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Yang Y, Hua Y, Zheng H, Jia R, Ye Z, Su G, Gu Y, Zhan K, Tang K, Qi S, Wu H, Qin S, Huang S. Biomarkers prediction and immune landscape in ulcerative colitis: Findings based on bioinformatics and machine learning. Comput Biol Med 2024; 168:107778. [PMID: 38070204 DOI: 10.1016/j.compbiomed.2023.107778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/02/2023] [Accepted: 11/28/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND Ulcerative colitis (UC) presents diagnostic and therapeutic difficulties. The primary objective of this study is to identify efficacious biomarkers for diagnosis and treatment, as well as acquire a deeper understanding of the immuneological characteristics associated with the disease. METHODS Datasets relating to UC were obtained from GEO database. Among these, three datasets were merged to create a metadata for bioinformatics analysis and machine learning. Additionally, one dataset specifically utilized for external validation. Least absolute shrinkage and selection operator (LASSO) and random forest (RF) were employed to screen signature genes. The artificial neural network (ANN) model and receiver operating characteristic (ROC) curve were used to assess the diagnostic performance of signature genes. The single sample gene set enrichment analysis (ssGSEA) was applied to reveal the immune landscape. Finally, the relationship between the signature genes, immune infiltration, and clinical characteristics was investigated through correlation analysis. RESULT By intersecting the result of LASSO, RF and WGCNA, 8 signature genes were identified, including S100A8, IL-1B, CXCL1, TCN1, MMP10, GREM1, DUOX2 and SLC6A14. The biological progress of this gene mostly encompasses acute inflammatory response, aggregation and chemotaxis of leukocyte, and response to lipopolysaccharide by mediating IL-17 signaling pathway, NF-kappa B signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway. Immune infiltration analysis shows 25 immune cells are significantly elevated in UC samples. Moreover, these signature genes exhibit a strong correlation with various immune cells and a mild to moderate correlation with the Mayo score. CONCLUSION S100A8, IL-1B, CXCL1, TCN1, MMP10, GREM1, DUOX2 and SLC6A14 have been identified as credible potential biomarkers for the diagnosis and therapy of UC. The immune response mediated by these signature biomarkers plays a crucial role in the occurrence and advancement of UC by means of the reciprocal interaction between the signature biomarkers and immune-infiltrated cells.
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Affiliation(s)
- Yuanming Yang
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Yiwei Hua
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Huan Zheng
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Rui Jia
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Zhining Ye
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Guifang Su
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Yueming Gu
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Kai Zhan
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Kairui Tang
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Shuhao Qi
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China
| | - Haomeng Wu
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, 510120, China; Guangdong Provincial Key Laboratory of Clinical Research on Traditional Chinese Medicine Syndrome, Guangzhou 510120, China
| | - Shumin Qin
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, 510120, China; Guangdong Provincial Key Laboratory of Clinical Research on Traditional Chinese Medicine Syndrome, Guangzhou 510120, China.
| | - Shaogang Huang
- Dongguan Hospital of Guangzhou University of Chinese Medicine, Dongguan, 523000, China; The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, 510120, China; Guangdong Provincial Key Laboratory of Clinical Research on Traditional Chinese Medicine Syndrome, Guangzhou 510120, China; Yang Chunbo academic experience inheritance studio of Guangdong provincial hospital of Chinese Medicine, Guangzhou, 510006, China.
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Rajalingam A, Sekar K, Ganjiwale A. Identification of Potential Genes and Critical Pathways in Postoperative Recurrence of Crohn's Disease by Machine Learning And WGCNA Network Analysis. Curr Genomics 2023; 24:84-99. [PMID: 37994325 PMCID: PMC10662376 DOI: 10.2174/1389202924666230601122334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 04/28/2023] [Accepted: 05/10/2023] [Indexed: 11/24/2023] Open
Abstract
Background Crohn's disease (CD) is a chronic idiopathic inflammatory bowel disease affecting the entire gastrointestinal tract from the mouth to the anus. These patients often experience a period of symptomatic relapse and remission. A 20 - 30% symptomatic recurrence rate is reported in the first year after surgery, with a 10% increase each subsequent year. Thus, surgery is done only to relieve symptoms and not for the complete cure of the disease. The determinants and the genetic factors of this disease recurrence are also not well-defined. Therefore, enhanced diagnostic efficiency and prognostic outcome are critical for confronting CD recurrence. Methods We analysed ileal mucosa samples collected from neo-terminal ileum six months after surgery (M6=121 samples) from Crohn's disease dataset (GSE186582). The primary aim of this study is to identify the potential genes and critical pathways in post-operative recurrence of Crohn's disease. We combined the differential gene expression analysis with Recursive feature elimination (RFE), a machine learning approach to get five critical genes for the postoperative recurrence of Crohn's disease. The features (genes) selected by different methods were validated using five binary classifiers for recurrence and remission samples: Logistic Regression (LR), Decision tree classifier (DT), Support Vector Machine (SVM), Random Forest classifier (RF), and K-nearest neighbor (KNN) with 10-fold cross-validation. We also performed weighted gene co-expression network analysis (WGCNA) to select specific modules and feature genes associated with Crohn's disease postoperative recurrence, smoking, and biological sex. Combined with other biological interpretations, including Gene Ontology (GO) analysis, pathway enrichment, and protein-protein interaction (PPI) network analysis, our current study sheds light on the in-depth research of CD diagnosis and prognosis in postoperative recurrence. Results PLOD2, ZNF165, BOK, CX3CR1, and ARMCX4, are the important genes identified from the machine learning approach. These genes are reported to be involved in the viral protein interaction with cytokine and cytokine receptors, lysine degradation, and apoptosis. They are also linked with various cellular and molecular functions such as Peptidyl-lysine hydroxylation, Central nervous system maturation, G protein-coupled chemoattractant receptor activity, BCL-2 homology (BH) domain binding, Gliogenesis and negative regulation of mitochondrial depolarization. WGCNA identified a gene co-expression module that was primarily involved in mitochondrial translational elongation, mitochondrial translational termination, mitochondrial translation, mitochondrial respiratory chain complex, mRNA splicing via spliceosome pathways, etc.; Both the analysis result emphasizes that the mitochondrial depolarization pathway is linked with CD recurrence leading to oxidative stress in promoting inflammation in CD patients. Conclusion These key genes serve as the novel diagnostic biomarker for the postoperative recurrence of Crohn's disease. Thus, among other treatment options present until now, these biomarkers would provide success in both diagnosis and prognosis, aiming for a long-lasting remission to prevent further complications in CD.
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Affiliation(s)
- Aruna Rajalingam
- Department of Life Sciences, Bangalore University, Bangalore, Karnataka, 560056, India
| | - Kanagaraj Sekar
- Laboratory for Structural Biology and Bio-computing, Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, 560012, India
| | - Anjali Ganjiwale
- Department of Life Sciences, Bangalore University, Bangalore, Karnataka, 560056, India
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