Background: Noonan syndrome is a common genetic syndrome caused by pathogenic variants in genes in the Ras/MAPK signaling pathway. The medical literature has an abundance of studies on Noonan syndrome, but few are from the African continent.
Methods: The medical literature was searched for studies on Noonan syndrome from the African continent and these reports were added to our experience in Africa. Facial analysis was reviewed from two previous reports from our group using a support vector machine (SVM) algorithm and an analysis using the Face2Gene convolutional neural network technology.
Results: Individuals with Noonan syndrome from reports in African populations have the classic phenotype characteristics including typical minor facial anomalies such as widely spaced eyes (31-100%), short stature (71-100%), and congenital heart disease with pulmonary stenosis found in 24-100% of patients. Similarly, the genotypes are similar with the majority of variants occurring in the gene PTPN11 (72%) and 36% of these variants occurred in the amino acid residue Asn308, which is most commonly found in other populations. The two separate facial analysis algorithms successfully discriminated Africans with NS from unaffected matched individuals with area under the curve (AUC) of the receiver operator characteristic of 0.94 (SVM) and 0.979 for the Face2Gene research methodology.
Conclusion: Few studies characterizing Noonan syndrome in Africans have been conducted, highlighting the need for more genetic and genomic research in African populations. Available clinical data, genotypes, and facial analysis technology data show that individuals of African descent with NS can be efficiently diagnosed using available standards.
Keywords: PTPN11; African populations; Noonan syndrome; RASopathy; facial analysis technology.
Published 2020. This article is a U.S. Government work and is in the public domain in the USA.