TY - JOUR

T1 - Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

AU - Wang, Yunpeng

AU - Thompson, Wesley K

AU - Schork, Andrew J

AU - Holland, Dominic

AU - Chen, Chi-Hua

AU - Bettella, Francesco

AU - Desikan, Rahul S

AU - Li, Wen

AU - Witoelar, Aree

AU - Zuber, Verena

AU - Devor, Anna

AU - Nöthen, Markus M

AU - Rietschel, Marcella

AU - Chen, Qiang

AU - Werge, Thomas

AU - Cichon, Sven

AU - Weinberger, Daniel R

AU - Djurovic, Srdjan

AU - O'Donovan, Michael

AU - Visscher, Peter M

AU - Andreassen, Ole A

AU - Dale, Anders M

AU - Knight, Jo

AU - Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium

PY - 2016/1

Y1 - 2016/1

N2 - 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 < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥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.

AB - 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 < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥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.

KW - Genetic Predisposition to Disease

KW - Genome, Human

KW - Genome-Wide Association Study

KW - Genomics

KW - Humans

KW - Linkage Disequilibrium

KW - Polymorphism, Single Nucleotide

KW - Schizophrenia

KW - Journal Article

KW - Research Support, N.I.H., Extramural

KW - Research Support, Non-U.S. Gov't

U2 - 10.1371/journal.pgen.1005803

DO - 10.1371/journal.pgen.1005803

M3 - Journal article

C2 - 26808560

VL - 12

JO - PLoS Genetics

JF - PLoS Genetics

SN - 1553-7390

IS - 1

M1 - e1005803

ER -