The Supplementary Materials Identifying Druggable Targets in Ovulatory Dysfunction-related Infertility: An Integrative Mendelian Randomization and pQTL Association Study

Figure S1 presents the results of a leave-one-out sensitivity analysis performed for the genetic instruments (SNPs) associated with the five proteins investigated. This analysis systematically examines the influence of individual SNPs by iteratively removing one SNP from the analysis and recalculating the causal estimate. The results show that the beta coefficients for all outcomes were consistently close to zero, indicating a negligible effect from any single SNP. This high degree of consistency across all iterations demonstrates that the overall findings are robust and not driven by any influential individual genetic variant.
Table S1 provides a detailed breakdown of the 4,479 protein-coding genes (approximately 22% of the 20,300 annotated in Ensembl v.73) that were classified as drug-targetable or potentially drug-targetable. The table categorizes these genes into a three-tiered classification system, specifying the genes belonging to each tier. This inventory forms a foundational resource for identifying and prioritizing genes with the highest potential for therapeutic intervention.
Table S2 details the first of two pQTL datasets integrated in this study, sourced from Zheng et al. This dataset comprises 738 cis-pQTLs (genetic variants located near the genes they regulate) which are associated with the plasma levels of 734 distinct proteins. This resource served as the primary genetic instrument set for the initial identification and prioritization of druggable genes in the subsequent Mendelian Randomization and analysis pipeline.