Bidirectional Mendelian Randomization analysis of iron status and uremia: no evidence of a causal relationship

Abstract

Iron status and uremia have been linked, but the causality remains ambiguous. This bidirectional study aimed to explore the causal association between genetically predicted iron status and uremia. Utilizing summary data from genome-wide association studies (GWAS) of iron status and uremia, a two-sample Mendelian Randomization (MR) design was employed. Iron status was assessed through serum iron (SI), serum ferritin (SF), total iron-binding capacity (TIBC), and transferrin saturation (TS), while uremia included renal failure and dialysis. The primary analysis was conducted using the Inverse Variance Weighted (IVW) method. Additional MR evaluation included the weighted median, weighted mode, simple mode, and MR-Egger regression methods. Sensitivity analysis included MR-Egger for pleiotropy, MR-PRESSO for detecting outliers, Cochran’s Q test for heterogeneity, and leave-one-out analysis for robustness. Genetically determined iron status did not have a causal effect on the risk of uremia (renal failure or dialysis). The primary IVW results indicated no statistically significant relationship between iron status and uremia (all p > 0.05). Consistent results were found through various methods. Similarly, there were no significant causal effects of uremia on iron status (all p > 0.05). Heterogeneity was observed in some associations, but pleiotropy was generally not evident. This bidirectional MR study provides no evidence for a causal relationship between genetically predicted iron status and the risk of uremia. These findings challenge prior observational associations and highlight the need for further mechanistic and interventional studies to elucidate the complex interplay between iron metabolism and kidney disease.

Keywords

• Chronic kidney disease (CKD)
• uremia
• iron metabolism disorders
• genetic predisposition to disease
• Mendelian Randomization analysis