Evidence map›Paper›PMID 27840598›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2016

Plasma metabolomic profiles in association with type 2 diabetes risk and prevalence in Chinese adults.

Danxia Yu, Steven C Moore, Charles E Matthews, Yong-Bing Xiang, Xianglan Zhang, Yu-Tang Gao, Wei Zheng, Xiao-Ou Shu

Open access · greenAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
3.3field-weighted citation impact, top 7% 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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it, 78 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Observational
  17. Article
  18. Article
  19. Article
  20. Article
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

8 authors at 3 institutions in 2 countries.

Danxia YuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, Nashville, TN 37203, USA.
Steven C MooreDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Charles E MatthewsDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Yong-Bing XiangShanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200031, China.
Xianglan ZhangDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, Nashville, TN 37203, USA.
Yu-Tang GaoShanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200031, China.
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, Nashville, TN 37203, USA.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, Nashville, TN 37203, USA.
Vanderbilt University · USNational Cancer Institute · USShanghai Cancer Institute · CN

Funding

Physical Activity, Energy Balance, and CancerZIACP010197 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBANES, DEMETRIUS · 2009 to 2025
$17.5M
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
Metabolite profiles and the risk of diabetes in AsiansR01DK108159 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GERSZTEN, ROBERT E, SHU, XIAO-OU · 2016 to 2019
$2.6M
Soy Food and Coronary Heart Disease in WomenR01HL079123 · NHLBI · VANDERBILT UNIVERSITY · PI SHU, XIAO-OU · 2005 to 2008
$1.7M
NCI NIH HHS N02 CP011010NCI NIH HHS R37 CA070867NCI NIH HHS UM1 CA173640NCI NIH HHS UM1 CA182910NHLBI NIH HHS R01 HL079123NIDDK NIH HHS R01 DK108159
6 · The paper itself

Abstract

Metabolomic studies have identified several metabolites associated with type 2 diabetes (T2D) in populations of European ancestry. East Asians, a population of particular susceptibility to T2D, were generally not included in previous studies. We examined the associations of plasma metabolites with risk and prevalence of T2D in 976 Chinese men and women (40-74 years of age) who were participants of two prospective cohort studies and had no cardiovascular disease or cancer at baseline. Sixty-eight prevalent and 73 incident T2D cases were included. Non-targeted metabolomics was conducted that detected 689 metabolites with known identities and 690 unknown metabolites. Multivariable logistic and Cox regressions were used to evaluate the associations of standardized metabolites with diabetes risk and prevalence. We identified 36 known metabolites and 10 unknown metabolites associated with prevalent and/or incident T2D at false discovery rate <0.05. The known metabolites are involved in metabolic pathways of glycolysis/gluconeogenesis, branched-chain amino acids, other amino acids, fatty acids, glycerophospholipids, androgen, and bradykinin. Six metabolites showed independent associations with incident T2D: 1,5-anhydroglucitol, mannose, valine, 3-methoxytyrosine, docosapentaenoate (22:5n3), and bradykinin-hydroxy-pro(3). Each standard deviation increase in these metabolites was associated with a 40-150 % change in risk of developing diabetes (30-80 % after further adjustment for glucose). Risk prediction was significantly improved by adding these metabolites in addition to known T2D risk factors, including central obesity and glucose. These findings suggest that hexoses, branched-chain amino acids, and yet to be validated novel plasma metabolites may improve risk prediction and mechanistic understanding of T2D in Chinese populations.

Indexed as

Chinese populationsEpidemiologyMetabolomicsProspective cohort studyType 2 diabetes

Identifiers

PMID27840598
PMCPMC5102259
OpenAlexW2202864399

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.