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1.
Exp Dermatol ; 29(3): 243-253, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31169925

RESUMO

Alopecia areata (AA) is a highly prevalent autoimmune disease that attacks the hair follicle and leads to hair loss that can range from small patches to complete loss of scalp and body hair. Our previous linkage and genome-wide association studies (GWAS) generated strong evidence for aetiological contributions from inherited genetic variants at different population frequencies, including both rare mutations and common polymorphisms. Additionally, we conducted gene expression (GE) studies on scalp biopsies of 96 patients and controls to establish signatures of active disease. In this study, we performed an integrative analysis on these two datasets to test the hypothesis that rare CNVs in patients with AA could be leveraged to identify drivers of disease in our AA GE signatures. We analysed copy number variants (CNVs) in a case-control cohort of 673 patients with AA and 16 311 controls independent of the case-control cohort of 96 research participants used in our GE study. Using an integrative computational analysis, we identified 14 genes whose expression levels were altered by CNVs in a consistent direction of effect, corresponding to gene expression changes in lesional skin of patients. Four of these genes were affected by CNVs in three or more unrelated patients with AA, including ATG4B and SMARCA2, which are involved in autophagy and chromatin remodelling, respectively. Our findings identified new classes of genes with potential contributions to AA pathogenesis.


Assuntos
Alopecia em Áreas/genética , Alopecia em Áreas/imunologia , Autofagia , Variações do Número de Cópias de DNA , Dosagem de Genes , Proteínas Relacionadas à Autofagia/genética , Cisteína Endopeptidases/genética , Perfilação da Expressão Gênica , Estudo de Associação Genômica Ampla , Genótipo , Cabelo/patologia , Folículo Piloso/fisiologia , Humanos , Mutação , Reação em Cadeia da Polimerase , Polimorfismo de Nucleotídeo Único , Couro Cabeludo/patologia , Fatores de Transcrição/genética
2.
Nat Commun ; 13(1): 800, 2022 02 10.
Artigo em Inglês | MEDLINE | ID: mdl-35145093

RESUMO

Alopecia areata is a complex genetic disease that results in hair loss due to the autoimmune-mediated attack of the hair follicle. We previously defined a role for both rare and common variants in our earlier GWAS and linkage studies. Here, we identify rare variants contributing to Alopecia Areata using a whole exome sequencing and gene-level burden analyses approach on 849 Alopecia Areata patients compared to 15,640 controls. KRT82 is identified as an Alopecia Areata risk gene with rare damaging variants in 51 heterozygous Alopecia Areata individuals (6.01%), achieving genome-wide significance (p = 2.18E-07). KRT82 encodes a hair-specific type II keratin that is exclusively expressed in the hair shaft cuticle during anagen phase, and its expression is decreased in Alopecia Areata patient skin and hair follicles. Finally, we find that cases with an identified damaging KRT82 variant and reduced KRT82 expression have elevated perifollicular CD8 infiltrates. In this work, we utilize whole exome sequencing to successfully identify a significant Alopecia Areata disease-relevant gene, KRT82, and reveal a proposed mechanism for rare variant predisposition leading to disrupted hair shaft integrity.


Assuntos
Alopecia em Áreas/genética , Alopecia em Áreas/metabolismo , Sequenciamento do Exoma , Queratinas Específicas do Cabelo/genética , Queratinas Tipo II/genética , Predisposição Genética para Doença , Variação Genética , Cabelo/metabolismo , Folículo Piloso/metabolismo , Humanos , Pele/metabolismo
3.
PNAS Nexus ; 1(3): pgac111, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-35899069

RESUMO

The primary forms of cicatricial (scarring) alopecia (PCA) are a group of inflammatory, irreversible hair loss disorders characterized by immune cell infiltrates targeting hair follicles (HFs). Lichen planopilaris (LPP), frontal fibrosing alopecia (FFA), and centrifugal cicatricial alopecia (CCCA) are among the main subtypes of PCAs. The pathogenesis of the different types of PCAs are poorly understood, and current treatment regimens yield inconsistent and unsatisfactory results. We performed high-throughput RNA-sequencing on scalp biopsies of a large cohort PCA patients to develop gene expression-based signatures, trained into machine-learning-based predictive models and pathways associated with dysregulated gene expression. We performed morphological and cytokine analysis to define the immune cell populations found in PCA subtypes. We identified a common PCA gene signature that was shared between LPP, FFA, and CCCA, which revealed a significant over-representation of mast cell (MC) genes, as well as downregulation of cholesterogenic pathways and upregulation of fibrosis and immune signaling genes. Immunohistological analyses revealed an increased presence of MCs in PCAs lesions. Our gene expression analyses revealed common pathways associated with PCAs, with a strong association with MCs. The indistinguishable differences in gene expression profiles and immune cell signatures between LPP, FFA, and CCCA suggest that similar treatment regimens may be effective in treating these irreversible forms of hair loss.

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