Evidence map›Paper›PMID 25254000›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2014

Human metabolic correlates of body mass index.

Steven C Moore, Charles E Matthews, Joshua N Sampson, Rachael Z Stolzenberg-Solomon, Wei Zheng, Qiuyin Cai, Yu Ting Tan, Wong-Ho Chow, Bu-Tian Ji, Da Ke Liu and 8 more

Open access · greenAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed, 2 pooled it
5.1field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

129 citing papers in PubMed, 2 syntheses or guidelines pooled it, 186 citations in OpenAlex.

  1. Pooled it
  2. P4 medicine and osteoporosis: a systematic review.Wiener klinische Wochenschrift · 2016
    Pooled it
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69 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 7 institutions in 3 countries.

Steven C MooreDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Charles E MatthewsDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Joshua N SampsonDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Rachael Z Stolzenberg-SolomonDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN.
Qiuyin CaiDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN.
Yu Ting TanShanghai Cancer Institute, Shanghai, China.
Wong-Ho ChowUniversity of Texas MD Anderson Cancer Center, Houston, TX, USA.
Bu-Tian JiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Da Ke LiuShanghai Cancer Institute, Shanghai, China.
Qian XiaoDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Simina M BocaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Michael F LeitzmannDepartment of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Franz-Josef-Strauss-Allee 11, 93053 Regensburg, Germany.
Gong YangDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN.
Yong Bing XiangShanghai Cancer Institute, Shanghai, China.
Rashmi SinhaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Xiao Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN.
Amanda J CrossDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
National Cancer Institute · USVanderbilt University · USNational Institutes of Health · USShanghai Cancer Institute · CNDivision of Cancer Epidemiology and GeneticsThe University of Texas MD Anderson Cancer Center · USUniversity of Regensburg · DE

Funding

Cohort Study of Cancer inhibitory Factors in MenR01CA082729 · NCI · VANDERBILT UNIVERSITY · PI SHU, XIAO-OU · 2001 to 2011
$6.3M
Shanghai Womens Health StudyUM1CA182910 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2014 to 2018
$5.9M
Shanghai Men's Health StudyUM1CA173640 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SHU, XIAO-OU · 2013 to 2017
$4.9M
Cancer Risk Reduction and Diet: A Cohort Study of WomenR37CA070867 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2009 to 2013
$4.7M
NCI NIH HHS R01 CA082729NCI NIH HHS R37 CA070867NCI NIH HHS UM1 CA173640NCI NIH HHS UM1 CA182910
6 · The paper itself

Abstract

backgroundA high body mass index (BMI) is a major risk factor for several chronic diseases, but the biology underlying these associations is not well-understood. Dyslipidemia, inflammation, and elevated levels of growth factors and sex steroid hormones explain some of the increased disease risk, but other metabolic factors not yet identified may also play a role.

designIn order to discover novel metabolic biomarkers of BMI, we used non-targeted metabolomics to assay 317 metabolites in blood samples from 947 participants and examined the cross-sectional associations between metabolite levels and BMI. Participants were from three studies in the United States and China. Height, weight, and potential confounders were ascertained by questionnaire (US studies) or direct measurement (Chinese study). Metabolite levels were measured using liquid-phase chromatography and gas chromatography coupled with mass spectrometry. We evaluated study-specific associations using linear regression, adjusted for age, gender, and smoking, and we estimated combined associations using random effects meta-analysis.

resultsThe meta-analysis revealed 37 metabolites significantly associated with BMI, including 19 lipids, 12 amino acids, and 6 others, at the Bonferroni significance threshold (p<0.00016). Eighteen of these associations had not been previously reported, including histidine, an amino acid neurotransmitter, and butyrylcarnitine, a lipid marker of whole-body fatty acid oxidation. Heterogeneity by study was minimal (all P

conclusionThese findings establish a baseline for the BMI metabolome, and suggest new targets for researchers attempting to clarify mechanistic links between high BMIs and disease risk.

Indexed as

adiposityBMIepidemiologymetabolomicsobesity

Identifiers

PMID25254000
PMCPMC4169991
OpenAlexW2052408325

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.