Literature DB >> 16801952

Subtyping schizophrenia: implications for genetic research.

A Jablensky1.   

Abstract

Phenotypic variability and likely extensive genetic heterogeneity have been confounding the search for the causes of schizophrenia since the inception of the diagnostic category. The inconsistent results of genetic linkage and association studies using the diagnostic category as the sole schizophrenia phenotype suggest that the current broad concept of schizophrenia does not demarcate a homogeneous disease entity. Approaches involving subtyping and stratification by covariates to reduce heterogeneity have been successful in the genetic study of other complex disorders, but rarely applied in schizophrenia research. This article reviews past and present attempts at delineating schizophrenia subtypes based on clinical features, statistically derived measures, putative genetic indicators, and intermediate phenotypes, highlighting the potential utility of multidomain neurocognitive endophenotypes.

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Year:  2006        PMID: 16801952     DOI: 10.1038/sj.mp.4001857

Source DB:  PubMed          Journal:  Mol Psychiatry        ISSN: 1359-4184            Impact factor:   15.992


  67 in total

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Review 6.  Very poor outcome schizophrenia: clinical and neuroimaging aspects.

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7.  Comments on the paper by D. Li and L. He: meta-analysis shows association between the tryptophan hydroxylase (TPH) gene and schizophrenia.

Authors:  P G Sand
Journal:  Hum Genet       Date:  2007-11       Impact factor: 4.132

Review 8.  Modern modularity and the road towards a modular psychiatry.

Authors:  Jürgen Zielasek; Wolfgang Gaebel
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9.  Clinical significance of auditory target P300 subcomponents in psychosis: Differential diagnosis, symptom profiles, and course.

Authors:  Greg Perlman; Dan Foti; Felicia Jackson; Roman Kotov; Eduardo Constantino; Greg Hajcak
Journal:  Schizophr Res       Date:  2015-04-29       Impact factor: 4.939

10.  Linkage and heritability analysis of migraine symptom groupings: a comparison of three different clustering methods on twin data.

Authors:  Carla C M Chen; Kerrie L Mengersen; Jonathan M Keith; Nicholas G Martin; Dale R Nyholt
Journal:  Hum Genet       Date:  2009-03-19       Impact factor: 4.132

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