A Framework for Multi-Omic Prediction of Treatment Response to Biologic Therapy for Psoriasis.

Autor:	Foulkes AC; The Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK. Electronic address: Amy.foulkes@manchester.ac.uk., Watson DS; Centre for Translational Bioinformatics, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, UK., Carr DF; Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK., Kenny JG; Centre for Genomic Research, The University of Liverpool, Liverpool, UK., Slidel T; MedImmune Ltd, Sir Aaron Klug Building, Granta Park Cambridge, UK., Parslew R; Dermatology Department, Kent Lodge, Broadgreen Hospital, Liverpool, UK., Pirmohamed M; Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK., Anders S; Centre for Molecular Biology of the University of Heidelberg (ZMBH), Heidelberg, Germany., Reynolds NJ; Institute of Cellular Medicine, Newcastle University and Department of Dermatology, Royal Victoria Infirmary, Newcastle upon Tyne, UK., Griffiths CEM; The Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK., Warren RB; The Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK., Barnes MR; Centre for Translational Bioinformatics, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, UK.
Jazyk:	angličtina
Zdroj:	The Journal of investigative dermatology [J Invest Dermatol] 2019 Jan; Vol. 139 (1), pp. 100-107. Date of Electronic Publication: 2018 Jul 17.
DOI:	10.1016/j.jid.2018.04.041
Abstrakt:	Biologic therapies have shown high efficacy in psoriasis, but individual response varies and is poorly understood. To inform biomarker discovery in the Psoriasis Stratification to Optimise Relevant Therapy (i.e., PSORT) study, we evaluated a comprehensive array of omics platforms across three time points and multiple tissues in a pilot investigation of 10 patients with severe psoriasis, treated with the tumor necrosis factor (TNF) inhibitor, etanercept. We used RNA sequencing to analyze mRNA and small RNA transcriptome in blood, lesional and nonlesional skin, and the SOMAscan platform to investigate the serum proteome. Using an integrative systems biology approach, we identified signals of treatment response in genes and pathways associated with TNF signaling, psoriasis pathology, and the major histocompatibility complex region. We found association between clinical response and TNF-regulated genes in blood and skin. Using a combination of differential expression testing, upstream regulator analysis, clustering techniques, and predictive modeling, we show that baseline samples are indicative of patient response to biologic therapies, including signals in blood, which have traditionally been considered unreliable for inference in dermatology. In conclusion, our pilot study provides both an analytical framework and empirical basis to estimate power for larger studies, specifically the ongoing PSORT study, which we show as powered for biomarker discovery and patient stratification. (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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