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Weighted gene co-expression based biomarker discovery for psoriasis detection
Sudharsana Sundarrajan1, Mohanapriya Arumugam1
1Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology University, India.
Gene
|August 16, 2016
Summary
Researchers identified key psoriasis genes using weighted gene coexpression network analysis (WGCNA). These psoriasis-specific hub signatures can help discover biomarkers and new therapeutic targets for this chronic skin disease.
Area of Science:
- Dermatology
- Systems Biology
- Genetics
Background:
- Psoriasis is a chronic inflammatory skin disease with unknown causes.
- It presents as red, scaly plaques on the skin.
- Psoriasis is a growing focus for new drug development.
Purpose of the Study:
- To identify novel molecular targets for psoriasis using a systems biology approach.
- To discover potential biomarkers and therapeutic targets for psoriasis.
Main Methods:
- Weighted Gene Coexpression Network Analysis (WGCNA) was applied to 58 psoriatic lesional samples.
- Gene coexpression patterns were analyzed to identify five gene modules.
- Psoriasis-specific hub signature genes were selected from each module and validated.
Main Results:
- Five distinct gene modules related to psoriasis were identified.
- Ten highly connected genes from each module were identified as psoriasis-specific hub signatures.
- A classifier using these signature genes accurately distinguished psoriatic from normal samples (0.95-1.0 accuracy).
Conclusions:
- The identified signature genes show potential as biomarkers for psoriasis.
- These genes may lead to the development of new therapeutic strategies for psoriasis.
- WGCNA is an effective approach for identifying key drivers of psoriasis and can be applied to other diseases.
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