PURPOSE: An evidence-based approach was used to determine the frequency distribution of genes contributing to the Charcot-Marie-Tooth (CMT) disease phenotype. METHODS: We performed a combined analysis of 11 population-based studies from various ethnic backgrounds to generate an evidence-based testing scheme. To estimate the relative frequencies of the responsible genes for which population-based studies are not available, we used our cohort of clinically classified patients with CMT and related neuropathies collected before the availability of genetic testing. RESULTS: Similar mutation frequencies were detected in the various studies, revealing a uniform distribution of pathogenic mutations. In CMT1 70% of patients harbor the CMT1A duplication, followed by GJB1 mutations at 8.8%. MPZ and PMP22 mutations are less common, identified on average in 2.9% and 1.5% of patients, respectively. Other genes not tested in population-based studies contribute to less than 1% of disease individually. In CMT2 MFN2 mutations are the most common, although population-based studies are not yet available. CONCLUSION: CMT represents a heterogeneous group of disorders at the molecular level. Nevertheless, testing for the CMT1A duplication (i.e., duplication of PMP22) alone yields an accurate molecular diagnosis in approximately half of all patients. If one further specifies the clinical type (demyelinating vs. axonal), the yield of detecting a molecular defect increases to 75% to 80% in the demyelinating or CMT1 group with a screening test that evaluates for CMT1A duplication/hereditary neuropathy with liability to pressure palsies deletion and GJB1 point mutations.
PURPOSE: An evidence-based approach was used to determine the frequency distribution of genes contributing to the Charcot-Marie-Tooth (CMT) disease phenotype. METHODS: We performed a combined analysis of 11 population-based studies from various ethnic backgrounds to generate an evidence-based testing scheme. To estimate the relative frequencies of the responsible genes for which population-based studies are not available, we used our cohort of clinically classified patients with CMT and related neuropathies collected before the availability of genetic testing. RESULTS: Similar mutation frequencies were detected in the various studies, revealing a uniform distribution of pathogenic mutations. In CMT1 70% of patients harbor the CMT1A duplication, followed by GJB1 mutations at 8.8%. MPZ and PMP22 mutations are less common, identified on average in 2.9% and 1.5% of patients, respectively. Other genes not tested in population-based studies contribute to less than 1% of disease individually. In CMT2 MFN2 mutations are the most common, although population-based studies are not yet available. CONCLUSION: CMT represents a heterogeneous group of disorders at the molecular level. Nevertheless, testing for the CMT1A duplication (i.e., duplication of PMP22) alone yields an accurate molecular diagnosis in approximately half of all patients. If one further specifies the clinical type (demyelinating vs. axonal), the yield of detecting a molecular defect increases to 75% to 80% in the demyelinating or CMT1 group with a screening test that evaluates for CMT1A duplication/hereditary neuropathy with liability to pressure palsies deletion and GJB1 point mutations.
Authors: Kinga Szigeti; Wojciech Wiszniewski; Gulam Mustafa Saifi; Diane L Sherman; Norbert Sule; Adekunle M Adesina; Pedro Mancias; Sozos Ch Papasozomenos; Geoffrey Miller; Laura Keppen; Donna Daentl; Peter J Brophy; James R Lupski Journal: Neurogenetics Date: 2007-08-24 Impact factor: 2.660
Authors: Clement Y Chow; Yanling Zhang; James J Dowling; Natsuko Jin; Maja Adamska; Kensuke Shiga; Kinga Szigeti; Michael E Shy; Jun Li; Xuebao Zhang; James R Lupski; Lois S Weisman; Miriam H Meisler Journal: Nature Date: 2007-06-17 Impact factor: 49.962
Authors: Britney L Grayson; Mary Ellen Smith; James W Thomas; Lily Wang; Phil Dexheimer; Joy Jeffrey; Pamela R Fain; Priyaanka Nanduri; George S Eisenbarth; Thomas M Aune Journal: PLoS One Date: 2010-11-15 Impact factor: 3.240
Authors: Yuji Okamoto; Meryem Tuba Goksungur; Davut Pehlivan; Christine R Beck; Claudia Gonzaga-Jauregui; Donna M Muzny; Mehmed M Atik; Claudia M B Carvalho; Zeliha Matur; Serife Bayraktar; Philip M Boone; Kaya Akyuz; Richard A Gibbs; Esra Battaloglu; Yesim Parman; James R Lupski Journal: Genet Med Date: 2013-10-17 Impact factor: 8.822