Introduction: Autophagy is necessary for the progression of psoriasis.
Aim: This study aimed to recognize possible autophagy-related genes in psoriasis via bioinformatics study to present a better standard for the clinical treatment and management of psoriasis.
Material And Methods: The GEO dataset was utilized to derive the mRNA expression profile of the database GSE78097. R software was utilized to find autophagy-associated genes that may be expressed in psoriasis. Then, a protein-protein interaction (PPI) correlation study of the differentially expressed autophagy-associated genes was carried out, and GO and KEGG enrichment analysis was used to investigate any potential signalling pathways linked.
Results: We identified a total of 156 autophagy-related genes in 27 psoriasis and 6 healthy skin tissue samples. The PPI network diagram findings demonstrate interactions among these autophagy-associated genes. Autophagy, protein processing, apoptosis, and mitochondria processes may be crucial in the development and occurrence of psoriasis suggested by KEGG and GO enrichment analysis.
Conclusions: Utilizing bioinformatics methods to recognize differentially expressed autophagy-related genes has further enhanced our understanding of psoriasis and provided new thinking for the study of the pathogenesis and therapeutic targets of psoriasis.
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| http://dx.doi.org/10.5114/ada.2024.145618 | DOI Listing |
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