Kim Jaehee, Heshka Stanley, Gallagher Dympna, Kotler Donald P, Mayer Laurel, Albu Jeanine, Shen Wei, Freda Pamela U, Heymsfield Steven B
Obesity Research Center, College of Physicians and Surgeons, Columbia University, New York, NY 10025, USA.
J Appl Physiol (1985). 2004 Aug;97(2):655-60. doi: 10.1152/japplphysiol.00260.2004. Epub 2004 Apr 16.
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.
骨骼肌(SM)是一个庞大且具有重要生理意义的部分。脂肪组织散布于SM肌群之间及内部,被称为肌间脂肪组织(IMAT)。本研究的目的是建立预测模型,将双能X线吸收法(DXA)估算的四肢瘦软组织(ALST)与通过磁共振成像量化的全身无IMAT的SM联系起来。对270名健康成年人[体重指数(BMI)<35 kg/m²]进行了ALST和全身无IMAT的SM评估。然后通过留一法并应用于一组SM质量各异的新受试者[神经性厌食症(AN)患者,n = 23;业余运动员,n = 16;肢端肥大症患者,n = 7]对SM预测模型进行验证。仅ALST就与全身无IMAT的SM高度相关[模型1:R² = 0.96,标准误差(SE) = 1.46 kg,P < 0.001];年龄(模型2:R² = 0.97,SE = 1.38 kg,P < 0.001)以及性别和种族(模型3:R² = 0.97,SE = 1.06 kg,两者P < 0.001)显著增强了预测模型。所有三个模型在运动员和肢端肥大症患者中得到验证,但总体上在AN组中显著(P < 0.01 - 0.001)高估了SM。然而,模型1在模型开发组范围内BMI的AN患者中得到验证(n = 11;BMI >16 kg/m²),但在BMI <16 kg/m²的患者中未得到验证(n = 12)。基于DXA的模型在选定人群中准确预测无IMAT的SM,因此为生理和流行病学研究中量化SM提供了新机会。