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Imaging genomics and response to treatment with antipsychotics in schizophrenia.

ABSTRACT: Recent important advancements in genomic research have opened the way to new strategies for public health management. One of these questions pertains to how individual genetic variation may be associated with individual variability in response to drug treatment. The field of pharmacogenetics may have a profound impact on treatment of complex psychiatric disorders like schizophrenia. However, pharmacogenetic studies in schizophrenia have produced conflicting results. The first studies examined potential associations between clinical response and drug receptor genes. Subsequent studies have tried to use more objective phenotypes still in association with drug receptor genes. More recently, other studies have sought the association between putative causative or modifier genes and intermediate phenotypes. Thus, conflicting results may be at least in part explained by variability and choice of the phenotype, by choice of candidate genes, or by the relatively little knowledge about the neurobiology of this disorder. We propose that choosing intermediate phenotypes that allow in vivo measurement of specific neuronal functions may be of great help in reducing several of the potential confounds intrinsic to clinical measurements. Functional neuroimaging is ideally suited to address several of these potential confounds, and it may represent a powerful strategy to investigate the relationship between behavior, brain function, genes, and individual variability in the response to treatment with antipsychotic drugs in schizophrenia. Preliminary evidence with potential susceptilibity genes such as COMT, DISC1, and GRM3 support these assumptions.

SUBMITTER: Blasi G

PROVIDER: S-EPMC3593360 | biostudies-other | 2006 Jan

REPOSITORIES: biostudies-other

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Imaging genomics and response to treatment with antipsychotics in schizophrenia.

Blasi Giuseppe G Bertolino Alessandro A

NeuroRx : the journal of the American Society for Experimental NeuroTherapeutics 20060101 1

Recent important advancements in genomic research have opened the way to new strategies for public health management. One of these questions pertains to how individual genetic variation may be associated with individual variability in response to drug treatment. The field of pharmacogenetics may have a profound impact on treatment of complex psychiatric disorders like schizophrenia. However, pharmacogenetic studies in schizophrenia have produced conflicting results. The first studies examined po ...[more]

PMID: 16490418

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Project description:BackgroundIt remains a challenge to predict the long-term response to antipsychotics in patients with schizophrenia who do not respond at an early stage. This study aimed to investigate the optimal predictive cut-off value for early non-response that would better predict later non-response to antipsychotics in patients with schizophrenia.MethodsThis multicenter, 8-week, open-label, randomized trial was conducted at 19 psychiatric centers throughout China. All enrolled participants were assigned to olanzapine, risperidone, amisulpride, or aripiprazole monotherapy for 8 weeks. The positive and negative syndrome scale (PANSS) was evaluated at baseline, week 2, week 4, and week 8. The main outcome was the prediction of nonresponse. Nonresponse is defined as a < 20% reduction in the total scores of PANSS from baseline to endpoint. Severity ratings of mild, moderate, and severe illness corresponded to baseline PANSS total scores of 58, 75, and 95, respectively.ResultsAt week 2, a reduction of < 5% in the PANSS total score showed the highest total accuracy in the severe and mild schizophrenia patients (total accuracy, 75.0% and 80.8%, respectively), and patients who were treated with the risperidone and amisulpride groups (total accuracy, 82.4%, and 78.2%, respectively). A 10% decrease exhibited the best overall accuracy in the moderate schizophrenia patients (total accuracy, 84.0%), olanzapine (total accuracy, 79.2%), and aripiprazole group (total accuracy, 77.4%). At week 4, the best predictive cut-off value was < 20%, regardless of the antipsychotic or severity of illness (total accuracy ranging from 89.8 to 92.1%).ConclusionsSymptom reduction at week 2 has acceptable discrimination in predicting later non-response to antipsychotics in schizophrenia, and a more accurate predictive cut-off value should be determined according to the medication regimen and baseline illness severity. The response to treatment during the next 2 weeks after week 2 could be further assessed to determine whether there is a need to change antipsychotic medication during the first four weeks.Trial registrationThis study was registered on Clinicaltrials.gov (NCT03451734).

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Imaging genomics and response to treatment with antipsychotics in schizophrenia.

Publications

Imaging genomics and response to treatment with antipsychotics in schizophrenia.

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