Journal of pain research · 2025
Druggable Genome-Wide Mendelian Randomization Identifies Distinct Therapeutic Targets for Low Back Pain, Intervertebral Disk Degeneration, and Sciatica.
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Sun Aochuan, Li Zhuangzhuang, Du Yike, Liu Hao, Zhan Qiuzhong, Liu Zhengtang
Аннотация
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.
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.