A highly sensitive genetic protocol to detect NF1 mutations

J Mol Diagn. 2011 Mar;13(2):113-22. doi: 10.1016/j.jmoldx.2010.09.002.


Neurofibromatosis type 1 (NF1) is a hereditary disorder caused by mutations in the NF1 gene. Detecting mutation in NF1 is hindered by the gene's large size, the lack of mutation hotspots, the presence of pseudogenes, and the wide variety of possible lesions. We developed a method for detecting germline mutations by combining an original RNA-based cDNA-PCR mutation detection method and denaturing high-performance liquid chromatography (DHPLC) with multiplex ligation-dependent probe amplification (MLPA). The protocol was validated in a cohort of 56 blood samples from NF1 patients who fulfilled NIH diagnostic criteria, identifying the germline mutation in 53 cases (95% sensitivity). The efficiency and reliability of this approach facilitated detection of different types of mutations, including single-base substitutions, deletions or insertions of one to several nucleotides, microdeletions, and changes in intragenic copy number. Because mutational screening for minor lesions was performed using cDNA and the characterization of mutated alleles was performed at both the RNA and genomic DNA level, the analysis provided insight into the nature of the different mutations and their effect on NF1 mRNA splicing. After validation, we implemented the protocol as a routine test. Here we present the overall unbiased spectrum of NF1 mutations identified in 93 patients in a cohort of 105. The results indicate that this protocol is a powerful new tool for the molecular diagnosis of NF1.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chromatography, High Pressure Liquid / methods*
  • DNA Copy Number Variations
  • DNA Mutational Analysis / methods*
  • Genes, Neurofibromatosis 1*
  • Germ-Line Mutation*
  • Humans
  • Molecular Diagnostic Techniques
  • Neurofibromatosis 1 / diagnosis*
  • Neurofibromatosis 1 / genetics*
  • Polymerase Chain Reaction / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity