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Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia? Findings From the GLACIER and
Ashfaq Ali1, Tibor V Varga2, Ivana A Stojkovic2
1From the Department of Clinical Sciences, Genetic & Molecular Epidemiology Unit (A.A., T.V.V., A.P., F.R., P.W.F.) and Department of Clinical Sciences, Diabetes & Cardiovascular Disease-Genetic Epidemiology (I.A.S., C.-A.S., M.O.-M.), Lund University, Malmö, Sweden; Department of Systems Medicine, Steno Diabetes Center, Gentofte, Denmark (A.A.); Department of Biobank Research (G.H., F.R.) and Department of Public Health & Clinical Medicine (P.W.F.), Umeå University, Umeå, Sweden; Human Genetics Programme, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton (I.B.); NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science (I.B.) and University of Cambridge, Metabolic Research Laboratories Institute of Metabolic Science (I.B.), Addenbrooke's Hospital, Cambridge, United Kingdom; Department of Genetics, Physical Anthropology & Animal Physiology, University of the Basque Country (UPV/EHU), Bilbao, Spain (A.P.); and Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA (P.W.F.). Paul.Franks@med.lu.se aqai@steno.dk.
Background:
Obesity is a major risk factor for dyslipidemia, but this relationship is highly variable. Recently published data from 2 Danish cohorts suggest that genetic factors may underlie some of this variability.
Methods And Results:
We tested whether established triglyceride-associated loci modify the relationship of body mass index (BMI) and triglyceride concentrations in 2 Swedish cohorts (the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk [GLACIER Study; N=4312] and the Malmö Diet and Cancer Study [N=5352]). The genetic loci were amalgamated into a weighted genetic risk score (WGRSTG) by summing the triglyceride-elevating alleles (weighted by their established marginal effects) for all loci. Both BMI and the WGRSTG were strongly associated with triglyceride concentrations in GLACIER, with each additional BMI unit (kg/m(2)) associated with 2.8% (P=8.4×10(-84)) higher triglyceride concentration and each additional WGRSTG unit with 2% (P=7.6×10(-48)) higher triglyceride concentration. Each unit of the WGRSTG was associated with 1.5% higher triglyceride concentrations in normal weight and 2.4% higher concentrations in overweight/obese participants (Pinteraction=0.056). Meta-analyses of results from the Swedish cohorts yielded a statistically significant WGRSTG×BMI interaction effect (Pinteraction=6.0×10(-4)), which was strengthened by including data from the Danish cohorts (Pinteraction=6.5×10(-7)). In the meta-analysis of the Swedish cohorts, nominal evidence of a 3-way interaction (WGRSTG×BMI×sex) was observed (Pinteraction=0.03), where the WGRSTG×BMI interaction was only statistically significant in females. Using protein-protein interaction network analyses, we identified molecular interactions and pathways elucidating the metabolic relationships between BMI and triglyceride-associated loci.
Conclusions:
Our findings provide evidence that body fatness accentuates the effects of genetic susceptibility variants in hypertriglyceridemia, effects that are most evident in females.
