Follow-up of potential novel Graves' disease susceptibility loci, identified in the UK WTCCC genome-wide nonsynonymous SNP study

Newby, Paul; Pickles, Oliver; Mazumdar, Srijan; Brand, Stephan; Carr-Smith, James; Pearce, Simon H. S.; Franklyn, Jayne A.; Evans, David M.; Simmonds, Matthew J.; Gough, Stephen

doi:10.1038/ejhg.2010.55

Cited by 15 publications

(12 citation statements)

References 19 publications

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“…Many of these studies rely on data from large case-specific studies such as the WTCCC [21], Farmingham Heart Study [22], or the International Cancer Genome Consortium (ICGC) [23]. Our study uses integrated data from all GWAS curated into the NIH GWAS Catalog.…”

Section: Discussionmentioning

confidence: 99%

Large Scale Analysis of Phenotype-Pathway Relationships Based on GWAS Results

2014

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The widely used pathway-based approach for interpreting Genome Wide Association Studies (GWAS), assumes that since function is executed through the interactions of multiple genes, different perturbations of the same pathway would result in a similar phenotype. This assumption, however, was not systemically assessed on a large scale. To determine whether SNPs associated with a given complex phenotype affect the same pathways more than expected by chance, we analyzed 368 phenotypes that were studied in >5000 GWAS. We found 216 significant phenotype-pathway associations between 70 of the phenotypes we analyzed and known pathways. We also report 391 strong phenotype-phenotype associations between phenotypes that are affected by the same pathways. While some of these associations confirm previously reported connections, others are new and could shed light on the molecular basis of these diseases. Our findings confirm that phenotype-associated SNPs cluster into pathways much more than expected by chance. However, this is true for <20% (70/368) of the phenotypes. Different types of phenotypes show markedly different tendencies: Virtually all autoimmune phenotypes show strong clustering of SNPs into pathways, while most cancers and metabolic conditions, and all electrophysiological phenotypes, could not be significantly associated with any pathway despite being significantly associated with a large number of SNPs. While this may be due to missing data, it may also suggest that these phenotypes could result only from perturbations of specific genes and not from other perturbations of the same pathway. Further analysis of pathway-associated versus gene-associated phenotypes is, therefore, needed in order to understand disease etiology and in order to promote better drug target selection.

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Section: Discussionmentioning

confidence: 99%

Large Scale Analysis of Phenotype-Pathway Relationships Based on GWAS Results

2014

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“…In the WTCCC study, although TSHR and FCRL3 loci were confirmed to be associated with GD, no additional locus was identified as a novel GD susceptibility locus. 14,25 Through the GWA and the subsequent replication studies, we identified 22 GD-associated SNPs within the MHC region. Among them, seven SNPs that were integrated into the multivariate logistic were successfully genotyped, 1119 GD cases versus 2718 controls, meta-analysis P-values), the replication study (34 SNPs, 432 GD cases versus 1157 controls, Cochrane-Armitage trend P-values) and the combined analysis of both studies (22 SNPs, 1551 GD cases versus 3875 controls, Cochrane-Armitage trend P-values), respectively.…”

Section: Discussionmentioning

confidence: 99%

Identification of independent risk loci for Graves’ disease within the MHC in the Japanese population

et al. 2011

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To identify genetic variants that confer the risk of Graves' disease (GD) in the Japanese population, we conducted a two-stage genome-wide association study (GWAS) using 1119 Japanese individuals with GD and 2718 unrelated controls, and a subsequent replication study using independent 432 GD cases and 1157 controls. We identified 34 single nucleotide polymorphisms (SNPs) to be significantly associated with GD in the GWAS phase. Twenty-two out of 34 SNPs remained positive in the replication study. All 22 SNPs were located within the major histocompatibility complex (MHC) locus on chromosome 6p21. No strong long-range linkage disequilibrium (LD) was observed among the 22 SNPs, indicating independent involvement of multiple loci within the MHC with the risk of GD. Multivariate stepwise logistic regression analysis selected rs3893464, rs4313034, rs3132613, rs4248154, rs2273017, rs9394159 and rs4713693, as markers for independent risk loci for GD. The analysis of LD between these seven SNPs and tagging SNPs for GD-associated human leukocyte antigen (HLA) alleles in the Japanese population (HLA-DPB1*0501 and HLA-A*0206) demonstrated that all of and five of seven SNPs were not in strong LD with HLA-DPB1*0501 and HLA-A*0206, respectively. Although causal variants remain to be identified, our results demonstrate the existence of multiple GD susceptibility loci within the MHC region.

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“…Although presently there is much less information linking KDMs to other therapeutic areas, there is suggestive genetic evidence that altered KDM activity may be relevant to a number of diseases. For instance, single nucleotide polymorphisms (SNPs) in KDM5A and KDM1A have been linked to the autoimmune diseases ankylosing spondylitis and Grave's disease respectively (Newby et al, 2010;Pointon et al, 2011). KDM6B has also been implicated in an autoimmune disease based on its overexpression in antineutrophil cytoplasmic autoantibody-associated vasculitis (Ciavatta et al, 2010).…”

Section: Lysine Demethylasesmentioning

confidence: 99%

Epigenetic pathway targets for the treatment of disease: accelerating progress in the development of pharmacological tools:IUPHARReview 11

Tough

Lewis

Rioja

et al. 2014

British J Pharmacology

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The properties of a cell are determined both genetically by the DNA sequence of its genes and epigenetically through processes that regulate the pattern, timing and magnitude of expression of its genes. While the genetic basis of disease has been a topic of intense study for decades, recent years have seen a dramatic increase in the understanding of epigenetic regulatory mechanisms and a growing appreciation that epigenetic misregulation makes a significant contribution to human disease. Several large protein families have been identified that act in different ways to control the expression of genes through epigenetic mechanisms. Many of these protein families are finally proving tractable for the development of small molecules that modulate their function and represent new target classes for drug discovery. Here, we provide an overview of some of the key epigenetic regulatory proteins and discuss progress towards the development of pharmacological tools for use in research and therapy.

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Follow-up of potential novel Graves' disease susceptibility loci, identified in the UK WTCCC genome-wide nonsynonymous SNP study

Cited by 15 publications

References 19 publications

Large Scale Analysis of Phenotype-Pathway Relationships Based on GWAS Results

Large Scale Analysis of Phenotype-Pathway Relationships Based on GWAS Results

Identification of independent risk loci for Graves’ disease within the MHC in the Japanese population

Epigenetic pathway targets for the treatment of disease: accelerating progress in the development of pharmacological tools:IUPHARReview 11

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