Dataset Information

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 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.

SUBMITTER: Federico A

PROVIDER: S-EPMC9703794 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis.

Federico Antonio A Pavel Alisa A Möbus Lena L McKean David D Del Giudice Giusy G Fortino Vittorio V Niehues Hanna H Rastrick Joe J Eyerich Kilian K Eyerich Stefanie S van den Bogaard Ellen E Smith Catherine C Weidinger Stephan S de Rinaldis Emanuele E Greco Dario D

Human genomics 20221128 1

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 lesio ...[more]

PMID: 36437479

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Dataset Information

The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis.

Publications

The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis.

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