Identification of genetically-supported new drug targets for osteomyelitis based on druggable genomes

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).

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.

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.

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.