The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis.
Biomarkers
Druggability
Network analysis
Psoriasis
Public data
Transcriptomics
Journal
Human genomics
ISSN: 1479-7364
Titre abrégé: Hum Genomics
Pays: England
ID NLM: 101202210
Informations de publication
Date de publication:
28 11 2022
28 11 2022
Historique:
received:
05
09
2022
accepted:
07
11
2022
entrez:
27
11
2022
pubmed:
28
11
2022
medline:
30
11
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 36437479
doi: 10.1186/s40246-022-00431-x
pii: 10.1186/s40246-022-00431-x
pmc: PMC9703794
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
62Informations de copyright
© 2022. The Author(s).
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