Molecular signatures define alopecia areata subtypes and transcriptional biomarkers

Ali Jabbari, Jane E. Cerise, James C. Chen, Julian Mackay-Wiggan, Madeleine Duvic, Vera Price, Maria Hordinsky, David Norris, Raphael Clynes, Angela M. Christiano

Research output: Contribution to journalArticlepeer-review

72 Scopus citations

Abstract

Alopecia areata (AA) is an autoimmune disease typified by nonscarring hair loss with a variable clinical course. In this study, we conducted whole genome gene expression analysis of 96 human scalp skin biopsy specimens from AA or normal control subjects. Based on gene expression profiling, samples formed distinct clusters based on the presence or absence of disease as well as disease phenotype (patchy disease compared with alopecia totalis or universalis). Differential gene expression analysis allowed us to robustly demonstrate graded immune activity in samples of increasing phenotypic severity and generate a quantitative gene expression scoring system that classified samples based on interferon and cytotoxic T lymphocyte immune signatures critical for disease pathogenesis.

Original languageEnglish (US)
Pages (from-to)240-247
Number of pages8
JournalEBioMedicine
Volume7
DOIs
StatePublished - May 1 2016

Bibliographical note

Publisher Copyright:
© 2016 The Authors.

Keywords

  • Alopecia areata
  • Autoimmune
  • Biomarkers

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