Clinical profile of comorbidity of rare diseases in a Tunisian patient: a case report associating incontinentia pigmenti and Noonan syndrome

Spectrum of Genetic Diseases in Tunisia: Current Situation and Main Milestones Achieved

Genetic diseases in Tunisia are a real public health problem given their chronicity and the lack of knowledge concerning their prevalence and etiology, and the high rates of consanguinity. Hence, we performed systematic reviews of the literature in order to provide a more recent spectrum of these disorders and to expose the challenges that still exist to tackle these kinds of diseases. A manual textual data mining was conducted using MeSH and PubMed databases. Collected data were classified according to the CIM-10 classification and the transmission mode. The spectrum of these diseases is estimated to be 589 entities. This suggests remarkable progress through the development of biomedical health research activities and building capacities. Sixty percent of the reported disorders are autosomal recessive, which could be explained by the high prevalence of endogamous mating. Congenital malformations (29.54%) are the major disease group, followed by metabolic diseases (22%). Sixty percent of the genetic diseases have a known molecular etiology. We also reported additional cases of comorbidity that seem to be a common phenomenon in our population. We also noticed that epidemiological data are scarce. Newborn and carrier screening was only limited to pilot projects for a few genetic diseases. Collected data are being integrated into a database under construction that will be a valuable decision-making tool. This study provides the current situation of genetic diseases in Tunisia and highlights their particularities. Early detection of the disease is important to initiate critical intervention and to reduce morbidity and mortality.

Noonan syndrome on the African Continent

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.