ArticlePloS one2021
A comprehensive integrated post-GWAS analysis of Type 1 diabetes reveals enhancer-based immune dysregulation.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Harnessing Machine Learning, a Subset of Artificial Intelligence, for Early Detection and Diagnosis of Type 1 Diabetes: A Systematic Review.International journal of molecular sciences · 2025Pooled it
- Article
- Aberrant Enhancer Regulation, Phase Separation, and Autoimmune Diseases.Clinical reviews in allergy & immunology · 2025Review
- The Impact of Stress on Autoimmune Disorders: Type 1 Diabetes Mellitus and Systemic Lupus Erythematosus.Cureus · 2025Review
- Vitamin D in Primary Sjogren's Syndrome (pSS) and the Identification of Novel Single-Nucleotide Polymorphisms Involved in the Development of pSS-Associated Diseases.Diagnostics (Basel, Switzerland) · 2024Review
- Teplizumab's immunomodulatory effects on pancreatic β-cell function in type 1 diabetes mellitus.Clinical diabetes and endocrinology · 2024Review
- Association of HLA Haplotypes with Autoimmune Pathogenesis in Newly Diagnosed Type 1 Romanian Diabetic Children: A Pilot, Single-Center Cross-Sectional Study.Life (Basel, Switzerland) · 2024Article
- Genetic and Epigenetic Aspects of Type 1 Diabetes Mellitus: Modern View on the Problem.Biomedicines · 2024Review
- How do immune cells shape type 1 diabetes? Insights from Mendelian randomization.Frontiers in endocrinology · 2024Article
- Teplizumab in Type 1 Diabetes Mellitus: An Updated Review.TouchREVIEWS in endocrinology · 2023Review
- Modulation of autoimmune diabetes by N-ethyl-N-nitrosourea- induced mutations in non-obese diabetic mice.Disease models & mechanisms · 2022Article
- Prediction of Drug Targets for Specific Diseases Leveraging Gene Perturbation Data: A Machine Learning Approach.Pharmaceutics · 2022Article
- Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics.Results and problems in cell differentiation · 2022Article
- Roles of extracellular vesicles associated non-coding RNAs in Diabetes Mellitus.Frontiers in endocrinology · 2022Review
- Nature vs. nurture: FOXP3, genetics, and tissue environment shape Treg function.Frontiers in immunology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
Type 1 diabetes (T1D) is an organ-specific autoimmune disease, whereby immune cell-mediated killing leads to loss of the insulin-producing β cells in the pancreas. Genome-wide association studies (GWAS) have identified over 200 genetic variants associated with risk for T1D. The majority of the GWAS risk variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes substantially contribute to T1D. However, identification of causal regulatory variants associated with T1D risk and their affected genes is challenging due to incomplete knowledge of non-coding regulatory elements and the cellular states and processes in which they function. Here, we performed a comprehensive integrated post-GWAS analysis of T1D to identify functional regulatory variants in enhancers and their cognate target genes. Starting with 1,817 candidate T1D SNPs defined from the GWAS catalog and LDlink databases, we conducted functional annotation analysis using genomic data from various public databases. These include 1) Roadmap Epigenomics, ENCODE, and RegulomeDB for epigenome data; 2) GTEx for tissue-specific gene expression and expression quantitative trait loci data; and 3) lncRNASNP2 for long non-coding RNA data. Our results indicated a prevalent enhancer-based immune dysregulation in T1D pathogenesis. We identified 26 high-probability causal enhancer SNPs associated with T1D, and 64 predicted target genes. The majority of the target genes play major roles in antigen presentation and immune response and are regulated through complex transcriptional regulatory circuits, including those in HLA (6p21) and non-HLA (16p11.2) loci. These candidate causal enhancer SNPs are supported by strong evidence and warrant functional follow-up studies.
Indexed as
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.