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Nat Genet. 2015 Jul;47(7):839-46. doi: 10.1038/ng.3330. Epub 2015 Jun 8.

Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls.

Author information

1
JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
2
1] JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. [2] Centre for Biostatistics, Institute of Population Health, University of Manchester, Manchester, UK.
3
University Neurology Unit, Addenbrooke's Hospital, Cambridge, UK.
4
1] Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK. [2] National Institute for Health Research Manchester Musculoskeletal Biomedical Research Unit, Central Manchester Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
5
1] JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. [2] Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK.

Abstract

Determining whether potential causal variants for related diseases are shared can identify overlapping etiologies of multifactorial disorders. Colocalization methods disentangle shared and distinct causal variants. However, existing approaches require independent data sets. Here we extend two colocalization methods to allow for the shared-control design commonly used in comparison of genome-wide association study results across diseases. Our analysis of four autoimmune diseases--type 1 diabetes (T1D), rheumatoid arthritis, celiac disease and multiple sclerosis--identified 90 regions that were associated with at least one disease, 33 (37%) of which were associated with 2 or more disorders. Nevertheless, for 14 of these 33 shared regions, there was evidence that the causal variants differed. We identified new disease associations in 11 regions previously associated with one or more of the other 3 disorders. Four of eight T1D-specific regions contained known type 2 diabetes (T2D) candidate genes (COBL, GLIS3, RNLS and BCAR1), suggesting a shared cellular etiology.

PMID:
26053495
PMCID:
PMC4754941
DOI:
10.1038/ng.3330
[Indexed for MEDLINE]
Free PMC Article

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