Introduction:
Effective treatment for acute kidney disease (AKI) is currently not available. Mendelian randomization (MR) approach has been widely used to discover novel therapeutic targets, and here we conducted a systematic druggable genome-wide MR to explore the therapeutic targets for AKI.
Methods:
We firstly acquired druggable genes of blood expression quantitative trait loci (eQTLs), and conducted a comprehensive analysis to assess the causal relationship of targets on AKI involving two-sample Mendelian randomization (MR, for mRNA), summary-based MR (SMR, for mRNA), and colocalization analysis (for coding genes). Phenome-wide MR (PheWAS) analysis, bulk RNA sequencing (RNA-seq) analysis, single-cell RNA sequencing analysis (scRNA-seq), candidate drugs prediction, and Schrodinger molecular docking were performed to provide valuable perspective for targeting drugs development and investigating biological mechanisms.
Results:
Fifteen druggable genes were identified to have causal associations with AKI risk (FDR <0.05, PSMR < 0.05), of which six targets (PDIA6, GRIK4, MBNL1, CARM1, LRPAP1, and TNFRSF14) showed significant changes in their transcriptional levels in human AKI samples compared to healthy controls (P <0.05). Our results further suggested that genetical inhibition of MNBL1 had a significant association with a lower risk of AKI after validation by co-localization analysis. GSVA analysis indicated that MNBL1 overexpression may be involved in adipocytokine signalling pathway, RIG-I-like receptor signalling pathway, apoptosis, and JAK-STAT signalling pathway (P <0.05, for all). In addition, the expression of MBNL1 in AKI showed a positive correlation with resting memory CD4 T cells (r = 0.586, P = 0.00614), but negative associations with plasma cells, CD8+ T cells and regulatory T cells (P < 0.05, for all). Further PheWAS revealed no potential side effects of treatments targeting MNBL1.
Conclusions:
Our study provides genetic evidence supporting the potential effects of targeting MBNL1 for AKI treatment, which may be useful for prioritizing drug development.
I have no potential conflict of interest to disclose.
I did not use generative AI and AI-assisted technologies in the writing process.