OpenSSL SSL_connect: Connection reset by peer in connection to v2.sherpa.ac.uk:443 PuSH - Publication Server of Helmholtz Zentrum München: Network-based SNP meta-analysis identifies joint and disjoint genetic features across common human diseases.

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Arnold, M. ; Hartsperger, M.L. ; Baurecht, H.* ; Rodriguez, E.* ; Wachinger, B. ; Franke, A.* ; Kabesch, M.* ; Winkelmann, J. ; Pfeufer, A. ; Romanos, M.* ; Illig, T. ; Mewes, H.-W. ; Stuempflen, V. ; Weidinger, S.*

Network-based SNP meta-analysis identifies joint and disjoint genetic features across common human diseases.

BMC Genomics 13:490 (2012)
Publ. Version/Full Text Volltext DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
ABSTRACT: BACKGROUND: Genome-wide association studies (GWAS) have provided a large set of genetic loci influencing the risk for many common diseases. Association studies typically analyze one specific trait in single populations in an isolated fashion without taking into account the potential phenotypic and genetic correlation between traits. However, GWA data can be efficiently used to identify overlapping loci with analogous or contrasting effects on different diseases. RESULTS: Here, we describe a new approach to systematically prioritize and interpret available GWA data. We focus on the analysis of joint and disjoint genetic determinants across diseases. Using network analysis, we show that variant-based approaches are superior to locus-based analyses. In addition, we provide a prioritization of disease loci based on network properties and discuss the roles of hub loci across several diseases. We demonstrate that, in general, agonistic associations appear to reflect current disease classifications, and present the potential use of effect sizes in refining and revising these agonistic signals. We further identify potential branching points in disease etiologies based on antagonistic variants and describe plausible small-scale models of the underlying molecular switches. CONCLUSIONS: The observation that a surprisingly high fraction (>15%) of the SNPs considered in our study are associated both agonistically and antagonistically with related as well as unrelated disorders indicates that the molecular mechanisms influencing causes and progress of human diseases are in part interrelated. Genetic overlaps between two diseases also suggest the importance of the affected entities in the specific pathogenic pathways and should be investigated further.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Genome-wide association study, Genetic overlap, Shared variant network, Disease comorbidity; GENOME-WIDE ASSOCIATION; IDIOPATHIC PULMONARY-FIBROSIS; INFLAMMATORY-BOWEL-DISEASE; CORONARY-ARTERY-DISEASE; SUSCEPTIBILITY LOCI; CROHNS-DISEASE; HAPLOTYPE MAP; LARGE-SCALE; ATRIAL-FIBRILLATION; CHROMOSOME 4Q25
ISSN (print) / ISBN 1471-2164
e-ISSN 1471-2164
Journal BMC Genomics
Quellenangaben Volume: 13, Issue: 1, Pages: , Article Number: 490 Supplement: ,
Publisher BioMed Central
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Human Genetics (IHG)
Research Unit Molecular Epidemiology (AME)