The fecal metabolome as a functional readout of the gut microbiome.
The fecal metabolome as a functional readout of the gut microbiome.
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DOI：
10.1038/s41588-018-0135-7
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发表时间：
2018-06
期刊：
影响因子：
30.8
通讯作者：
Menni C
中科院分区：
文献类型：
--
作者：
Zierer J;Jackson MA;Kastenmüller G;Mangino M;Long T;Telenti A;Mohney RP;Small KS;Bell JT;Steves CJ;Valdes AM;Spector TD;Menni C
人类肠道微生物组在人类健康中发挥着关键作用，但 16S 表征缺乏定量功能注释。粪便代谢组提供了微生物活性的功能读数，并且可以用作介导这些相互作用的中间表型。在对粪便代谢组的首次全面描述中，检查了基于人群的双胞胎研究 (TwinsUK) 中 786 名个体的 1116 种代谢物，发现粪便代谢组仅受宿主遗传学的适度影响 (h2=17.9%)。 NAT2 基因的一个复制位点与粪便代谢特征相关。粪便代谢组在很大程度上反映了肠道微生物组成，解释了平均 67.7% (±18.8%) 的变异。它与内脏脂肪量密切相关，说明了微生物对腹部肥胖影响的潜在机制。粪便代谢分析似乎是探索微生物组组成、宿主表型和可遗传的复杂性状之间联系的新工具。
The human gut microbiome plays a key role in human health, but 16S characterization lacks quantitative functional annotation. The fecal metabolome provides a functional readout of microbial activity and could be used as an intermediate phenotype mediating these interactions. In the first comprehensive description of the fecal metabolome, examining 1116 metabolites of 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (h2=17.9%). One replicated locus at the NAT2 gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral fat mass, illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling appears as a novel tool to explore links between microbiome composition, host phenotypes, and heritable complex traits.
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影响因子：
2.6
作者：
McDonagh EM;Boukouvala S;Aklillu E;Hein DW;Altman RB;Klein TE
通讯作者：
Klein TE
遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
11
作者：
Marcobal, A.;Kashyap, P. C.;Sonnenburg, J. L.
通讯作者：
Sonnenburg, J. L.
DOI：
10.1073/pnas.1000080107
发表时间：
2011-03-15
影响因子：
11.1
作者：
Caporaso, J. Gregory;Lauber, Christian L.;Knight, Rob
通讯作者：
Knight, Rob
影响因子：
8.6
作者：
Dehaven CD;Evans AM;Dai H;Lawton KA
通讯作者：
Lawton KA