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Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis

Atopic dermatitis (AD) is a skin disease that is heterogeneous both in terms of clinical manifestations and molecular profiles. It is increasingly recognized that AD is a systemic rather than a local disease and should be assessed in the context of whole-body pathophysiology. Here we show, via integ...

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Autores principales: Sekita, Aiko, Kawasaki, Hiroshi, Fukushima-Nomura, Ayano, Yashiro, Kiyoshi, Tanese, Keiji, Toshima, Susumu, Ashizaki, Koichi, Miyai, Tomohiro, Yazaki, Junshi, Kobayashi, Atsuo, Namba, Shinichi, Naito, Tatsuhiko, Wang, Qingbo S., Kawakami, Eiryo, Seita, Jun, Ohara, Osamu, Sakurada, Kazuhiro, Okada, Yukinori, Amagai, Masayuki, Koseki, Haruhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545679/
https://www.ncbi.nlm.nih.gov/pubmed/37783685
http://dx.doi.org/10.1038/s41467-023-41857-8
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author Sekita, Aiko
Kawasaki, Hiroshi
Fukushima-Nomura, Ayano
Yashiro, Kiyoshi
Tanese, Keiji
Toshima, Susumu
Ashizaki, Koichi
Miyai, Tomohiro
Yazaki, Junshi
Kobayashi, Atsuo
Namba, Shinichi
Naito, Tatsuhiko
Wang, Qingbo S.
Kawakami, Eiryo
Seita, Jun
Ohara, Osamu
Sakurada, Kazuhiro
Okada, Yukinori
Amagai, Masayuki
Koseki, Haruhiko
author_facet Sekita, Aiko
Kawasaki, Hiroshi
Fukushima-Nomura, Ayano
Yashiro, Kiyoshi
Tanese, Keiji
Toshima, Susumu
Ashizaki, Koichi
Miyai, Tomohiro
Yazaki, Junshi
Kobayashi, Atsuo
Namba, Shinichi
Naito, Tatsuhiko
Wang, Qingbo S.
Kawakami, Eiryo
Seita, Jun
Ohara, Osamu
Sakurada, Kazuhiro
Okada, Yukinori
Amagai, Masayuki
Koseki, Haruhiko
author_sort Sekita, Aiko
collection PubMed
description Atopic dermatitis (AD) is a skin disease that is heterogeneous both in terms of clinical manifestations and molecular profiles. It is increasingly recognized that AD is a systemic rather than a local disease and should be assessed in the context of whole-body pathophysiology. Here we show, via integrated RNA-sequencing of skin tissue and peripheral blood mononuclear cell (PBMC) samples along with clinical data from 115 AD patients and 14 matched healthy controls, that specific clinical presentations associate with matching differential molecular signatures. We establish a regression model based on transcriptome modules identified in weighted gene co-expression network analysis to extract molecular features associated with detailed clinical phenotypes of AD. The two main, qualitatively differential skin manifestations of AD, erythema and papulation are distinguished by differential immunological signatures. We further apply the regression model to a longitudinal dataset of 30 AD patients for personalized monitoring, highlighting patient heterogeneity in disease trajectories. The longitudinal features of blood tests and PBMC transcriptome modules identify three patient clusters which are aligned with clinical severity and reflect treatment history. Our approach thus serves as a framework for effective clinical investigation to gain a holistic view on the pathophysiology of complex human diseases.
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spelling pubmed-105456792023-10-04 Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis Sekita, Aiko Kawasaki, Hiroshi Fukushima-Nomura, Ayano Yashiro, Kiyoshi Tanese, Keiji Toshima, Susumu Ashizaki, Koichi Miyai, Tomohiro Yazaki, Junshi Kobayashi, Atsuo Namba, Shinichi Naito, Tatsuhiko Wang, Qingbo S. Kawakami, Eiryo Seita, Jun Ohara, Osamu Sakurada, Kazuhiro Okada, Yukinori Amagai, Masayuki Koseki, Haruhiko Nat Commun Article Atopic dermatitis (AD) is a skin disease that is heterogeneous both in terms of clinical manifestations and molecular profiles. It is increasingly recognized that AD is a systemic rather than a local disease and should be assessed in the context of whole-body pathophysiology. Here we show, via integrated RNA-sequencing of skin tissue and peripheral blood mononuclear cell (PBMC) samples along with clinical data from 115 AD patients and 14 matched healthy controls, that specific clinical presentations associate with matching differential molecular signatures. We establish a regression model based on transcriptome modules identified in weighted gene co-expression network analysis to extract molecular features associated with detailed clinical phenotypes of AD. The two main, qualitatively differential skin manifestations of AD, erythema and papulation are distinguished by differential immunological signatures. We further apply the regression model to a longitudinal dataset of 30 AD patients for personalized monitoring, highlighting patient heterogeneity in disease trajectories. The longitudinal features of blood tests and PBMC transcriptome modules identify three patient clusters which are aligned with clinical severity and reflect treatment history. Our approach thus serves as a framework for effective clinical investigation to gain a holistic view on the pathophysiology of complex human diseases. Nature Publishing Group UK 2023-10-02 /pmc/articles/PMC10545679/ /pubmed/37783685 http://dx.doi.org/10.1038/s41467-023-41857-8 Text en © The Author(s) 2023 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 Article
Sekita, Aiko
Kawasaki, Hiroshi
Fukushima-Nomura, Ayano
Yashiro, Kiyoshi
Tanese, Keiji
Toshima, Susumu
Ashizaki, Koichi
Miyai, Tomohiro
Yazaki, Junshi
Kobayashi, Atsuo
Namba, Shinichi
Naito, Tatsuhiko
Wang, Qingbo S.
Kawakami, Eiryo
Seita, Jun
Ohara, Osamu
Sakurada, Kazuhiro
Okada, Yukinori
Amagai, Masayuki
Koseki, Haruhiko
Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
title Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
title_full Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
title_fullStr Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
title_full_unstemmed Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
title_short Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
title_sort multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545679/
https://www.ncbi.nlm.nih.gov/pubmed/37783685
http://dx.doi.org/10.1038/s41467-023-41857-8
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