Evidence map›Paper›PMID 37328862›Full record

ArticleCardiovascular diabetology2023

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts.

Mengya Shi, Siyu Han, Kristin Klier, Gisela Fobo, Corinna Montrone, Shixiang Yu, Makoto Harada, Ann-Kristin Henning, Nele Friedrich, Martin Bahls and 13 more

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

  1. Pooled it
  2. Metabolomics Data Analysis with TIGER.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Dysregulated Fatty Acid Metabolism in Preeclampsia Among Highland Andeans: Insights Into Adaptive and Maladaptive Placental Metabolic Phenotypes.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    Article
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  5. The Performance ofFoods (Basel, Switzerland) · 2025
    Article
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  8. Article
  9. Identifying Metabolomic Mediators of the Physical Activity and Colorectal Cancer Relationship.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
  10. Review
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  15. Obesity-Related Ciliopathies: Focus on Advances of Biomarkers.International journal of molecular sciences · 2024
    Review
  16. Article
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  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

23 authors.

Mengya ShiTUM School of Medicine, Technical University of Munich (TUM), Munich, Germany.
Siyu HanTUM School of Medicine, Technical University of Munich (TUM), Munich, Germany.
Kristin KlierDepartment of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
Gisela FoboInstitute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Corinna MontroneInstitute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Shixiang YuTUM School of Medicine, Technical University of Munich (TUM), Munich, Germany.
Makoto HaradaInstitute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Ann-Kristin HenningInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.
Nele FriedrichInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.
Martin BahlsGerman Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany.
Marcus DörrGerman Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany.
Matthias NauckInstitute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.
Henry VölzkeGerman Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany.
Georg HomuthInterfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.
Hans J GrabeDepartment of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
Cornelia PrehnMetabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Jerzy AdamskiInstitute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Karsten SuhreDepartment of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City-Qatar Foundation, Doha, Qatar.
Wolfgang RathmannGerman Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany.
Andreas RueppInstitute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Johannes HertelDepartment of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
Annette Peters *German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany.
Rui Wang-Sattler *Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. rui.wang-sattler@helmholtz-munich.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways.

methodsWe quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed.

resultsWe identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism.

conclusionOur identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2HypertensionMetabolic SyndromeBiomarkersHumansMetabolomicsRisk FactorsBiomarkersAmino acidsBCAAsCardiovascular diseaseHyperglycemiaHypertensionLysophosphatidylcholinesMetabolic syndromeMetabolomicsObesityPhosphatidylcholines

Identifiers

PMID37328862
PMCPMC10276453

What Socratic 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 Socratic graph.