome-wide association study (GWAS) with 132 individuals with AQP4-IgG-positive NMOSD and 1244 controls. Genetic instruments for plasma and cerebrospinal fluid (CSF) proteins were identified. Sensitivity analyses were conducted using Bayesian co-localization, reverse causality testing and phenotype scanning. Additionally, a comparison and analysis of protein-protein interactions (PPI) were conducted to identify potential causal proteins. The implications of these findings were further explored by evaluating existing NMOSD drugs and their respective targets. Results Four proteins were identified at the FDR correction via MR analysis (p < 0.05). Higher levels of PF4V1 (OR = 0.47; 95% CI, 0.29–0.78; p = 3.39 × 10−3) and FAM3B (OR = 0.12; 95% CI, 0.03–0.45; p = 1.65 × 10−3) were associated with a reduced risk of NMOSD, whereas elevated SERPINA1 (OR = 2.28; 95% CI, 1.29–4.04; p= 4.71 × 10−3) and CLEC11A (OR = 13.45; 95% CI, 1.29–4.04; p = 4.71 × 10−3) were related to an increased risk of NMOSD. Bayesian co-localization showed that the protein-related genes shared the same mutation as NMOSD (all PPH4>0.80). Reverse causality testing showed no evidence of NMOSD-driven protein changes (all p > 0.05). PPI analysis revealed SERPINA1 interacts with PF4V1 (combined score = 0.72). Drug evaluation identified Mercaptoethanol and Ferrous gluconate as repurposing candidates. Conclusion Increased levels of plasma CLEC11A and SERPINA1 are correlated with an elevated risk of NMOSD, whereas elevated levels of plasma PF4V1 and CSF FAM3B are associated with a decreased risk of NMOSD. The opposing effects of risk or protective proteins suggest synergistic targeting could improve efficacy beyond current immunosuppressive regimens. Nonetheless, clinical trials are required to confirm the findings.