Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

Wang, Y. and Thompson, W. K. and Schork, A. J. and Holland, D. and Chen, C. H. and Bettella, F. and Desikan, R. S. and Li, W. and Witoelar, A. and Zuber, V. and Devor, A. and Bipolar, Disorder and Schizophrenia Working Group of the Psychiatric Genomics, Consortium and Enhancing Neuro Imaging Genetics through Meta Analysis, Consortium and Nothen, M. M. and Rietschel, M. and Chen, Q. and Werge, T. and Cichon, S. and Weinberger, D. R. and Djurovic, S. and O'Donovan, M. and Visscher, P. M. and Andreassen, O. A. and Dale, A. M.. (2016) Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS. PLoS Genetics, 12 (1). e1005803.

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Official URL: https://edoc.unibas.ch/61590/

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Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic ("z-score") of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a "relative enrichment score" for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p /=80% and </=90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedizin > Department of Biomedicine, University Hospital Basel > Human Genetics (Cichon)
UniBasel Contributors:Cichon, Sven
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:16 Apr 2019 15:59
Deposited On:16 Apr 2019 15:59

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