Thomas E Heineman1, D Gareth R Evans, Fabien Campagne, Samuel H Selesnick. 1. *Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medical College/New York Presbyterian Hospital, New York, New York, U.S.A.; †University Department of Genomic Medicine, University of Manchester, MAHSC, St Mary's Hospital, Manchester, England, U.K.; and ‡Department of Physiology and Biophysics and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, U.S.A.
Abstract
HYPOTHESIS: Computer-based (in silico) protein modeling to examine genotype-phenotype relationships for a given mutation has been applied to many genes but never to NF2. BACKGROUND: Missense mutations in the merlin protein occur in approximately 9% of patients with neurofibromatosis type 2 (NF2). Within this subset of patients, no genotype-phenotype correlations have been established. The aim of this study was to determine if genotype correlates with phenotype in the cohort of NF2 patients with missense mutations as a first step to defining a method to predict clinical phenotype from genotype for these patients. METHODS: We analyzed 45 patients with NF2 as a result of missense mutations drawn from the United Kingdom NF2 registry. Our analysis included 17 different NF2 mutations from NF2 patients and six single-nucleotide polymorphisms (SNP)--presumed benign because they are observed in the dbSNP National Center for Biotechnology Information database and 1000 Genomes. We analyzed the mutations using three mutation tolerance prediction approaches: Align GVGD, SIFT, and PolyPhen-2. The mutation sites were also modeled on the three-dimensional crystal structure of merlin to investigate the spatial relationship of NF2-causing mutations. RESULTS: Two mutation tolerance predictors (SIFT and PolyPhen-2) were able to distinguish NF2-causing mutations from non-NF2-causing SNPs (p < 0.05). Mapping mutations on the molecular structure of merlin suggest that mutations resulting in greater structural conflicts within the protein are more likely to correlate with severe phenotypes. CONCLUSION: This work is a step toward a better understanding of genotype-phenotype relationships in NF2 caused by missense mutations using a computer-based methodology.
HYPOTHESIS: Computer-based (in silico) protein modeling to examine genotype-phenotype relationships for a given mutation has been applied to many genes but never to NF2. BACKGROUND: Missense mutations in the merlin protein occur in approximately 9% of patients with neurofibromatosis type 2 (NF2). Within this subset of patients, no genotype-phenotype correlations have been established. The aim of this study was to determine if genotype correlates with phenotype in the cohort of NF2patients with missense mutations as a first step to defining a method to predict clinical phenotype from genotype for these patients. METHODS: We analyzed 45 patients with NF2 as a result of missense mutations drawn from the United Kingdom NF2 registry. Our analysis included 17 different NF2 mutations from NF2patients and six single-nucleotide polymorphisms (SNP)--presumed benign because they are observed in the dbSNP National Center for Biotechnology Information database and 1000 Genomes. We analyzed the mutations using three mutation tolerance prediction approaches: Align GVGD, SIFT, and PolyPhen-2. The mutation sites were also modeled on the three-dimensional crystal structure of merlin to investigate the spatial relationship of NF2-causing mutations. RESULTS: Two mutation tolerance predictors (SIFT and PolyPhen-2) were able to distinguish NF2-causing mutations from non-NF2-causing SNPs (p < 0.05). Mapping mutations on the molecular structure of merlin suggest that mutations resulting in greater structural conflicts within the protein are more likely to correlate with severe phenotypes. CONCLUSION: This work is a step toward a better understanding of genotype-phenotype relationships in NF2 caused by missense mutations using a computer-based methodology.
Authors: Steffen Rosahl; Christopher Bohr; Michael Lell; Klaus Hamm; Heinrich Iro Journal: GMS Curr Top Otorhinolaryngol Head Neck Surg Date: 2017-12-18
Authors: Christine T Dinh; Eric Nisenbaum; Darius Chyou; Carly Misztal; Denise Yan; Rahul Mittal; Juan Young; Mustafa Tekin; Fred Telischi; Cristina Fernandez-Valle; Xue-Zhong Liu Journal: Otol Neurotol Date: 2020-06 Impact factor: 2.619
Authors: Katherine V Sadler; Charlie F Rowlands; Philip T Smith; Claire L Hartley; Naomi L Bowers; Nicola Y Roberts; Jade L Harris; Andrew J Wallace; D Gareth Evans; Ludwine M Messiaen; Miriam J Smith Journal: Hum Mutat Date: 2022-04-02 Impact factor: 4.700