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Transcriptomic analysis of frontal fibrosing alopecia

ABSTRACT: Transcriptomic analysis of frontal fibrosing alopecia

PROVIDER: PRJNA517414 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR8494850_1.fastq.gz	Fastqsanger.gz
	SRR8494850_2.fastq.gz	Fastqsanger.gz
	SRR8494851_1.fastq.gz	Fastqsanger.gz
	SRR8494851_2.fastq.gz	Fastqsanger.gz
	SRR8494852_1.fastq.gz	Fastqsanger.gz

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Metabolomics Analysis of Frontal Fibrosing Alopecia

Project description:Scarring alopecia consists of a collection of disorders characterized by destruction of hair follicles, replacement with fibrous scar tissue, and irreversible hair loss. Alopecia affects men and women worldwide and can be a significant source of psychological stress and depression for affected individuals. The purpose of this study was to explore metabolic profiles in scalp tissue samples from normal control subjects (n=6) and in matched samples obtained from affected (n=12) and unaffected (n=12) areas of the scalp in patients with lymphocytic Frontal Fibrosing Alopecia (FFA). Frontal fibrosing alopecia results from destruction of hair follicles by an inflammatory lymphocytic infiltrate that is localized around the upper portion of the hair follicle.

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Protein Profiling of Forehead and Scalp Corneocytes in Androgenetic versus Frontal Fibrosing Alopecia

Project description:Protein profiling offers an effective approach to characterizing the departure from normal of epidermis in disease states. The present investigation tested the hypothesis that the differentiation of epidermal corneocytes is perturbed in the forehead of subjects exhibiting frontal fibrosing alopecia. To this end, samples were collected by tape stripping from subjects diagnosed with this condition and compared to those from asymptomatic control subjects and from those exhibiting androgenetic alopecia. Unlike the latter, which exhibited only 3 proteins significantly different from controls, forehead samples from frontal fibrosing alopecia subjects displayed 72 proteins significantly different from controls, nearly two-thirds having lower expression. Comparison to corresponding profiles in scalp samples from frontal fibrosing alopecia and androgenetic alopecia suggested the perturbation of epidermal differentiation in the former was even greater in the scalp.

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Tissue and circulating microRNA co-expression analysis reveals potential involvement of miRNAs in the pathobiology of frontal fibrosing alopecia [skin]

Project description:Frontal fibrosing alopecia (FFA), a clinical variant of follicular lichen planus, is a predominantly postmenopausal, immune-mediated, inflammatory, primary lymphocytic cicatricial alopecia. FFA mainly involves the scalp, facial hair and eyebrows but also affects other body regions. MicroRNAs (miRNAs) have emerged as potential candidates of pathobiologic, diagnostic and therapeutic interest in chronic inflammatory, fibrotic and autoimmune diseases. To explore miRNAs in FFA for their disease relevance we isolated plasma from venous blood from 10 biopsy-proven treatment-naïve FFA cases and 10 matched controls and undertook miRNA expression analysis using the Human Fibrosis miRNA PCR Array (Qiagen). A separate cohort of 7 active FFA cases and 7 matched healthy controls were ascertained for tissue microRNA analysis and all 14 scalp-biopsy-extracted microRNA samples were subjected to microarray analysis on Affymetrix GeneChip miRNA 4.0 arrays. We generated a list of communities for the two skin tissue networks (cases and controls) and identified cluster centres (exemplars) as representative miRNAs of each community. Twenty exemplars in the control network were significantly enriched in the plasma (control) dataset compared to 27 for FFA. Amongst these, there were 17 miRNAs common in both networks, 9 of which were representative in the FFA disease phenotype. Random Forest analysis suggested that 4 circulating miRNAs (hsa-let-7d-5p, hsa-miR-18a-5p, has-miR-20a-5p and hsa-miR-19a-3p) can discriminate between FFA and controls. Our study of skin and plasma miRNA co-expression highlights circulating miRNAs of potential predictive value as biomarkers that should now be validated in larger cohorts.

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