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S28-03 - Pharmacogenetics of Therapy Response in Schizophrenia
- I. Spellmann, D. Rujescu, R. Musil, A. Mayr, I. Giegling, J. Genius, P. Zill, S. Dehning, A.M. Hartmann, B. Bondy, N. Müller, H.-J. Möller, M. Riedel
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- Journal:
- European Psychiatry / Volume 25 / Issue S1 / 2010
- Published online by Cambridge University Press:
- 17 April 2020, 25-E63
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Pharmacogenetics in schizophrenia comprises pharmacokinetical and pharmacodynamical aspects as well as an approach to identify candidate genes associated with therapy response or side effects. Firstly focussing on classical drug targets like dopaminergic or serotonergic receptors, currently also developmental and regulatory genes presumably associated with effects of antipsychotic therapy are identified. The aim of this study was to investigate associations between therapy response in schizophrenic patients and different polymorphisms previously been identified within a genome wide array in rodents treated with MK-801 and/or haloperidol combined with some well-known schizophrenia candidate genes. We genotyped for 200 different polymorphisms in 285 schizophrenic patients, who were treated with different antipsychotics within randomized controlled trials. Psychopathology was measured weekly using the PANSS scale. Correlations between psychopathology and genotypes were calculated by using a linear model (ANCOVA).
We found significant associations between some well-known candidate genes (e.g. D2-, 5HT1A-, and α1A-receptors) and different PANSS subscales at baseline and after four weeks of antipsychotic treatment considered as therapy response. Furthermore we also identified several significant associations between some genes introduced from the animal model and psychopathology at baseline and towards therapy response. Some of them were formerly described in the literature (e.g. Homer1, Phospholipase C and Transthyretin), but most of them have not been related to schizophrenia or antipsychotic treatment by now (e.g. PLEKHA6, CLIC6 and SOSTDC1).
This indicates an involvement of genes in the pathophysiology of schizophrenia apart from yet known candidate genes and might further help in detecting differential therapy response in individuals with schizophrenia.
S28-04 - Pharmacogenetics of Extrapyramidal Motor Side Effects in the Treatment of Schizophrenia
- R. Musil, D. Rujescu, I. Spellmann, A. Mayr, P. Zill, I. Giegling, B. Bondy, N. Müller, H.-J. Möller, M. Riedel
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- Journal:
- European Psychiatry / Volume 25 / Issue S1 / 2010
- Published online by Cambridge University Press:
- 17 April 2020, 25-E64
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Introduction
Since the introduction of second generation antipsychotics (SGA) extrapyramidal-motor symptoms (EPS) have become a lesser problem in the treatment of schizophrenic patients. Yet, some SGAs display these adverse events and first generation antipsychotics are still widely used. Several genetic polymorphisms have been found to be associated with the occurance of EPS.
ObjectivesIn this study we tried to identify genes related to EPS from an animal model and then replicated the findings in schizophrenic patients.
AimsTo identify new genes and show their relevance in the treatment of schizophrenic patients.
MethodsRats were treated with haloperidol or saline and differential gene expression was assessed by using microarrays. We genotyped 285 schizophrenic patients for candidate genes and differentially expressed genes derived from the animal model. All patients were treated monotherapeutically with different antipsychotics within randomized controlled trials. EPS were assessed weekly using the ESRS and BAS. We used a linear model (ANCOVA) with PANSS total at baseline, type of medication and premedication as covariates for all investigated SNP's.
ResultsWe found several SNPs to be associated with the occurance of EPS. The best results were obtained for SNPs within the genes of Phospholipase C epsilon 1 (PLCe1), Methionine Sulfoxide Reductase B3 (MSRB3), Chloride Intracellular Channel 6 (CLIC6), Prolactin Receptor (PRLR) and Dopamine Receptor D4 (DRD4). Effect sizes were between 1.7 and 4.9.
ConclusionsWe could replicate some findings of the literature and identified four new genes possibly related to EPS. Some of these genes were recently related to schizophrenia.
The validity of self-rated psychotic symptoms in depressed inpatients
- F. Seemüller, M. Riedel, M. Obermeier, R. Schennach-Wolff, I. Spellmann, S. Meyer, M. Bauer, M. Adli, K. Kronmüller, M. Ising, P. Brieger, G. Laux, W. Bender, I. Heuser, J. Zeiler, W. Gaebel, H.-J. Möller
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- Journal:
- European Psychiatry / Volume 27 / Issue 7 / October 2012
- Published online by Cambridge University Press:
- 15 April 2020, pp. 547-552
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Background
Self-ratings of psychotic experiences might be biased by depressive symptoms.
MethodData from a large naturalistic multicentre trial on depressed inpatients (n = 488) who were assessed on a biweekly basis until discharge were analyzed. Self-rated psychotic symptoms as assessed with the 90-Item Symptom Checklist (SCL-90) were correlated with the SCL-90 total score, the SCL-90 depression score, the Beck Depression Inventory (BDI), the Hamilton Depression Rating Scale 21 item (HAMD-21) total score, the Montgomery Åsberg Depression Rating Scale (MADRS) total score and the clinician-rated paranoid-hallucinatory score of the Association for Methodology and Documentation in Psychiatry (AMDP) scale.
ResultsAt discharge the SCL-90 psychosis score correlated highest with the SCL-90 depression score (0.78, P<0.001) and with the BDI total score (0.64, P<0.001). Moderate correlations were found for the MADRS (0.34, P<0.001), HAMD (0.37, P<0.001) and AMDP depression score (0.33, P<0.001). Only a weak correlation was found between the SCL-90 psychosis score and the AMDP paranoid-hallucinatory syndrome score (0.15, P<0.001). Linear regression showed that change in self-rated psychotic symptoms over the treatment course was best explained by a change in the SCL-90 depression score (P<0.001). The change in clinician-rated AMDP paranoid-hallucinatory score had lesser influence (P = 0.02).
ConclusionsIn depressed patients self-rated psychotic symptoms correlate poorly with clinician-rated psychotic symptoms. Caution is warranted when interpreting results from epidemiological surveys using self-rated psychotic symptom questionnaires as indicators of psychotic symptoms. Depressive symptoms which are highly prevalent in the general population might influence such self-ratings.
EPA-1415 – Pharmacogenetics of Antipsychotic-induced Weight Gain in Schizophrenic Patients
- R. Musil, I. Spellmann, M. Riedel, S. Rospleszcz, A. Borck, P. Falkai, P. Zill
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- Journal:
- European Psychiatry / Volume 29 / Issue S1 / 2014
- Published online by Cambridge University Press:
- 15 April 2020, p. 1
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Background
Antipsychotic-induced weight gain (AIWG) is a major drawback in the treatment of schizophrenic patients with second-generation antipsychotics (SGAs). Pharmacogenetic studies have established several polymorphisms in genes of different pathways contributing to the development of weight gain in schizophrenic patients. However interactions of genetic polymorphisms and clinical predictors have not been studied extensively enough to reliable predict weight gain before initiating antipsychotic treatment.
MethodsWe analyzed several single-nucleotide polymorphisms (SNPs) of candidate genes (e.g. APOA, GHRL, SNAP-25, LDLR, LPL, INSIG2, Resistin, 5HTR2C, MC4R) and clinical predictors (e.g. age gender, BMI at baseline, number of episodes, pretreatment, PANSS-scores) in a sample of 259 (n=138 for regression analyses) schizophrenic patients participating in different monotherapeutic trials of atypical antipsychotics (risperidone, olanzapine, quetiapine, amisulpride, aripiprazole) with up to six weeks of treatment. We used Univariate tests, regression analysis and Classification and Regression-Tree (CART)-analysis to determine relevant clinical and genetic predictors and their interactions.
ResultsWe found younger age, male gender and weight at baseline as strongest clinical predictors. APOA variants and the Resistin -420 C/G rs1862513 polymorphism were associated with weight gain in the overall patient sample. Heterocygotic GC-allele carriers (n=53) gained less weight (1 kg) compared to 2,2 kg in homocygotic G-allele carriers (n=76) (p<0.0075). We found several interactions of the clinical predictors and genetic variants or type of used SGAs in linear regression models. Use of quetiapine and olanzapine and PANSS total scores showed significant interactions over the time. APOA polymorphisms showed a tendency towards significance in linear regression models (p=0.09). The Resistin -420 C/G rs1862513 polymorphism showed significant interaction in patients treated with risperidone (p<0.0001) and amisulpride (p=0.0006) in a model adjusted for all clinical predictors. CART-analyses support to some extend the relevance of the Resistin polymorphism.
DiscussionIn this sample we found a polymorphism in the Resistin gene (-420 C/G rs1862513) to potentially contribute to AIWG. CART-analysis shows interactions of several clinical predictors and this polymorphism. Our approach of combining clinical and genetic predictors may help to identify subgroups of patients a priori of SGA treatment in order to reduce development of severe weight gain. Further investigations on larger samples are necessary to confirm our results.