In:
Frontiers in Molecular Neuroscience, Frontiers Media SA, Vol. 17 ( 2024-5-21)
Abstract:
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 plays a key role in it. However, the potential mechanisms on how aging-related inflammation (inflammaging) promotes MS have not been fully understood. Therefore, there is an urgent need to integrate the underlying mechanisms between inflammaging 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 inflammaging model was used to identify relative risk factors, by identifying 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 inflammaging and MS. Results A series of risk factors were identified, such as the protein homeostasis, cellular homeostasis, neurodevelopment and energy metabolism. The inflammaging indices were further validated in different cancer types. Therefore, various risk factors were integrated, and even both the theories of inflammaging and immunosenescence were further confirmed. Conclusion In conclusion, our study systematically investigated the potential relationships between inflammaging and MS through a series of computational approaches, and could present a novel thought for other aging-related diseases.
Type of Medium:
Online Resource
ISSN:
1662-5099
DOI:
10.3389/fnmol.2024.1398665
DOI:
10.3389/fnmol.2024.1398665.s001
Language:
Unknown
Publisher:
Frontiers Media SA
Publication Date:
2024
detail.hit.zdb_id:
2452967-9
