ArticleDiabetes2020
Large-Scale Analyses Provide No Evidence for Gene-Gene Interactions Influencing Type 2 Diabetes Risk.
Article in Diabetes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 11 citations in OpenAlex.
- Functional implications of polygenic risk for schizophrenia in human neurons.Nature communications · 2026Article
- Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation.Nature reviews. Endocrinology · 2025Review
- Article
- Palmitoylation couples insulin hypersecretion with β cell failure in diabetes.Cell metabolism · 2023Article
- Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing.Genetics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
A growing number of genetic loci have been shown to influence individual predisposition to type 2 diabetes (T2D). Despite longstanding interest in understanding whether nonlinear interactions between these risk variants additionally influence T2D risk, the ability to detect significant gene-gene interaction (GGI) effects has been limited to date. To increase power to detect GGI effects, we combined recent advances in the fine-mapping of causal T2D risk variants with the increased sample size available within UK Biobank (375,736 unrelated European participants, including 16,430 with T2D). In addition to conventional single variant-based analysis, we used a complementary polygenic score-based approach, which included partitioned T2D risk scores that capture biological processes relevant to T2D pathophysiology. Nevertheless, we found no evidence in support of GGI effects influencing T2D risk. The current study was powered to detect interactions between common variants with odds ratios >1.2, so these findings place limits on the contribution of GGIs to the overall heritability of T2D.
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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.