ArticleDiabetes, obesity & metabolism2009
Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data.
Article in Diabetes, obesity & metabolism, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- The influence of ICAM1 rs5498 on diabetes mellitus risk: evidence from a meta-analysis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2019Pooled it
- Diabetes, Protein Misfolding, and Heat Stress: Molecular Insights and Translational Perspectives.TH open : companion journal to thrombosis and haemostasis · 2026Review
- Apolipoprotein M gene polymorphisms in childhood-onset type 1 diabetes in southern Brazil.International journal of biochemistry and molecular biology · 2023Article
- Apolipoprotein M-A Marker or an Active Player in Type II Diabetes?Frontiers in endocrinology · 2021Review
- The Role of Heat Shock Proteins in Type 1 Diabetes.Frontiers in immunology · 2020Review
- Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis.Nature communications · 2017Article
- HLA-DRB1*03 as a risk factor for microalbuminuria in same duration of type 1 diabetes: a case control study.BMC nephrology · 2016Article
- Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 Diabetes.PloS one · 2016Article
- MOBAS: identification of disease-associated protein subnetworks using modularity-based scoring.EURASIP journal on bioinformatics & systems biology · 2015Article
- Protein interaction-based genome-wide analysis of incident coronary heart disease.Circulation. Cardiovascular genetics · 2011Article
- From SNPs to genes: disease association at the gene level.PloS one · 2011Article
- The type 1 diabetes - HLA susceptibility interactome--identification of HLA genotype-specific disease genes for type 1 diabetes.PloS one · 2010Article
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 at 2 institutions in 2 countries.
Funding
Abstract
aimTo develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1 genes.
methodsWe have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation.
resultsA total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in beta-cell development and diabetic complications.
conclusionsThe extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D.
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.