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Updated: Apr 15, 2026

Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
Published on: June 23, 2015
Identification of therapeutic targets for chronic kidney disease through Mendelian randomization analysis of
Run-Sen Liang1, Jin-Qi Su1, Xiang-Qi Wu1
1Guangdong Provincial Key Laboratory of Autophagy and Major Chronic Non-communicable Diseases, Key Laboratory of Prevention and Management of Chronic Kidney Diseases of Zhanjiang City, Institute of Nephrology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Abstract:
Chronic Kidney Disease (CKD) is a multifaceted and gradually advancing condition characterized by a complex pathogenesis. The current therapeutic options for CKD remain limited in efficacy. Consequently, the identification and exploration of novel drug targets for CKD are of paramount importance. We identified cis-expression quantitative trait loci (cis-eQTLs) with potential as drug targets from the eQTLGen Consortium database to serve as the exposure. For the outcome, we utilized a genome-wide association study (GWAS) of chronic kidney disease (CKD) from the FinnGen database, which comprised a case group of 11,265 individuals and a control group of 436,208 individuals. MR analysis was employed to investigate druggable genes closely associated with CKD. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to elucidate the functional roles of these significant genes. Finally, a colocalization analysis was conducted to determine the likelihood that a cis-eQTL for a druggable gene and CKD share a causal variant. The expression of 12 genes was found to be significantly associated with CKD risk, with a false discovery rate (FDR) of less than 0.05. GO and KEGG enrichment analyses indicated that these genes are primarily involved in the regulation of MAP kinase activity, regulation of protein serine/threonine kinase activity, Gap junction, Platelet activation and Oxytocin signaling pathway. The colocalization analysis results suggested that CKD and the TUBB gene may share a causal variant, with a posterior probability (PP.H4) exceeding 80% (TUBB: 97.27%). Compelling statistical evidence indicates that TUBB represents the most promising pharmacological target for the treatment of CKD. This study not only identifies potential therapeutic targets but also offers valuable insights for future drug development in the context of CKD.
Insights
This study identifies TUBB as a promising drug target for Chronic Kidney Disease (CKD) by analyzing genetic data. Further research into TUBB could lead to new CKD treatments.
Area of Science:
- Genetics
- Pharmacology
- Nephrology
Background:
- Chronic Kidney Disease (CKD) has limited treatment options due to complex pathogenesis.
- Novel drug targets are crucial for effective CKD therapy.
- Genetic studies offer a pathway to identify potential therapeutic targets.
Purpose of the Study:
- To identify druggable genes associated with Chronic Kidney Disease (CKD) using genetic data.
- To explore the functional roles of identified genes in CKD pathogenesis.
- To evaluate TUBB as a potential pharmacological target for CKD treatment.
Main Methods:
- Utilized cis-expression quantitative trait loci (cis-eQTLs) from eQTLGen as exposure.
- Employed genome-wide association study (GWAS) data for CKD from FinnGen (11,265 cases, 436,208 controls).
- Performed Mendelian Randomization (MR), Gene Ontology (GO), KEGG, and colocalization analyses.
Main Results:
- Identified 12 genes significantly associated with CKD risk (FDR < 0.05).
- Enrichment analyses revealed involvement in MAP kinase activity, protein kinase activity, Gap junction, Platelet activation, and Oxytocin signaling.
- Colocalization analysis strongly implicated TUBB gene with CKD (PP.H4 > 80%, TUBB: 97.27%).
Conclusions:
- TUBB emerges as a highly promising pharmacological target for CKD.
- This research provides valuable insights for developing novel CKD therapeutics.
- Genetic association studies are effective in discovering potential drug targets for complex diseases.
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