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Target-Enrichment Sequencing and Copy Number Evaluation in Inherited Polyneuropathy

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收录情况: ◇ SCIE ◇ CPCI(ISTP)

单位: [1]China Japan Friendship Hosp, Neurol, Beijing, Peoples R China [2]Mayo Clin, Rochester, MN USA [3]Mayo Clin, Biomed Stat & Informat, Rochester, MN USA [4]Mayo Clin, Lab Med & Pathol, Rochester, MN USA [5]Mayo Clin, Med Genome Facil, Rochester, MN USA [6]Mayo Clin, Neurol, Rochester, MN USA [7]Mayo Clin, Dept Lab Genet & Pathol, Med Genet, Neurol, Rochester, MN USA [8]Univ Penn, Neurol, Media, PA USA
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Objective: To assess the efficiency of target-enrichment next-generation sequencing (NGS) with copy number assessment in inherited neuropathy diagnosis. Methods: A 197 polyneuropathy gene panel was designed to assess for mutations in 93 patients with inherited or idiopathic neuropathy without known genetic cause. We applied our novel copy number variation algorithm on NGS data, and validated the identified copy number mutations using CytoScan (Affymetrix). Cost and efficacy of this targeted NGS approach was compared to earlier evaluations. Results: Average coverage depth was; similar to 760x (median = 600, 99.4% > 100x). Among 93 patients, 18 mutations were identified in 17 cases (18%), including 3 copy number mutations: 2 PMP22 duplications and 1 MPZ duplication. The 2 patients with PMP22 duplication presented with bulbar and respiratory involvement and had absent extremity nerve conductions, leading to axonal diagnosis. Average onset age of these 17 patients was 25 years (2-61 years), vs 45 years for those without genetic discovery. Among those with onset age less than 40 years, the diagnostic yield of targeted NGS approach is high (27%) and cost savings is significant (similar to 20%). However, the cost savings for patients with late onset age and without family history is not demonstrated. Conclusions: Incorporating copy number analysis in target-enrichment NGS approach improved the efficiency of mutation discovery for chronic, inherited, progressive length-dependent polyneuropathy diagnosis. The new technology is facilitating a simplified genetic diagnostic algorithm utilizing targeted NGS, clinical phenotypes, age at onset, and family history to improve diagnosis efficiency. Our findings prompt a need for updating the current practice parameters and payer guidelines.

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出版当年[2015]版:
大类 | 1 区 医学
小类 | 1 区 临床神经病学
最新[2025]版:
大类 | 1 区 医学
小类 | 1 区 临床神经病学
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出版当年[2014]版:
Q1 CLINICAL NEUROLOGY
最新[2023]版:
Q1 CLINICAL NEUROLOGY

影响因子: 最新[2023版] 最新五年平均[2021-2025] 出版当年[2014版] 出版当年五年平均[2010-2014] 出版前一年[2013版] 出版后一年[2015版]

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第一作者单位: [7]Mayo Clin, Dept Lab Genet & Pathol, Med Genet, Neurol, Rochester, MN USA
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