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Nat Commun. 2019 Jun 3;10(1):2417. doi: 10.1038/s41467-019-10310-0.

Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation.

Author information

1
NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, 0424, Oslo, Norway. oleksandr.frei@gmail.com.
2
Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA, 92037, USA.
3
Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92093, USA.
4
NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, 0424, Oslo, Norway.
5
Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
6
Department of Cognitive Sciences, University of California at San Diego, La Jolla, CA, 92093, USA.
7
Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA.
8
Department of Medical Genetics, Oslo University Hospital, 0424, Oslo, Norway.
9
NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, 5020, Bergen, Norway.
10
Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, 92093, USA.
11
Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Capital Region of Denmark, Roskilde, 4000, Denmark.
12
Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA, 92037, USA. andersmdale@gmail.com.
13
Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92093, USA. andersmdale@gmail.com.
14
Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA. andersmdale@gmail.com.
15
Department of Psychiatry, University of California, San Diego, La Jolla, CA, 92093, USA. andersmdale@gmail.com.

Abstract

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. Here we introduce a statistical tool, MiXeR, which quantifies polygenic overlap irrespective of genetic correlation, using GWAS summary statistics. MiXeR results are presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that 8.3 K variants causally influence schizophrenia and 6.4 K influence bipolar disorder. Among these variants, 6.2 K are shared between the disorders, which have a high genetic correlation. Further, MiXeR uncovers polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, the phenotypes share 8.3 K causal variants, while 2.5 K additional variants influence only educational attainment. By considering the polygenicity, discoverability and heritability of complex phenotypes, MiXeR analysis may improve our understanding of cross-trait genetic architectures.

PMID:
31160569
PMCID:
PMC6547727
DOI:
10.1038/s41467-019-10310-0
[Indexed for MEDLINE]
Free PMC Article

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