1. Using genotype data to distinguish pleiotropy from heterogeneity: deciphering coheritability in autoimmune and neuropsychiatric diseases
- Author
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Dorothée Diogo, Kamil Slowikowski, Buhm Han, Suna Onengut-Gumuscu, E Stahl, Dahqvist, Soumya Raychaudhuri, Xinli Hu, Lars Klareskog, Yu Rang Park, Naomi R. Wray, Peter K. Gregersen, Twj Huizinga, Eun Na Kim, Jennie G. Pouget, Wei Chen, Jane Worthington, Cue Hyunkyu Lee, Stephen S. Rich, and Stephen Eyre
- Subjects
Genetics ,0303 health sciences ,Genetic heterogeneity ,Genomics ,Biology ,medicine.disease ,Phenotype ,Genetic architecture ,3. Good health ,03 medical and health sciences ,0302 clinical medicine ,Pleiotropy ,Schizophrenia ,Genotype ,medicine ,Major depressive disorder ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
Shared genetic architecture between phenotypes may be driven by a common genetic basis (pleiotropy) or a subset of genetically similar individuals (heterogeneity). We developed BUHMBOX, a well-powered statistical method to distinguish pleiotropy from heterogeneity using genotype data. We observed a shared genetic basis between 11 of 17 tested autoimmune diseases and type I diabetes (T1D, p0.2 using 6,670 T1D cases and 7,279 RA cases), suggesting that shared genetic features in autoimmunity are due to pleiotropy. We observed a shared genetic basis between seronegative and seropostive RA (p
- Published
- 2015
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