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Network properties of complex human disease genes identified through genome-wide association studies
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysik.ORCID-id: 0000-0003-2156-1096
Vise andre og tillknytning
2009 (engelsk)Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 4, nr 11, s. e8090-Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Background Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias.

Principal findings We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process.

Conclusions This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.

sted, utgiver, år, opplag, sider
2009. Vol. 4, nr 11, s. e8090-
Emneord [en]
topological features; interactome; microarray; expression; centrality; disorders; traits
HSV kategori
Identifikatorer
URN: urn:nbn:se:umu:diva-30109DOI: 10.1371/journal.pone.0008090ISI: 000272828400029OAI: oai:DiVA.org:umu-30109DiVA, id: diva2:279809
Tilgjengelig fra: 2009-12-07 Laget: 2009-12-07 Sist oppdatert: 2018-06-08bibliografisk kontrollert

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