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Molecular signatures define alopecia areata subtypes and transcriptional biomarkers.

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.

SUBMITTER: Jabbari A

PROVIDER: S-EPMC4909368 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Molecular signatures define alopecia areata subtypes and transcriptional biomarkers.

Jabbari Ali A Cerise Jane E JE Chen James C JC Mackay-Wiggan Julian J Duvic Madeleine M Price Vera V Hordinsky Maria M Norris David D Clynes Raphael R Christiano Angela M AM

EBioMedicine 20160331

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 a ...[more]

PMID: 27322477

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Project description:IntroductionIndividuals with alopecia areata (AA) may experience significant impacts on their health-related quality of life. The novel Alopecia Areata Patient Priority Outcomes (AAPPO) questionnaire has been developed to assess hair loss signs, emotional symptoms, and activity limitations associated with AA. The objective of this study was to evaluate psychometric properties and establish scoring of the AAPPO in adults and adolescents with AA.MethodsScoring and measurement properties of the AAPPO were examined using baseline and 2-week follow-up data from a prospective, noninterventional, web-based study of 121 patients with AA (85 adults aged ≥ 18 years, 36 adolescents aged 12-17 years) with Severity of Alopecia Tool (SALT) ≥ 25% scalp hair loss.ResultsExploratory and confirmatory factor analysis supported four single Hair Loss (HL) items, an Emotional Symptoms domain (ES; 4 items), and an Activity Limitations domain (AL; 3 items). Among all patients, the multi-item ES and AL domains had strong internal consistency (α ≥ 0.87); all HL items and domain scores had strong test-retest reliability (weighted kappa or intraclass correlation coefficients ≥ 0.78). All HL item scores demonstrated strong construct validity (r ≥ 0.52) compared with the patient-reported Alopecia Areata Symptom and Impact Scale (AASIS) hair loss subscale score; ES and AL domain scores exhibited strong construct validity (r ≥ 0.66) compared with the SF-36 Mental Component Summary (MCS) score. Using SALT scores, HL mean item scores were better (lower) in the 25-49% SALT subgroup versus those with highest SALT scores (76-100%); however, ES mean domain scores were better in the SALT 76-100% subgroup in the same comparison (p < 0.0001). Using AASIS and MCS score-created subgroups, ES and AL mean domain scores demonstrated hypothesized differences across subgroups (all p values < 0.0001).ConclusionThe AAPPO questionnaire is a reliable, valid disease-specific measure of hair loss severity and impact in individuals with AA.

Dataset Information

Molecular signatures define alopecia areata subtypes and transcriptional biomarkers.

Publications

Molecular signatures define alopecia areata subtypes and transcriptional biomarkers.

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