Protein Level Ratios as Causal Factors in Primary Sclerosing Cholangitis: Insights from a Two-Sample Mendelian Randomization Study

Background Primary Sclerosing Cholangitis (PSC) currently lacks effective biomarkers and therapeutic targets. The study of protein level ratios may offer new insights for addressing this challenge. Methods The summary statistics for PSC in this study was sourced from the International PSC Study Group, encompassing 2,871 PSC patients and 12,019 control participants. Protein quantitative trait loci data were sourced from the Olink proteomics platform, facilitating the identification of 2,821 significant protein level ratios. Furthermore, we conducted a Mendelian Randomization analysis to explore the causal relationship between the two factors, applying a stringent Bonferroni correction threshold of 1.77E-5. The primary analytical method employed was the Inverse Variance Weighted (IVW) approach, which was further reinforced by comprehensive heterogeneity analyses, horizontal pleiotropy testing, outlier detection, and “leave-one-out” sensitivity analysis. Results We identified a positive causal association between the protein level ratios of Low-Density Lipoprotein Receptor-Related Protein 11/ Nectin Cell Adhesion Molecule 2 (IVW odds ratio (OR): 1.84; 95% confidence interval (CI): 1.40–2.41, P = 1.07E-05) and Tumor Necrosis Factor Receptor Superfamily Member 13B/ Tumor Necrosis Factor Receptor Superfamily Member 9 (IVW OR: 2.72, 95% CI: 1.77–4.19, P = 5.56E-06) and the risk of PSC. Conversely, the protein level ratios of Lymphotoxin Alpha/ Lymphotoxin Beta Receptor (IVW OR: 0.50, 95% CI: 0.43–0.58, P = 7.58E-20) and Nectin Cell Adhesion Molecule 2/ Tumor Necrosis Factor Receptor Superfamily Member 14 (IVW OR: 0.55, 95% CI: 0.44–0.69, P = 2.17E-07) were found to have an inverse causal relationship with the risk of PSC. Significantly, all analyses demonstrated a lack of horizontal pleiotropy and heterogeneity. Conclusion These results identify potential new biomarkers for PSC diagnosis and suggest targets for treatment, laying the groundwork for future drug development.