Facial clues to the photosensitive trichothiodystrophy phenotype in childhood.
Journal
Journal of human genetics
ISSN: 1435-232X
Titre abrégé: J Hum Genet
Pays: England
ID NLM: 9808008
Informations de publication
Date de publication:
Jun 2023
Jun 2023
Historique:
received:
01
10
2022
accepted:
12
02
2023
revised:
12
02
2023
medline:
26
5
2023
pubmed:
23
2
2023
entrez:
22
2
2023
Statut:
ppublish
Résumé
Among genodermatoses, trichothiodystrophies (TTDs) are a rare genetically heterogeneous group of syndromic conditions, presenting with skin, hair, and nail abnormalities. An extra-cutaneous involvement (craniofacial district and neurodevelopment) can be also a part of the clinical picture. The presence of photosensitivity describes three forms of TTDs: MIM#601675 (TTD1), MIM#616390 (TTD2) and MIM#616395 (TTD3), that are caused by variants afflicting some components of the DNA Nucleotide Excision Repair (NER) complex and with more marked clinical consequences. In the present research, 24 frontal images of paediatric patients with photosensitive TTDs suitable for facial analysis through the next-generation phenotyping (NGP) technology were obtained from the medical literature. The pictures were compared to age and sex-matched to unaffected controls using 2 distinct deep-learning algorithms: DeepGestalt and GestaltMatcher (Face2Gene, FDNA Inc., USA). To give further support to the observed results, a careful clinical revision was undertaken for each facial feature in paediatric patients with TTD1 or TTD2 or TTD3. Interestingly, a distinctive facial phenotype emerged by the NGP analysis delineating a specific craniofacial dysmorphic spectrum. In addition, we tabulated every single detail within the observed cohort. The novelty of the present research includes the facial characterization in children with the photosensitive types of TTDs through the 2 different algorithms. This result can become additional criteria for early diagnosis, and for subsequent targeted molecular investigations as well as a possible tailored multidisciplinary personalized management.
Identifiants
pubmed: 36810639
doi: 10.1038/s10038-023-01134-4
pii: 10.1038/s10038-023-01134-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
437-443Informations de copyright
© 2023. The Author(s), under exclusive licence to The Japan Society of Human Genetics.
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