The American Journal of Human GeneticsGenetic & Genomic MedicinePeer-reviewed journal article
The relationship between genotype- and phenotype-based estimates of genetic liability to psychiatric disorders, in practice and in theory.
Morten Dybdahl KrebsiD, Vivek AppaduraiiD, Kajsa-Lotta Georgii HellbergiD, Henrik OhlssoniD, Jette SteinbachiD, Emil M. PederseniD, Thomas Mears WergeiD, Jan SundquistiD, Kristina SundquistiD, Richard BorderiD, Na CaiiD, Noah ZaitleniD, Andy W. DahliD, Bjarni Jóhann VilhjálmssoniD, Jonathan Flint CiD, Silviu‐Alin BacanuiD, Kenneth S. KendleriD, Andrew Joseph SchorkiD
Abstract
Genetics as a science has roots in studying phenotypes of relatives, but molecular approaches facilitate direct measurements of genomic variation within individuals. Agricultural and human biomedical research are both emphasizing genotype-based instruments, like polygenic scores, as the future of breeding programs or precision medicine and genetic epidemiology. However, unlike in agriculture, there is an emerging consensus that family variables act nearly independent of genotypes in models of human disease. To advance our understanding of this phenomenon, we use 2,066,057 family records of 99,645 genotyped probands from the iPSYCH2015 case-cohort study to show that state-of-the-field genotype- and phenotype-based genetic instruments explain largely independent components of liability to psychiatric disorders. We support these empirical results with novel theoretical analysis and simulations to describe, in a human biomedical context, parameters affecting current and future performance of the two approaches, their expected interrelationships, and consistency of observed results with expectations under simple additive, polygenic liability models of disease. We conclude, at least for psychiatric disorders, that phenotype- and genotype-based genetic instruments are likely noisy measures of the same underlying additive genetic liability, should be seen for the near future as complementary, and integrated to a greater extent.
- organism: human
- assay: GWAS summary statistics
- research focus: benchmarking
- approach: statistical model
- Citations
- 25
- FWCI
- 11.11
- Field percentile
- top 1%
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