Abstract
Background: The link between white blood cells (WBC) and depression has been studied, but the causal relationship remains unclear. This study aimed to elucidate the potential bidirectional causal links between six specific WBC count features and depression using a two-sample Mendelian randomization (MR) analysis, leveraging summary statistics from genome-wide association studies (GWAS). Method: The dataset on depression (N = 406,986) was sourced from the FinnGen database, while the dataset on WBC (N = 563,085) was obtained from a combined dataset of Blood Cell Consortium (BCX) and UK Biobank. The MR analyses employed include inverse variance weighted (IVW), MR-Egger, weighted median, contamination mixture method (conmix), and constrained maximum likelihood-based Mendelian randomization (cML-MA). A threshold p < 0.05 after false discovery rate (FDR) correction was set as the criterion for causality based on IVW. Results: Reverse MR analysis indicated a causal relationship where depression leads to an increase in overall WBC count (IVW beta = 0.031, p = 0.015, p (FDR) = 0.044) and specifically in basophil count (IVW beta = 0.038, p = 0.006, p (FDR) = 0.038), with a marginally significant impact on lymphocyte count (beta = 0.029, p = 0.036, p (FDR) = 0.071). Furthermore, forward MR analysis suggested a potential role of monocyte count in decreasing depression risk (p = 0.028), though this association did not retain statistical significance after FDR correction. Conclusion: These findings suggest that depression may causally influence the immune system by elevating overall WBC and basophil counts, with a marginally significant increase in lymphocyte levels. Conversely, higher monocyte count might confer some protection against depression, albeit with less statistial certainty. This study provides novel insights into the complex interplay between depression and immune function.