Evidence map›Paper›PMID 30242179›Full record

ArticleScientific reports2018

Characterization of different fat depots in NAFLD using inflammation-associated proteome, lipidome and metabolome.

Alen Lovric, Marit Granér, Elias Bjornson, Muhammad Arif, Rui Benfeitas, Kristofer Nyman, Marcus Ståhlman, Markku O Pentikäinen, Jesper Lundbom, Antti Hakkarainen and 7 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
3.2field-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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

  1. Biomarker discovery in NAFLD: insights from metabolomics and vote counting meta-analysis.Metabolomics : Official journal of the Metabolomic Society · 2025
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  15. Multiomics Analysis Reveals the Impact of Microbiota on Host Metabolism in Hepatic Steatosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
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  17. Non-invasive assessment of metabolic dysfunction-associated fatty liver disease.Therapeutic advances in endocrinology and metabolism · 2022
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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

17 authors at 4 institutions in 2 countries.

Alen LovricScience for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
Marit GranérHeart and Lung Center, Division of Cardiology, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Elias BjornsonDepartment of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Muhammad ArifScience for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
Rui BenfeitasScience for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
Kristofer NymanDepartment of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Marcus StåhlmanDepartment of Molecular and Clinical Medicine/Wallenberg Lab, University of Gothenburg, and Sahlgrenska University Hospital, Gothenburg, Sweden.
Markku O PentikäinenHeart and Lung Center, Division of Cardiology, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Jesper LundbomDepartment of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Antti HakkarainenDepartment of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.ORCID 0000-0002-7367-2532
Reijo SirénDepartment of General Practice and Primary Health Care, Health Care Centre of City of Helsinki and University of Helsinki, Helsinki, Finland.ORCID 0000-0002-5191-6145
Markku S NieminenHeart and Lung Center, Division of Cardiology, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Nina LundbomDepartment of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Kirsi LauermaDepartment of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland.
Marja-Riitta TaskinenHeart and Lung Center, Division of Cardiology, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland. marja-riitta.taskinen@helsinki.fi.
Adil MardinogluScience for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden. adilm@scilifelab.se.
Jan BorenDepartment of Molecular and Clinical Medicine/Wallenberg Lab, University of Gothenburg, and Sahlgrenska University Hospital, Gothenburg, Sweden. jan.boren@wlab.gu.se.ORCID 0000-0003-0786-8091
University of Helsinki · FISahlgrenska University Hospital · SEScience for Life Laboratory · SEChalmers University of Technology · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-alcoholic fatty liver disease (NAFLD) is recognized as a liver manifestation of metabolic syndrome, accompanied with excessive fat accumulation in the liver and other vital organs. Ectopic fat accumulation was previously associated with negative effects at the systemic and local level in the human body. Thus, we aimed to identify and assess the predictive capability of novel potential metabolic biomarkers for ectopic fat depots in non-diabetic men with NAFLD, using the inflammation-associated proteome, lipidome and metabolome. Myocardial and hepatic triglycerides were measured with magnetic spectroscopy while function of left ventricle, pericardial and epicardial fat, subcutaneous and visceral adipose tissue were measured with magnetic resonance imaging. Measured ectopic fat depots were profiled and predicted using a Random Forest algorithm, and by estimating the Area Under the Receiver Operating Characteristic curves. We have identified distinct metabolic signatures of fat depots in the liver (TAG50:1, glutamate, diSM18:0 and CE20:3), pericardium (N-palmitoyl-sphinganine, HGF, diSM18:0, glutamate, and TNFSF14), epicardium (sphingomyelin, CE20:3, PC38:3 and TNFSF14), and myocardium (CE20:3, LAPTGF-β1, glutamate and glucose). Our analyses highlighted non-invasive biomarkers that accurately predict ectopic fat depots, and reflect their distinct metabolic signatures in subjects with NAFLD.

Indexed as

Adipose TissueBiomarkersCohort StudiesFatsHeart VentriclesHumansInflammationIntra-Abdominal FatLiverMagnetic Resonance ImagingMaleMetabolic SyndromeMetabolomeMyocardiumNon-alcoholic Fatty Liver DiseasePericardiumBiomarkersFatsProteomeTriglycerides

Identifiers

PMID30242179
PMCPMC6155005
OpenAlexW2892252863

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.