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Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease

Previously, we demonstrated an integrated genomic convergence and network analysis approach to identify the candidate genes associated with the complex neurodegenerative disorder, Alzheimer’s disease (AD). Here, we performed a pilot study to validate the in silico approach by studying the associatio...

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Autores principales: Talwar, Puneet, Kushwaha, Suman, Rawat, Chitra, Kaur, Harpreet, Srivastava, Ankit, Agarwal, Rachna, Chandna, Puneet, Tucci, Paolo, Saso, Luciano, Kukreti, Ritushree
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696000/
https://www.ncbi.nlm.nih.gov/pubmed/34956307
http://dx.doi.org/10.3389/fgene.2021.722221
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author Talwar, Puneet
Kushwaha, Suman
Rawat, Chitra
Kaur, Harpreet
Srivastava, Ankit
Agarwal, Rachna
Chandna, Puneet
Tucci, Paolo
Saso, Luciano
Kukreti, Ritushree
author_facet Talwar, Puneet
Kushwaha, Suman
Rawat, Chitra
Kaur, Harpreet
Srivastava, Ankit
Agarwal, Rachna
Chandna, Puneet
Tucci, Paolo
Saso, Luciano
Kukreti, Ritushree
author_sort Talwar, Puneet
collection PubMed
description Previously, we demonstrated an integrated genomic convergence and network analysis approach to identify the candidate genes associated with the complex neurodegenerative disorder, Alzheimer’s disease (AD). Here, we performed a pilot study to validate the in silico approach by studying the association of genetic variants from three identified critical genes, APOE, EGFR, and ACTB, with AD. A total of 103 patients with AD and 146 healthy controls were recruited. A total of 46 single-nucleotide polymorphisms (SNPs) spanning the three genes were genotyped, of which only 19 SNPs were included in the final analyses after excluding non-polymorphic and Hardy–Weinberg equilibrium-violating SNPs. Apart from our previously reported APOE ε4, four other SNPs in APOE (rs405509, rs7259620, −rs769449, and rs7256173), one in EGFR (rs6970262), and one in ACTB (rs852423) showed a significant association with AD (p < 0.05). Our results validate the reliability of genomic convergence and network analysis approach in identifying the AD-associated candidate genes.
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spelling pubmed-86960002021-12-24 Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease Talwar, Puneet Kushwaha, Suman Rawat, Chitra Kaur, Harpreet Srivastava, Ankit Agarwal, Rachna Chandna, Puneet Tucci, Paolo Saso, Luciano Kukreti, Ritushree Front Genet Genetics Previously, we demonstrated an integrated genomic convergence and network analysis approach to identify the candidate genes associated with the complex neurodegenerative disorder, Alzheimer’s disease (AD). Here, we performed a pilot study to validate the in silico approach by studying the association of genetic variants from three identified critical genes, APOE, EGFR, and ACTB, with AD. A total of 103 patients with AD and 146 healthy controls were recruited. A total of 46 single-nucleotide polymorphisms (SNPs) spanning the three genes were genotyped, of which only 19 SNPs were included in the final analyses after excluding non-polymorphic and Hardy–Weinberg equilibrium-violating SNPs. Apart from our previously reported APOE ε4, four other SNPs in APOE (rs405509, rs7259620, −rs769449, and rs7256173), one in EGFR (rs6970262), and one in ACTB (rs852423) showed a significant association with AD (p < 0.05). Our results validate the reliability of genomic convergence and network analysis approach in identifying the AD-associated candidate genes. Frontiers Media S.A. 2021-12-09 /pmc/articles/PMC8696000/ /pubmed/34956307 http://dx.doi.org/10.3389/fgene.2021.722221 Text en Copyright © 2021 Talwar, Kushwaha, Rawat, Kaur, Srivastava, Agarwal, Chandna, Tucci, Saso and Kukreti. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Talwar, Puneet
Kushwaha, Suman
Rawat, Chitra
Kaur, Harpreet
Srivastava, Ankit
Agarwal, Rachna
Chandna, Puneet
Tucci, Paolo
Saso, Luciano
Kukreti, Ritushree
Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease
title Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease
title_full Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease
title_fullStr Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease
title_full_unstemmed Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease
title_short Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer’s Disease
title_sort validating a genomic convergence and network analysis approach using association analysis of identified candidate genes in alzheimer’s disease
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696000/
https://www.ncbi.nlm.nih.gov/pubmed/34956307
http://dx.doi.org/10.3389/fgene.2021.722221
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