Pathway profiling of obesity using the Weighted Interaction SNP Hub (WISH) network method

Lisette JA Kogelman, Sameer Pant, Steve Horvath, Merete Fredholm, Haja N Kadarmideen

Research output: Other contribution to conferenceAbstractpeer-review


Objectives: Obesity is a worldwide epidemic, causing many health problems, resulting from the interaction between genetic and environmental factors. Using founder breeds divergent with respect to obesity traits we created an F2 pig population (454 pigs), which was intensively phenotyped for 36 phenotypes and genotyped using a 60K SNP Chip. In Genome Wide Association Studies (GWAS), marginal SNP (but not interaction) effects are estimated explaining a small proportion of the genetic variation. The main objective of this study was to develop a Weighted Interaction SNP Hub (WISH) Network method and apply it to the F2 population in order to elucidate highly interconnected genetic variant modules, hub SNPs and their corresponding pathways involved in the pathogenesis of obesity.

Methods: A genetic Obesity Index (OI), based on estimated breeding values for key traits was constructed and used for selection of 150 animals (50 high, 50 median, 50 low). We created an algorithm to develop scale-free WISH networks, whereby interactions are expressed as correlations between allele substitution effects of SNPs, following the Weighted Gene Coexpression Network Analysis (WGCNA) method. After calculating the adjacency matrix, modules were formed based on their topological overlap, showing the degree of overlap in shared neighbors between SNP-pairs. By investigating differentially correlated modules to different OI groups and key traits, different subtypes of obesity could be predicted. Annotation and functional enrichment analyses of resulting SNP modules was performed to indicate biological relevance.

Results: Preliminary results show that the WISH network method detects several modules, each consisting of SNP hubs in the network of top SNPs selected based on GWAS results. Annotation and enrichment of these modules shows key functional and biological pathways related to obesity.

Conclusion: Based on the WGCNA framework that has been used to study co-expressed pathways using microarray data, we developed a new method called the WISH Networks and applied it to build SNP interaction networks. This resulted in the detection of various SNP modules affecting obesity. Analysis of these modules will result in the identification of biomarkers and pathways related to obesity.
Original languageEnglish
Number of pages1
Publication statusPublished - 2013
EventJoint Conference of the Human Genome Meeting 2013 and the 21st International Congress of Genetics: HGM2013/21st ICG - The Sands Expo and Convention Center, Marina Bay Sands, Singapore, Singapore
Duration: 13 Apr 201318 Apr 2013 (Conference information) (Abstract book)


ConferenceJoint Conference of the Human Genome Meeting 2013 and the 21st International Congress of Genetics
Abbreviated titleGenetics and Genomics of Global Health and Sustainability
Internet address


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