TY - JOUR
T1 - Human and computational models of atopic dermatitis
T2 - A review and perspectives by an expert panel of the International Eczema Council
AU - Eyerich, Kilian
AU - Brown, Sara J.
AU - Perez White, Bethany E.
AU - Tanaka, Reiko J.
AU - Bissonette, Robert
AU - Dhar, Sandipan
AU - Bieber, Thomas
AU - Hijnen, Dirk J.
AU - Guttman-Yassky, Emma
AU - Irvine, Alan
AU - Thyssen, Jacob P.
AU - Vestergaard, Christian
AU - Werfel, Thomas
AU - Wollenberg, Andreas
AU - Paller, Amy S.
AU - Reynolds, Nick J.
N1 - Funding Information:
K.E. is funded by an ERC grant (IMCIS, 676858) and the German Research Foundation (EY97/3-1). S.J.B. holds a Wellcome Trust Senior Research Fellowship in Clinical Science (106865/Z/15/Z). B.E.P.W. is supported by the Dermatology Foundation and the National Institutes of Health (NIH)/National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS; P30AR057216 and 1K01AR072773-01A1). N.J.R.’s research/laboratory is funded in part by the Newcastle National Institute of Health Research (NIHR) Biomedical Research Centre, the Newcastle NIHR Medtech and In vitro diagnostic Co-operative, and the Newcastle MRC/EPSRC Molecular Pathology Node. J.P.T. is funded by an unrestricted grant from the Lundbeck Foundation.Disclosure of potential conflict of interest: K. Eyerich is funded by an ERC grant (IMCIS, 676858) and the German Research Foundation (EY97/3-2) and is a consultant and advisor/board member for Abbvie, Almirall, Berlin Chemie, Celgene, Hexal, Janssen, Leo, Lilly, Novartis, and Sanofi. S. J. Brown holds a Wellcome Trust Senior Research Fellowship in Clinical Science (106865/Z/15/Z) and reports honorarium from the British Society for Paediatric Dermatology and other support from the British Association of Dermatologists. B. E. Perez White reports grants from the Dermatology Foundation Research Career Development Award and from the National Institute of Arthritis, Musculoskeletal and Skin Diseases K01 Mentored Research Career Development Award and P30 Skin Disease Research Center Grant. R. J. Tanaka reports grants from the Engineering and Physical Sciences Research Council (EPSRC), the Royal Society, and the British Skin Foundation. R. Bissonette is an investigator, consultant, advisory board member, and speaker for and/or receives honoraria from Aquinox Pharma, Antiobix, Asana, Astellas, Brickell Biotech, Dermavant, Dermira, Dignity Sciences, Eli Lilly, Galderma, Glenmark, GlaxoSmithKline-Stiefel, Hoffman-LaRoche Ltd, Kiniksa, Leo Pharma, Neokera, Pfizer, Regeneron, Sienna, and Vitae and is also Shareholder of Innovaderm Research. T. Bieber is a consultant for Dermavant, AbbVie, Kymab, and Glenmark and a lecturer and consultant for Sanofi, Novartis, Lilly, Pfizer, and Almirall. E. Guttman-Yassky is a consultant and/or advisory board member for and/or received grants and/or personal fees from Novartis, Pfizer, Regeneron, Asnan, Dermira, Sanofi, Eli Lilly, Asana Bioscience, Kyowa Kirin, Allergan, Escalier, AbbVie, Celgene, Gladerma, Glenmark, LEO Pharmaceuticals, Novartis, Pfizer, Regeneron, DS Biopharma, Janssen Biotech, Innovaderm, Ralexar, Novan, Dermavant, Mitsubishi Tanabe, Concert, Amgen, and DBV. J. P. Thyssen is funded by an unrestricted grant from the Lundbeck Foundation. A. Wollenberg reports personal fees and/or grants and/or nonfinancial support from Almirall, Anacor, Astellas, Beiersdorf, Bioderma, Celgene, Chugai, Galderma, GlaxoSmithKline, Hans Karrer, Leo Pharma, L'Oreal, MEDA, MSD, Novartis, Pierre Fabre, Pfizer, Regeneron, and Sanofi. A. A. Paller is an investigator or consultant with and receives honoraria from AbbVie, Anaptysbio, Eli Lilly, Galderma, Incyte, Leo, Janssen, Novartis, Sanofi-Regeneron, Amgen, Asana, Dermavant, Dermira, Galderma, Forte, Matrisys, Menlo, Morphosys/Galapagos, and Pfizer. N. J. Reynolds has received grant support through Newcastle University from AstraZeneca, Bristol-Myers Squibb, Genentech, and GlaxoSmithKline and his research/laboratory is funded in part by the Newcastle National Institute of Health Research (NIHR) Biomedical Research Centre, the Newcastle NIHR Medtech and In vitro diagnostic Co-operative, and the Newcastle MRC/EPSRC Molecular Pathology Node. The rest of the authors declare that they have no relevant conflicts of interest.
Funding Information:
K.E. is funded by an ERC grant (IMCIS, 676858) and the German Research Foundation (EY97/3-1). S.J.B. holds a Wellcome Trust Senior Research Fellowship in Clinical Science (106865/Z/15/Z). B.E.P.W. is supported by the Dermatology Foundation and the National Institutes of Health (NIH)/ National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS; P30AR057216 and 1K01AR072773-01A1). N.J.R.’s research/laboratory is funded in part by the Newcastle National Institute of Health Research (NIHR) Biomedical Research Centre , the Newcastle NIHR Medtech and In vitro diagnostic Co-operative , and the Newcastle MRC / EPSRC Molecular Pathology Node. J.P.T. is funded by an unrestricted grant from the Lundbeck Foundation .
Publisher Copyright:
© 2018 The Authors
PY - 2019/1
Y1 - 2019/1
N2 - Atopic dermatitis (AD) is a prevalent disease worldwide and is associated with systemic comorbidities representing a significant burden on patients, their families, and society. Therapeutic options for AD remain limited, in part because of a lack of well-characterized animal models. There has been increasing interest in developing experimental approaches to study the pathogenesis of human AD in vivo, in vitro, and in silico to better define pathophysiologic mechanisms and identify novel therapeutic targets and biomarkers that predict therapeutic response. This review critically appraises a range of models, including genetic mutations relevant to AD, experimental challenge of human skin in vivo, tissue culture models, integration of “omics” data sets, and development of predictive computational models. Although no one individual model recapitulates the complex AD pathophysiology, our review highlights insights gained into key elements of cutaneous biology, molecular pathways, and therapeutic target identification through each approach. Recent developments in computational analysis, including application of machine learning and a systems approach to data integration and predictive modeling, highlight the applicability of these methods to AD subclassification (endotyping), therapy development, and precision medicine. Such predictive modeling will highlight knowledge gaps, further inform refinement of biological models, and support new experimental and systems approaches to AD.
AB - Atopic dermatitis (AD) is a prevalent disease worldwide and is associated with systemic comorbidities representing a significant burden on patients, their families, and society. Therapeutic options for AD remain limited, in part because of a lack of well-characterized animal models. There has been increasing interest in developing experimental approaches to study the pathogenesis of human AD in vivo, in vitro, and in silico to better define pathophysiologic mechanisms and identify novel therapeutic targets and biomarkers that predict therapeutic response. This review critically appraises a range of models, including genetic mutations relevant to AD, experimental challenge of human skin in vivo, tissue culture models, integration of “omics” data sets, and development of predictive computational models. Although no one individual model recapitulates the complex AD pathophysiology, our review highlights insights gained into key elements of cutaneous biology, molecular pathways, and therapeutic target identification through each approach. Recent developments in computational analysis, including application of machine learning and a systems approach to data integration and predictive modeling, highlight the applicability of these methods to AD subclassification (endotyping), therapy development, and precision medicine. Such predictive modeling will highlight knowledge gaps, further inform refinement of biological models, and support new experimental and systems approaches to AD.
KW - Atopic dermatitis
KW - atopic eczema
KW - endotype
KW - human models
KW - machine learning
KW - mechanistic models
KW - precision medicine
KW - skin equivalents
KW - systems biology
KW - tissue culture models
UR - http://www.scopus.com/inward/record.url?scp=85057800409&partnerID=8YFLogxK
U2 - 10.1016/j.jaci.2018.10.033
DO - 10.1016/j.jaci.2018.10.033
M3 - Article
C2 - 30414395
AN - SCOPUS:85057800409
SN - 0091-6749
VL - 143
SP - 36
EP - 45
JO - Journal of Allergy and Clinical Immunology
JF - Journal of Allergy and Clinical Immunology
IS - 1
ER -