A review of genotrichoses and hair pathology associated with inherited skin diseases

Author:

Doolan Brent J1ORCID,Rayinda Tuntas2ORCID,Chiu Frank P3ORCID,McGrath John A1ORCID,Onoufriadis Alexandros 14ORCID

Affiliation:

1. St John’s Institute of Dermatology, School of Basic and Medical Biosciences, King’s College London , London , UK

2. Department of Dermatology and Venereology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada , Yogyakarta , Indonesia

3. University of Queensland Diamantina Institute, University of Queensland, Dermatology Research Centre , Brisbane, QLD , Australia

4. Laboratory of Medical Biology and Genetics, School of Medicine, Aristotle University of Thessaloniki , Thessaloniki , Greece

Abstract

Abstract Genetic hair disorders, also known as genotrichoses, are characterized by abnormalities of hair structure, growth or differentiation, giving rise to a spectrum of phenotypes such as hypertrichosis, hypotrichosis and atrichia. These disorders may present as isolated phenotypes or be part of more complex phenotypes including abnormalities in skin or other organs. Genetic discoveries for hair disorders have been recently augmented with the advent of next-generation sequencing (NGS) technologies. We reviewed the literature and summarized disease–gene associations for inherited hair disorders, as well as genodermatoses presenting with hair abnormalities discovered by NGS technologies. We identified 28 nonsyndromic hair disorders, involving 25 individual genes and four unidentified genes. We have also discovered that approximately 30% of all the genodermatoses that were identified by NGS approaches demonstrated hair abnormalities as part of their phenotype. This review underscores the huge impact of NGS technologies in disclosing the genetics of hair disorders and the potential these discoveries provide for future translational research and new therapies.

Publisher

Oxford University Press (OUP)

Subject

Dermatology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine learning (ML) techniques as effective methods for evaluating hair and skin assessments: A systematic review;Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine;2023-12-29

2. WNT10A gene variants at the root of short anagen hair syndrome;British Journal of Dermatology;2023-09-28

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