Determinants of the urinary and serum metabolome in children from six European populations.
Determinants of the urinary and serum metabolome in children from six European populations.
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DOI：
10.1186/s12916-018-1190-8
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发表时间：
2018-11-08
期刊：
影响因子：
9.3
通讯作者：
Coen M
中科院分区：
文献类型：
--
作者：
Lau CE;Siskos AP;Maitre L;Robinson O;Athersuch TJ;Want EJ;Urquiza J;Casas M;Vafeiadi M;Roumeliotaki T;McEachan RRC;Azad R;Haug LS;Meltzer HM;Andrusaityte S;Petraviciene I;Grazuleviciene R;Thomsen C;Wright J;Slama R;Chatzi L;Vrijheid M;Keun HC;Coen M
生命早期的环境和饮食会影响整个生命过程中的发育和健康。尿液和血清的代谢表型是阐明环境-健康相互作用的一种补充性系统方法。然而，缺乏结合这些生物液体分析的儿童大规模代谢组学研究。在这里，我们试图通过利用作为人类早期生命暴露体项目（http：//www.example.com）的一部分而建立的独特生物库，来确定儿童代谢组的主要决定因素，并确定代谢物与欧洲儿童的年龄、性别、BMI和饮食习惯的关联。www.projecthelix.eu使用高通量1H核磁共振（NMR）光谱和靶向LC-MS/MS代谢组学分析（Biocrates AbsoluteIDQ p180试剂盒）测量了从6个欧洲国家出生队列招募的1192名儿童（6-11岁）的匹配尿液和血清样本的代谢表型。我们发现尿和血清肌酐与年龄呈正相关。与BMI z评分的代谢相关性包括与尿4-脱氧赤藓糖酸以及缬氨酸、血清肉毒碱、短链酰基肉毒碱（C3、C5）、谷氨酸、支链氨基酸、溶血磷脂酰胆碱（lysoPC a C14：0、lysoPC a C16：1、lysoPC a C18：1、lysoPC a C18：2）和鞘脂（SM C16：0、SM C16：1、SM C18：1）的新相关性。饮食代谢物相关性包括尿肌酸和血清磷脂酰胆碱（4）与肉类摄入，血清磷脂酰胆碱（12）与鱼类，尿马尿酸与蔬菜，尿脯氨酸甜菜碱和马尿酸与水果摄入。血清中的人群特异性方差（年龄、性别、BMI、种族、饮食和原产国）比尿液特征更好;这些因素解释了血清代谢物中9.0%的中位方差，而尿液代谢物中5.1%的中位方差。代谢途径的相关性被确定，相应的代谢产物的浓度在尿液和血清之间显著相关（r > 0.18）。我们已经建立了一个泛欧洲的参考代谢组的尿液和血清的健康儿童，并收集了关键的资源，以前没有提供未来的调查代谢组对儿童健康的影响。研究的六个欧洲队列人群与年龄，性别，BMI z评分和主要饮食习惯有共同的代谢相关性。此外，我们已经确定了一个新的代谢之间的苏氨酸catenorase和儿童的BMI的关联。本文的在线版本（10.1186/s12916-018-1190-8）包含补充材料，可供授权用户使用。
Environment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment–health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project (http://www.projecthelix.eu). Metabolic phenotypes of matched urine and serum samples from 1192 children (aged 6–11) recruited from birth cohorts in six European countries were measured using high-throughput 1H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit). We identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythreonic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of corresponding metabolites were significantly correlated (r > 0.18) between urine and serum. We have established a pan-European reference metabolome for urine and serum of healthy children and gathered critical resources not previously available for future investigations into the influence of the metabolome on child health. The six European cohort populations studied share common metabolic associations with age, sex, BMI z-score and main dietary habits. Furthermore, we have identified a novel metabolic association between threonine catabolism and BMI of children. The online version of this article (10.1186/s12916-018-1190-8) contains supplementary material, which is available to authorized users.
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影响因子：
4.4
作者：
Carayol M;Leitzmann MF;Ferrari P;Zamora-Ros R;Achaintre D;Stepien M;Schmidt JA;Travis RC;Overvad K;Tjønneland A;Hansen L;Kaaks R;Kühn T;Boeing H;Bachlechner U;Trichopoulou A;Bamia C;Palli D;Agnoli C;Tumino R;Vineis P;Panico S;Quirós JR;Sánchez-Cantalejo E;Huerta JM;Ardanaz E;Arriola L;Agudo A;Nilsson J;Melander O;Bueno-de-Mesquita B;Peeters PH;Wareham N;Khaw KT;Jenab M;Key TJ;Scalbert A;Rinaldi S
通讯作者：
Rinaldi S
DOI：
10.1016/j.beem.2012.03.002
发表时间：
2012-10-01
影响因子：
7.4
作者：
Berends, L. M.;Ozanne, S. E.
通讯作者：
Ozanne, S. E.
影响因子：
2.6
作者：
Baker, Marissa G.;Simpson, Christopher D.;Seixas, Noah
通讯作者：
Seixas, Noah
DOI：
10.1111/cea.12213
发表时间：
2013-12
期刊：
Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology
影响因子：
--
作者：
Bisgaard H;Vissing NH;Carson CG;Bischoff AL;Følsgaard NV;Kreiner-Møller E;Chawes BL;Stokholm J;Pedersen L;Bjarnadóttir E;Thysen AH;Nilsson E;Mortensen LJ;Olsen SF;Schjørring S;Krogfelt KA;Lauritzen L;Brix S;Bønnelykke K
通讯作者：
Bønnelykke K
代谢组学揭示了与儿童早期相关的动态代谢变化。
影响因子：
3.7
作者：
Chiu CY;Yeh KW;Lin G;Chiang MH;Yang SC;Chao WJ;Yao TC;Tsai MH;Hua MC;Liao SL;Lai SH;Cheng ML;Huang JL
通讯作者：
Huang JL