TY - JOUR
T1 - Williams–Beuren syndrome in diverse populations
AU - Kruszka, Paul
AU - Porras, Antonio R.
AU - de Souza, Deise Helena
AU - Moresco, Angélica
AU - Huckstadt, Victoria
AU - Gill, Ashleigh D.
AU - Boyle, Alec P.
AU - Hu, Tommy
AU - Addissie, Yonit A.
AU - Mok, Gary T.K.
AU - Tekendo-Ngongang, Cedrik
AU - Fieggen, Karen
AU - Prijoles, Eloise J.
AU - Tanpaiboon, Pranoot
AU - Honey, Engela
AU - Luk, Ho Ming
AU - Lo, Ivan F.M.
AU - Thong, Meow Keong
AU - Muthukumarasamy, Premala
AU - Jones, Kelly L.
AU - Belhassan, Khadija
AU - Ouldim, Karim
AU - El Bouchikhi, Ihssane
AU - Bouguenouch, Laila
AU - Shukla, Anju
AU - Girisha, Katta M.
AU - Sirisena, Nirmala D.
AU - Dissanayake, Vajira H.W.
AU - Paththinige, C. Sampath
AU - Mishra, Rupesh
AU - Kisling, Monisha S.
AU - Ferreira, Carlos R.
AU - de Herreros, María Beatriz
AU - Lee, Ni Chung
AU - Jamuar, Saumya S.
AU - Lai, Angeline
AU - Tan, Ee Shien
AU - Ying Lim, Jiin
AU - Wen-Min, Cham Breana
AU - Gupta, Neerja
AU - Lotz-Esquivel, Stephanie
AU - Badilla-Porras, Ramsés
AU - Hussen, Dalia Farouk
AU - El Ruby, Mona O.
AU - Ashaat, Engy A.
AU - Patil, Siddaramappa J.
AU - Dowsett, Leah
AU - Eaton, Alison
AU - Innes, A. Micheil
AU - Shotelersuk, Vorasuk
AU - Badoe, Ëben
AU - Wonkam, Ambroise
AU - Obregon, María Gabriela
AU - Chung, Brian H.Y.
AU - Trubnykova, Milana
AU - La Serna, Jorge
AU - Gallardo Jugo, Bertha Elena
AU - Chávez Pastor, Miguel
AU - Abarca Barriga, Hugo Hernán
AU - Megarbane, Andre
AU - Kozel, Beth A.
AU - van Haelst, Mieke M.
AU - Stevenson, Roger E.
AU - Summar, Marshall
AU - Adeyemo, A. Adebowale
AU - Morris, Colleen A.
AU - Moretti-Ferreira, Danilo
AU - Linguraru, Marius George
AU - Muenke, Maximilian
N1 - Publisher Copyright:
© 2018 Wiley Periodicals, Inc.
PY - 2018/5
Y1 - 2018/5
N2 - Williams–Beuren syndrome (WBS) is a common microdeletion syndrome characterized by a 1.5Mb deletion in 7q11.23. The phenotype of WBS has been well described in populations of European descent with not as much attention given to other ethnicities. In this study, individuals with WBS from diverse populations were assessed clinically and by facial analysis technology. Clinical data and images from 137 individuals with WBS were found in 19 countries with an average age of 11 years and female gender of 45%. The most common clinical phenotype elements were periorbital fullness and intellectual disability which were present in greater than 90% of our cohort. Additionally, 75% or greater of all individuals with WBS had malar flattening, long philtrum, wide mouth, and small jaw. Using facial analysis technology, we compared 286 Asian, African, Caucasian, and Latin American individuals with WBS with 286 gender and age matched controls and found that the accuracy to discriminate between WBS and controls was 0.90 when the entire cohort was evaluated concurrently. The test accuracy of the facial recognition technology increased significantly when the cohort was analyzed by specific ethnic population (P-value < 0.001 for all comparisons), with accuracies for Caucasian, African, Asian, and Latin American groups of 0.92, 0.96, 0.92, and 0.93, respectively. In summary, we present consistent clinical findings from global populations with WBS and demonstrate how facial analysis technology can support clinicians in making accurate WBS diagnoses.
AB - Williams–Beuren syndrome (WBS) is a common microdeletion syndrome characterized by a 1.5Mb deletion in 7q11.23. The phenotype of WBS has been well described in populations of European descent with not as much attention given to other ethnicities. In this study, individuals with WBS from diverse populations were assessed clinically and by facial analysis technology. Clinical data and images from 137 individuals with WBS were found in 19 countries with an average age of 11 years and female gender of 45%. The most common clinical phenotype elements were periorbital fullness and intellectual disability which were present in greater than 90% of our cohort. Additionally, 75% or greater of all individuals with WBS had malar flattening, long philtrum, wide mouth, and small jaw. Using facial analysis technology, we compared 286 Asian, African, Caucasian, and Latin American individuals with WBS with 286 gender and age matched controls and found that the accuracy to discriminate between WBS and controls was 0.90 when the entire cohort was evaluated concurrently. The test accuracy of the facial recognition technology increased significantly when the cohort was analyzed by specific ethnic population (P-value < 0.001 for all comparisons), with accuracies for Caucasian, African, Asian, and Latin American groups of 0.92, 0.96, 0.92, and 0.93, respectively. In summary, we present consistent clinical findings from global populations with WBS and demonstrate how facial analysis technology can support clinicians in making accurate WBS diagnoses.
KW - Africa
KW - Asia
KW - Latin America
KW - Middle East
KW - Williams
KW - Williams–Beuren
KW - diverse populations
KW - facial analysis technology
KW - syndrome
UR - http://www.scopus.com/inward/record.url?scp=85045847358&partnerID=8YFLogxK
U2 - 10.1002/ajmg.a.38672
DO - 10.1002/ajmg.a.38672
M3 - Artículo
C2 - 29681090
AN - SCOPUS:85045847358
SN - 1552-4825
VL - 176
SP - 1128
EP - 1136
JO - American Journal of Medical Genetics, Part A
JF - American Journal of Medical Genetics, Part A
IS - 5
ER -