[An Artificial Neural Network Diagnostic Model for Scleroderma and Immune Cell Infiltration Analysis Based on Mitochondria-associated Genes]

Overview

Journal Nan Fang Yi Ke Da Xue Xue Bao

Specialty General Medicine

Date 2024 Jun 11

PMID 38862450

Authors

Z Zuo

Q Meng

J Cui

K Guo

H Bian

Affiliations

Soon will be listed here.

Abstract

Objective: To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.

Methods: The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes, and the differential genes were identified by Random forest, LASSO regression and SVM algorithms. Based on these differential genes, an artificial neural network model was constructed, and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807. The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma. The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.

Results: A total of 24 differential genes were obtained, including 11 up-regulated and 13 down-regulated genes. Seven most relevant mitochondria-related genes (POLB, GSR, KRAS, NT5DC2, NOX4, IGF1, and TGM2) were screened using 3 machine learning algorithms, and the artificial neural network diagnostic model was constructed. The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis (0.740 for the verification dataset and 0.980 for cross-over validation). RT-qPCR detected significant up-regulation of POLB, GSR, KRAS, NOX4, IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma. Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells, immature B cells, resting dendritic cells, memory activated CD4T cells, M0 macrophages, monocytes, resting memory CD4T cells and mast cell activation.

Conclusion: The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

References

Leek J, Johnson W, Parker H, Jaffe A, Storey J . The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012; 28(6):882-3. PMC: 3307112. DOI: 10.1093/bioinformatics/bts034. View

Li K, Zhu X, Liu H, Zhang S, Li X, Xiao N . NT5DC2 promotes tumor cell proliferation by stabilizing EGFR in hepatocellular carcinoma. Cell Death Dis. 2020; 11(5):335. PMC: 7206140. DOI: 10.1038/s41419-020-2549-2. View

Henderson J, Duffy L, Stratton R, Ford D, OReilly S . Metabolic reprogramming of glycolysis and glutamine metabolism are key events in myofibroblast transition in systemic sclerosis pathogenesis. J Cell Mol Med. 2020; 24(23):14026-14038. PMC: 7754020. DOI: 10.1111/jcmm.16013. View

Orteu C, Ong V, Denton C . Scleroderma mimics - Clinical features and management. Best Pract Res Clin Rheumatol. 2020; 34(1):101489. DOI: 10.1016/j.berh.2020.101489. View

Qiu L, Gong G, Wu W, Li N, Li Z, Chen S . A novel prognostic signature for idiopathic pulmonary fibrosis based on five-immune-related genes. Ann Transl Med. 2021; 9(20):1570. PMC: 8576669. DOI: 10.21037/atm-21-4545. View

Kaufman B, Van Houten B . POLB: A new role of DNA polymerase beta in mitochondrial base excision repair. DNA Repair (Amst). 2017; 60:A1-A5. PMC: 5713914. DOI: 10.1016/j.dnarep.2017.11.002. View

Cardamone C, Parente R, De Feo G, Triggiani M . Mast cells as effector cells of innate immunity and regulators of adaptive immunity. Immunol Lett. 2016; 178:10-4. DOI: 10.1016/j.imlet.2016.07.003. View

Jimenez S, Castro S, Piera-Velazquez S . Role of growth factors in the pathogenesis of tissue fibrosis in systemic sclerosis. Curr Rheumatol Rev. 2015; 6(4):283-94. DOI: 10.2174/157339710793205611. View

Jaguin M, Fardel O, Lecureur V . AhR-dependent secretion of PDGF-BB by human classically activated macrophages exposed to DEP extracts stimulates lung fibroblast proliferation. Toxicol Appl Pharmacol. 2015; 285(3):170-8. DOI: 10.1016/j.taap.2015.04.007. View

10.

Rongvaux A . Innate immunity and tolerance toward mitochondria. Mitochondrion. 2017; 41:14-20. DOI: 10.1016/j.mito.2017.10.007. View

11.

Boyang C, Yuexing L, Yiping Y, Haiyang Y, Xufei Z, Liancheng G . Construction and analysis of heart failure diagnosis model based on random forest and artificial neural network. Medicine (Baltimore). 2022; 101(41):e31097. PMC: 9575800. DOI: 10.1097/MD.0000000000031097. View

12.

Cho S, Oh Y, Jeong E, Park S, Lee D, Wang X . Amplification of transglutaminase 2 enhances tumor-promoting inflammation in gastric cancers. Exp Mol Med. 2020; 52(5):854-864. PMC: 7272405. DOI: 10.1038/s12276-020-0444-7. View

13.

Wang K, Zu C, Zhang Y, Wang X, Huan X, Wang L . Blocking TG2 attenuates bleomycin-induced pulmonary fibrosis in mice through inhibiting EMT. Respir Physiol Neurobiol. 2020; 276:103402. DOI: 10.1016/j.resp.2020.103402. View

14.

Swanson M, Weidemann D, Harshman L . The impact of rural status on pediatric chronic kidney disease. Pediatr Nephrol. 2023; 39(2):435-446. PMC: 10182542. DOI: 10.1007/s00467-023-06001-0. View

15.

Zhou X, Trinh-Minh T, Tran-Manh C, Giessl A, Bergmann C, Gyorfi A . Impaired Mitochondrial Transcription Factor A Expression Promotes Mitochondrial Damage to Drive Fibroblast Activation and Fibrosis in Systemic Sclerosis. Arthritis Rheumatol. 2021; 74(5):871-881. DOI: 10.1002/art.42033. View

16.

Schubbert S, Zenker M, Rowe S, Boll S, Klein C, Bollag G . Germline KRAS mutations cause Noonan syndrome. Nat Genet. 2006; 38(3):331-6. DOI: 10.1038/ng1748. View

17.

Aslam A, Salam A, Griffiths C, McGrath J . Naevus sebaceus: a mosaic RASopathy. Clin Exp Dermatol. 2013; 39(1):1-6. DOI: 10.1111/ced.12209. View

18.

Couto N, Wood J, Barber J . The role of glutathione reductase and related enzymes on cellular redox homoeostasis network. Free Radic Biol Med. 2016; 95:27-42. DOI: 10.1016/j.freeradbiomed.2016.02.028. View

19.

Hamaguchi Y, Fujimoto M, Matsushita T, Hasegawa M, Takehara K, Sato S . Elevated serum insulin-like growth factor (IGF-1) and IGF binding protein-3 levels in patients with systemic sclerosis: possible role in development of fibrosis. J Rheumatol. 2008; 35(12):2363-71. DOI: 10.3899/jrheum.080340. View

20.

Li S . Scleroderma in Children and Adolescents: Localized Scleroderma and Systemic Sclerosis. Pediatr Clin North Am. 2018; 65(4):757-781. DOI: 10.1016/j.pcl.2018.04.002. View