Identification of Potential Pleiotropic Genes for Immune and Skeletal Diseases Using Multivariate MetaCCA Analysis.

ABSTRACT

Background: Immune and skeletal systems physiologically and pathologically interact with each other. Immune and skeletal diseases may share potential pleiotropic genetics factors, but the shared specific genes are largely unknown. Objective: This study aimed to investigate the overlapping genetic factors between multiple diseases (including rheumatoid arthritis (RA), psoriasis, osteoporosis, osteoarthritis, sarcopenia, and fracture). Methods: The canonical correlation analysis (metaCCA) approach was used to identify the shared genes for six diseases by integrating genome-wide association study (GWAS)-derived summary statistics. The versatile Gene-based Association Study (VEGAS2) method was further applied to refine and validate the putative pleiotropic genes identified by metaCCA. Results: About 157 (p<8.19E-6), 319 (p<3.90E-6), and 77 (p<9.72E-6) potential pleiotropic genes were identified shared by two immune diseases, four skeletal diseases, and all of the six diseases, respectively. The top three significant putative pleiotropic genes shared by both immune and skeletal diseases, including HLA-B, TSBP1, and TSBP1-AS1 (pmajor histocompatibility complex (MHC) region. Nineteen of 77 putative pleiotropic genes identified by metaCCA analysis were associated with at least one disease in the VEGAS2 analysis. Specifically, the majority (18) of these 19 putative validated pleiotropic genes were associated with RA.

Conclusion:

The metaCCA method identified some pleiotropic genes shared by the immune and skeletal diseases. These findings help to improve our understanding of the shared genetic mechanisms and signaling pathways underlying immune and skeletal diseases.