A Novel Method for Pathway Identification Based on Attractor and Crosstalk in Polyarticular Juvenile Idiopathic
Yuanji Wang1, Shunhua Lin1, Changhui Li1
1Department of Orthopaedics, The People's Hospital of Rizhao, Rizhao, Shandong, China (mainland).
Insights
Juvenile idiopathic arthritis (JIA) involves complex pathway dysregulation. A new method using attractor and crosstalk analysis identified the p53 signaling and non-alcoholic fatty liver disease pathways as key to polyarticular JIA progression.
Area of Science:
- Immunology and Systems Biology
- Computational Biology
- Pediatric Rheumatology
Background:
- Juvenile idiopathic arthritis (JIA) is a prevalent inflammatory condition with an unknown cause.
- Polyarticular JIA (pJIA) affects multiple joints and presents a significant clinical challenge.
Purpose of the Study:
- To develop and validate a novel computational method for identifying dysregulated biological pathways in pJIA.
- To pinpoint specific pathways contributing to the pathogenesis of pJIA.
Main Methods:
- Gene expression data from 61 pJIA patients and 59 healthy controls were analyzed.
- Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interaction data were integrated.
- A novel approach combining attractor and crosstalk analysis was employed to assess pathway integrity and influence.
Main Results:
- The analysis identified seven significant attractors (p<0.01) and 14 influential pathways (RP<0.01).
- Two key pathways, the p53 signaling pathway (KEGG: 04115) and non-alcoholic fatty liver disease (NAFLD) pathway (KEGG: 04932), were found to be significantly dysfunctional in pJIA.
- These identified pathways are strongly associated with pJIA progression.
Conclusions:
- A novel computational framework utilizing attractor and crosstalk analysis effectively identifies dysregulated pathways in pJIA.
- This approach offers a promising tool for understanding JIA pathogenesis and developing future therapeutic strategies.
Abstract:
BACKGROUND Juvenile idiopathic arthritis (JIA) is one of the most common inflammatory disorders of unknown etiology. We introduced a novel method to identify dysregulated pathways associated with polyarticular JIA (pJIA). MATERIAL AND METHODS Gene expression profiling of 61 children with pJIA and 59 healthy controls were collected from E-GEOD-13849; 300 pathways were obtained from Kyoto Encyclopedia of Genes and Genomes (KEGG) database and 787,896 protein-protein interaction sets were gathered from the Retrieval of Interacting Genes. Attractor and crosstalk were designed to complement each other to increase the integrity of pathways assessment. Then, impact factor was used to assess the interactions inter-pathways, and RP-value was used to evaluate the comprehensive influential ability of attractors. RESULTS There were seven attractors with p<0.01 and 14 pathways with RP<0.01. Finally, two significantly dysfunctional pathways were found, which were related to pJIA progression: p53 signaling pathway (KEGG ID: 04115) and non-alcoholic fatty liver disease (NAFLD) (KEGG ID: 04932). CONCLUSIONS A novel approach that identified the dysregulated pathways in pJIA was constructed based on attractor and crosstalk. The new process is expected to be efficient in the upcoming era of medicine.
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