Identification of crucial inflammaging related risk factors in multiple sclerosis - Xu, Mengchu; Wang, Huize; Ren, Siwei; Wang, Bing; Yang, Wenyan; Lv, Ling; Sha, Xianzheng; Li, Wenya; Wang, Yin (Frontiers in Molecular Neuroscience, 2024)
Background: Multiple sclerosis(MS) is an immune-mediated disease characterized by inflammatory demyelinating lesions in the central nervous system. Studies have shown that the inflammation is vital to both the onset and progression of MS, where aging play a key role in it. However, the potential mechanisms on how aging-related inflammation(inflamm-aging) promotes MS have not been fully understood. Therefore, there is an urgent need to integrate the underlying mechanisms between inflamm-aging and MS, where meaningful prediction models are needed. Methods: First, both aging and disease models were developed using machine learning methods, respectively. Then, an integrated inflamm-aging model was used to identify relative risk factors, by indentifying essential “aging-inflammation-disease” triples. Finally, a series of bioinformatics analyses(including network analysis, enrichment analysis, sensitivity analysis and pan-cancer analysis) were further used to explore the potential mechanisms between inflamm-aging and MS. Results: A series of risk factors were identified, such as the protein homeostasis, cellular homeostasis, neurodevelopment and energy metabolism. The inflamm-aging indices were further validated in different cancer types. Therefore, various risk factors were integrated, and even both the theories of inflamm-aging and immunosenescence were further confirmed. Conclusion: In conclusion, our study systematically investigated the potential relationships between inflamm-aging and MS through a series of computational approaches, and could present a novel thought for for other aging-related diseases.