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Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm2 and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R2 = 0.63, RMSE = 42.4 cm2, calibration slope = 0.94) but lower in MESA (R2 = 0.44, RMSE = 60.7 cm2, calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.

Background Identifying associations between serum metabolites and visceral adipose tissue ( VAT ) could provide novel biomarkers of VAT and insights into the pathogenesis of obesity-related diseases. We aimed to discover and replicate metabolites reflecting pathways related to VAT . Methods and Results Associations between fasting serum metabolites and VAT area (by computed tomography or magnetic resonance imaging) were assessed with cross-sectional linear regression of individual-level data from participants in MESA (Multi-Ethnic Study of Atherosclerosis; discovery, N=1103) and the NEO (Netherlands Epidemiology of Obesity) study (replication, N=2537). Untargeted 1H nuclear magnetic resonance metabolomics profiling of serum was performed in MESA, and metabolites were replicated in the NEO study using targeted 1H nuclear magnetic resonance spectroscopy. A total of 30 590 metabolomic spectral variables were evaluated. After adjustment for age, sex, race/ethnicity, socioeconomic status, smoking, physical activity, glucose/lipid-lowering medication, and body mass index, 2104 variables representing 24 nonlipid and 49 lipid/lipoprotein subclass metabolites remained significantly associated with VAT ( P=4.88×10-20-1.16×10-3). These included conventional metabolites, amino acids, acetylglycoproteins, intermediates of glucose and hepatic metabolism, organic acids, and subclasses of apolipoproteins, cholesterol, phospholipids, and triglycerides. Metabolites mapped to 31 biochemical pathways, including amino acid substrate use/metabolism and glycolysis/gluconeogenesis. In the replication cohort, acetylglycoproteins, branched-chain amino acids, lactate, glutamine (inversely), and atherogenic lipids remained associated with VAT ( P=1.90×10-35-8.46×10-7), with most associations remaining after additional adjustment for surrogates of VAT (glucose level, waist circumference, and serum triglycerides), reflecting novel independent associations. Conclusions We identified and replicated a metabolite panel associated with VAT in 2 community-based cohorts. These findings persisted after adjustment for body mass index and appear to define a metabolic signature of visceral adiposity.

The aim of this study was to investigate the associations among sex hormone–binding globulin (SHBG), visceral adipose tissue (VAT), liver fat content, and risk of type 2 diabetes (T2D). In the Netherlands Epidemiology of Obesity study, 5,690 women (53%) and men (47%) without preexisting diabetes were included and followed for incident T2D. SHBG concentrations were measured in all participants, VAT was measured using MRI, and liver fat content was measured using proton magnetic resonance spectroscopy in a random subset of 1,822 participants. We examined associations between SHBG and liver fat using linear regression and bidirectional Mendelian randomization analyses and between SHBG and T2D using Cox regression adjusted for confounding and additionally for VAT and liver fat to examine mediation. Mean age was 56 (SD 6) years, mean BMI was 30 (SD 4) kg/m2, median SHBG was 47 (interquartile range [IQR] 34–65) nmol/L in women and 34 (26–43) nmol/L in men, and median liver fat was 3.4% (IQR 1.6–8.2%) in women and 6.0% (2.9–13.5%) in men. Compared with the highest SHBG quartile, liver fat was 2.9-fold (95% CI 2.4, 3.4) increased in women and 1.6-fold (95% CI 1.3, 1.8) increased in men, and the hazard ratio of T2D was 4.9 (95% CI 2.4, 9.9) in women and 1.8 (1.1, 2.9) in men. Genetically predicted SHBG was associated with liver fat content (women: SD −0.45 [95% CI −0.55, −0.35]; men: natural logarithm, −0.25 [95% CI −0.34, −0.16]). VAT and liver fat together mediated 43% (women) and 60% (men) of the SHBG-T2D association. To conclude, in a middle-aged population with overweight, the association between low SHBG and increased risk of T2D was, for a large part, mediated by increased VAT and liver fat. Article Highlights: The objective of this study was to unravel the associations between sex hormone–binding globulin (SHBG) and type 2 diabetes (T2D). The extent to which the association between low SHBG and increased risk of T2D was mediated by visceral adipose tissue (VAT) and liver fat was examined. VAT and liver fat were found to mediate a large part of the association between SHBG and T2D. Both lifestyle and medical interventions that increase SHBG may reduce VAT, liver fat, and the risk of T2D. [ABSTRACT FROM AUTHOR]