Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Abtahi, Rezvan, Karimzadeh, Parvaneh, Aryani, Omid, Akbarzadeh, Diba, Salehpour, Shadab, Rezayi, Alireza, Tonekaboni, Seyed Hassan, Emameh, Reza Zolfaghari, Houshmand, Massoud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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
_version_ 1784640556540887040
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
work_keys_str_mv AT abtahirezvan identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT karimzadehparvaneh identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT aryaniomid identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT akbarzadehdiba identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT salehpourshadab identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT rezayialireza identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT tonekaboniseyedhassan identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT emamehrezazolfaghari identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations
AT houshmandmassoud identificationofnovelmutationsamongiraniannpc1patientsabioinformaticsapproachtopredictpathogenicmutations