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

Overview

Journal Front Genet

Date 2021 Dec 27

PMID 34956307

Citations 5

Authors

Puneet Talwar

Suman Kushwaha

Chitra Rawat

Harpreet Kaur

Ankit Srivastava

Rachna Agarwal

Puneet Chandna

Paolo Tucci

Luciano Saso

Ritushree Kukreti

Affiliations

Soon will be listed here.

Abstract

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 approach by studying the association of genetic variants from three identified critical genes, , , and , 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 ε4, four other SNPs in (rs405509, rs7259620, -rs769449, and rs7256173), one in (rs6970262), and one in (rs852423) showed a significant association with AD ( < 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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