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

48 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

Funding Information:
This work was supported in part by US Public Health Service National Institutes of Health NIAMS grants R01AR056016 (to AMC), R21AR061881 (to AMC and RC), U01AR067173 (to AMC) and P30AR044535 (the Columbia University Skin Disease Research Center), as well as the Locks of Love Foundation and the Alopecia Areata Initiative . JEC and JCC are supported by the T32GM082771 Medical Genetics Training Grant (issued to AMC). AJ is supported by a NIAMS grant ( K08AR069111 ), a Physician Scientist Career Development Award from the Dermatology Foundation, the Louis V. Gerstner Jr Scholars Program, and the Irving Scholars Program from the Irving Institute for Clinical and Translational Research at the Columbia University Medical Center.

Publisher Copyright:
© 2016 The Authors.

Keywords

  • Alopecia areata
  • Autoimmune
  • Biomarkers

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