Mendelian randomization analysis reveals causal relationships between circulating cell traits and renal disorders.

Purpose: The aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders.

Methods: We applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a  < 0.05.

Results: Our results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10-2.06,  = 0.033,  = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13-1.98,  = 0.027,  = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06-1.43,  = 0.041,  = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08-1.36,  = 0.007,  = 0.001). No evidence of pleiotropy was determined.

Conclusion: Our findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.