Journal article
Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia, Bipolar Disorder, and Major Depressive Disorder
American journal of human genetics, Vol.96(2), pp.283-294
02/05/2015
DOI: 10.1016/j.ajhg.2014.12.006
PMCID: PMC4320268
PMID: 25640677
Abstract
Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.
Details
- Title: Subtitle
- Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia, Bipolar Disorder, and Major Depressive Disorder
- Creators
- Robert Maier - University of QueenslandGerhard Moser - University of QueenslandGuo-Bo Chen - University of QueenslandStephan Ripke - Broad InstituteCross-Disorder Working Group of the Psychiatric Genomics ConsortiumWilliam Coryell - University of Iowa, PsychiatryJames B Potash - University of Iowa, PsychiatryWilliam A Scheftner - Rush University Medical CenterJianxin Shi - National Institutes of HealthMyrna M Weissmann - Columbia UniversityChristina M Hultman - Karolinska InstitutetMikael Landén - Karolinska InstitutetDouglas F Levinson - Stanford UniversityKenneth S Kendler - Virginia Commonwealth UniversityJordan W Smoller - Broad InstituteNaomi R Wray - University of QueenslandS. Hong Lee - University of Queensland
- Resource Type
- Journal article
- Publication Details
- American journal of human genetics, Vol.96(2), pp.283-294
- DOI
- 10.1016/j.ajhg.2014.12.006
- PMID
- 25640677
- PMCID
- PMC4320268
- ISSN
- 0002-9297
- eISSN
- 1537-6605
- Language
- English
- Date published
- 02/05/2015
- Academic Unit
- Psychiatry; Stead Family Department of Pediatrics
- Record Identifier
- 9984281651102771
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