Evidence map›Paper›PMID 21900154›Full record

ArticleMolecular & cellular proteomics : MCP2011

Discovery and validation of serum protein changes in type 1 diabetes patients using high throughput two dimensional liquid chromatography-mass spectrometry and immunoassays.

Wenbo Zhi, Ashok Sharma, Sharad Purohit, Eric Miller, Bruce Bode, Stephen W Anderson, John Chip Reed, R Dennis Steed, Leigh Steed, Diane Hopkins and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  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

11 authors at 3 institutions in 1 country.

Wenbo ZhiCenter for Biotechnology and Genomic Medicine, Georgia Health Sciences University, Augusta, GA 30912, USA.
Ashok Sharma
Sharad Purohit
Eric Miller
Bruce Bode
Stephen W Anderson
John Chip Reed
R Dennis Steed
Leigh Steed
Diane Hopkins
Jin-Xiong She
Augusta University Health · USDiabetes & Endocrine Associates · USAtlanta Diabetes Associates · US

Funding

Studies of the Immunopathogenesis of Type 1 DiabetesR01HD037800 · NICHD · UNIVERSITY OF FLORIDA · PI SHE, JIN-XIONG · 1999 to 2006
$4.6M
Proteomic changes/progression of human type 1 diabetesR33HD050196 · NICHD · AUGUSTA UNIVERSITY · PI SHE, JIN-XIONG · 2006 to 2008
$1.5M
Development of microarray-based biomarkers for type 1 diR33DK069878 · NIDDK · AUGUSTA UNIVERSITY · PI SHE, JIN-XIONG · 2006 to 2008
$1.1M
NICHD NIH HHS 2R01HD37800NICHD NIH HHS 4R33HD050196NICHD NIH HHS R01 HD037800NICHD NIH HHS R33 HD050196NIDDK NIH HHS 4R33-DK069878NIDDK NIH HHS R33 DK069878
6 · The paper itself

Abstract

Type 1 diabetes (T1D) is expected to cause significant changes in the serum proteome; however, few studies have systematically assessed the proteomic profile change associated with the disease. In this study, a semiquantitative spectral counting-based two dimensional liquid chromatography mass spectrometry platform was used to analyze serum samples from T1D patients and controls. In this discovery phase, significant differences were found for 21 serum proteins implicated in inflammation, oxidation, metabolic regulation, and autoimmunity. To assess the validity of these findings, six candidate proteins including adiponectin, insulin-like growth factor binding protein 2, serum amyloid protein A, C-reactive protein, myeloperoxidase, and transforming growth factor beta induced were selected for subsequent immune assays for 1139 T1D patients and 848 controls. A series of statistical analyses using cases and controls matched for age, sex, and genetic risk confirmed that T1D patients have significantly higher serum levels for four of the six proteins: adiponectin (odds ratio (OR) = 1.95, p = 10(-27)), insulin-like growth factor binding protein 2 (OR = 2.02, p < 10(-20)), C-reactive protein (OR = 1.13, p = 0.007), serum amyloid protein A (OR = 1.51, p < 10(-16)); whereas the serum levels were significantly lower in patients than controls for the two other proteins: transforming growth factor beta induced (OR = 0.74, p < 10(-5)) and myeloperoxidase (OR = 0.51, p < 10(-41)). Compared with subjects in the bottom quartile, subjects in the top quartile for adiponectin (OR = 6.29, p < 10(-37)), insulin-like growth factor binding protein 2 (OR = 7.95, p < 10(-46)), C-reactive protein (OR = 1.38, p = 0.025), serum amyloid protein A (OR = 3.36, p < 10(-16)) had the highest risk of T1D, whereas subjects in the top quartile of transforming growth factor beta induced (OR = 0.41, p < 10(-11)) and myeloperoxidase (OR = 0.10, p < 10(-43)) had the lowest risk of T1D. These findings provided valuable information on the proteomic changes in the sera of T1D patients.

Indexed as

AdiponectinAdolescentAdultAgedAged, 80 and overAge FactorsbetaIG-H3 ProteinBiomarkersCase-Control StudiesChildChild, PreschoolChromatography, LiquidC-Reactive ProteinDiabetes Mellitus, Type 1Enzyme-Linked Immunosorbent AssayExtracellular Matrix ProteinsAdiponectinbetaIG-H3 ProteinBiomarkersC-Reactive ProteinExtracellular Matrix ProteinsInsulin-Like Growth Factor Binding Protein 2PeroxidaseSerum Amyloid A ProteinTransforming Growth Factor beta

Identifiers

PMID21900154
PMCPMC3226412
OpenAlexW2134551390

What OpenQuestion holds

Textmetadata
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.