ArticleDiabetologia2014
Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes.
Article in Diabetologia, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 89 papers, 2 of them syntheses that pooled it.
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Who cites it
89 citing papers in PubMed, 2 syntheses or guidelines pooled it, 133 citations in OpenAlex.
- ISPAD Clinical Practice Consensus Guidelines 2024: Screening, Staging, and Strategies to Preserve Beta-Cell Function in Children and Adolescents with Type 1 Diabetes.Hormone research in paediatrics · 2024Guideline
- Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes.International journal of molecular sciences · 2020Pooled it
- Residual β cell function in long-term type 1 diabetes associates with reduced incidence of hypoglycemia.The Journal of clinical investigation · 2021Trial
- Development and application of type 1 diabetes polygenic scores across diverse populations.Diabetologia · 2026Review
- Development and validation of a trans-ancestry polygenic risk score for type 1 diabetes.Diabetologia · 2026Article
- Article
- Genetic association and machine learning improve the prediction of type 1 diabetes risk.Nature genetics · 2026Article
- Genetic Risk and Transition Through Preclinical Stages of Type 1 Diabetes.The Journal of clinical endocrinology and metabolism · 2026Article
- Preclinical Diagnosis of Type 1 Diabetes: Reality or Utopia.Biomedicines · 2025Review
- Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation.Nature reviews. Endocrinology · 2025Review
- Type 1 diabetes risk factors, risk prediction and presymptomatic detection: Evidence and guidance for screening.Diabetes, obesity & metabolism · 2025Review
- Effects of parental autoimmune diseases on type 1 diabetes in offspring can be partially explained by HLA and non-HLA polymorphisms.Cell genomics · 2025Article
- Protocol for the development of a core outcome set for type 1 diabetes risk screening.BMJ open · 2025Article
- Genetic Associations With C-peptide Levels Before Type 1 Diabetes Diagnosis in At-risk Relatives.The Journal of clinical endocrinology and metabolism · 2025Article
- The stage- and subgroup-specific impact of non-HLA polymorphisms on preclinical type 1 diabetes progression.Heliyon · 2025Article
- Type 1 Diabetes Genetic Risk Scores: History, Application and Future Directions.Current diabetes reports · 2025Review
- Age-standardized incidence, prevalence, mortality rates and future projections of autoimmune diseases in China: a systematic analysis based on GBD 2021.Immunologic research · 2025Article
- Identifying genetically predisposed type 1 diabetes mellitus individuals in a Southern Brazilian population: The construction of a genetic risk score.Genetics and molecular biology · 2025Article
- Lessons and Applications of Omics Research in Diabetes Epidemiology.Current diabetes reports · 2024Review
- Genetic and Epigenetic Aspects of Type 1 Diabetes Mellitus: Modern View on the Problem.Biomedicines · 2024Review
29 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aims/hypothesisMore than 40 regions of the human genome confer susceptibility for type 1 diabetes and could be used to establish population screening strategies. The aim of our study was to identify weighted sets of SNP combinations for type 1 diabetes prediction.
methodsWe applied multivariable logistic regression and Bayesian feature selection to the Type 1 Diabetes Genetics Consortium (T1DGC) dataset with genotyping of HLA plus 40 SNPs within other type 1 diabetes-associated gene regions in 4,574 cases and 1,207 controls. We tested the weighted models in an independent validation set (765 cases, 423 controls), and assessed their performance in 1,772 prospectively followed children.
resultsThe inclusion of 40 non-HLA gene SNPs significantly improved the prediction of type 1 diabetes over that provided by HLA alone (p = 3.1 × 10(-25)), with a receiver operating characteristic AUC of 0.87 in the T1DGC set, and 0.84 in the validation set. Feature selection identified HLA plus nine SNPs from the PTPN22, INS, IL2RA, ERBB3, ORMDL3, BACH2, IL27, GLIS3 and RNLS genes that could achieve similar prediction accuracy as the total SNP set. Application of this ten SNP model to prospectively followed children was able to improve risk stratification over that achieved by HLA genotype alone.
conclusionsWe provided a weighted risk model with selected SNPs that could be considered for recruitment of infants into studies of early type 1 diabetes natural history or appropriately safe prevention.
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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.