Evidence map›Paper›PMID 37308750›Full record

ArticleDiabetologia2023

Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study.

Hong Luo, Alina Bauer, Jana Nano, Agnese Petrera, Wolfgang Rathmann, Christian Herder, Stefanie M Hauck, Benjamin B Sun, Annika Hoyer, Annette Peters and 1 more

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Diabetologia, 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
10.3field-weighted citation impact, top 1% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 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 2 countries.

Hong LuoInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.ORCID http://orcid.org/0000-0003-3538-3147
Alina BauerInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Jana NanoInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Agnese PetreraMetabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.ORCID http://orcid.org/0000-0002-0583-6195
Wolfgang RathmannInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine Universität Düsseldorf, Düsseldorf, Germany.ORCID http://orcid.org/0000-0001-7804-1740
Christian HerderGerman Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany.ORCID http://orcid.org/0000-0002-2050-093X
Stefanie M HauckMetabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.ORCID http://orcid.org/0000-0002-1630-6827
Benjamin B SunTranslation Sciences, Research & Development, Biogen Inc., Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-6347-2281
Annika HoyerBiostatistics and Medical Biometry, Medical School OWL, Bielefeld University, Bielefeld, Germany.ORCID http://orcid.org/0000-0002-0241-9951
Annette PetersInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.ORCID http://orcid.org/0000-0001-6645-0985
Barbara ThorandInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany. barbara.thorand@helmholtz-munich.de.ORCID http://orcid.org/0000-0002-8416-6440
Helmholtz Zentrum München · DEBielefeld University · DEBiogen (United States) · USDeutsches Diabetes-Zentrum e.V. · DEDüsseldorf University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisThis study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development.

methodsWe measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA

resultsWe identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624). CONCLUSIONS/

interpretationWe identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.

Indexed as

Diabetes Mellitus, Type 2Interleukin-27Prediabetic StateCohort StudiesCross-Sectional StudiesGlucoseHumansInsulinProteomicsVascular Endothelial Growth Factor DGlucoseInsulinInterleukin-27Vascular Endothelial Growth Factor DCohort studyMendelian randomisationProteomicsTraits of glucose and insulinType 2 diabetes

Identifiers

PMID37308750
OpenAlexW4380359084

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.