Physiological determinants and impacts of the adipocyte phenotype

Predicting Cardiometabolic Risk From Visceral Abdominal Adiposity in Persons With Chronic Spinal Cord Injury

Persons with spinal cord injury (SCI) have increased adiposity that may predispose to cardiovascular disease compared to those who are able-bodied (AB). The purpose of this study was to determine the relationships between dual energy X-ray absorptiometry (DXA)-derived visceral adipose tissue (VAT) and biomarkers of lipid metabolism and insulin resistance in persons with chronic SCI. A prospective observational study in participants with chronic SCI and age- and gender-matched AB controls. The study was conducted at a Department of Veterans Affairs Medical Center and Private Rehabilitation Hospital. The quantification of DXA-derived VAT volume (VAT_vol) and blood-derived markers of lipid and carbohydrate metabolism were determined in 100 SCI and 51 AB men. The VAT_vol was acquired from a total body DXA scan and analyzed using iDXA enCore CoreScan software (GE Lunar). Blood samples were collected for the serum lipid profile and plasma and glucose concentrations, with the latter two values used to calculate a measure of insulin resistance. In the SCI and AB groups, VAT% was significantly correlated with most cardiometabolic biomarkers. The results of the binary logistic regression analysis revealed that participants who had a VAT_vol above the cutoff value of 1630 cm³ were 3.1-, 4.8-, 5.6-, 19.2-, and 16.7-times more likely to have high serum triglycerides (R²_N= 0.09, p = 0.014), low serum high density lipoprotein cholesterol (R²_N = 0.16, p < 0.001), HOMA2-IR (R²_N = 0.18, p < 0.001), metabolic syndrome (R²_N = 0.25, p < 0.001), and a 10-yr Framingham Risk Score ≥ 10% (R²_N = 0.16, p = 0.001), respectively, when compared to participants below this VAT_vol cutoff value. Our findings reveal that persons with chronic SCI have a higher VAT_vol than that of AB controls, and VAT_vol correlates directly with biomarkers of lipid and carbohydrate metabolism that are strong predictors of cardiometabolic disorders.