Drug repurposing opportunities for chronic kidney disease

Abstract

The development of targeted drugs for the early prevention and management of chronic kidney disease (CKD) is of great importance. However, the success rates and cost-effectiveness of traditional drug development approaches are extremely low. Utilizing large sample genome-wide association study data for drug repurposing has shown promise in many diseases but has not yet been explored in CKD. Herein, we investigated actionable druggable targets to improve renal function using large-scale Mendelian randomization and colocalization analyses. We combined two population-scale independent genetic datasets and validated findings with cell-type-dependent eQTL data of kidney tubular and glomerular samples. We ultimately prioritized two drug targets, opioid receptor-like 1 and F12, with potential genetic support for restoring renal function and subsequent treatment of CKD. Our findings explore the potential pathological mechanisms of CKD, bridge the gap between the molecular mechanisms of pathogenesis and clinical intervention, and provide new strategies in future clinical trials of CKD.

Keywords: Bioinformatics.

Graphical abstract

Figure 1

Study framework This study utilized Mendelian randomization and colocalization analysis to reveal actionable druggable targets to cure chronic kidney disease. The expression levels of F12 and OPRL1 hold great potential in chronic kidney disease prevention and management, which might act through anti-inflammation, anti-thrombosis and anti-hypertension.

Figure 2

Miami plots of results from actionable druggable genome-wide MR analysis The red dot line corresponds to p = 0.000396 for significant MR estimate. The gene with smallest p-value in both CKD and eGFR was F12.

Figure 3

Regional association plots around (A) rs35716097 and (B) rs4408777 in CKD Plots are produced in LocusZoom and show the most strongly associated SNP (presented as purple diamond). The color reflects LD correlation (r2) using 1000G EUR population as reference. The left y axis indicates -log10(p value) of SNPs and the x axis indicates the chromosomal positions of SNPs (GRCh37). The right y axis represents the genetic recombination rates.

Figure 4

Forest plot of results from actionable druggable genome-wide MR analysis with glomeruli and tubule cell-type-dependent eQTL dataset Genes included in this figure was those with PPH4 > 0.8 in colocalization analysis.