Are there genetic paths common to obesity, cardiovascular disease outcomes, and cardiovascular risk factors?
Clustering of obesity, coronary artery disease, and cardiovascular disease risk factors is observed in epidemiological studies and clinical settings. Twin and family studies have provided some supporting evidence for the clustering hypothesis. Loci nearest a lead single nucleotide polymorphism (SNP) showing genome-wide significant associations with coronary artery disease, body mass index, C-reactive protein, blood pressure, lipids, and type 2 diabetes mellitus were selected for pathway and network analyses. Eighty-seven autosomal regions (181 SNPs), mapping to 56 genes, were found to be pleiotropic. Most pleiotropic regions contained genes associated with coronary artery disease and plasma lipids, whereas some exhibited coaggregation between obesity and cardiovascular disease risk factors. We observed enrichment for liver X receptor (LXR)/retinoid X receptor (RXR) and farnesoid X receptor/RXR nuclear receptor signaling among pleiotropic genes and for signatures of coronary artery disease and hepatic steatosis. In the search for functionally interacting networks, we found that 43 pleiotropic genes were interacting in a network with an additional 24 linker genes. ENCODE (Encyclopedia of DNA Elements) data were queried for distribution of pleiotropic SNPs among regulatory elements and coding sequence variations. Of the 181 SNPs, 136 were annotated to ≥ 1 regulatory feature. An enrichment analysis found over-representation of enhancers and DNAse hypersensitive regions when compared against all SNPs of the 1000 Genomes pilot project. In summary, there are genomic regions exerting pleiotropic effects on cardiovascular disease risk factors, although only a few included obesity. Further studies are needed to resolve the clustering in terms of DNA variants, genes, pathways, and actionable targets.
From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore.
Tuomo
T
Rankinen
From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore.
Mark A
MA
Sarzynski
From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore.
Sujoy
S
Ghosh
From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore. claude.bouchard@pbrc.edu.
Claude
C
Bouchard
D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000235:genetics*; D015897:Comorbidity; D003327:Coronary Disease / Q000453:epidemiology / Q000235:genetics; D019049:Developed Countries; D004200:Diseases in Twins / Q000453:epidemiology / Q000235:genetics; D050171:Dyslipidemias / Q000453:epidemiology / Q000235:genetics; D004742:Enhancer Elements, Genetic; D004843:Epistasis, Genetic; D005260:Female; D053263:Gene Regulatory Networks; D058685:Genetic Pleiotropy; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology / Q000235:genetics; D020412:Multifactorial Inheritance; D009765:Obesity / Q000453:epidemiology / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable; D012307:Risk Factors; D057185:Sedentary Behavior; D017678:Sex Distribution; D012907:Smoking / Q000453:epidemiology; D016896:Treatment Outcome; D018433:Twin Studies as Topic
cluster analysis; gene networks; genetic pleiotropism