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Spectrum of MECP2 mutations in Vietnamese patients with RETT syndrome

Overview of attention for article published in BMC Medical Genomics, August 2018
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Title
Spectrum of MECP2 mutations in Vietnamese patients with RETT syndrome
Published in
BMC Medical Genomics, August 2018
DOI 10.1186/s12881-018-0658-x
Pubmed ID
Authors

Huong Le Thi Thanh, Trinh Do Thi Diem, Chinh Vu Duy, Ha Ly Thi Thanh, Hoa Bui Thi Phuong, Liem Nguyen Thanh

Abstract

Rett syndrome (RTT) is a severe neurodevelopmental disorder in children characterized by a normal neurodevelopmental process in the first 6-18 months followed by a period of motor and vocal deterioration with stereotypic hand movements. Incidence of RTT is mostly due to de novo mutation in the MECP2 gene (methyl-CpG-binding protein 2). The study assessed 27 female patients presented with classical RTT phenotype age range from 18 months to 48 months. Specialist carried out the clinical evaluation and diagnosis according to RTT diagnosis criteria. Blood samples from patients were then collected for genomic DNA extraction. We next performed MECP2 gene amplification and sequencing of the whole coding region to screen for mutations. MECP2 mutation was found in 20 patients (74%) including: 2 missense, 4 nonsense, 6 frameshift and 2 deletion mutation. The study identified 14 pathogenic mutations which we found 4 mutation, to our knowledge and extensive search, not priory reported in any mutation database or publication: c.1384-1385DelGT, c.1205insT, c.717delC and c.1132_1207del77. High percentage of C > T (70%) in CpG sites mutation was found. Our result reveals a high percentage of C > T mutation in CpG hot spot, which is more prone to modification and more likely to be detected in RTT as a disorder is strictly due to de novo mutations. The study is the first to identify the mutation spectrum of MECP2 gene in Vietnamese patients and also an important step toward better diagnosis and care for RTT patients in Vietnam.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 15%
Student > Doctoral Student 3 12%
Other 3 12%
Student > Bachelor 3 12%
Student > Ph. D. Student 2 8%
Other 3 12%
Unknown 8 31%
Readers by discipline Count As %
Medicine and Dentistry 7 27%
Neuroscience 3 12%
Biochemistry, Genetics and Molecular Biology 2 8%
Computer Science 1 4%
Arts and Humanities 1 4%
Other 2 8%
Unknown 10 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 August 2018.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from BMC Medical Genomics
#1,682
of 2,444 outputs
Outputs of similar age
#264,704
of 340,721 outputs
Outputs of similar age from BMC Medical Genomics
#32
of 55 outputs
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