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The molecular subtypes of autoimmune diseases
- Source :
- Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1348-1363 (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
Abstract
- Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS ''inflammation & EGF'' subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.
Details
- Language :
- English
- ISSN :
- 20010370
- Volume :
- 23
- Issue :
- 1348-1363
- Database :
- Directory of Open Access Journals
- Journal :
- Computational and Structural Biotechnology Journal
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.138f4a1e08794a46a4fb692c7cf51756
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.csbj.2024.03.026