Murphy Rachel A, Moore Steven C, Playdon Mary, Meirelles Osorio, Newman Anne B, Milijkovic Iva, Kritchevsky Stephen B, Schwartz Ann, Goodpaster Bret H, Sampson Joshua, Cawthon Peggy, Simonsick Eleanor M, Gerszten Robert E, Clish Clary B, Harris Tamara B
Centre of Excellence in Cancer Prevention, School of Population and Public Health, University of British Columbia, Vancouver, Canada.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
J Gerontol A Biol Sci Med Sci. 2017 Oct 1;72(10):1352-1359. doi: 10.1093/gerona/glw245.
To identify biomarkers of body mass index, body fat, trunk fat, and appendicular lean mass, nontargeted metabolomics was performed in plasma from 319 black men in the Health, Aging and Body Composition study (median age 72 years, median body mass index 26.8 kg/m2). Body mass index was calculated from measured height and weight; percent fat, percent trunk fat, and appendicular lean mass were measured with dual-energy x-ray absorptiometry. Pearson partial correlations between body composition measures and metabolites were adjusted for age, study site, and smoking. Out of 350 metabolites, body mass index, percent fat, percent trunk fat, and appendicular lean mass were significantly correlated with 92, 48, 96, and 43 metabolites at p less than .0014. Metabolites most strongly correlated with body composition included carnitine, a marker of fatty acid oxidation (positively correlated), triacylglycerols (positively correlated), and amino acids including branched-chain amino acids (positively correlated except for acetylglycine and serine). Gaussian Graphical Models of metabolites found that 25 lipid metabolites clustered into a single network. Groups of five amino acids, three plasmalogens, and two carnitines were also observed. Findings confirm prior reports of associations between amino acids, lean mass, and fat mass in addition to associations not previously reported. Future studies should consider whether these metabolites are relevant for metabolic disease processes.
为了识别体重指数、体脂、躯干脂肪和四肢瘦体重的生物标志物，我们在健康、衰老和身体成分研究中对319名黑人男性的血浆进行了非靶向代谢组学分析（中位年龄72岁，中位体重指数26.8kg/m²）。体重指数根据测量的身高和体重计算得出；体脂百分比、躯干脂肪百分比和四肢瘦体重通过双能X线吸收法测量。身体成分测量值与代谢物之间的Pearson偏相关系数针对年龄、研究地点和吸烟情况进行了校正。在350种代谢物中，体重指数、体脂百分比、躯干脂肪百分比和四肢瘦体重与92、48、96和43种代谢物显著相关，p值小于0.0014。与身体成分相关性最强的代谢物包括肉碱（脂肪酸氧化的标志物，呈正相关）、三酰甘油（呈正相关）以及包括支链氨基酸在内的氨基酸（除乙酰甘氨酸和丝氨酸外呈正相关）。代谢物的高斯图形模型发现25种脂质代谢物聚集成一个单一网络。还观察到五组氨基酸、三组缩醛磷脂和两组肉碱。研究结果证实了先前关于氨基酸、瘦体重和脂肪量之间关联的报道，以及一些此前未报道的关联。未来的研究应考虑这些代谢物是否与代谢疾病过程相关。
