The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis
Abstract In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integ...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-11-01
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| Series: | Human Genomics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40246-022-00431-x |
| _version_ | 1828095774338056192 |
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| author | Antonio Federico Alisa Pavel Lena Möbus David McKean Giusy del Giudice Vittorio Fortino Hanna Niehues Joe Rastrick Kilian Eyerich Stefanie Eyerich Ellen van den Bogaard Catherine Smith Stephan Weidinger Emanuele de Rinaldis Dario Greco |
| author_facet | Antonio Federico Alisa Pavel Lena Möbus David McKean Giusy del Giudice Vittorio Fortino Hanna Niehues Joe Rastrick Kilian Eyerich Stefanie Eyerich Ellen van den Bogaard Catherine Smith Stephan Weidinger Emanuele de Rinaldis Dario Greco |
| author_sort | Antonio Federico |
| collection | DOAJ |
| description | Abstract In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic lesions and uninvolved skin. Moreover, we curated and exploited a wide range of functional information from multiple public sources in order to systematically annotate the inferred networks. The integrated analysis of transcriptomics data and co-expression networks highlighted genes that are frequently dysregulated and show aberrant patterns of connectivity in the psoriatic lesion compared with the unaffected skin. Our approach allowed us to also identify plausible, previously unknown, actors in the expression of the psoriasis phenotype. Finally, we characterized communities of co-expressed genes associated with relevant molecular functions and expression signatures of specific immune cell types associated with the psoriasis lesion. Overall, integrating experimental driven results with curated functional information from public repositories represents an efficient approach to empower knowledge generation about psoriasis and may be applicable to other complex diseases. |
| first_indexed | 2024-04-11T07:18:53Z |
| format | Article |
| id | doaj.art-8473f595cc8244e4b27dafb8dc20816a |
| institution | Directory Open Access Journal |
| issn | 1479-7364 |
| language | English |
| last_indexed | 2024-04-11T07:18:53Z |
| publishDate | 2022-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Human Genomics |
| spelling | doaj.art-8473f595cc8244e4b27dafb8dc20816a2022-12-22T04:37:49ZengBMCHuman Genomics1479-73642022-11-0116111610.1186/s40246-022-00431-xThe integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasisAntonio Federico0Alisa Pavel1Lena Möbus2David McKean3Giusy del Giudice4Vittorio Fortino5Hanna Niehues6Joe Rastrick7Kilian Eyerich8Stefanie Eyerich9Ellen van den Bogaard10Catherine Smith11Stephan Weidinger12Emanuele de Rinaldis13Dario Greco14Faculty of Medicine and Health Technology, Tampere UniversityFaculty of Medicine and Health Technology, Tampere UniversityFaculty of Medicine and Health Technology, Tampere UniversitySanofi Immunology and Inflammation Research Therapeutic Area, Precision Immunology ClusterFaculty of Medicine and Health Technology, Tampere UniversityInstitute of Biomedicine, University of Eastern FinlandDepartment of Dermatology, Radboud University Medical Center, Radboud Institute for Molecular Life SciencesImmunology Therapeutic Area, UCB PharmaDepartment of Dermatology and Allergy, Technical University of MunichZAUM-Center of Allergy and Environment, Technical University and Helmholtz Center MunichDepartment of Dermatology, Radboud University Medical Center, Radboud Institute for Molecular Life SciencesSt. John’s Institute of Dermatology, King’s College LondonDepartment of Dermatology, Kiel UniversitySanofi Immunology and Inflammation Research Therapeutic Area, Precision Immunology ClusterFaculty of Medicine and Health Technology, Tampere UniversityAbstract In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic lesions and uninvolved skin. Moreover, we curated and exploited a wide range of functional information from multiple public sources in order to systematically annotate the inferred networks. The integrated analysis of transcriptomics data and co-expression networks highlighted genes that are frequently dysregulated and show aberrant patterns of connectivity in the psoriatic lesion compared with the unaffected skin. Our approach allowed us to also identify plausible, previously unknown, actors in the expression of the psoriasis phenotype. Finally, we characterized communities of co-expressed genes associated with relevant molecular functions and expression signatures of specific immune cell types associated with the psoriasis lesion. Overall, integrating experimental driven results with curated functional information from public repositories represents an efficient approach to empower knowledge generation about psoriasis and may be applicable to other complex diseases.https://doi.org/10.1186/s40246-022-00431-xPsoriasisTranscriptomicsNetwork analysisBiomarkersPublic dataDruggability |
| spellingShingle | Antonio Federico Alisa Pavel Lena Möbus David McKean Giusy del Giudice Vittorio Fortino Hanna Niehues Joe Rastrick Kilian Eyerich Stefanie Eyerich Ellen van den Bogaard Catherine Smith Stephan Weidinger Emanuele de Rinaldis Dario Greco The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis Human Genomics Psoriasis Transcriptomics Network analysis Biomarkers Public data Druggability |
| title | The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis |
| title_full | The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis |
| title_fullStr | The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis |
| title_full_unstemmed | The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis |
| title_short | The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis |
| title_sort | integration of large scale public data and network analysis uncovers molecular characteristics of psoriasis |
| topic | Psoriasis Transcriptomics Network analysis Biomarkers Public data Druggability |
| url | https://doi.org/10.1186/s40246-022-00431-x |
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