Aims/hypothesis The anatomic location of excess body fat has an impact on associated cardiometabolic morbidity, and visceral adipose tissue (VAT) is more pathogenic than subcutaneous adipose tissue (SAT). However, VAT or SAT alone provides little information regarding the relative distribution of body fat. We hypothesised that the propensity to store energy in VAT relative to SAT depots may be a correlate of cardiometabolic risk, and tested this hypothesis using the VAT/SAT ratio as a metric of fat distribution. Methods We investigated associations of the VAT/SAT ratio with cardiometabolic traits in 3,223 participants (48% women) from the Framingham Heart Study. Fat depots were quantified by multidetector computed tomography (CT) scanning. Results In women and men, higher VAT/SAT ratio was associated (p<0.05) with most assessed cardiovascular risk factors reflecting blood pressure, dyslipidaemia and insulin resistance. Additional adjustment for BMI did not materially change the findings in women, and generally strengthened associations in men. Further adjustment for VAT attenuated some associations in women, but those with lower HDL-cholesterol, higher triacylglycerol (both p<0.0001) and higher prevalence of hypertension (p=0.02), diabetes (p=0.01) and the metabolic syndrome (p=0.005) remained significant. Similarly, in men, associations with higher systolic (p=0.006) and diastolic blood pressure (p=0.03), higher fasting glucose (p=0.0005), lower HDL-cholesterol and higher triacylglycerol (both p<0.0001) and higher prevalence of diabetes (p=0.006) remained significant. Conclusions/interpretation VAT/SAT ratio is a correlate of cardiometabolic risk, above and beyond BMI and VAT. The propensity to store fat viscerally versus subcutaneously may be a unique risk factor independent of absolute fat volumes.
Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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