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dc.contributor.authorMerikangas, Alison K
dc.contributor.authorCorvin, Aiden P
dc.contributor.authorGallagher, Louise
dc.date.accessioned2012-02-01T10:45:07Z
dc.date.available2012-02-01T10:45:07Z
dc.date.issued2012-02-01T10:45:07Z
dc.identifier.citationTrends Genet. 2009 Dec;25(12):536-44. Epub 2009 Nov 10.en_GB
dc.identifier.issn0168-9525 (Print)en_GB
dc.identifier.issn0168-9525 (Linking)en_GB
dc.identifier.pmid19910074en_GB
dc.identifier.doi10.1016/j.tig.2009.10.006en_GB
dc.identifier.urihttp://hdl.handle.net/10147/207801
dc.description.abstractCopy-number variation (CNV) is the most prevalent type of structural variation in the human genome. There is emerging evidence that copy-number variants (CNVs) provide a new vista on understanding susceptibility to neuropsychiatric disorders. Some challenges in the interpretation of current CNV studies include the use of overlapping samples, differing phenotypic definitions, an absence of population norms for CNVs and a lack of consensus in methods for CNV detection and analysis. Here, we review current CNV association study methods and results in autism spectrum disorders (ASD) and schizophrenia, and provide suggestions for design approaches to future studies that might maximize the translation of this work to etiological understanding.
dc.language.isoengen_GB
dc.subject.meshAnimalsen_GB
dc.subject.meshAutistic Disorder/*geneticsen_GB
dc.subject.mesh*DNA Copy Number Variationsen_GB
dc.subject.meshHumansen_GB
dc.subject.meshSchizophrenia/*geneticsen_GB
dc.titleCopy-number variants in neurodevelopmental disorders: promises and challenges.en_GB
dc.contributor.departmentDepartment of Psychiatry, Trinity Centre for Health Sciences, St. James Hospital,, Dublin, Ireland. merikana@tcd.ieen_GB
dc.identifier.journalTrends in genetics : TIGen_GB
dc.description.provinceLeinster
html.description.abstractCopy-number variation (CNV) is the most prevalent type of structural variation in the human genome. There is emerging evidence that copy-number variants (CNVs) provide a new vista on understanding susceptibility to neuropsychiatric disorders. Some challenges in the interpretation of current CNV studies include the use of overlapping samples, differing phenotypic definitions, an absence of population norms for CNVs and a lack of consensus in methods for CNV detection and analysis. Here, we review current CNV association study methods and results in autism spectrum disorders (ASD) and schizophrenia, and provide suggestions for design approaches to future studies that might maximize the translation of this work to etiological understanding.


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