Causal relationship between 731 immune cells and the risk of diabetic nephropathy: a two‑sample bidirectional...

Previous observational studies have indicated associations between various immune cells and diabetic nephropathy (DN). However, the causality remains unclear. We aimed to further evaluate the causal association between immune cells and DN using bidirectional two-sample Mendelian randomization (MR) analysis.

The DN data were retrieved from the IEU OpenGWAS Project database, while the data for 731 immune cells were sourced from GWAS summary statistics by Orru ̀ et al. The investigation into the causal relationship between immune cells and DN employed the inverse variance weighted (IVW), weighted median (WME), and MR-Egger methods. The stability and reliability of the findings underwent evaluation through Cochran's Q test, MR-Egger intercept's P-value, MR-PRESSO, and Leave-One-Out (LOO) method.

The IVW estimates suggested a positive causal effect of CD25 on IgD-CD38dim B cell, CD25 on naive-mature B cell, CD127 on granulocyte, SSC-A on HLA DR + Natural Killer, HLA DR on plasmacytoid Dendritic Cell, and HLA DR on Dendritic Cell on DN. Conversely, the abundance of Myeloid Dendritic Cell, CD62L- Dendritic Cell %Dendritic Cell, CD86+ myeloid Dendritic Cell %Dendritic Cell, CD14- CD16-, CX3CR1 on CD14- CD16-, and SSC-A on CD4+ T cell had negative causal effects on DN. However, after correcting the P value for significant causality results using the FDR method, it was concluded that only Myeloid Dendritic Cells had a causal relationship with DN (FDR-p = 0.041), while the other immune cells showed no significant association with DN, so their relationship was suggestive. The results were stable with no observed horizontal pleiotropy and heterogeneity. Reverse MR analysis indicated no causal relationship between DN and the increased risk of positively identified immune cells.

This study provides an initial insight into the genetic perspective of the causal relationship between immune cells and DN. It establishes a crucial theoretical foundation for future endeavors in precision medicine and individualized treatment.