4.7 Article

The Missing Risk: MRI and MRS Phenotyping of Abdominal Adiposity and Ectopic Fat

Journal

OBESITY
Volume 20, Issue 1, Pages 76-87

Publisher

WILEY
DOI: 10.1038/oby.2011.142

Keywords

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Funding

  1. United Kingdom Medical Research Council (MRC)
  2. NIHR Biomedical Research Centre
  3. Medical Research Council [MC_U120061305] Funding Source: researchfish
  4. National Institute for Health Research [NF-SI-0508-10112] Funding Source: researchfish
  5. MRC [MC_U120061305] Funding Source: UKRI

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Individual compartments of abdominal adiposity and lipid content within the liver and muscle are differentially associated with metabolic risk factors, obesity and insulin resistance. Subjects with greater intra-abdominal adipose tissue (IAAT) and hepatic fat than predicted by clinical indices of obesity may be at increased risk of metabolic diseases despite their normal size. There is a need for accurate quantification of these potentially hazardous depots and identification of novel subphenotypes that recognize individuals at potentially increased metabolic risk. We aimed to calculate a reference range for total and regional adipose tissue (AT) as well as ectopic fat in liver and muscle in healthy subjects. We studied the relationship between age, body-mass, BMI, waist circumference (WC), and the distribution of AT, using whole-body magnetic resonance imaging (MRI), in 477 white volunteers (243 male, 234 female). Furthermore, we used proton magnetic resonance spectroscopy (MRS) to determine intrahepatocellular (IHCL) and intramyocellular (IMCL) lipid content. The anthropometric variable which provided the strongest individual correlation for adiposity and ectopic fat stores was WC in men and BMI in women. In addition, we reveal a large variation in IAAT, abdominal subcutaneous AT (ASAT), and IHCL depots not fully predicted by clinically obtained measurements of obesity and the emergence of a previously unidentified subphenotype. Here, we demonstrate gender-and age-specific patterns of regional adiposity in a large UK-based cohort and identify anthropometric variables that best predict individual adiposity and ectopic fat stores. From these data we propose the thin-on-the-outside fat-on-the-inside (TOFI) as a subphenotype for individuals at increased metabolic risk.

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