Ruotong Yao, Yangguang Lu, Di Lu, Haiyong Ren, Xiang Wang, Bingyuan Lin, Siyao Chen, Yusheng Zhu, Feng Chen, Yukai Wang, Yi Gao, Jiawen Shen, Qiaofeng Guo, Kai Huang
{"title":"Identification of genetically-supported new drug targets for osteomyelitis based on druggable genomes.","authors":"Ruotong Yao, Yangguang Lu, Di Lu, Haiyong Ren, Xiang Wang, Bingyuan Lin, Siyao Chen, Yusheng Zhu, Feng Chen, Yukai Wang, Yi Gao, Jiawen Shen, Qiaofeng Guo, Kai Huang","doi":"10.1186/s40246-025-00826-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Limited drug treatment data are available for osteomyelitis (OM), an inflammatory bone condition secondary to infection. Given its genetic characteristics, it is necessary to integrate genetics into drug development for osteomyelitis. This study applied pharmacogenomics to identify new drug targets for osteomyelitis using Mendelian randomization (MR).</p><p><strong>Methods: </strong>Following the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization guidelines, expression and protein quantitative trait loci (QTL) analysis was applied to simulate drug exposure. Single nucleotide polymorphisms were selected as instrumental variables for MR analysis using blood QTL data and independent osteomyelitis genome-wide association study datasets from UK Biobank and FinnGen R10. A random-effects model meta-analysis combining the results from two datasets was performed. Bayesian co-localization analysis was conducted to validate the targets. Sensitivity analyses were performed using various MR methods, with MR-Egger regression and Cochran's Q test being conducted to assess the horizontal pleiotropy and heterogeneity of the instrumental variables.</p><p><strong>Results: </strong>At α = 1 × 10<sup>-5</sup>, the meta-analysis identified 12 drug target mechanisms. Gene expression of QDPR, TGM1, NTSR1, CBR3, and NEK6 was positively correlated with osteomyelitis risk, whereas HLA-DRB1, LAMC1, LTB4R, MAPK3, FPR1, ABAT, and LTA4H were negatively correlated with this risk. Five potential drug repurposing opportunities and three drugs that may increase osteomyelitis risk were identified. Sensitivity analyses highlighted LTA4H, LAMC1, QDPR, and NEK6 as having the strongest genetic evidence based on MR-Egger regression and protein QTL tests.</p><p><strong>Conclusions: </strong>This study identified 12 new genetically supported drug targets for osteomyelitis, thereby providing a genetic foundation for new drug development, repurposing existing drugs, and personalized treatment.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"117"},"PeriodicalIF":4.3000,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12505852/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Genomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40246-025-00826-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Limited drug treatment data are available for osteomyelitis (OM), an inflammatory bone condition secondary to infection. Given its genetic characteristics, it is necessary to integrate genetics into drug development for osteomyelitis. This study applied pharmacogenomics to identify new drug targets for osteomyelitis using Mendelian randomization (MR).
Methods: Following the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization guidelines, expression and protein quantitative trait loci (QTL) analysis was applied to simulate drug exposure. Single nucleotide polymorphisms were selected as instrumental variables for MR analysis using blood QTL data and independent osteomyelitis genome-wide association study datasets from UK Biobank and FinnGen R10. A random-effects model meta-analysis combining the results from two datasets was performed. Bayesian co-localization analysis was conducted to validate the targets. Sensitivity analyses were performed using various MR methods, with MR-Egger regression and Cochran's Q test being conducted to assess the horizontal pleiotropy and heterogeneity of the instrumental variables.
Results: At α = 1 × 10-5, the meta-analysis identified 12 drug target mechanisms. Gene expression of QDPR, TGM1, NTSR1, CBR3, and NEK6 was positively correlated with osteomyelitis risk, whereas HLA-DRB1, LAMC1, LTB4R, MAPK3, FPR1, ABAT, and LTA4H were negatively correlated with this risk. Five potential drug repurposing opportunities and three drugs that may increase osteomyelitis risk were identified. Sensitivity analyses highlighted LTA4H, LAMC1, QDPR, and NEK6 as having the strongest genetic evidence based on MR-Egger regression and protein QTL tests.
Conclusions: This study identified 12 new genetically supported drug targets for osteomyelitis, thereby providing a genetic foundation for new drug development, repurposing existing drugs, and personalized treatment.
期刊介绍：
Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics.
Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
