A Mendelian randomization-based approach to explore the relationship between leukocyte counts and breast cancer risk in European ethnic groups

Abstract

Exploring the potential association between peripheral blood leukocyte counts and breast cancer risk by Mendelian randomization (MR) analysis methods. Genetic data related to peripheral blood sorting counts of leukocytes were collected from a genome-wide association study by Blood Cell Consortium (BCX). Single nucleotide polymorphic loci predicting peripheral blood sorting counts of these leukocytes were selected as instrumental variables according to the correlation assumption, independence assumption and exclusivity assumption of MR. The data on breast cancer and its subtypes were obtained from Breast Cancer Association Consortium (BCAC) and FinnGen Consortium. In this study, the Inverse-Variance Weighted (IVW), Weighted Median, MR-Egger, Maximum Likelihood (ML), MR-PRESSO and Constrained Maximum Likelihood and Model Averaging (cML-MA) methods of random effects models were used for MR analysis. Cochran’s Q analysis, and MR-Egger intercept analysis were applied for sensitivity analysis. IVW and cML-MA were considered the primary analytical tools, and the results of the other 4 MRs were used as complementary and validation. The results suggest that there is no significant causal relationship between leukocyte count and breast cancer risk (IVW OR = 0.98 [95% CI: 0.93–1.03], p-value = 0.35; CML-MA OR = 1.01 [95% CI: 0.98–1.05], p-value = 0.51). In addition, we analyzed whether there was a potential correlation between the five main types of categorized leukocyte counts and different breast cancer subtypes. We did not find significant evidence to support a significant correlation between leukocyte counts and breast cancer subtypes.