The Normal Limits, Subclinical Significance, Related Metabolic Derangements and Distinct Biological Effects of Body Site-Specific Adiposity in Relatively Healthy Population

<div><p>Background</p><p>The accumulation of visceral adipose tissue that occurs with normal aging is associated with increased cardiovascular risks. However, the clinical significance, biological effects, and related cardiometabolic derangements of body-site specific adiposity in a relatively healthy population have not been well characterized.</p><p>Materials and Methods</p><p>In this cross-sectional study, we consecutively enrolled 608 asymptomatic subjects (mean age: 47.3 years, 27% female) from 2050 subjects undergoing an annual health survey in Taiwan. We measured pericardial (PCF) and thoracic peri-aortic (TAT) adipose tissue volumes by 16-slice multi-detector computed tomography (MDCT) (Aquarius 3D Workstation, TeraRecon, San Mateo, CA, USA) and related these to clinical characteristics, body fat composition (Tanita 305 Corporation, Tokyo, Japan), coronary calcium score (CCS), serum insulin, high-sensitivity C-reactive protein (Hs-CRP) level and circulating leukocytes count. Metabolic risk was scored by Adult Treatment Panel III guidelines.</p><p>Results</p><p>TAT, PCF, and total body fat composition all increased with aging and higher metabolic scores (all p<0.05). Only TAT, however, was associated with higher circulating leukocyte counts (ß-coef.:0.24, p<0.05), serum insulin (ß-coef.:0.17, p<0.05) and high sensitivity C-reactive protein (ß-coef.:0.24, p<0.05). These relationships persisted after adjustment in multivariable models (all p<0.05). A TAT volume of 8.29 ml yielded the largest area under the receiver operating characteristic curve (AUROC: 0.79, 95%CI: 0.74–0.83) to identify metabolic syndrome. TAT but not PCF correlated with higher coronary calcium score after adjustment for clinical variables (all p<0.05).</p><p>Conclusion</p><p>In our study, we observe that age-related body-site specific accumulation of adipose tissue may have distinct biological effects. Compared to other adiposity measures, peri-aortic adiposity is more tightly associated with cardiometabolic risk profiles and subclinical atherosclerosis in a relatively healthy population.</p></div

Comparison of body fat composition, pericardial and thoracic peri-aortic adipose tissue with age quartiles and numbers of abnormal metabolic components. A

<p>) Increases in adiposity across age quartiles in our cohort (all p for trend <0.05). <b>B</b>). Larger numbers of abnormal metabolic components were associated with higher body fat composition and increasing visceral adipose tissue burden (all p for trend <0.001). Metabolic category 0, metabolic score = 0; 1, metabolic score = 1; 2, metabolic score = 2; 3, metabolic score ≥3. Abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061997#pone-0061997-g001" target="_blank">Figure 1</a>. ★p<0.05, ★★p<0.01, ★★★p<0.001 by ANOVA post hoc paired comparison</p

Baseline characteristics of the study population by age quartiles.

<p>BMI: body mass index; BSA: body surface area; DBP: diastolic blood pressure; eGFR: estimated glomerular filtration rate; HbA1c: glycosylated hemoglobin level; HDL: high-density lipoprotein; HOMA-IR: homeostasis model assessment-estimated insulin resistance; LDL: low-density lipoprotein; SBP: systolic blood pressure; TG: Triglycerides.</p

Relationship between clinical variables, anthropometric measures and measures of various adiposity.

<p>hs-CRP, high sensitivity C-reactive protein; WBC Count, circulating white blood cell count; PCF, pericardial adipose tissue; TAT, thoracic peri-aortic adipose tissue. Other abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061997#pone-0061997-t001" target="_blank">Table 1</a>.</p>*<p>p<0.05, ^¥p<0.1.</p

Distributions of body fat composition and both visceral adipose tissue volumes (PCF and TAT) in our study cohort.

<p>PCF, pericardial adipose tissue; TAT, thoracic peri-aortic adipose tissue.</p

Odds of having abnormal metabolic markers according to tertiles of adiposity measures.

*<p>p<0.05, ^¥p<0.1.</p><p>OR, odds ratio; CI, confidence interval. Other abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061997#pone-0061997-t001" target="_blank">Tables 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061997#pone-0061997-t002" target="_blank">2</a>.</p

The association of adiposity measures with hs-CRP and coronary calcium score after adjustment for age, gender, and anthropometric data.

<p>Abbreviations as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061997#pone-0061997-t001" target="_blank">Table 1</a> & <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061997#pone-0061997-t002" target="_blank">2</a>. SD, standard deviation.</p><p>Model 1; Adjusted for age & gender;</p><p>Model 2: Adjusted for age, gender, systolic blood pressure and anthropometrics (BMI, BSA & Waist, sequentially);</p><p>Model 3: Adjusted for age, gender, systolic blood pressure, cholesterol, fasting glucose, eGFR, HDL, exercise, drinking, smoking behavior & anthrpometrics (BMI, BSA & Waist, sequentially).</p>*<p>denotes p<0.05, ^¥denotes p> = 0.05 & <0.1.</p

Receiver operating characteristic (ROC) curves for each measure of adiposity in identifying metabolic syndrome, with individual 95% confidence interval (95% CI) reported

<p>. Furthermore, the difference between each area under ROC (AUROC) was calculated with p value provided for statistical significance (p of ΔAUROC). The area under the ROC curve (AUROC) was largest for peri-aortic adipose tissue (p of ΔAUROC: 0.00562).</p

Correlation between measures of various adiposity (body fat composition and both visceral adipose tissue volume) and circulating WBC counts.

<p>Though body fat composition and visceral adipose tissue volumes had positive linear correlations with WBC numbers, only the correlation with TAT remained significant after multivariable adjustment. Clinical variables in the model included age, gender, systolic blood pressure, fasting glucose, cholesterol, high-density lipoprotein, estimated glomerular filtration rate, exercise, smoking and alcohol consumption. BMI, body-mass index; BSA; body surface area; WBC, white blood cell; PCF, pericardial adipose tissue; TAT, thoracic peri-aortic adipose tissue.</p