Identification of Potential Ferroptosis Biomarkers and Analysis of Immune Cell Infiltration in Psoriasis Using Machine Learning - Wu X; Sun Y; Wei S; Hu H; Yang B (Dove Medical Press, 2024)
Xiaoyan Wu,1,2 Yuzhe Sun,2,3 Shuyi Wei,2,3 Huoyou Hu,1 Bin Yang2 1Shenzhen Second People's Hospital, the First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, People's Republic of China; 2Department of Dermatology, the First Affiliated Hospital of Jinan University, Guangzhou, 510630, People's Republic of China; 3Department of Dermatology, Dermatology Hospital of Southern Medical University, Guangzhou, 510091, People's Republic of ChinaCorrespondence: Huoyou Hu, Shenzhen Second People's Hospital, 3002 Sungang West Road, Shenzhen, Guangdong, 518035, People's Republic of China, Tel +86-13554918106, Email huhuoyou1029@163.com Bin Yang, Jinan University, 601 West Huangpu Avenue, Guangzhou, Guangdong, 510632, People's Republic of China, Tel +86-13922207231, Email yangbin1@smu.edu.cnBackground: Ferroptosis is a type of cell death characterized by the accumulation of iron-dependent lethal lipid peroxides, which is associated with various pathophysiological processes. Psoriasis is a chronic autoimmune skin disease accompanied by abnormal immune cell infiltration and excessive production of lipid reactive oxygen species (ROS). Currently, its pathogenesis remains elusive, especially the potential role of ferroptosis in its pathophysiological process.Methods: The microarrays GSE13355 (58 psoriatic skin specimens versus 122 healthy skin specimens) and the ferroptosis database were employed to identify the common differentially expressed genes (DEGs) associated with psoriasis and ferroptosis. The functions of common DEGs were investigated through functional enrichment analysis and protein-protein interaction analysis. The potential diagnostic markers for psoriasis among the common DEGs were identified using four machine-learning algorithms. DGIdb was utilized to explore potential therapeutic agents for psoriasis. Additionally, CIBERSORT was employed to investigate immune infiltration in psoriasis.Results: A total of 8 common DEGs associated with psoriasis and ferroptosis were identified, which are involved in intercellular signaling and affect pathways of cell response to stress and stimulation. Four machine-learning algorithms were employed to identify poly (ADP-ribose) polymerase 12 (PARP12), frizzled homolog 7 (FZD7), and arachidonate 15-lipoxygenase (ALOX15B) among the eight common DEGs as potential diagnostic markers for psoriasis. A total of 18 drugs targeting the five common DEGs were identified as potential candidates for treating psoriasis. Additionally, significant changes were observed in the immune microenvironment of patients with psoriasis.Conclusion: This study has contributed to our enhanced comprehension of ferroptosis-related genes as potential biomarkers for psoriasis diagnosis, as well as the alterations in the immune microenvironment associated with psoriasis. Our findings offer valuable insights into the diagnosis and treatment of psoriasis.Keywords: psoriasis, ferroptosis, biomarker, immune