Person:

Hoffmann, Udo

Background: Excess accumulation of abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) is associated with adverse levels of adipokines and cardiovascular disease risk. Whether fat quality is associated with adipokines has not been firmly established. This study examined the association between abdominal SAT and VAT density, an indirect measure of fat quality, with a panel of metabolic regulatory biomarkers secreted by adipose tissue or the liver independently of absolute fat volumes. Methods and Results: We evaluated 1829 Framingham Heart Study participants (44.9% women). Abdominal SAT and VAT density was estimated indirectly by adipose tissue attenuation using computed tomography. Adipokines included adiponectin, leptin receptor, leptin, fatty acid‐binding protein 4 (FABP‐4), retinol‐binding protein 4 (RBP‐4), and fetuin‐A. Fat density was associated with all the biomarkers evaluated, except fetuin‐A. Lower fat density (ie, more‐negative fat attenuation) was associated with lower adiponectin and leptin receptor, but higher leptin and FABP‐4 levels (all P<0.0001). SAT density was inversely associated with RPB‐4 in both sexes, whereas the association between VAT density and RPB‐4 was only observed in men (P<0.0001). In women, after additional adjustment for respective fat volume, SAT density retained the significant associations with adiponectin, leptin, FABP‐4, and RBP‐4; and VAT density with adiponectin only (all P<0.0001). In men, significant associations were maintained upon additional adjustment for respective fat volume (P<0.005). Conclusions: Lower abdominal fat density was associated with a profile of biomarkers suggestive of greater cardiometabolic risk. These observations support that fat density may be a valid biomarker of cardiometabolic risk.

Background & Aims Non-alcoholic fatty liver disease (NAFLD) is associated with an increased risk of cardiovascular related death, particularly in those with hepatic fibrosis. We determined the prevalence of predicted fibrosis based on non-invasive fibrosis markers and the association of hepatic fibrosis with cardiovascular risk factors. Methods: Cross-sectional study of 575 Framingham Heart Study participants with NAFLD based on computed tomography. We determined the prevalence of predicted fibrosis based on the aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio, AST to platelet ratio index (APRI), the Fibrosis-4 score (FIB4), and the NAFLD Fibrosis Score (NFS). Using multivariable logistic regression models, we examined the association between low, indeterminate, or high risk for fibrosis according to the NFS and various cardiometabolic risk factors. Results: The predicted risk of fibrosis was 12%, 4%, 5%, and 32% for the NFS, FIB4, APRI, and AST/ALT ratio, respectively. In multivariable models, participants with a high risk for advanced fibrosis by the NFS had a wider pulse pressure (adjusted mean difference = 6.87 mm Hg; p = 0.0002) and an increased odds of hypertension (OR 2.92; p = 0.007) compared to those with low risk of fibrosis. There were no statistically significant differences between other cardiovascular risk factors for those with a high versus low risk of fibrosis. Conclusions: The AST/ALT ratio, APRI, and NFS give widely disparate predictions of liver fibrosis. Participants with a high risk for fibrosis based on NFS had wider pulse pressure and increased odds of hypertension. Whether modifying these risk factors impacts cardiovascular endpoints in NAFLD patients remains unknown.

Background: Thoracic periaortic adipose tissue (TAT) is associated with atherosclerosis and cardiovascular disease (CVD) risk factors and may play a role in obesity‐mediated vascular disease. We sought to determine the prevalence, distribution, and risk factor correlates of high TAT. Methods and Results: Participants from the Framingham Heart Study (n=3246, 48% women, mean age 51.1 years) underwent multidetector computed tomography; high TAT and visceral adipose tissue (VAT) were defined on the basis of sex‐specific 90th percentiles in a healthy referent sample. The prevalence of high TAT was 38.1% in women and 35.7% in men. Among individuals without high VAT, 10.1% had high TAT. After adjustment for age and VAT, both women and men with high TAT in the absence of high VAT were older and had a higher prevalence of CVD (P<0.0001) compared with those without high TAT. In addition, men in this group were more likely to be smokers (P=0.02), whereas women were more likely to have low high‐density lipoprotein cholesterol (P=0.005). Conclusions: Individuals in our community‐based sample with high TAT in the absence of high VAT were characterized by an adverse cardiometabolic profile. This adipose tissue phenotype may identify a subset of individuals with distinct metabolic characteristics.

Background: Ectopic fat density is associated with cardiovascular disease (CVD) risk factors above and beyond fat volume. Volumetric measures of ectopic fat have been associated with CVD risk factors and subclinical atherosclerosis. The aim of this study was to investigate the association between fat density and subclinical atherosclerosis. Methods and Results: Participants were drawn from the Multi‐Detector Computed Tomography (MDCT) substudy of the Framingham Heart Study (n=3079; mean age, 50.1 years; 49.2% women). Fat density was indirectly estimated by computed tomography attenuation (Hounsfield Units [HU]) on abdominal scan slices. Visceral fat (VAT), subcutaneous fat (SAT), and pericardial fat HU and volumes were quantified using standard protocols; coronary and abdominal aortic calcium (CAC and AAC, respectively) were measured radiographically. Multivariable‐adjusted logistic regression models were used to evaluate the association between adipose tissue HU and the presence of CAC and AAC. Overall, 17.1% of the participants had elevated CAC (Agatston score [AS]>100), and 23.3% had elevated AAC (AS>age‐/sex‐specific cutoffs). Per 5‐unit decrement in VAT HU, the odds ratio (OR) for elevated CAC was 0.76 (95% confidence interval [CI], 0.65 to 0.89; P=0.0005), even after adjustment for body mass index or VAT volume. Results were similar for SAT HU. With decreasing VAT HU, we also observed an OR of 0.79 (95% CI, 0.67 to 0.92; P=0.004) for elevated AAC after multivariable adjustment. We found no significant associations between SAT HU and AAC. There was no significant association between pericardial fat HU and either CAC or AAC. Conclusions: Lower VAT and SAT HU, indirect estimates of fat quality, are associated with a lower risk of subclinical atherosclerosis.

Background: Visceral adipose tissue (VAT) and fatty liver differ in their associations with cardiovascular risk compared with subcutaneous adipose tissue (SAT). Several biomarkers have been linked to metabolic derangements and may contribute to the pathogenicity of fat depots. We examined the association between fat depots on multidetector computed tomography and metabolic regulatory biomarkers. Methods and Results: Participants from the Framingham Heart Study (n=1583, 47% women) underwent assessment of SAT, VAT, and liver attenuation. We measured circulating biomarkers secreted by adipose tissue or liver (adiponectin, leptin, leptin receptor, fatty acid binding protein 4, fetuin‐A, and retinol binding protein 4). Using multivariable linear regression models, we examined relations of fat depots with biomarkers. Higher levels of fat depots were positively associated with leptin and fatty acid binding protein 4 but negatively associated with adiponectin (all P<0.001). Associations with leptin receptor, fetuin‐A, and retinol binding protein 4 varied according to fat depot type or sex. When comparing the associations of SAT and VAT with biomarkers, VAT was the stronger correlate of adiponectin (β=−0.28 [women]; β=−0.30 [men]; both P<0.001), whereas SAT was the stronger correlate of leptin (β=0.62 [women]; β=0.49 [men]; both P<0.001; P<0.001 for comparing VAT versus SAT). Although fetuin‐A and retinol binding protein 4 are secreted by the liver in addition to adipose tissue, associations of liver attenuation with these biomarkers was not stronger than that of SAT or VAT. Conclusions: SAT, VAT, and liver attenuation are associated with metabolic regulatory biomarkers with differences in the associations by fat depot type and sex. These findings support the possibility of biological differences between fat depots.

Objective: Prior studies on the association of physical activity (PA) and non-alcoholic fatty liver disease are limited by reliance on subjective measures of PA. We examined the association between objectively measured PA and hepatic steatosis defined by computed tomography (CT). Methods: We conducted a cross-sectional study of 1060 Framingham Heart Study participants who participated in the Multi-Detector CT 2 substudy and who underwent assessment of PA via accelerometry. Hepatic steatosis was estimated by liver attenuation, as measured by CT. We explored the relationship between liver attenuation and PA using multivariable regression models. Results: In multivariable-adjusted models, we observed an inverse association between PA and liver attenuation. Each 30 min/day increase in moderate-to-vigorous PA (MVPA) was associated with a reduced odds of hepatic steatosis (OR=0.62, p<0.001). This association was attenuated and no longer statistically significant after adjustment for BMI (OR=0.77, p=0.05) or VAT (OR=0.83, p=0.18). Participants who met the national PA recommendations of engaging in ≥150 minutes/week of MVPA, had the lowest odds of hepatic steatosis, even after adjusting for BMI (OR=0.63, p=0.007) or VAT (OR=0.67, p=0.03). Conclusions: There is an inverse association between PA and hepatic steatosis. Participants who met the national PA guidelines had the lowest prevalence of hepatic steatosis.

Background: Prolactin is an anterior pituitary hormone that may modulate the adverse effects of obesity. Prolactin has been associated with cardiovascular disease mortality, but less is known about whether prolactin predicts incidence of cardiovascular disease risk factors. Methods and Results: Our sample (n=3232, mean age 40.4 years, 52.1% women) was drawn from Framingham Heart Study participants who attended 2 examinations an average of 6.1 years apart. After excluding those with elevated prolactin (>30 mg/dL for women, >20 mg/dL for men), multivariable‐adjusted regressions modeled the associations between baseline prolactin and changes in cardiovascular disease risk factors. Models were adjusted for age, sex, baseline value of the risk factor, smoking status, hormone replacement therapy, and menopausal status and additionally for body mass index. Mean prolactin levels were 11.9 mg/dL (SD 5.2) in women and 8.0 mg/dL (SD 2.9) in men. No associations were observed for change in weight, body composition, total cholesterol, triglycerides, or fasting glucose. In women, for example, for each 5‐mg/dL increment in prolactin, odds of incident hypercholesterolemia were 1.06, which was not significant (95% CI 0.91–1.23, P=0.46). Some exceptions were of note. In women, for each 5‐mg/dL increment in prolactin, we observed increased odds of low high‐density lipoprotein cholesterol at follow‐up (odds ratio 1.50, 95% CI 1.18–1.91, P=0.001) that persisted after adjustment for body mass index (P=0.001). In men, a 5‐mg/dL increment in prolactin was associated with increased odds of incident hypertension (odds ratio 1.61, 95% CI 1.18–2.20 P=0.002) and incident diabetes (odds ratio 1.70, 95% CI 1.04–2.78, P=0.03). Conclusions: Prolactin is not associated with a comprehensive panel of incident cardiovascular disease risk factors. Measurement of circulating prolactin levels in the community likely does not provide substantial insight into cardiometabolic risk.