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Systematic Analysis of GWAS Data Reveals Genomic Hotspots for Shared Mechanisms between Neurodegenerative Diseases

 
: Naz, Mufassra; Younesi, Erfan; Hofmann-Apitius, Martin

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Volltext ()

Journal of Alzheimer’s Disease & Parkinsonism. Online journal 7 (2017), Nr.5, Art. 368
https://www.omicsonline.org/alzheimers-disease-parkinsonism.php
ISSN: 2161-0460
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer SCAI ()

Abstract
Objective: In this study, we have tried to reveal molecular mechanisms underlying “shared genetic variants” and developed a strategy to identify candidate mechanisms for shared aetiology of a pair of diseases, to uncover biological relationships between quantitative traits or related neurodegenerative diseases.

Methods: Genetic variants were collected from GWAS catalog, belonged to multiple disease association studies. Meta-analysis was performed by using Metal (a whole genome association analysis toolset), and normalized them for their different sample sizes. LD analysis was done with Haploreg DB V.4.0. Subsequently, the ENSEMBL variant database was used as a reference database. Additionally, these shared SNPs were interpreted with Regulome DB V.1.1 and finally ranked the variant lists according to predicted functional consequences attributes. Afterwards evidences were collected from gene expression studies, patents, knock-out studies and other literature.

Results: Pair-wise analysis also revealed that AD and PD have the largest number of shared disease-associated loci. Additionally, tau locus is discovered in a very novel and unique perspective of stress induced shared pathology of AD and PD, which provides suggestive evidence that the molecular mechanisms influencing aetiology and progression of selective neurodegenerative diseases are at least partly interrelated.

Conclusion: Genetic overlap between these diseases suggests that genomic locus should be considered to investigate the effects of GWAS variants rather than individual genetic variants, particularly to investigate shared pathology.

: http://publica.fraunhofer.de/dokumente/N-525143.html