Integrated network analysis of transcriptomic and proteomic data in psoriasis.
BACKGROUND
Psoriasis is complex inflammatory skin pathology of autoimmune origin. Several cell types are perturbed in this pathology, and underlying signaling events are complex and still poorly understood.


RESULTS
In order to gain insight into molecular machinery underlying the disease, we conducted a comprehensive meta-analysis of proteomics and transcriptomics of psoriatic lesions from independent studies. Network-based analysis revealed similarities in regulation at both proteomics and transcriptomics level. We identified a group of transcription factors responsible for overexpression of psoriasis genes and a number of previously unknown signaling pathways that may play a role in this process. We also evaluated functional synergy between transcriptomics and proteomics results.


CONCLUSIONS
We developed network-based methodology for integrative analysis of high throughput data sets of different types. Investigation of proteomics and transcriptomics data sets on psoriasis revealed versatility in regulatory machinery underlying pathology and showed complementarities between two levels of cellular organization.
Piruzian
Eleonora
E
Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkina St, 3 GSP-1, 119991 Moscow, Russia.
Bruskin
Sergey
S
Ishkin
Alex
A
Abdeev
Rustam
R
Moshkovskii
Sergey
S
Melnik
Stanislav
S
Nikolsky
Yuri
Y
Nikolskaya
Tatiana
T
D000328:Adult; D001706:Biopsy; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D007249:Inflammation; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D040901:Proteomics / Q000379:methods*; D011565:Psoriasis / Q000378:metabolism*; D012867:Skin / Q000473:pathology; D049490:Systems Biology; D014158:Transcription, Genetic