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Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations
BACKGROUND: Niemann-Pick disease type C (NPC) is a rare lysosomal neurovisceral storage disease caused by mutations in the NPC 1 (95%) or NPC2 (5%) genes. The products of NPC1 and NPC2 genes play considerable roles in glycolipid and cholesterol trafficking, which could consequently lead to NPC disea...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793247/ https://www.ncbi.nlm.nih.gov/pubmed/35086560 http://dx.doi.org/10.1186/s41065-022-00224-1 |
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author | Abtahi, Rezvan Karimzadeh, Parvaneh Aryani, Omid Akbarzadeh, Diba Salehpour, Shadab Rezayi, Alireza Tonekaboni, Seyed Hassan Emameh, Reza Zolfaghari Houshmand, Massoud |
author_facet | Abtahi, Rezvan Karimzadeh, Parvaneh Aryani, Omid Akbarzadeh, Diba Salehpour, Shadab Rezayi, Alireza Tonekaboni, Seyed Hassan Emameh, Reza Zolfaghari Houshmand, Massoud |
author_sort | Abtahi, Rezvan |
collection | PubMed |
description | BACKGROUND: Niemann-Pick disease type C (NPC) is a rare lysosomal neurovisceral storage disease caused by mutations in the NPC 1 (95%) or NPC2 (5%) genes. The products of NPC1 and NPC2 genes play considerable roles in glycolipid and cholesterol trafficking, which could consequently lead to NPC disease with variable phenotypes displaying a broad spectrum of symptoms. MATERIALS: In the present study 35 Iranian NPC unrelated patients were enrolled. These patients were first analysed by the Filipin Staining test of cholesterol deposits in cells for NPC diagnostics. Genomic DNA was extracted from the samples of peripheral blood leukocytes in EDTA following the manufacturer's protocol. All exon–intron boundaries and coding exons of the NPC1gene were amplified by polymerase chain reaction (PCR) using appropriate sets of primers. Thereafter, the products of PCR were sequenced and analysed using the NCBI database (https://blast.ncbi.nlm.nih.gov/Blast.cgi). The variants were reviewed by some databases including the Human Gene Mutation Database (HGMD) (http://www.hgmd.cf.ac.uk/ac/index.php) and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar (. Moreover, all the variants were manually classified in terms of the American College of Medical Genetics and Genomics (ACMG) guideline. RESULTS: The sequence analysis revealed 20 different variations, 10 of which are new, including one nonsense mutation (c.406C > T); three small deletions, (c.3126delC, c.2920_2923delCCTG, and c.2037delG); and six likely pathogenic missense mutations, (c.542C > A, c.1970G > A, c.1993C > G, c.2821 T > C, c.2872C > G, and c.3632 T > A). Finally, the pathogenicity of these new variants was determined using the ACMG guidelines. CONCLUSION: The present study aimed to facilitate the prenatal diagnosis of NPC patients in the future. In this regard, we identified 10 novel mutations, and verified that the majority of them occurred in six NPC1 exons (5, 8, 9, 13, 19, and 21), that should be considered with a high priority for Iranian patients' cost-effective evaluation. |
format | Online Article Text |
id | pubmed-8793247 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87932472022-02-03 Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations Abtahi, Rezvan Karimzadeh, Parvaneh Aryani, Omid Akbarzadeh, Diba Salehpour, Shadab Rezayi, Alireza Tonekaboni, Seyed Hassan Emameh, Reza Zolfaghari Houshmand, Massoud Hereditas Research BACKGROUND: Niemann-Pick disease type C (NPC) is a rare lysosomal neurovisceral storage disease caused by mutations in the NPC 1 (95%) or NPC2 (5%) genes. The products of NPC1 and NPC2 genes play considerable roles in glycolipid and cholesterol trafficking, which could consequently lead to NPC disease with variable phenotypes displaying a broad spectrum of symptoms. MATERIALS: In the present study 35 Iranian NPC unrelated patients were enrolled. These patients were first analysed by the Filipin Staining test of cholesterol deposits in cells for NPC diagnostics. Genomic DNA was extracted from the samples of peripheral blood leukocytes in EDTA following the manufacturer's protocol. All exon–intron boundaries and coding exons of the NPC1gene were amplified by polymerase chain reaction (PCR) using appropriate sets of primers. Thereafter, the products of PCR were sequenced and analysed using the NCBI database (https://blast.ncbi.nlm.nih.gov/Blast.cgi). The variants were reviewed by some databases including the Human Gene Mutation Database (HGMD) (http://www.hgmd.cf.ac.uk/ac/index.php) and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar (. Moreover, all the variants were manually classified in terms of the American College of Medical Genetics and Genomics (ACMG) guideline. RESULTS: The sequence analysis revealed 20 different variations, 10 of which are new, including one nonsense mutation (c.406C > T); three small deletions, (c.3126delC, c.2920_2923delCCTG, and c.2037delG); and six likely pathogenic missense mutations, (c.542C > A, c.1970G > A, c.1993C > G, c.2821 T > C, c.2872C > G, and c.3632 T > A). Finally, the pathogenicity of these new variants was determined using the ACMG guidelines. CONCLUSION: The present study aimed to facilitate the prenatal diagnosis of NPC patients in the future. In this regard, we identified 10 novel mutations, and verified that the majority of them occurred in six NPC1 exons (5, 8, 9, 13, 19, and 21), that should be considered with a high priority for Iranian patients' cost-effective evaluation. BioMed Central 2022-01-27 /pmc/articles/PMC8793247/ /pubmed/35086560 http://dx.doi.org/10.1186/s41065-022-00224-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Abtahi, Rezvan Karimzadeh, Parvaneh Aryani, Omid Akbarzadeh, Diba Salehpour, Shadab Rezayi, Alireza Tonekaboni, Seyed Hassan Emameh, Reza Zolfaghari Houshmand, Massoud Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations |
title | Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations |
title_full | Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations |
title_fullStr | Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations |
title_full_unstemmed | Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations |
title_short | Identification of novel mutations among Iranian NPC1 patients: a bioinformatics approach to predict pathogenic mutations |
title_sort | identification of novel mutations among iranian npc1 patients: a bioinformatics approach to predict pathogenic mutations |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793247/ https://www.ncbi.nlm.nih.gov/pubmed/35086560 http://dx.doi.org/10.1186/s41065-022-00224-1 |
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