ReviewThe review of diabetic studies : RDS2012
Novel biomarkers in type 1 diabetes.
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.
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.
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.
Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Exploratory bioinformatics analysis for identifying candidate biomarkers of type 1 diabetes mellitus.PeerJ · 2026Article
- Optimized protocol for shotgun label-free proteomic analysis of pancreatic islets.Biology methods & protocols · 2024Review
- Effect of Epstein-Barr Virus Infection on Selected Immunological Parameters in Children with Type 1 Diabetes.International journal of molecular sciences · 2023Article
- Differential Profile of Plasma Circular RNAs in Type 1 Diabetes Mellitus.Diabetes & metabolism journal · 2020Article
- Article
- Biobanking for Translational Diabetes Research in India.BioResearch open access · 2020Review
- Serum biomarkers for diagnosis and prediction of type 1 diabetes.Translational research : the journal of laboratory and clinical medicine · 2018Review
- Where, How, and When: Positioning Posttranslational Modification Within Type 1 Diabetes Pathogenesis.Current diabetes reports · 2016Review
- Concise Review: Cell-Based Therapies and Other Non-Traditional Approaches for Type 1 Diabetes.Stem cells (Dayton, Ohio) · 2016Review
- Metabolomics in childhood diabetes.Pediatric diabetes · 2016Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
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.
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What OpenQuestion holds
Registered trials
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.