Evidence map›Paper›PMID 23804262›Full record

ReviewThe review of diabetic studies : RDS2012

Novel biomarkers in type 1 diabetes.

Yulan Jin, Jin-Xiong She

Open access · bronzeAbstract readReview
In one paragraph

Review in The review of diabetic studies : RDS, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.6field-weighted citation impact, top 28% 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

11 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Serum biomarkers for diagnosis and prediction of type 1 diabetes.Translational research : the journal of laboratory and clinical medicine · 2018
    Review
  8. Review
  9. Review
  10. Metabolomics in childhood diabetes.Pediatric diabetes · 2016
    Review
  11. 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

2 authors at 1 institution in 1 country.

Yulan JinCenter for Biotechnology and Genomic Medicine and Department of Pathology, Medical College of Georgia, Georgia Regents University, Augusta, GA 30912, USA.
Jin-Xiong She
Augusta University Health · 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
Development of microarray-based biomarkers for type 1 diR21DK069878 · NIDDK · MEDICAL COLLEGE OF GEORGIA (MCG) · PI SHE, JIN-XIONG · 2004 to 2005
$733k
Proteomic changes/progression of human type 1 diabetesR21HD050196 · NICHD · MEDICAL COLLEGE OF GEORGIA (MCG) · PI SHE, JIN-XIONG · 2004 to 2005
$715k
NICHD NIH HHS 2R01HD37800NICHD NIH HHS 4R33HD050196NICHD NIH HHS R01 HD037800NICHD NIH HHS R21 HD050196NICHD NIH HHS R33 HD050196NIDDK NIH HHS 4R33DK069878NIDDK NIH HHS R21 DK069878NIDDK NIH HHS R33 DK069878
6 · The paper itself

Abstract

Biomarkers are useful tools for research into type 1 diabetes (T1D) for a number of purposes, including elucidation of disease pathogenesis, risk prediction, and therapeutic monitoring. Susceptibility genes and islet autoantibodies are currently the most useful biomarkers for T1D risk prediction. However, these markers do not fully meet the needs of scientists and physicians for several reasons. First, improvement of the specificity and sensitivity is still desirable to achieve better positive predictive values. Second, autoantibodies appear relatively late in the disease process, thus limiting their value in early disease prediction. Third, the currently available biomarkers are not useful for assessing therapeutic outcomes because some are not involved in the disease process (autoantibodies) and others do not change during disease progression (susceptibility genes). Therefore, considerable effort has been devoted to the discovery of novel T1D biomarkers in the last three decades. The advent of high-throughput technologies for genetic, transcriptomic, and proteomic studies has allowed genome-wide examinations of genetic polymorphisms, global gene changes, and protein expression changes in T1D patients and prediabetic subjects. These large-scale studies resulted in the discovery of a large number of susceptibility genes and changes in gene and protein expression. While these studies have provided a number of novel biomarker candidates, their clinical benefits remain to be evaluated in prospective studies, and no new "star biomarker" has been identified until now. Previous studies suggest that significant improvements in study design and analytical methodologies have to be made to identify clinically relevant biomarkers. In this review, we discuss progress, opportunities, challenges, and future directions in the development of T1D biomarkers, mainly by focusing on the genetic, transcriptomic, and proteomic aspects.

Indexed as

AnimalsBiomarkersDiabetes Mellitus, Type 1GenomeHumansPolymorphism, GeneticProteomicsTranscriptomeBiomarkers

Identifiers

PMID23804262
PMCPMC3740692
OpenAlexW1956941574

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.