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Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?

Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of p...

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Autores principales: Curry, Philippa D. K., Morris, Andrew P., Barton, Anne, Bluett, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925377/
https://www.ncbi.nlm.nih.gov/pubmed/36243888
http://dx.doi.org/10.1038/s41397-022-00290-8
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author Curry, Philippa D. K.
Morris, Andrew P.
Barton, Anne
Bluett, James
author_facet Curry, Philippa D. K.
Morris, Andrew P.
Barton, Anne
Bluett, James
author_sort Curry, Philippa D. K.
collection PubMed
description Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to ‘trial and error’ drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management.
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spelling pubmed-99253772023-02-15 Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis? Curry, Philippa D. K. Morris, Andrew P. Barton, Anne Bluett, James Pharmacogenomics J Review Article Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to ‘trial and error’ drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management. Nature Publishing Group UK 2022-10-15 2023 /pmc/articles/PMC9925377/ /pubmed/36243888 http://dx.doi.org/10.1038/s41397-022-00290-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Article
Curry, Philippa D. K.
Morris, Andrew P.
Barton, Anne
Bluett, James
Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?
title Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?
title_full Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?
title_fullStr Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?
title_full_unstemmed Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?
title_short Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?
title_sort do genetics contribute to tnf inhibitor response prediction in psoriatic arthritis?
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925377/
https://www.ncbi.nlm.nih.gov/pubmed/36243888
http://dx.doi.org/10.1038/s41397-022-00290-8
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