Computational Systems Biology of Psoriasis: Are We Ready for the Age of Omics and Systems Biomarkers?

Sevimoglu T., ARĞA K. Y.

OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY, cilt.19, sa.11, ss.669-687, 2015 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 19 Konu: 11
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1089/omi.2015.0096
  • Sayfa Sayıları: ss.669-687


Computational biology and omics' systems sciences are greatly impacting research on common diseases such as cancer. By contrast, dermatology covering an array of skin diseases with high prevalence in society, has received relatively less attention from omics' and computational biosciences. We are focusing on psoriasis, a common and debilitating autoimmune disease involving skin and joints. Using computational systems biology and reconstruction, topological, modular, and a novel correlational analyses (based on fold changes) of biological and transcriptional regulatory networks, we analyzed and integrated data from a total of twelve studies from the Gene Expression Omnibus (sample size=534). Samples represented a comprehensive continuum from lesional and nonlesional skin, as well as bone marrow and dermal mesenchymal stem cells. We identified and propose here a JAK/STAT signaling pathway significant for psoriasis. Importantly, cytokines, interferon-stimulated genes, antimicrobial peptides, among other proteins, were involved in intrinsic parts of the proposed pathway. Several biomarker and therapeutic candidates such as SUB1 are discussed for future experimental studies. The integrative systems biology approach presented here illustrates a comprehensive perspective on the molecular basis of psoriasis. This also attests to the promise of systems biology research in skin diseases, with psoriasis as a systemic component. The present study reports, to the best of our knowledge, the largest set of microarray datasets on psoriasis, to offer new insights into the disease mechanisms with a proposal of a disease pathway. We call for greater computational systems biology research and analyses in dermatology and skin diseases in general.