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      “Genotype-first” approaches on a curious case of idiopathic progressive cognitive decline

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          Abstract

          Background

          In developing countries, many cases with rare neurological diseases remain undiagnosed due to limited diagnostic experience. We encountered a case in China where two siblings both began to develop idiopathic progressive cognitive decline starting from age six, and were suspected to have an undiagnosed neurological disease.

          Methods

          Initial clinical assessments included review of medical history, comprehensive physical examination, genetic testing for metabolic diseases, blood tests and brain imaging. We performed exome sequencing with Agilent SureSelect exon capture and Illumina HiSeq2000 platform, followed by variant annotation and selection of rare, shared mutations that fit a recessive model of inheritance. To assess functional impacts of candidate variants, we performed extensive biochemical tests in blood and urine, and examined their possible roles by protein structure modeling.

          Results

          Exome sequencing identified NAGLU as the most likely candidate gene with compound heterozygous mutations (chr17:40695717C > T and chr17:40693129A > G in hg19 coordinate), which were documented to be pathogenic. Sanger sequencing confirmed the recessive patterns of inheritance, leading to a genetic diagnosis of Sanfilippo syndrome (mucopolysaccharidosis IIIB). Biochemical tests confirmed the complete loss of activity of alpha-N-acetylglucosaminidase (encoded by NAGLU) in blood, as well as significantly elevated dermatan sulfate and heparan sulfate in urine. Structure modeling revealed the mechanism on how the two variants affect protein structural stability.

          Conclusions

          Successful diagnosis of a rare genetic disorder with an atypical phenotypic presentation confirmed that such “genotype-first” approaches can particularly succeed in areas of the world with insufficient medical genetics expertise and with cost-prohibitive in-depth phenotyping.

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          Most cited references34

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          Mapping genes for complex traits in domestic animals and their use in breeding programmes.

          Genome-wide panels of SNPs have recently been used in domestic animal species to map and identify genes for many traits and to select genetically desirable livestock. This has led to the discovery of the causal genes and mutations for several single-gene traits but not for complex traits. However, the genetic merit of animals can still be estimated by genomic selection, which uses genome-wide SNP panels as markers and statistical methods that capture the effects of large numbers of SNPs simultaneously. This approach is expected to double the rate of genetic improvement per year in many livestock systems.
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            The RCSB Protein Data Bank: new resources for research and education

            The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) develops tools and resources that provide a structural view of biology for research and education. The RCSB PDB web site (http://www.rcsb.org) uses the curated 3D macromolecular data contained in the PDB archive to offer unique methods to access, report and visualize data. Recent activities have focused on improving methods for simple and complex searches of PDB data, creating specialized access to chemical component data and providing domain-based structural alignments. New educational resources are offered at the PDB-101 educational view of the main web site such as Author Profiles that display a researcher’s PDB entries in a timeline. To promote different kinds of access to the RCSB PDB, Web Services have been expanded, and an RCSB PDB Mobile application for the iPhone/iPad has been released. These improvements enable new opportunities for analyzing and understanding structure data.
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              The frequency of lysosomal storage diseases in The Netherlands.

              We have calculated the relative frequency and the birth prevalence of lysosomal storage diseases (LSDs) in The Netherlands based on all 963 enzymatically confirmed cases diagnosed during the period 1970-1996. The combined birth prevalence for all LSDs is 14 per 100,000 live births. Glycogenosis type II is the most frequent LSD with a birth prevalence of 2.0 per 100,000 live births, representing 17% of all diagnosed cases. Within the group of lipidoses, metachromatic leukodystrophy (MLD) is the most frequent LSD. MLD was diagnosed in 24% of lipidoses and the calculated birth prevalence was 1.42 per 100,000 for all types combined. Krabbe disease, diagnosed in 17% of cases, also belongs to the more frequent lipid storage diseases in The Netherlands with a birth prevalence of 1.35 per 100,000. The birth prevalence of Gaucher disease, commonly regarded as the most frequent lipid storage disease is 1.16 per 100,000 for all types combined. The combined birth prevalence for all lipid storage diseases is 6.2 per 100,000 live births. Within the group of mucopolysaccharidoses (MPSs), MPS I has the highest calculated birth prevalence of 1.19 per 100,000 (25% of all cases of MPS diagnosed), which is slightly more frequent than MPS IIIA with an estimated birth prevalence of 1.16 per 100,000. As a group, MPS III comprises 47% of all MPS cases diagnosed and the combined birth prevalence is 1.89 per 100,000 live births. The birth prevalence of MPS II is 0.67 per 100,000 (1.30 per 100,000 male live births). All other MPSs are rare. The combined birth prevalence for all MPSs is 4.5 per 100,000 live births. Mucolipidoses and oligosaccharidoses are very rare with birth prevalences between 0.04 and 0.20 for individual diseases. Only 49 cases were diagnosed between 1970 and 1996. Their combined birth prevalence is 1.0 per 100,000 live births.
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                Author and article information

                Contributors
                tlingshi@jnu.edu.cn
                13710475291@163.com
                xxhuang321@163.com
                lingxuey@163.com
                tianyunl@stanford.edu
                glyon@cshl.edu
                tlil@jnu.edu.cn
                kaiwang@usc.edu
                Journal
                BMC Med Genomics
                BMC Med Genomics
                BMC Medical Genomics
                BioMed Central (London )
                1755-8794
                3 December 2014
                3 December 2014
                2014
                : 7
                : 1
                : 66
                Affiliations
                [ ]Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, Guangdong 510623 China
                [ ]Guangdong Medical Key Laboratory of Brain Function and Diseases, Jinan University, Guangzhou, Guangdong 510623 China
                [ ]GHM Collaboration and Innovation Center for Tissue Regeneration and Repair, Jinan University, Guangzhou, Guangdong 510623 China
                [ ]Neonatal Intensive Care Unit, The 1st Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510623 China
                [ ]Department of Endocrinology and Metabolism, Guangzhou Women and Children’s Medical Center, Guangzhou, Guangdong 510623 China
                [ ]Medical Imaging Center, The 1st Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510623 China
                [ ]Department of Genetics, Stanford University, Stanford, CA 94305 USA
                [ ]Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11797 USA
                [ ]Department of Neurology, The 1st Affiliated Hospital, Jinan University, Guangzhou, Guangdong 510632 China
                [ ]Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90089 USA
                [ ]Department of Psychiatry & Behavioral Sciences, University of Southern California, Los Angeles, CA 90089 USA
                Article
                66
                10.1186/s12920-014-0066-9
                4267425
                25466957
                177d636e-8c56-4109-9efa-f4c941d4217b
                © Shi et al.; licensee BioMed Central Ltd. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 July 2014
                : 20 November 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                Genetics

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