Noonan syndrome in diverse populations
- Paul Kruszka,
- Antonio R. Porras,
- Yonit A. Addissie,
- Angélica Moresco,
- Sofia Medrano,
- Gary T.K. Mok
- National Human Genome Research Institute (NHGRI),
- Children's National Health System,
- Hospital de Pediatría Garrahan,
- The University of Hong Kong Li Ka Shing Faculty of Medicine,
- University of Cape Town,
- University of Rwanda
Open access
Publication Information
Output type
Original language
EnglishPages from-to (Number of pages)
Pages 2323-2334 (12 pages)Journal (Volume, Issue Number)
American Journal of Medical Genetics, Part A (Volume 173, Issue 9)Publication milestones
- Published - 09/2017
Publication status
ISSN
1552-4825Publication IDs
- Scopus: 85026314237
- PubMed: 28748642
Abstract
Noonan syndrome (NS) is a common genetic syndrome associated with gain of function variants in genes in the Ras/MAPK pathway. The phenotype of NS has been well characterized in populations of European descent with less attention given to other groups. In this study, individuals from diverse populations with NS were evaluated clinically and by facial analysis technology. Clinical data and images from 125 individuals with NS were obtained from 20 countries with an average age of 8 years and female composition of 46%. Individuals were grouped into categories of African descent (African), Asian, Latin American, and additional/other. Across these different population groups, NS was phenotypically similar with only 2 of 21 clinical elements showing a statistically significant difference. The most common clinical characteristics found in all population groups included widely spaced eyes and low-set ears in 80% or greater of participants, short stature in more than 70%, and pulmonary stenosis in roughly half of study individuals. Using facial analysis technology, we compared 161 Caucasian, African, Asian, and Latin American individuals with NS with 161 gender and age matched controls and found that sensitivity was equal to or greater than 94% for all groups, and specificity was equal to or greater than 90%. In summary, we present consistent clinical findings from global populations with NS and additionally demonstrate how facial analysis technology can support clinicians in making accurate NS diagnoses. This work will assist in earlier detection and in increasing recognition of NS throughout the world.
