A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.

Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
PLoS Genetics (Impact Factor: 8.17). 10/2011; 7(10):e1002322. DOI: 10.1371/journal.pgen.1002322
Source: PubMed

ABSTRACT Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

  • [Show abstract] [Hide abstract]
    ABSTRACT: -Metabolic syndrome (MetS) refers to the clustering of cardio-metabolic risk factors including dyslipidemia, central adiposity, hypertension and hyperglycemia in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS.
    Circulation Cardiovascular Genetics 07/2014; · 6.73 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cancer comorbidities often reflect the complex pathogenesis of cancers and provide valuable clues to discover the underlying genetic mechanisms of cancers. In this study, we systematically mine and analyze cancer-specific comorbidity from the FDA Adverse Event Reporting System. We stratified 3,354,043 patients based on age and gender, and developed a network-based approach to extract comorbidity patterns from each patient group. We compared the comorbidity patterns among different patient groups and investigated the effect of age and gender on cancer comorbidity patterns. The results demonstrated that the comorbidity relationships between cancers and non-cancer diseases largely depend on age and gender. A few exceptions are depression, anxiety, and metabolic syndrome, whose comorbidity relationships with cancers are relatively stable among all patients. Literature evidences demonstrate that these stable cancer comorbidities reflect the pathogenesis of cancers. We applied our comorbidity mining approach on colorectal cancer and detected its comorbid associations with metabolic syndrome components, diabetes, and osteoporosis. Our results not only confirmed known cancer comorbidities but also generated novel hypotheses, which can illuminate the common pathophysiology between cancers and their co-occurring diseases.
    Cancer informatics 01/2014; 13(Suppl 1):37-44.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Metabolic syndrome (MetS) is a cluster of metabolic traits associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus. Central obesity and insulin resistance are thought to play key roles in the pathogenesis of the MetS. The MetS has a significant genetic component, and therefore linkage analysis, candidate gene approach, and genome-wide association (GWA) studies have been applied in the search of gene variants for the MetS. A few variants have been identified, located mostly in or near genes regulating lipid metabolism. GWA studies for the individual components of the MetS have reported several loci having pleiotropic effects on multiple MetS-related traits. Genetic studies have provided so far only limited evidence for a common genetic background of the MetS. Epigenetic factors (DNA methylation and histone modification) are likely to play important roles in the pathogenesis of the MetS, and they might mediate the effects of environmental exposures on the risk of the MetS. Further research is needed to clarify the role of genetic variation and epigenetic mechanisms in the development of the MetS.
    Reviews in Endocrine and Metabolic Disorders 08/2014; 15(4). · 4.58 Impact Factor

Full-text (2 Sources)

Available from
May 27, 2014