Literature DB >> 15090482

Intermuscular adipose tissue-free skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in adults.

Jaehee Kim1, Stanley Heshka, Dympna Gallagher, Donald P Kotler, Laurel Mayer, Jeanine Albu, Wei Shen, Pamela U Freda, Steven B Heymsfield.   

Abstract

Skeletal muscle (SM) is a large and physiologically important compartment. Adipose tissue is found interspersed between and within SM groups and is referred to as intermuscular adipose tissue (IMAT). The study objective was to develop prediction models linking appendicular lean soft tissue (ALST) estimates by dual-energy X-ray absorptiometry (DXA) with whole body IMAT-free SM quantified by magnetic resonance imaging. ALST and total-body IMAT-free SM were evaluated in 270 healthy adults [body mass index (BMI) of <35 kg/m(2)]. The SM prediction models were then validated by the leave-one-out method and by application in a new group of subjects who varied in SM mass [anorexia nervosa (AN), n = 23; recreational athletes, n = 16; patients with acromegaly, n = 7]. ALST alone was highly correlated with whole body IMAT-free SM [model 1: R(2) = 0.96, standard error (SE) = 1.46 kg, P < 0.001]; age (model 2: R(2) = 0.97, SE = 1.38 kg, P < 0.001) and sex and race (model 3: R(2) = 0.97, SE = 1.06 kg, both P < 0.001) added significantly to the prediction models. All three models validated in the athletes and patients with acromegaly but significantly (P < 0.01-0.001) over-predicted SM in the AN group as a whole. However, model 1 was validated in AN patients with BMIs in the model-development group range (n = 11; BMI of >16 kg/m(2)) but not in those with a BMI of <16 kg/m(2) (n = 12). The DXA-based models are accurate for predicting IMAT-free SM in selected populations and thus provide a new opportunity for quantifying SM in physiological and epidemiological investigations.

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Mesh:

Year:  2004        PMID: 15090482     DOI: 10.1152/japplphysiol.00260.2004

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  60 in total

1.  Changes in regional body composition explain increases in energy expenditure in elite junior basketball players over the season.

Authors:  Analiza M Silva; Diana A Santos; Catarina N Matias; Paulo M Rocha; Edio L Petroski; Cláudia S Minderico; Luís B Sardinha
Journal:  Eur J Appl Physiol       Date:  2011-11-24       Impact factor: 3.078

2.  Bone mineral density in Klinefelter syndrome is reduced and primarily determined by muscle strength and resorptive markers, but not directly by testosterone.

Authors:  A Bojesen; N Birkebæk; K Kristensen; L Heickendorff; L Mosekilde; J S Christiansen; C H Gravholt
Journal:  Osteoporos Int       Date:  2010-07-24       Impact factor: 4.507

3.  Body composition, fitness, and metabolic health during strength and endurance training and their combination in middle-aged and older women.

Authors:  Elina Sillanpää; David E Laaksonen; Arja Häkkinen; Laura Karavirta; Benjamin Jensen; William J Kraemer; Kai Nyman; Keijo Häkkinen
Journal:  Eur J Appl Physiol       Date:  2009-03-06       Impact factor: 3.078

4.  Prediction of limb lean tissue mass from bioimpedance spectroscopy in persons with chronic spinal cord injury.

Authors:  Christopher M Cirnigliaro; Michael F La Fountaine; Racine Emmons; Steven C Kirshblum; Pierre Asselin; Ann M Spungen; William A Bauman
Journal:  J Spinal Cord Med       Date:  2013-09       Impact factor: 1.985

5.  Intermuscular adipose tissue directly modulates skeletal muscle insulin sensitivity in humans.

Authors:  Stephan Sachs; Simona Zarini; Darcy E Kahn; Kathleen A Harrison; Leigh Perreault; Tzu Phang; Sean A Newsom; Allison Strauss; Anna Kerege; Jonathan A Schoen; Daniel H Bessesen; Thomas Schwarzmayr; Elisabeth Graf; Dominik Lutter; Jan Krumsiek; Susanna M Hofmann; Bryan C Bergman
Journal:  Am J Physiol Endocrinol Metab       Date:  2019-01-08       Impact factor: 4.310

6.  IGF-1 levels across the spectrum of normal to elevated in acromegaly: relationship to insulin sensitivity, markers of cardiovascular risk and body composition.

Authors:  Tirissa J Reid; Zhezhen Jin; Wei Shen; Carlos M Reyes-Vidal; Jean Carlos Fernandez; Jeffrey N Bruce; Jane Kostadinov; Kalmon D Post; Pamela U Freda
Journal:  Pituitary       Date:  2015-12       Impact factor: 4.107

7.  Total body skeletal muscle mass: estimation by creatine (methyl-d3) dilution in humans.

Authors:  Richard V Clark; Ann C Walker; Robin L O'Connor-Semmes; Michael S Leonard; Ram R Miller; Stephen A Stimpson; Scott M Turner; Eric Ravussin; William T Cefalu; Marc K Hellerstein; William J Evans
Journal:  J Appl Physiol (1985)       Date:  2014-04-24

8.  Creatine ( methyl-d3) dilution in urine for estimation of total body skeletal muscle mass: accuracy and variability vs. MRI and DXA.

Authors:  Richard V Clark; Ann C Walker; Ram R Miller; Robin L O'Connor-Semmes; Eric Ravussin; William T Cefalu
Journal:  J Appl Physiol (1985)       Date:  2017-08-31

9.  Lower visceral and subcutaneous but higher intermuscular adipose tissue depots in patients with growth hormone and insulin-like growth factor I excess due to acromegaly.

Authors:  Pamela U Freda; Wei Shen; Steven B Heymsfield; Carlos M Reyes-Vidal; Eliza B Geer; Jeffrey N Bruce; Dympna Gallagher
Journal:  J Clin Endocrinol Metab       Date:  2008-03-18       Impact factor: 5.958

10.  Greater lean tissue and skeletal muscle mass are associated with higher bone mineral content in children.

Authors:  Karen B Dorsey; John C Thornton; Steven B Heymsfield; Dympna Gallagher
Journal:  Nutr Metab (Lond)       Date:  2010-05-11       Impact factor: 4.169

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