Evidence map›Paper›PMID 39582071›Full record

ArticleScientific reports2024

Unveiling therapeutic targets for spinal stenosis from genetic insights: a Mendelian randomization analysis.

Zhaopeng Fan, Bohong Chen, Le Ding, Hua Guo

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Zhaopeng FanSchool of Medicine, Xi'an Jiaotong University, Xi'an, China.
Bohong ChenDepartment of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Le DingSchool of Medicine, Yan'an University, Yan'an, China.
Hua GuoDepartment of Orthopedics, Xi'an Fifth Hospital, Xi'an, China. 13991817800@139.com.

Funding

the Science and Technology Program in Xi'an of Shaanxi Province in China 22YXYJ0004the Scientific Research Program of the Health and Wellness Commission in Shaanxi Province of China 2021B001the Scientific Research Program of the Health and Wellness Commission in Xi'an of Shaanxi Province in China 2022ms01
6 · The paper itself

Abstract

Spinal stenosis is a commonly chronic spinal degenerative disease, which is a major cause of pain and dysfunction in the elderly. Mendelian randomization (MR) has been widely applied to repurpose licensed drugs and identify novel therapeutic targets. Consequently, we intended to identify new therapeutic targets for spinal stenosis and to analyze their possible mechanisms and potential side effects.We conducted the Mendelian randomization analysis to identify potential drug targets for the management of spinal stenosis. Cis-expressed quantitative trait loci (cis-eQTL) data as genetic instrumental variables were acquired from the eQTLGen consortium. The summary statistics for single nucleotide polymorphism (SNP) associations of spinal stenosis were obtained from the FinnGen study(20,807 cases and 294,770 controls). Co-localization analysis was performed to determine whether there was shared causal variation between the SNPs associated with spinal stenosis as well as the eQTL. Multiple external validations were performed to reinforce the reliability and stability of the findings utilizing the cis-eQTL from the GTEx portal, the Ferkingstad et al. pQTL dataset, and the Sun et al. pQTL dataset. The viability of the identified drug targets for future clinical applications was elucidated through the phenome-wide association study and drug candidate prediction. Three drug targets (BMP6, DLK1, and GFPT1) exhibited significant causal associations with spinal stenosis in the eQTLGen cohort by MR analysis, which was strongly supported by the results of the co-localization analysis. The causal association of DLK1 and GFPT1 with spinal stenosis remained remarkable with multiple external validations. Multivariate MR and phenome-wide association study analysis indicated that both targets were not associated with other traits. In addition, phenome-wide association study analysis and drug prediction analysis demonstrated the potential of these two targets for future clinical applications. In this study, DLK1 and GFPT1 were identified as promising novel therapeutic targets for spinal stenosis, providing initial genetic insights for drug development in spinal stenosis.

Indexed as

Mendelian Randomization AnalysisPolymorphism, Single NucleotideQuantitative Trait LociSpinal StenosisGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansDrug targetsGeneticsMendelian randomizationSpinal stenosis

Identifiers

PMID39582071
PMCPMC11586425

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