Published in

Wiley, Obesity, 1(20), p. 76-87, 2012

DOI: 10.1038/oby.2011.142

Links

Tools

Export citation

Search in Google Scholar

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

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

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.