Association study of 167 candidate genes for schizophrenia selected by a multi-domain evidence-based prioritization algorithm and neurodevelopmental hypothesis
Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n=3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of mi...
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creator | Zhao, Zhongming Webb, Bradley T Jia, Peilin Bigdeli, T Bernard Maher, Brion S van den Oord, Edwin Bergen, Sarah E Amdur, Richard L O'Neill, Francis A Walsh, Dermot Thiselton, Dawn L Chen, Xiangning Pato, Carlos N Riley, Brien P Kendler, Kenneth S Fanous, Ayman H |
description | Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n=3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted. |
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We ranked all known human genes (n=3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. 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This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. 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We ranked all known human genes (n=3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. 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As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.</description><subject>Algorithms</subject><subject>Autism</subject><subject>Biology</subject><subject>Brain</subject><subject>Consortia</subject><subject>Databases, Genetic</subject><subject>Diabetes</subject><subject>DNA microarrays</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetics</subject><subject>Genome-wide association studies</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotypes</subject><subject>Health risk assessment</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Informatics</subject><subject>Kinases</subject><subject>Mathematics</subject><subject>Medicine</subject><subject>Mental disorders</subject><subject>Meta-analysis</subject><subject>Meta-Analysis as 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Xiangning</au><au>Pato, Carlos N</au><au>Riley, Brien P</au><au>Kendler, Kenneth S</au><au>Fanous, Ayman H</au><aucorp>International Schizophrenia Consortium</aucorp><aucorp>The International Schizophrenia Consortium</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Association study of 167 candidate genes for schizophrenia selected by a multi-domain evidence-based prioritization algorithm and neurodevelopmental hypothesis</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-07-29</date><risdate>2013</risdate><volume>8</volume><issue>7</issue><spage>e67776</spage><epage>e67776</epage><pages>e67776-e67776</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n=3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23922650</pmid><doi>10.1371/journal.pone.0067776</doi><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
subjects | Algorithms Autism Biology Brain Consortia Databases, Genetic Diabetes DNA microarrays Gene expression Genes Genetic Predisposition to Disease Genetics Genome-wide association studies Genome-Wide Association Study Genomes Genomics Genotypes Health risk assessment Humans Hypotheses Informatics Kinases Mathematics Medicine Mental disorders Meta-analysis Meta-Analysis as Topic Models, Genetic Nervous System - growth & development Nervous System - pathology Neurodevelopment Polymorphism, Single Nucleotide - genetics Precision medicine Protein interaction Proteins Psychiatry Publishing Ranking Schizophrenia Schizophrenia - genetics Single-nucleotide polymorphism |
title | Association study of 167 candidate genes for schizophrenia selected by a multi-domain evidence-based prioritization algorithm and neurodevelopmental hypothesis |
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