Construction and validation of the diagnostic model of keloid based on weighted gene co-expression network analysis (WGCNA) and differential expression analysis

• DOI: 10.1080/2000656x.2021.2024557
• Publication Date: 2022-01-09T07:31:32Z
• Authors: Jiaheng Xie; Xiang Zhang; Kai Zhang; Chuyan Wu; Gang Yao; Jingping Shi; Liang Chen; Yiming Hu; Dan Wu; Guoyong Yin; Ming Wang
• Keywords: Keloid

Keloid is a disease that seriously affects the aesthetic appearance of body. In contrast to normal skin or hypertrophic scars, keloid tissue extends beyond initial site injury. Patients may complain pain, itching, burning. Although multiple treatments exist, none uniformly successful. Genetic advances have made it possible explore differences in gene expression between keloids and skin. Identifying biomarker for beneficial mechanism exploration treatment development keloid. this study, we identified seven genes with significant through weighted co-expression network analysis(WGCNA) differential analysis. Then, by Lasso regression, constructed diagnostic model using five these genes. Further studies found could be divided into high-risk low-risk groups model, immunity, m6A methylation, pyroptosis. Finally, verified accuracy clinical RNA-sequencing data.