Molecular signatures define alopecia areata subtypes and transcriptional biomarkers

• Gene expression analysis of 96 scalp biopsies from patients with alopecia areata (AA) and healthy controls was performed.
• Samples from AA patchy, alopecia universalis/totalis and control patients formed distinct clusters by gene expression.
• A set of gene expression biomarkers, the Alopecia Areata Disease Activity Index (ALADIN), was formulated.
• ALADIN distinguished AA phenotypes and normal controls.
• ALADIN may have utility in clinical trials of AA.Alopecia areata is a disease characterized by autoimmune attack of the hair follicle. A complete understanding of the signaling pathways involved in the disease is lacking. Based on gene expression profiling of skin samples from 96 patients and controls, a set of biomarkers, termed the Alopecia Areata Disease Activity Index, or ALADIN, was formulated. ALADIN was able to distinguish samples from patients with patchy disease from samples from patients with the more extensive forms of disease. The usefulness of this biomarker tool is ready to be assessed in clinical trials of therapeutics for alopecia areata.

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.