Sneha Shrotri , Andrea Daamen , Kathryn Kingsmore , Prathyusha Bachali , Amrie Grammer , Peter Lipsky
{"title":"Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis","authors":"Sneha Shrotri , Andrea Daamen , Kathryn Kingsmore , Prathyusha Bachali , Amrie Grammer , Peter Lipsky","doi":"10.1016/j.xjidi.2024.100333","DOIUrl":null,"url":null,"abstract":"<div><div>Abnormalities in gene expression profiles characterize patients with inflammatory skin diseases, including psoriasis, and changes may reflect the action of specific therapeutic agents. To examine this, gene expression analysis of psoriatic skin was assessed by Gene Set Variation Analysis using informative gene modules, and longitudinal data were analyzed to assess the impact of various treatments. Ridge penalized logistic regression was employed to derive a transcriptomic score. Psoriatic lesional skin exhibited perturbations in gene expression profiles at baseline, with enrichment of signatures for neutrophils, keratinocytes, IFN, IL-12 complex, IL-1 cytokines, TNF, and T helper 17. Treatment with a variety of agents reduced lesional gene expression abnormalities to those in nonlesional skin. Specific gene expression abnormalities at baseline identified clinical responders to each treatment. Changes in gene expression over time were less pronounced in nonlesional skin and lesional skin in clinical nonresponders. The combined transcriptomic scores showed significant positive correlations with PASI scores in clinical responders over time. Overall, gene expression abnormalities characterize the severity of psoriatic skin lesions, can be used to predict responsiveness to individual treatments, and revert toward those of nonlesional skin with effective therapy. Therefore, gene expression analysis can be useful to support management of patients with psoriasis.</div></div>","PeriodicalId":73548,"journal":{"name":"JID innovations : skin science from molecules to population health","volume":"5 2","pages":"Article 100333"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11732706/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JID innovations : skin science from molecules to population health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266702672400081X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abnormalities in gene expression profiles characterize patients with inflammatory skin diseases, including psoriasis, and changes may reflect the action of specific therapeutic agents. To examine this, gene expression analysis of psoriatic skin was assessed by Gene Set Variation Analysis using informative gene modules, and longitudinal data were analyzed to assess the impact of various treatments. Ridge penalized logistic regression was employed to derive a transcriptomic score. Psoriatic lesional skin exhibited perturbations in gene expression profiles at baseline, with enrichment of signatures for neutrophils, keratinocytes, IFN, IL-12 complex, IL-1 cytokines, TNF, and T helper 17. Treatment with a variety of agents reduced lesional gene expression abnormalities to those in nonlesional skin. Specific gene expression abnormalities at baseline identified clinical responders to each treatment. Changes in gene expression over time were less pronounced in nonlesional skin and lesional skin in clinical nonresponders. The combined transcriptomic scores showed significant positive correlations with PASI scores in clinical responders over time. Overall, gene expression abnormalities characterize the severity of psoriatic skin lesions, can be used to predict responsiveness to individual treatments, and revert toward those of nonlesional skin with effective therapy. Therefore, gene expression analysis can be useful to support management of patients with psoriasis.