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

Aiko Sekita, Hiroshi Kawasaki, Ayano Fukushima-Nomura, Kiyoshi Yashiro, Keiji Tanese, Susumu Toshima, Koichi Ashizaki, Tomohiro Miyai, Junshi Yazaki, Atsuo Kobayashi, Shinichi Namba, Tatsuhiko Naito, Qingbo S. Wang, Eiryo Kawakami, Jun Seita, Osamu Ohara, Kazuhiro Sakurada, Yukinori Okada (), Masayuki Amagai () and Haruhiko Koseki ()
Additional contact information
Aiko Sekita: RIKEN Center for Integrative Medical Sciences
Hiroshi Kawasaki: RIKEN Center for Integrative Medical Sciences
Ayano Fukushima-Nomura: Keio University School of Medicine
Kiyoshi Yashiro: Keio University School of Medicine
Keiji Tanese: Keio University School of Medicine
Susumu Toshima: RIKEN Center for Integrative Medical Sciences
Koichi Ashizaki: RIKEN Center for Integrative Medical Sciences
Tomohiro Miyai: RIKEN Center for Integrative Medical Sciences
Junshi Yazaki: RIKEN Center for Integrative Medical Sciences
Atsuo Kobayashi: RIKEN Center for Integrative Medical Sciences
Shinichi Namba: Osaka University Graduate School of Medicine
Tatsuhiko Naito: Osaka University Graduate School of Medicine
Qingbo S. Wang: RIKEN Center for Integrative Medical Sciences
Eiryo Kawakami: RIKEN Information R&D and Strategy Headquarters
Jun Seita: RIKEN Center for Integrative Medical Sciences
Osamu Ohara: Kazusa DNA Research Institute
Kazuhiro Sakurada: RIKEN Information R&D and Strategy Headquarters
Yukinori Okada: RIKEN Center for Integrative Medical Sciences
Masayuki Amagai: RIKEN Center for Integrative Medical Sciences
Haruhiko Koseki: RIKEN Center for Integrative Medical Sciences

Nature Communications, 2023, vol. 14, issue 1, 1-16

Abstract: Abstract 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.

Date: 2023
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DOI: 10.1038/s41467-023-41857-8

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