MR was performed using summary statistics from two sources: the INTERVAL protein-quantitative trait loci (pQTL) Study (1,890 circulating proteins and 3301 healthy individuals) and the Breast Cancer Association Consortium (BCAC; 106,278 invasive cases and 91,477 controls). The inverse-variance (IVW) weighted method was used as the main analysis to evaluate the associations between genetically predicted proteins and risk of five different intrinsic-like breast cancer subtypes and the weighted median MR method, the Egger regression, the MR-PRESSO, and the MRLocus method were performed as secondary analysis.
We identified 98 unique proteins significantly associated with risk of one or more subtypes (Benjamini-Hochberg false discovery rate < 0.05, Figure 1). Among them, 51 were potentially specific to luminal A-like subtype, 14 to luminal B/Her2-negative-like, 11 to triple negative, 3 to luminal B-like, and 2 to Her2-enriched-like breast cancer (n total = 81). Associations for three proteins (ICAM1, PLA2R1, and TXNDC12) showed evident heterogeneity across the subtypes. For example, higher levels of genetically predicted ICAM1 (per unit of increase) were associated with an increased risk of luminal B/HER2-negative-like cancer (OR = 1.06, 95% CI = 1.03 - 1.08, BH-FDR = 2.43x10-4) while inversely associated with triple negative breast cancer with borderline significance (OR = 0.97, 95% CI = 0.95 - 0.99, BH-FDR = 0.065, P heterogeneity < 0.005).
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