ReviewJournal of medical genetics2021
Emerging roles of rare and low-frequency genetic variants in type 1 diabetes mellitus.
Review in Journal of medical genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Association of CTLA-4 rs231775 and rs3087243 Polymorphisms with Latent Autoimmune Diabetes in Adults: A Meta-Analysis.Biochemical genetics · 2022Pooled it
- Discovering Novel Loci of Chronic Kidney Disease via Principal Component Analysis-Based Multiple-Trait Genome-Wide Association Study.American journal of nephrology · 2025Article
- Deciphering DNA repair gene mutational landscape in uterine corpus endometrial carcinoma patients using next generation sequencing.American journal of cancer research · 2024Article
- A genomic data archive from the Network for Pancreatic Organ donors with Diabetes.Scientific data · 2023Article
- Advanced Delivery Strategies for Immunotherapy in Type I Diabetes Mellitus.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2023Review
- The missing heritability in type 1 diabetes.Diabetes, obesity & metabolism · 2022Review
- Review
- Exome sequencing identifies a disease variant of the mitochondrial ATP-Mg/Pi carrier SLC25A25 in two families with kidney stones.Molecular genetics & genomic medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Type 1 diabetes mellitus (T1DM) is defined as an autoimmune disorder and has enormous complexity and heterogeneity. Although its precise pathogenic mechanisms are obscure, this disease is widely acknowledged to be precipitated by environmental factors in individuals with genetic susceptibility. To date, the known susceptibility loci, which have mostly been identified by genome-wide association studies, can explain 80%-85% of the heritability of T1DM. Researchers believe that at least a part of its missing genetic component is caused by undetected rare and low-frequency variants. Most common variants have only small to modest effect sizes, which increases the difficulty of dissecting their functions and restricts their potential clinical application. Intriguingly, many studies have indicated that rare and low-frequency variants have larger effect sizes and play more significant roles in susceptibility to common diseases, including T1DM, than common variants do. Therefore, better recognition of rare and low-frequency variants is beneficial for revealing the genetic architecture of T1DM and for providing new and potent therapeutic targets for this disease. Here, we will discuss existing challenges as well as the great significance of this field and review current knowledge of the contributions of rare and low-frequency variants to T1DM.
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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.