Trynka, G., Hunt, K. A., Bockett, N. A., Romanos, J., Mistry, V., Szperl, A. et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nat. Genet. 43, 1193-1201

Genetics Department, University Medical Center and University of Groningen, The Netherlands.
Nature Genetics (Impact Factor: 29.35). 11/2011; 43(12):1193-201. DOI: 10.1038/ng.998
Source: PubMed


Using variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene regulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease.

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Available from: Sabyasachi Senapati, Oct 02, 2015
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    • "Widely available preliminary findings, such as for coeliac disease, would most likely fall into the category of those findings that are low risk with clinical validity, and might be of some use to some individuals [22]. There is doubt regarding the precise phenotype for this condition and more work is needed to determine exactly which genes are causal [26]. But cohort members might want this information, as changes in lifestyle can improve the quality of life for sufferers. "
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    ABSTRACT: Population-based, prospective longitudinal cohort studies are considering the issues surrounding returning findings to individuals as a result of genomic and other medical research studies. While guidance is being developed for clinical settings, the process is less clear for those conducting longitudinal research. This paper discusses work conducted on behalf of The UK Cohort and Longitudinal Study Enhancement Resource programme (CLOSER) to examine consent requirements, process considerations and specific examples of potential findings in the context of the 1958 British Birth cohort. Beyond deciding which findings to return, there are questions of whether re-consent is needed and the possible impact on the study, how the feedback process will be managed, and what resources are needed to support that process. Recommendations are made for actions a cohort study should consider taking when making vital decisions regarding returning findings. Any decisions need to be context-specific, arrived at transparently, communicated clearly, and in the best interests of both the participants and the study.
    Emerging Themes in Epidemiology 08/2014; 11(1):10. DOI:10.1186/1742-7622-11-10 · 2.59 Impact Factor
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    • "all of which showed significant association in the previous GWAS and follow-up studies by Dubois et al. [7]. These loci were subsequently included in a high-resolution association analysis by Trynka et al. [10] to refine their positions. The locus on chromosome 3p21.31 is intergenic between CCR3 and CCR2. "
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    ABSTRACT: We performed a genome-wide association study (GWAS) of 1550 North American celiac disease cases and 3084 controls. Twelve SNPs, distributed across four regions (3p21.31, 4q27, 6q15, 6q25), were significantly associated with disease (p-value <1.0×10-7), and a further seven SNPs, across four additional regions (1q24.3, 10p15.1, 6q22.31, 17q21.32) had suggestive evidence (1.0×10-7 < p-value < 1.0×10-6). This study replicated a previous suggestive association within FRMD4B (3p14.1), confirming it as a celiac disease locus. All four regions with significant associations and two regions with suggestive results (1q24.3, 10p15.1) were known disease loci. The 6q22.31 and 10p11.23 regions were not replicated. A total of 410 SNPs distributed across the eight significant and suggestive regions were tested for association with dermatitis herpetiformis and microscopic colitis. Preliminary, suggestive statistical evidence for association with the two traits was found at chromosomes 3p21.31, 6q15, 6q25, 1q24.3 and 10p11.23, with future studies being required to validate the reported associations.
    PLoS ONE 07/2014; 9(7):e101428. DOI:10.1371/journal.pone.0101428 · 3.23 Impact Factor
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    • "One strategy is to finemap the association signal by intensively genotyping the common and rare SNPs at the associated regions. This approach has been successfully used to analyze SNPs that associate with celiac disease by employing the Immunochip, which contains high-density SNPs at immune-associated loci, including rare variants [30]. "
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    ABSTRACT: The completion of the human genome sequence in 2003 clearly marked the beginning of a new era for biomedical research. It spurred technological progress that was unprecedented in the life sciences, including the development of high-throughput technologies to detect genetic variation and gene expression. The study of genetics has become "big data science". One of the current goals of genetic research is to use genomic information to further our understanding of common complex diseases. An essential first step was made towards this goal by the identification of thousands of single nucleotide polymorphisms showing robust association with hundreds of different traits and diseases. As insight into common genetic variation has expanded enormously and the technology to identify more rare variation has become available, we can utilize these advances to gain a better understanding of disease etiology. This will lead to developments in personalized medicine and P4 healthcare. Here, we review some of the historical events and perspectives before and after the completion of the human genome sequence. We also describe the success of large-scale genetic association studies and how these are expected to yield more insight into complex disorders. We show how we can now combine gene-oriented research and systems-based approaches to develop more complex models to help explain the etiology of common diseases. This article is part of a Special Issue entitled: From Genome to Function.
    Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 05/2014; 1842(10). DOI:10.1016/j.bbadis.2014.05.002 · 4.88 Impact Factor
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