Turner syndrome in diverse populations.
Abnormalities, Multiple
/ diagnosis
Adolescent
Adult
Asian People
/ genetics
Child
Child, Preschool
Chromosomes, Human, X
/ genetics
Face
/ abnormalities
Facial Recognition
Female
Hispanic or Latino
/ genetics
Humans
Infant
Infant, Newborn
Male
Middle Aged
Noonan Syndrome
/ diagnosis
Phenotype
Population Surveillance
Turner Syndrome
/ diagnosis
White People
/ genetics
Young Adult
Turner syndrome
diverse populations
facial analysis technology
health disparities
Journal
American journal of medical genetics. Part A
ISSN: 1552-4833
Titre abrégé: Am J Med Genet A
Pays: United States
ID NLM: 101235741
Informations de publication
Date de publication:
02 2020
02 2020
Historique:
received:
11
09
2019
revised:
25
11
2019
accepted:
05
12
2019
pubmed:
20
12
2019
medline:
12
1
2021
entrez:
20
12
2019
Statut:
ppublish
Résumé
Turner syndrome (TS) is a common multiple congenital anomaly syndrome resulting from complete or partial absence of the second X chromosome. In this study, we explore the phenotype of TS in diverse populations using clinical examination and facial analysis technology. Clinical data from 78 individuals and images from 108 individuals with TS from 19 different countries were analyzed. Individuals were grouped into categories of African descent (African), Asian, Latin American, Caucasian (European descent), and Middle Eastern. The most common phenotype features across all population groups were short stature (86%), cubitus valgus (76%), and low posterior hairline 70%. Two facial analysis technology experiments were conducted: TS versus general population and TS versus Noonan syndrome. Across all ethnicities, facial analysis was accurate in diagnosing TS from frontal facial images as measured by the area under the curve (AUC). An AUC of 0.903 (p < .001) was found for TS versus general population controls and 0.925 (p < .001) for TS versus individuals with Noonan syndrome. In summary, we present consistent clinical findings from global populations with TS and additionally demonstrate that facial analysis technology can accurately distinguish TS from the general population and Noonan syndrome.
Identifiants
pubmed: 31854143
doi: 10.1002/ajmg.a.61461
pmc: PMC8141514
mid: NIHMS1578084
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
303-313Subventions
Organisme : NHGRI NIH HHS
ID : U01 HG009716
Pays : United States
Organisme : NHLBI NIH HHS
ID : U24 HL135600
Pays : United States
Informations de copyright
Published 2019. This article is a U.S. Government work and is in the public domain in the USA.
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