Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis

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 infor...

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Main Authors: Sneha Shrotri, Andrea Daamen, Kathryn Kingsmore, Prathyusha Bachali, Amrie Grammer, Peter Lipsky
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:JID Innovations
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Online Access:http://www.sciencedirect.com/science/article/pii/S266702672400081X
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author Sneha Shrotri
Andrea Daamen
Kathryn Kingsmore
Prathyusha Bachali
Amrie Grammer
Peter Lipsky
author_facet Sneha Shrotri
Andrea Daamen
Kathryn Kingsmore
Prathyusha Bachali
Amrie Grammer
Peter Lipsky
author_sort Sneha Shrotri
collection DOAJ
description 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.
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spelling doaj-art-8250c95d4e574b6597ac0b39d3d8a1a92025-08-20T02:52:31ZengElsevierJID Innovations2667-02672025-03-015210033310.1016/j.xjidi.2024.100333Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in PsoriasisSneha Shrotri0Andrea Daamen1Kathryn Kingsmore2Prathyusha Bachali3Amrie Grammer4Peter Lipsky5AMPEL BioSolutions LLC, Charlottesville, Virginia, USA; RILITE Research Institute, Charlottesville, Virginia, USAAMPEL BioSolutions LLC, Charlottesville, Virginia, USA; RILITE Research Institute, Charlottesville, Virginia, USA; Correspondence: Andrea Daamen, AMPEL BioSolutions LLC, 250 West Main Street, Suite 300, Charlottesville, Virginia 22902, USA.AMPEL BioSolutions LLC, Charlottesville, Virginia, USA; RILITE Research Institute, Charlottesville, Virginia, USAAMPEL BioSolutions LLC, Charlottesville, Virginia, USA; RILITE Research Institute, Charlottesville, Virginia, USAAMPEL BioSolutions LLC, Charlottesville, Virginia, USA; RILITE Research Institute, Charlottesville, Virginia, USAAMPEL BioSolutions LLC, Charlottesville, Virginia, USA; RILITE Research Institute, Charlottesville, Virginia, USAAbnormalities 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.http://www.sciencedirect.com/science/article/pii/S266702672400081XBioinformaticsDrug reactionsInflammatory skin diseasesPsoriasis
spellingShingle Sneha Shrotri
Andrea Daamen
Kathryn Kingsmore
Prathyusha Bachali
Amrie Grammer
Peter Lipsky
Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis
JID Innovations
Bioinformatics
Drug reactions
Inflammatory skin diseases
Psoriasis
title Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis
title_full Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis
title_fullStr Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis
title_full_unstemmed Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis
title_short Transcriptomic Analysis Identifies Disease Severity and Therapeutic Response in Psoriasis
title_sort transcriptomic analysis identifies disease severity and therapeutic response in psoriasis
topic Bioinformatics
Drug reactions
Inflammatory skin diseases
Psoriasis
url http://www.sciencedirect.com/science/article/pii/S266702672400081X
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AT kathrynkingsmore transcriptomicanalysisidentifiesdiseaseseverityandtherapeuticresponseinpsoriasis
AT prathyushabachali transcriptomicanalysisidentifiesdiseaseseverityandtherapeuticresponseinpsoriasis
AT amriegrammer transcriptomicanalysisidentifiesdiseaseseverityandtherapeuticresponseinpsoriasis
AT peterlipsky transcriptomicanalysisidentifiesdiseaseseverityandtherapeuticresponseinpsoriasis