Machine learning reveals distinct gene signature profiles in lesional and nonlesional regions of inflammatory skin diseases

Science Advances, Journal Year: 2022, Volume and Issue: 8(17)

Published: April 29, 2022

Analysis of gene expression from cutaneous lupus erythematosus, psoriasis, atopic dermatitis, and systemic sclerosis using set variation analysis (GSVA) revealed that lesional samples each condition had unique features, but all four diseases displayed common enrichment in multiple inflammatory signatures. These findings were confirmed by both classification regression tree machine learning (ML) models. Nonlesional disease also differed normal other ML. Notably, the features used nonlesional more distinct than their counterparts, GSVA disease. data show skin have profiles abnormalities, especially skin, suggest a model which disease-specific abnormalities “prelesional” may permit environmental stimuli to trigger responses leading shared manifestations

Language: Английский

Lupus-prone NZM2328 mice exhibit enhanced UV-induced myeloid cell recruitment and activation in a type I interferon dependent manner

Journal of Autoimmunity, Journal Year: 2024, Volume and Issue: 149, P. 103296 - 103296

Published: Sept. 5, 2024

Language: Английский