Identification of a novel immunosenescence-related genes and integrative analyses in patients with psoriasis.

BACKGROUND

Immunosenescence, characterized by age-related changes in the immune system, may contribute to the onset and progression of psoriasis, a condition whose incidence increases with age and often requires intensified medication in older patients.

METHODS

This study utilized bioinformatics analyses to identify differentially expressed immunosenescence-related genes in psoriasis patients from the GEO database. Enrichment, correlation, and interaction network analyses were conducted to explore their involvement in immune and inflammation pathways. Machine learning models were employed to predict psoriasis onset and validated using external datasets. Patient stratification based on gene expression patterns assessed differential responses to biologic inhibitors targeting specific genes.

RESULTS

Immunosenescence emerged as a significant factor in psoriasis pathogenesis, with genes such as BACH2 potentially influencing T cell activation and disease outcomes. Lower BACH2 expression levels were associated with poorer treatment responses in psoriasis patients.

CONCLUSIONS

This study sheds light on immunosenescence-related mechanisms in psoriasis, suggesting BACH2 as a potential disease diagnosis biomarker. Further research into BACH2's role in psoriasis pathophysiology is warranted to advance tailored treatment strategies.