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Druggable Genome-Wide Mendelian Randomization Identifies Distinct Therapeutic Targets for Low Back Pain,
Aochuan Sun1, Zhuangzhuang Li1,2, Yike Du1,3
1The Department of Geriatrics, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, People's Republic of China.
Objective:
There are no effective drugs for the treatment of low back pain (LBP), intervertebral disk degeneration (IVDD), or sciatica. We aimed to identify potential therapeutic targets through druggable genome-wide Mendelian randomization (MR) analysis.
Methods:
This study utilized large-scale expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs), integrating existing druggable genome data. Conducted two-sample MR analysis to estimate the causal relationships between druggable genes with LBP, IVDD, and sciatica. Furthermore, we employed Bayesian colocalization, summary data-based Mendelian randomization (SMR) analysis, and the Steiger filtering test to validate our results and identify therapeutic targets. Additionally, we used a phenome-wide MR approach to assess the side effects or other indications of the identified therapeutic targets.
Results:
MR analysis identified 10 candidate druggable genes associated with LBP, 18 candidate druggable genes with IVDD, and 8 candidate druggable genes with sciatica. By applying Bayesian colocalization (posterior probability for H4>80%), SMR analysis (P<0.05), and the Steiger filtering test (TRUE), we identified one therapeutic target for LBP (P2RY13), four for IVDD (CAPN10, AKR1C2, BTN1A1, EIF2AK3), and four for sciatica (NT5C, GPX1, SUMO2, DAG1). Phenome-wide MR analysis revealed potential adverse cardiac metabolic effects associated with NT5C.
Conclusion:
Our study integrated eQTL and pQTL data to identify nine phenotype-specific therapeutic targets for LBP, IVDD, and sciatica. These findings highlight potential candidates for future drug repurposing, experimental validation, and the development of mechanism-based therapies tailored to each condition.
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