Evidence map›Paper›PMID 29187192›Full record

ArticleBMC medicine2017

Comprehensive metabolic profiling of chronic low-grade inflammation among generally healthy individuals.

Maik Pietzner, Anne Kaul, Ann-Kristin Henning, Gabi Kastenmüller, Anna Artati, Markus M Lerch, Jerzy Adamski, Matthias Nauck, Nele Friedrich

Abstract read
In one paragraph

Article in BMC medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing 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

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

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14 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

9 authors.

Maik PietznerInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany. maik.pietzner@uni-greifswald.de.
Anne KaulInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany.
Ann-Kristin HenningInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany.
Gabi KastenmüllerInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, D-85764, Neuherberg, Germany.
Anna ArtatiInstitute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Ingolstädter Landstraße 1, D-85764, Neuherberg, Germany.
Markus M LerchDepartment of Medicine A, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany.
Jerzy AdamskiInstitute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Ingolstädter Landstraße 1, D-85764, Neuherberg, Germany.
Matthias NauckInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany.
Nele FriedrichInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Str. NK, 17475, Greifswald, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammation occurs as an immediate protective response of the immune system to a harmful stimulus, whether locally confined or systemic. In contrast, a persisting, i.e., chronic, inflammatory state, even at a low-grade, is a well-known risk factor in the development of common diseases like diabetes or atherosclerosis. In clinical practice, laboratory markers like high-sensitivity C-reactive protein (hsCRP), white blood cell count (WBC), and fibrinogen, are used to reveal inflammatory processes. In order to gain a deeper insight regarding inflammation-related changes in metabolism, the present study assessed the metabolic patterns associated with alterations in inflammatory markers.

methodsBased on mass spectrometry and nuclear magnetic resonance spectroscopy we determined a comprehensive panel of 613 plasma and 587 urine metabolites among 925 apparently healthy individuals. Associations between inflammatory markers, namely hsCRP, WBC, and fibrinogen, and metabolite levels were tested by linear regression analyses controlling for common confounders. Additionally, we tested for a discriminative signature of an advanced inflammatory state using random forest analysis.

resultsHsCRP, WBC, and fibrinogen were significantly associated with 71, 20, and 19 plasma and 22, 3, and 16 urine metabolites, respectively. Identified metabolites were related to the bradykinin system, involved in oxidative stress (e.g., glutamine or pipecolate) or linked to the urea cycle (e.g., ornithine or citrulline). In particular, urine 3'-sialyllactose was found as a novel metabolite related to inflammation. Prediction of an advanced inflammatory state based solely on 10 metabolites was well feasible (median AUC: 0.83).

conclusionsComprehensive metabolic profiling confirmed the far-reaching impact of inflammatory processes on human metabolism. The identified metabolites included not only those already described as immune-modulatory but also completely novel patterns. Moreover, the observed alterations provide molecular links to inflammation-associated diseases like diabetes or cardiovascular disorders.

Indexed as

MetabolomicsAdultAtherosclerosisBiomarkersCardiovascular DiseasesC-Reactive ProteinFemaleHumansInflammationInflammation MediatorsMaleMass SpectrometryMiddle AgedNuclear Magnetic Resonance, BiomolecularRisk FactorsBiomarkersC-Reactive ProteinInflammation MediatorsC-reactive proteinFibrinogenInflammationMass spectrometryMetabolomicsNuclear magnetic resonance spectroscopyWhite blood cell count

Identifiers

PMID29187192
PMCPMC5708081

What OpenQuestion holds

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LicenceCC BY
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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.