Turner syndrome in diverse populations

Abstract

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.

Rubinstein–Taybi syndrome in diverse populations

“…Our results show that regardless of ethnic backgrounds, this technology is overall excellent in discriminating individuals with RSTS from unaffected controls (Table 2). However, as equally found in a previous study of an ethnically diverse cohort of individuals with Turner syndrome (Kruszka et al, 2020) (Bartsch et al, 2010;Fergelot et al, 2016;Stevens, 2019).…”

“…Our results show that regardless of ethnic backgrounds, this technology is overall excellent in discriminating individuals with RSTS from unaffected controls (Table 2). However, as equally found in a previous study of an ethnically diverse cohort of individuals with Turner syndrome (Kruszka et al, 2020), facial analysis technology for RSTS was most accurate in the Asian group (AUC: 0.99) and least in the African group (AUC: 0.79). This result may be very informative to clinicians, especially in resource‐constrained areas where the unavailability of molecular genetic testing most often imposes diagnosis and management of patients on clinical grounds only.…”

“…This work is part of our ongoing series of studies on common human malformation syndromes in populations underrepresented in the medical literature (Dowsett et al, 2019; Kruszka, Addissie, et al, 2017; Kruszka, Porras, Addissie, et al, 2017; Kruszka, Porras, Sobering, et al, 2017; Kruszka et al, 2018; 2020; Muenke, Adeyemo, & Kruszka, 2016).…”

“…We conducted three separate sets of experiments with de‐identified RSTS patients images alongside their age‐, sex‐, and/or ethnicity‐matched unaffected controls: the first experiment compared a cohort of RSTS patients to sex‐ and age‐matched unaffected controls; the second compared RSTS patients from five populations groups (African, Middle Eastern, Asian, Latin American and Caucasian) to sex‐, age‐, and ethnicity‐matched unaffected controls, and the last experiment compared two separate groups of RSTS patients of diverse ethnicities with variants in CREBBP or EP300 genes to sex‐ and age‐matched unaffected controls (patients' characteristics available in Table S3). As applied in previous studies (Kruszka, Hu, et al, 2019; Kruszka et al, 2020), the discrimination ability of this algorithm was measured using the area under the receiver operating characteristic curve (AUC), with an AUC of 1.0 (100% correct prediction) representing a perfect discrimination between individuals with RSTS and controls, and an AUC of 0.5 (50% correct prediction) representing no discrimination between cohorts.…”

Facial Recognition Intensity in Disease Diagnosis Using Automatic Facial Recognition

“…Angelman syndrome showed six facial features, with maximum penetrance of facial phenotypes of 100% and FRI of 8. Turner syndrome showed six facial phenotypes and the maximum penetrance of facial phenotypes was 56% [31]; therefore, FRI of Turner syndrome was 3.36. Fetal alcohol spectrum disorders (FASD) were associated with four facial phenotypes with maximum penetrance of 100% [29], resulting in FRI of 4.…”