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PLoS One. 2010 Apr 20;5(4):e10247. doi: 10.1371/journal.pone.0010247.

Evaluation of the psoriasis transcriptome across different studies by gene set enrichment analysis (GSEA).

Author information

1
Laboratory for Investigative Dermatology, The Rockefeller University, New York, New York, United States of America.

Abstract

BACKGROUND:

Our objective was to develop a consistent molecular definition of psoriasis. There have been several published microarray studies of psoriasis, and we compared disease-related genes identified across these different studies of psoriasis with our own in order to establish a consensus.

METHODOLOGY/PRINCIPAL FINDINGS:

We present a psoriasis transcriptome from a group of 15 patients enrolled in a clinical study, and assessed its biological validity using a set of important pathways known to be involved in psoriasis. We also identified a key set of cytokines that are now strongly implicated in driving disease-related pathology, but which are not detected well on gene array platforms and require more sensitive methods to measure mRNA levels in skin tissues. Comparison of our transcriptome with three other published lists of psoriasis genes showed apparent inconsistencies based on the number of overlapping genes. We extended the well-established approach of Gene Set Enrichment Analysis (GSEA) to compare a new study with these other published list of differentially expressed genes (DEG) in a more comprehensive manner. We applied our method to these three published psoriasis transcriptomes and found them to be in good agreement with our study.

CONCLUSIONS/SIGNIFICANCE:

Due to wide variability in clinical protocols, platform and sample handling, and subtle disease-related signals, intersection of published DEG lists was unable to establish consensus between studies. In order to leverage the power of multiple transcriptomes reported by several laboratories using different patients and protocols, more sophisticated methods like the extension of GSEA presented here, should be used in order to overcome the shortcomings of overlapping individual DEG approach.

PMID:
20422035
PMCID:
PMC2857878
DOI:
10.1371/journal.pone.0010247
[Indexed for MEDLINE]
Free PMC Article

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