Research Description

Genotype-Phenotype Relationship between Neurofibromatosis Type 1 Mutation Type and Location and its Associated Cognitive Clinical Measures

Neurofibromatosis type 1, an autosomal-dominant genetic disease caused by a mutation in the NF1 gene, is characterized by the growth of neural crest cells, resulting in tumor development along the nerves of the body. Individuals with NF1 exhibit characteristic café-au-lait spots, learning disabilities, and bone abnormalities.

The NF1 gene encodes the protein neurofibromin, which is responsible for suppressing tumors. Mutations in the NF1 gene lead to a nonfunctional form of neurofibromin, resulting in tumor development. It remains unclear exactly how these mutations lead to many of the other associated symptoms.

The NF1 mutations are unique and varied among affected individuals. Analysis of this large gene is essential to understanding how such a large protein affects many different tissues. My project will seek to establish if there is a genotype-phenotype relationship between the NF1 mutation type/location and its associated cognitive measures. Over half of the children with NF1 experience cognitive disorders such as attention deficit hyperactivity disorder, which leads us to believe there is a correlation between mutations and these cognitive disorders. A specific germline mutation may significantly influence this particular phenotype. I plan to continue mutational analysis on a set of DNA from affected patients. I will carry out PCR amplification and analysis of the exons most frequently associated with NF1. I will perform SSCP gel electrophoresis, HPLC, restriction endonuclease digests, and reverse transcription of RNA samples. Those samples exhibiting abnormal chromatograms or gel patterns will be sequenced to determine the exact abnormality. While most of the mutations will likely be pathogenic, some may result in in-frame insertion or deletion. In this case, I will screen the unaffected sibling’s DNA. Finally, I can characterize the mutations based on their predicted effect on protein domains, which can then be compared to clinical data to look for correlations with any cognitive measures.