| Title: | Revealing the pathophysiological processes of musculoskeletal diseases and multiple age-related disorders through multi-omics data |
| Lead Institution: | The Second Affiliated Hospital, Chongqing Medical University |
| Principal investigator: |
Application 624933
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About
Research Outline: This initiative seeks to examine the common mechanisms underlying musculoskeletal ailments and age-associated disorders. It emphasizes musculoskeletal disorders (e.g., osteoarthritis, osteoporosis, sarcopenia) and their associations with age-related ailments (e.g., cardiovascular, neurological, and endocrine diseases). By integrating multi-omics data (imaging, genomics, transcriptomics, proteomics, exome), the project will elucidate genetic, epigenetic, and metabolic relationships, thereby enabling early diagnosis and precise treatment. Research questions: What are the underlying mechanisms of musculoskeletal illnesses such as osteoarthritis, osteoporosis, and sarcopenia? What common molecular processes are present in musculoskeletal and age-related diseases? In what ways can genetic differences and metabolic dysregulation influence disease progression throughout various phases of aging? Can multi-omics data discern biomarkers for early diagnosis and intervention? Objectives of the Research: Investigate the genetic and molecular pathways behind musculoskeletal and age-related illnesses through multi-omics data analysis. Investigate the relationship among metabolic dysregulation, hereditary factors, and age-associated illnesses. Determine biomarkers for early diagnosis and individualized treatment by multi-omics analysis. Consolidate multi-omics data to develop an extensive model of common disease pathways. Scientific Rationale: Musculoskeletal disorders are intricately associated with aging and exhibit characteristics such as inflammation, cellular senescence, and metabolic failure. The aging process impacts various systems, including cardiovascular, neurodegenerative, and endocrine, which are frequently interconnected. This project will discover common pathways by integrating multi-omics data, thereby enhancing early diagnosis, prevention, and treatment.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 20908 | Genome-wide association study of sarcopenia index reveals sex-stratified genetic architecture | Yumeng Mu (+6) | 2026 | Biology of Sex Differences |
Enabling scientific discoveries that improve human health