Evidence map›Paper›PMID 31504048›Full record

ArticlePloS one2019

Proteomics approach to identify serum biomarkers associated with the progression of diabetes in Korean patients with abdominal obesity.

Sang Woo Kim, Jung-Won Choi, Jong Won Yun, In-Sung Chung, Ho Chan Cho, Seung-Eun Song, Seung-Soon Im, Dae-Kyu Song

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
3.6field-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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

  1. Pooled it
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  9. Hallmarks of the metabolic secretome.Trends in endocrinology and metabolism: TEM · 2024
    Review
  10. Article
  11. Article
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  13. Article
  14. Antidiabetic effects ofFrontiers in pharmacology · 2023
    Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  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

8 authors at 3 institutions in 1 country.

Sang Woo KimInstitute for Bio-Medical Convergence, College of Medicine, Catholic Kwandong University, Gangneung-si, Gangwon-do, South Korea.
Jung-Won ChoiInstitute for Bio-Medical Convergence, College of Medicine, Catholic Kwandong University, Gangneung-si, Gangwon-do, South Korea.
Jong Won YunDepartment of Biotechnology, Daegu University, Kyungsan, Kyungbuk, South Korea.
In-Sung ChungDivision of Occupational and Environmental Medicine and Department of Preventive Medicine, Keimyung, University School of Medicine, Daegu, South Korea.
Ho Chan ChoDepartment of Internal Medicine, Keimyung, University School of Medicine, Daegu, South Korea.
Seung-Eun SongDepartment of Physiology and Obesity-mediated Disease Research Center, Keimyung, University School of Medicine, Daegu, South Korea.
Seung-Soon ImDepartment of Physiology and Obesity-mediated Disease Research Center, Keimyung, University School of Medicine, Daegu, South Korea.ORCID 0000-0002-2743-2108
Dae-Kyu SongDepartment of Physiology and Obesity-mediated Disease Research Center, Keimyung, University School of Medicine, Daegu, South Korea.
Keimyung University · KRCatholic Kwandong University International St. Mary's Hospital · KRDaegu University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes is a metabolic disease with a group of metabolic derangements and inflammatory reactants in the serum. Despite the substantial public health implications, markers of diabetes progression with abdominal obesity are still needed to facilitate early detection and treatment. In this study, we performed a proteomic approach to identify differential target proteins underlying diabetes progression in patients with abdominal obesity. Proteomic differences were investigated in the serum of controls and patients with prediabetes or diabetes with or without abdominal obesity by 2-DE combined with MALDI-TOF-MS. Proteomics data were validated by western blot analyses and major protein-protein interactions were assessed using a network analysis with String database. Among 245 matched protein spots, 36 exhibited marked differences in normal patients with abdominal obesity, prediabetes, and diabetes compared to levels in normal patients without abdominal obesity. Seven (Alpha-1-antichymotrypsin, Alpha-1-antitrypsin, Apolipoprotein A-I, haptoglobin, retinol-binding protein 4, transthyretin, and zinc-alpha2-glycoprotein) of these spots exhibited significant differences between normal and prediabetes/diabetes patients. After a network analysis, functional annotation using Gene Ontology indicated that most of the identified proteins were involved in lipid transport, lipid localization, and the regulation of serum lipoprotein particle levels. Our results indicated that variation in the levels of these identified protein biomarkers has been reported in normal, prediabetes and diabetic Assessment of the levels of these biomarkers may contribute to the development of biomarkers for not only early diagnosis but also in prognosis of diabetes mellitus type 2.

Indexed as

AdipokinesAdultalpha 1-AntitrypsinApolipoproteinsBiomarkersCarrier ProteinsDiabetes MellitusFemaleGlycoproteinsHaptoglobinsHumansMaleMiddle AgedObesity, AbdominalPrealbuminProteomeAdipokinesalpha 1-AntitrypsinApolipoproteinsAZGP1 protein, humanBiomarkersCarrier ProteinsGlycoproteinsHaptoglobinsPrealbuminProteomeRetinol-Binding ProteinsZn-Alpha-2-Glycoprotein

Identifiers

PMID31504048
PMCPMC6736247
OpenAlexW2972340108

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.