Evidence map›Paper›PMID 36837846›Full record

ArticleMetabolites2023

Metabolic Signatures Elucidate the Effect of Body Mass Index on Type 2 Diabetes.

Qiuling Dong, Sidra Sidra, Christian Gieger, Rui Wang-Sattler, Wolfgang Rathmann, Cornelia Prehn, Jerzy Adamski, Wolfgang Koenig, Annette Peters, Harald Grallert and 1 more

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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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

11 authors at 5 institutions in 3 countries.

Qiuling DongResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.ORCID 0000-0002-3369-4120
Sidra SidraInstitute for Medical Information Processing, Biometry and Epidemiology (IBE), Ludwig-Maximilians-Universität München, 81377 Munich, Germany.
Christian GiegerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
Rui Wang-SattlerInstitute of Translational Genomics, Helmholtz Zentrum München, 85764 Neuherberg, Germany.ORCID 0000-0002-8794-8229
Wolfgang RathmannInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany.
Cornelia PrehnMetabolomics and Proteomics Core Facility, Helmholtz Zentrum München, 85764 Neuherberg, Germany.ORCID 0000-0002-1274-4715
Jerzy AdamskiInstitute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany.
Wolfgang KoenigGerman Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, 81377 Munich, Germany.ORCID 0000-0002-2064-9603
Annette PetersInstitute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.ORCID 0000-0001-6645-0985
Harald GrallertResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
Sapna SharmaResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.ORCID 0000-0003-1039-8879
Helmholtz Zentrum München · DEDeutsches Diabetes-Zentrum e.V. · DELudwig-Maximilians-Universität München · DEUniversität Ulm · DEUniversity of Ljubljana · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.

Indexed as

mediationmendelian randomizationmetabolomicsobesitytype 2 diabetestype 2 diabetes pathology

Identifiers

PMID36837846
PMCPMC9965667
OpenAlexW4319316967

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.