NeuroArray, A Custom CGH Microarray to Decipher Copy Number Variants in Alzheimer's Disease.

Abstract:

Background:Copy Number Variants (CNVs) represent a prevailing type of structural variation (deletions or duplications) in the human genome. In the last few years, several studies have demonstrated that CNVs represent significant mutations in Alzheimer's Disease (AD) hereditability. Currently, innovative high-throughput platforms and bioinformatics algorithms are spreading to screening CNVs involved in different neurological diseases. In particular, the use of custom arrays, based on libraries of probes that can detect significant genomic regions, have greatly improved the resolution of targeted regions and the identification of chromosomal aberrations. Objective:In this work, we report the use of NeuroArray, a custom CGH microarray useful to screening and further investigate the role of the recurring genomic aberrations in patients with confirmed or suspected AD. Methods:The custom oligonucleotide aCGH design includes 641 genes and 9118 exons, linked to AD. The genomic DNA was isolated from blood samples of AD affected patients. The entire protocol of custom NeuroArray included digestion, labelling and hybridization steps as a standard aCGH assay. Results:The NeuroArray analysis revealed the presence of amplifications in several genes associated with AD. In the coding regions of these genes, 14,586 probes were designed with a 348 bp median probe spacing. The majority of targeted AD genes map on chromosomes 1 and 10. A significant aspect of the NeuroArray design is that 95% of the total exon targets is covered by at least one probe, a resolution higher than CGH array platforms commercially available. Conclusion:By identifying with a high sensitivity the chromosomal abnormalities in a large panel of AD-related genes and other neurological diseases, the NeuroArray platform is a valid tool for clinical diagnosis.

journal_name

Curr Genomics

journal_title

Current genomics

authors

Cuccaro D,Guarnaccia M,Iemmolo R,D'Agata V,Cavallaro S

doi

10.2174/1389202919666180122141425

subject

Has Abstract

pub_date

2018-09-01 00:00:00

pages

499-504

issue

6

eissn

1389-2029

issn

1875-5488

pii

CG-19-499

journal_volume

19

pub_type

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