ArticleCurrent diabetes reports2013
Bridging the gap between genetic associations and molecular mechanisms for type 2 diabetes.
Article in Current diabetes reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
4 citing papers in PubMed, 12 citations in OpenAlex.
- IMPC impact on preclinical mouse models.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Transcribing β-cell mitochondria in health and disease.Molecular metabolism · 2017Review
- Identification of a regulatory variant that binds FOXA1 and FOXA2 at the CDC123/CAMK1D type 2 diabetes GWAS locus.PLoS genetics · 2014Article
- The pancreatic β cell: recent insights from human genetics.Trends in endocrinology and metabolism: TEM · 2014Article
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 2 institutions in 1 country.
Funding
Abstract
Type 2 diabetes is a global pandemic for which there is currently no disease-modifying treatment. New and targeted therapeutics are greatly needed, but progress in identifying novel targets for therapeutic intervention is severely hampered by poor understanding of disease pathogenesis. Over the past 6 years, the success of genome-wide association studies has led to an unprecedented increase in the number of loci robustly associating with type 2 diabetes risk. Each of these signals offers the opportunity to uncover biological insights into disease pathogenesis, which, if harnessed effectively, hold the promise to deliver new pathways for therapeutic intervention, strategies for patient stratification, and potentially, biomarkers for identifying those at greatest risk of developing diabetes. We review the progress that has been made and the approaches being adopted and discuss the inherent challenges in moving from association signals, which largely map to poorly annotated sequence, to transcripts, mechanisms, and disease biology.
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Identifiers
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.