Accurate Classification of NF1 Gene Variants in 84 Italian Patients with Neurofibromatosis Type 1

• Main Authors: Alessandro Stella, Patrizia Lastella, Daria Carmela Loconte, Nenad Bukvic, Dora Varvara, Margherita Patruno, Rosanna Bagnulo, Rosaura Lovaglio, Nicola Bartolomeo, Gabriella Serio, Nicoletta Resta
• Format: Article
• Language: English
• Published: MDPI AG 2018-04-01
• Series: Genes
• Subjects: neurofibromatosis type 1; NF1 gene; variant classification; in silico analysis; splicing
• Online Access: http://www.mdpi.com/2073-4425/9/4/216

Neurofibromatosis type 1 (NF1) is one of the most common autosomal dominant genetic diseases. It is caused by mutations in the NF1 gene encoding for the large protein, neurofibromin. Genetic testing of NF1 is cumbersome because 50% of cases are sporadic, and there are no mutation hot spots. In addition, the most recognizable NF1 clinical features—café-au-lait (CALs) spots and axillary and/or inguinal freckling—appear early in childhood but are rather non-specific. Thus, the identification of causative variants is extremely important for early diagnosis, especially in paediatric patients. Here, we aimed to identify the underlying genetic defects in 72 index patients referred to our centre for NF1. Causative mutations were identified in 58 subjects, with 29 being novel changes. We evaluated missense and non-canonical splicing mutations with both protein and splicing prediction algorithms. The ratio of splicing mutations detected was higher than that reported in recent patients’ series and in the Human Gene Mutation Database (HGMD). After applying in silico predictive tools to 41 previously reported missense variants, we demonstrated that 46.3% of these putatively missense mutations were forecasted to alter splicing instead. Our data suggest that mutations affecting splicing can be frequently underscored if not analysed in depth. We confirm that hamartomas can be useful for diagnosing NF1 in children. Lisch nodules and cutaneous neurofibromas were more frequent in patients with frameshifting mutations. In conclusion, we demonstrated that comprehensive in silico analysis can be a highly specific method for predicting the nature of NF1 mutations and may help in assuring proper patient care.