Article

Phenotype Evaluation and Genomewide Linkage Study of Clinical Variables in Schizophrenia

MRC Centre for Neuropsychiatric Genetics and Genomics, Department of Psychological Medicine and Neurology, School of Medicine, Cardiff University, Heath Park, Cardiff, UK.
American Journal of Medical Genetics Part B Neuropsychiatric Genetics (Impact Factor: 3.42). 12/2011; 156B(8):929-40. DOI: 10.1002/ajmg.b.31240
Source: PubMed

ABSTRACT

Genetic factors are likely to influence clinical variation in schizophrenia, but it is unclear which variables are most suitable as phenotypes and which molecular genetic loci are involved. We evaluated clinical variable phenotypes and applied suitable phenotypes in genome-wide covariate linkage analysis. We ascertained 170 affected relative pairs (168 sibling-pairs and two avuncular pairs) with DSM-IV schizophrenia or schizoaffective disorder from the United Kingdom. We defined psychotic symptom dimensions, age at onset (AAO), and illness course using the OPCRIT checklist. We evaluated phenotypes using within sibling-pair correlations and applied suitable phenotypes in multipoint covariate linkage analysis based on 372 microsatellite markers at ∼10 cM intervals. The statistical significance of linkage results was assessed by simulation. The positive and disorganized symptom dimensions, AAO, and illness course qualified as suitable phenotypes. There were no genome-wide significant linkage results. There was suggestive evidence of linkage for the positive dimension on chromosomes 2q32, 10q26, and 20q12; the disorganized dimension on 8p21 and 17q21; and illness course on 2q33 and 22q11. The linkage peak for disorganization on 17q21 remained suggestive after correction for multiple testing. To our knowledge, this is the first study to integrate phenotype evaluation and genome-wide covariate linkage analysis for symptom dimensions and illness history variables in sibling-pairs with schizophrenia. The significant within-pair correlations strengthen the evidence that some clinical variables within schizophrenia are suitable phenotypes for molecular genetic investigations. At present there are no genome-wide significant linkage results for these phenotypes, but a number of suggestive findings warrant further investigation.

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    • "The presentation of schizophrenia is indeed diverse – with symptoms ranging from delusions, to disorganization to emotional withdrawal. And from a disease biology perspective these distinct symptoms, subscales and dimensions are increasingly thought to have distinct genetic, neurobiological and neuroanatomical bases (Goghari et al., 2010; Hamshere et al., 2011; Sorg et al., 2013). Not surprisingly then, it has been claimed that a particular receptor profile could impact in a specific symptom dimension (e.g. "
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    ABSTRACT: The clinical expression of schizophrenia is generally reported to be expressed by three to five different factors (i.e. positive, negative, disorganization, excitability, anxiety-depression symptoms). It is often claimed that antipsychotic medications are particularly helpful for positive symptoms, but not for the others, suggesting a differential efficacy for different aspects of the disorder. We formally tested this claim. Using Structural Equation Modeling in two large [1884 patients] clinical trials in schizophrenia, we compared the model of a common general effect of antipsychotics to models whereby the antipsychotics have multiple and differential effects on the different factors of the illness. We validated the generalizability of the model in further trials involving antipsychotics in chronic [1460 patients] and first-episode patients [1053 patients]. Across different populations, different trials and different antipsychotics - the best-fitting model suggests that symptom response in schizophrenia is underpinned by a single general effect with secondary and minor lower-order effects on specific symptom domains. This single-factor model explained nearly 80% of the variance, was superior to the assumption of unique efficacy for specific domains; and replicated across antipsychotics and illness stages. Despite theoretical and pharmacological claims the differential efficacy of antipsychotics on the various dimensions of schizophrenia is not supported in the prevailing data. The implication of this finding for the measurement of treatment response and our understanding of the neurobiology of antipsychotic action, for clinical practice and for future drug development are discussed.
    Full-text · Article · Apr 2014 · European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology
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    • "The presentation of schizophrenia is indeed diverse – with symptoms ranging from delusions, to disorganization to emotional withdrawal. And from a disease biology perspective these distinct symptoms, subscales and dimensions are increasingly thought to have distinct genetic, neurobiological and neuroanatomical bases (Goghari et al., 2010; Hamshere et al., 2011; Sorg et al., 2013). Not surprisingly then, it has been claimed that a particular receptor profile could impact in a specific symptom dimension (e.g. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The clinical expression of schizophrenia is generally reported to be expressed by three to five different factors (i.e. positive, negative, disorganization, excitability, anxiety-depression symptoms). It is often claimed that antipsychotic medications are particularly helpful for positive symptoms, but not for the others, suggesting a differential efficacy for different aspects of the disorder. We formally tested this claim. Using Structural Equation Modelling in two large [1884 patients] clinical trials in schizophrenia, we compared the model of a common general effect of antipsychotics to models whereby the antipsychotics have multiple and differential effects on the different factors of the illness. We validated the generalizability of the model in further trials involving antipsychotics in chronic [1460 patients] and first-episode patients [1053 patients]. Across different populations, different trials and different antipsychotics – the best-fitting model suggests that symptom response in schizophrenia is underpinned by a single general effect with secondary and minor lower-order effects on specific symptom domains. This single-factor model explained nearly 80% of the variance, was superior to the assumption of unique efficacy for specific domains; and replicated across antipsychotics and illness stages. Despite theoretical and pharmacological claims the differential efficacy of antipsychotics on the various dimensions of schizophrenia is not supported in the prevailing data. The implication of this finding for the measurement of treatment response and our understanding of the neurobiology of antipsychotic action, for clinical practice and for future drug development are discussed.
    Full-text · Article · Jan 2014
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    ABSTRACT: The vast differences observed in clinical fea-tures of schizophrenia are undoubtedly mediated in part by genetic influences. Schizophrenia has been conceptu-alized as either a collection of disorders with overlapping features or a singular diagnostic entity with modifying influences giving rise to the observed range of manifesta-tions. Accordingly, attempts to connect genetic and phe-notypic heterogeneity have predominantly investigated the genetic foundations for clinically defined subgroups or explored the effects of putative risk genes on observed variation in schizophrenia. Some evidence exists to sup-port both perspectives, and they are not mutually exclu-sive. The past few years have witnessed revolutionary advances in the understanding of the genetic risk factors for schizophrenia. Subsequent investigations of genetic and clinical heterogeneity have begun to integrate these findings and make use of the genotyping advances, allowing genome-wide and rare variation to be studied more readily. Recent studies incorporating symptoms, family history, age at onset, severity, sex, cognition, and environmental influences as either subtypes with a genetic basis or features modified by genetic loci are reviewed herein. Keywords Genetic heterogeneity . Age of onset . Pharmacogenomics . Gene–environment interaction . Schizophrenia . Modifier genes Introduction
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