Multi-omics Mendelian Randomization and Single-Cell Analysis Identify Novel Therapeutic Targets for Osteosarcopenia

Background Osteosarcopenia, defined by the coexistence of osteoporosis and sarcopenia, presents a significant health challenge for aging populations. The purpose of current study was to identify potential therapeutic targets for osteosarcopenia using integrative analysis methods, including multi-omics Mendelian Randomization (MR) and single-cell RNA sequencing (scRNA-seq). Methods An integrative analysis using transcriptome, proteome wide MR, Summary-based MR (SMR), and colocalization analysis was performed. Data from large-scale genome-wide association studies (GWAS) of plasma transcriptome, proteome were analyzed. The expression data for these candidate targets across different tissues and cell types to further explore how they might contribute to the development of osteosarcopenia. Results The MR analysis identified 331 genes, 20 and 24 proteins in the eQTLgen, deCODE and Fenland datasets that were causally associated with osteosarcopenia traits. Twelve causal targets were validated in at least two datasets, and the causal direction was generally consistent. Among these, MGP, CTSS and SNUPN were recognized as protective factors, while MMP16, ART4, and PSMD9 were associated with an increased risk of osteosarcopenia. Validation was further supported by SMR and colocalization analyses. The tissue and single-cell expression of these candidate targets suggested that MGP and CTSS may directly influence the musculoskeletal system, while the others might not. Conclusions : Our findings suggest that ART4, MMP16, and PSMD9 may be risk factors for osteosarcopenia, whereas MGP, SNUPN and CTSS show protective potential. Further investigations are needed to validate these targets and investigate their roles in specific tissues and cellular contexts, advancing osteosarcopenia management strategies.