Evidence map›Paper›PMID 28378853›Full record

ArticleEuropean journal of clinical nutrition2017

Serum metabolomic profiling highlights pathways associated with liver fat content in a general population sample.

M Koch, S Freitag-Wolf, S Schlesinger, J Borggrefe, J R Hov, M K Jensen, J Pick, M R P Markus, T Höpfner, G Jacobs and 13 more

Abstract read
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In one paragraph

Article in European journal of clinical nutrition, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

23 authors.

M KochInstitute of Epidemiology, Kiel University, Kiel, Germany.
S Freitag-WolfInstitute of Medical Informatics and Statistics, Kiel University, Kiel, Germany.
S SchlesingerInstitute of Epidemiology, Kiel University, Kiel, Germany.
J BorggrefeDepartment of Radiology, University of Cologne, Cologne, MA, USA.
J R HovDivision of Cancer Medicine, Department of Transplantation Medicine, Surgery and Transplantation, Norwegian PSC Research Center, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
M K JensenDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
J PickNutritional Epidemiology, Department of Nutrition and Food Science, Rheinische Friedrich-Wilhelms-University Bonn, Bonn, Germany.
M R P MarkusDepartment of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany.
T HöpfnerInstitute of Epidemiology, Kiel University, Kiel, Germany.
G JacobsInstitute of Epidemiology, Kiel University, Kiel, Germany.
S SiegertCologne Center for Genomics, University of Cologne, Cologne, Germany.
A ArtatiInstitute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Neuherberg, Germany.
G KastenmüllerInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.
W Römisch-MarglInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany.
J AdamskiInstitute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Neuherberg, Germany.
T IlligHannover Unified Biobank, Hannover Medical School, Hannover, Germany.
M NothnagelCologne Center for Genomics, University of Cologne, Cologne, Germany.
T H KarlsenDivision of Cancer Medicine, Department of Transplantation Medicine, Surgery and Transplantation, Norwegian PSC Research Center, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
S SchreiberInstitute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.
A FrankeInstitute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.
M KrawczakInstitute of Medical Informatics and Statistics, Kiel University, Kiel, Germany.
U NöthlingsNutritional Epidemiology, Department of Nutrition and Food Science, Rheinische Friedrich-Wilhelms-University Bonn, Bonn, Germany.
W LiebInstitute of Epidemiology, Kiel University, Kiel, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesFatty liver disease (FLD) is an important intermediate trait along the cardiometabolic disease spectrum and strongly associates with type 2 diabetes. Knowledge of biological pathways implicated in FLD is limited. An untargeted metabolomic approach might unravel novel pathways related to FLD. SUBJECTS/

methodsIn a population-based sample (n=555) from Northern Germany, liver fat content was quantified as liver signal intensity using magnetic resonance imaging. Serum metabolites were determined using a non-targeted approach. Partial least squares regression was applied to derive a metabolomic score, explaining variation in serum metabolites and liver signal intensity. Associations of the metabolomic score with liver signal intensity and FLD were investigated in multivariable-adjusted robust linear and logistic regression models, respectively. Metabolites with a variable importance in the projection >1 were entered in in silico overrepresentation and pathway analyses.

resultsIn univariate analysis, the metabolomics score explained 23.9% variation in liver signal intensity. A 1-unit increment in the metabolomic score was positively associated with FLD (n=219; odds ratio: 1.36; 95% confidence interval: 1.27-1.45) adjusting for age, sex, education, smoking and physical activity. A simplified score based on the 15 metabolites with highest variable importance in the projection statistic showed similar associations. Overrepresentation and pathway analyses highlighted branched-chain amino acids and derived gamma-glutamyl dipeptides as significant correlates of FLD.

conclusionsA serum metabolomic profile was associated with FLD and liver fat content. We identified a simplified metabolomics score, which should be evaluated in prospective studies.

Indexed as

Lipid MetabolismAgedAlcohol DrinkingBiological Specimen BanksBiomarkersCohort StudiesComputational BiologyCross-Sectional StudiesDipeptidesExpert SystemsFatty Liver, AlcoholicFemaleGlutamic AcidHumansLiverMagnetic Resonance ImagingBiomarkersDipeptidesGlutamic Acid

Identifiers

PMID28378853

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.