Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
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,...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-41857-8 |
| _version_ | 1797558536979349504 |
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| author | 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 Haruhiko Koseki |
| author_facet | 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 Haruhiko Koseki |
| author_sort | Aiko Sekita |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T17:31:50Z |
| format | Article |
| id | doaj.art-a3febd05fa144c68a981cadc89884897 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-10T17:31:50Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-a3febd05fa144c68a981cadc898848972023-11-20T09:59:36ZengNature PortfolioNature Communications2041-17232023-10-0114111610.1038/s41467-023-41857-8Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitisAiko Sekita0Hiroshi Kawasaki1Ayano Fukushima-Nomura2Kiyoshi Yashiro3Keiji Tanese4Susumu Toshima5Koichi Ashizaki6Tomohiro Miyai7Junshi Yazaki8Atsuo Kobayashi9Shinichi Namba10Tatsuhiko Naito11Qingbo S. Wang12Eiryo Kawakami13Jun Seita14Osamu Ohara15Kazuhiro Sakurada16Yukinori Okada17Masayuki Amagai18Haruhiko Koseki19RIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesDepartment of Dermatology, Keio University School of MedicineDepartment of Dermatology, Keio University School of MedicineDepartment of Dermatology, Keio University School of MedicineRIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesDepartment of Statistical Genetics, Osaka University Graduate School of MedicineDepartment of Statistical Genetics, Osaka University Graduate School of MedicineRIKEN Center for Integrative Medical SciencesAdvanced Data Science Project, RIKEN Information R&D and Strategy HeadquartersRIKEN Center for Integrative Medical SciencesKazusa DNA Research InstituteAdvanced Data Science Project, RIKEN Information R&D and Strategy HeadquartersRIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesRIKEN Center for Integrative Medical SciencesAbstract 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.https://doi.org/10.1038/s41467-023-41857-8 |
| spellingShingle | 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 Haruhiko Koseki Multifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis Nature Communications |
| 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 |
| url | https://doi.org/10.1038/s41467-023-41857-8 |
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