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Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis

BACKGROUND: Limb-girdle muscular dystrophy (LGMD) is the most common adult-onset class of muscular dystrophies in India, but a majority of suspected LGMDs in India remain unclassified to the genetic subtype level. The next-generation sequencing (NGS)-based approaches have allowed molecular character...

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Autores principales: Dastur, Rashna Sam, Gaitonde, Pradnya Satish, Kachwala, Munira, Nallamilli, Babi R. R., Ankala, Arunkanth, Khadilkar, Satish V., Atchayaram, Nalini, Gayathri, N., Meena, A. K., Rufibach, Laura, Shira, Sarah, Hegde, Madhuri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5586129/
https://www.ncbi.nlm.nih.gov/pubmed/28904466
http://dx.doi.org/10.4103/aian.AIAN_129_17
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author Dastur, Rashna Sam
Gaitonde, Pradnya Satish
Kachwala, Munira
Nallamilli, Babi R. R.
Ankala, Arunkanth
Khadilkar, Satish V.
Atchayaram, Nalini
Gayathri, N.
Meena, A. K.
Rufibach, Laura
Shira, Sarah
Hegde, Madhuri
author_facet Dastur, Rashna Sam
Gaitonde, Pradnya Satish
Kachwala, Munira
Nallamilli, Babi R. R.
Ankala, Arunkanth
Khadilkar, Satish V.
Atchayaram, Nalini
Gayathri, N.
Meena, A. K.
Rufibach, Laura
Shira, Sarah
Hegde, Madhuri
author_sort Dastur, Rashna Sam
collection PubMed
description BACKGROUND: Limb-girdle muscular dystrophy (LGMD) is the most common adult-onset class of muscular dystrophies in India, but a majority of suspected LGMDs in India remain unclassified to the genetic subtype level. The next-generation sequencing (NGS)-based approaches have allowed molecular characterization and subtype diagnosis in a majority of these patients in India. MATERIALS AND METHODS: (I) To select probable dysferlinopathy (LGMD2B) cases from other LGMD subtypes using two screening methods (i) to determine the status of dysferlin protein expression in blood (peripheral blood mononuclear cell) by monocyte assay (ii) using a predictive algorithm called automated LGMD diagnostic assistant (ALDA) to obtain possible LGMD subtypes based on clinical symptoms. (II) Identification of gene pathogenic variants by NGS for 34 genes associated with LGMD or LGMD like muscular dystrophies, in cases showing: absence of dysferlin protein by the monocyte assay and/or a typical dysferlinopathy phenotype, with medium to high predictive scores using the ALDA tool. RESULTS: Out of the 125 patients screened by NGS, 96 were confirmed with two dysferlin variants, of which 84 were homozygous. Single dysferlin pathogenic variants were seen in 4 patients, whereas 25 showed no variants in the dysferlin gene. CONCLUSION: In this study, 98.2% of patients with absence of the dysferlin protein showed one or more variants in the dysferlin gene and hence has a high predictive significance in diagnosing dysferlinopathies. However, collection of blood samples from all over India for protein analysis is expensive. Our analysis shows that the use of the “ALDA tool” could be a cost-effective alternative method. Identification of dysferlin pathogenic variants by NGS is the ultimate method for diagnosing dysferlinopathies though follow-up with the monocyte assay can be useful to understand the phenotype in relation to the dysferlin protein expression and also be a useful biomarker for future clinical trials.
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spelling pubmed-55861292017-09-13 Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis Dastur, Rashna Sam Gaitonde, Pradnya Satish Kachwala, Munira Nallamilli, Babi R. R. Ankala, Arunkanth Khadilkar, Satish V. Atchayaram, Nalini Gayathri, N. Meena, A. K. Rufibach, Laura Shira, Sarah Hegde, Madhuri Ann Indian Acad Neurol Original Article BACKGROUND: Limb-girdle muscular dystrophy (LGMD) is the most common adult-onset class of muscular dystrophies in India, but a majority of suspected LGMDs in India remain unclassified to the genetic subtype level. The next-generation sequencing (NGS)-based approaches have allowed molecular characterization and subtype diagnosis in a majority of these patients in India. MATERIALS AND METHODS: (I) To select probable dysferlinopathy (LGMD2B) cases from other LGMD subtypes using two screening methods (i) to determine the status of dysferlin protein expression in blood (peripheral blood mononuclear cell) by monocyte assay (ii) using a predictive algorithm called automated LGMD diagnostic assistant (ALDA) to obtain possible LGMD subtypes based on clinical symptoms. (II) Identification of gene pathogenic variants by NGS for 34 genes associated with LGMD or LGMD like muscular dystrophies, in cases showing: absence of dysferlin protein by the monocyte assay and/or a typical dysferlinopathy phenotype, with medium to high predictive scores using the ALDA tool. RESULTS: Out of the 125 patients screened by NGS, 96 were confirmed with two dysferlin variants, of which 84 were homozygous. Single dysferlin pathogenic variants were seen in 4 patients, whereas 25 showed no variants in the dysferlin gene. CONCLUSION: In this study, 98.2% of patients with absence of the dysferlin protein showed one or more variants in the dysferlin gene and hence has a high predictive significance in diagnosing dysferlinopathies. However, collection of blood samples from all over India for protein analysis is expensive. Our analysis shows that the use of the “ALDA tool” could be a cost-effective alternative method. Identification of dysferlin pathogenic variants by NGS is the ultimate method for diagnosing dysferlinopathies though follow-up with the monocyte assay can be useful to understand the phenotype in relation to the dysferlin protein expression and also be a useful biomarker for future clinical trials. Medknow Publications & Media Pvt Ltd 2017 /pmc/articles/PMC5586129/ /pubmed/28904466 http://dx.doi.org/10.4103/aian.AIAN_129_17 Text en Copyright: © 2006 - 2017 Annals of Indian Academy of Neurology http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Dastur, Rashna Sam
Gaitonde, Pradnya Satish
Kachwala, Munira
Nallamilli, Babi R. R.
Ankala, Arunkanth
Khadilkar, Satish V.
Atchayaram, Nalini
Gayathri, N.
Meena, A. K.
Rufibach, Laura
Shira, Sarah
Hegde, Madhuri
Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis
title Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis
title_full Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis
title_fullStr Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis
title_full_unstemmed Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis
title_short Detection of Dysferlin Gene Pathogenic Variants in the Indian Population in Patients Predicted to have a Dysferlinopathy Using a Blood-based Monocyte Assay and Clinical Algorithm: A Model for Accurate and Cost-effective Diagnosis
title_sort detection of dysferlin gene pathogenic variants in the indian population in patients predicted to have a dysferlinopathy using a blood-based monocyte assay and clinical algorithm: a model for accurate and cost-effective diagnosis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5586129/
https://www.ncbi.nlm.nih.gov/pubmed/28904466
http://dx.doi.org/10.4103/aian.AIAN_129_17
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