Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways

Research output: Contribution to journalJournal articleResearchpeer-review

  • David A Ewald
  • Dana Malajian
  • James G Krueger
  • Christopher T Workman
  • Tianjiao Wang
  • Suyan Tian
  • Litman, Thomas
  • Emma Guttman-Yassky
  • Mayte Suárez-Fariñas

BACKGROUND: Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies.

METHODS: We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome.

RESULTS: This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD "classifier genes" discriminate lesional from nonlesional skin, and may evaluate therapeutic responses.

CONCLUSIONS: Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease.

Original languageEnglish
JournalBMC Medical Genomics
Volume8
Pages (from-to)60
ISSN1755-8794
DOIs
Publication statusPublished - 12 Oct 2015
Externally publishedYes

    Research areas

  • Atherosclerosis/complications, Dermatitis, Atopic/complications, Gene Expression Profiling/methods, Gene Regulatory Networks, Humans, Lipid Metabolism/genetics, Th2 Cells/immunology

ID: 200580118