Pharmacogenetic predictor of extrapyramidal symptoms induced by antipsychotics: multilocus interaction in the mTOR pathway

Genomic profile of Parkinson's disease in Asians

Parkinson's Disease (PD) has witnessed an alarming rise in prevalence, highlighting the suboptimal nature of early diagnostic and therapeutic strategies. To address this issue, genetic testing has emerged as a potential avenue. In this comprehensive review, we have meticulously summarized the variants associated with PD in Asian populations. Our review reveals that these variants exert their influence on diverse biological pathways, encompassing the autophagy-lysosome pathway, cholesterol metabolism, circadian rhythm regulation, immune system response, and synaptic function. Conventionally, PD has been linked to other diseases; however, our findings shed light on a shared genetic susceptibility among these conditions, implying an underlying pathophysiological mechanism that unifies them. Moreover, it is noteworthy that these PD-associated variants can significantly impact drug responses during therapeutic interventions. This review not only provides a consolidated overview of the genetic variants associated with PD in Asian populations but also contributes novel insights into the intricate relationships between PD and other diseases by elucidating shared genetic components. These findings underscore the importance of personalized approaches in diagnosing and treating PD based on individual genetic profiles to optimize patient outcomes.

Identification of novel proteins associated with movement-related adverse antipsychotic effects by integrating GWAS data and human brain proteomes

Genome-wide association studies (GWAS) have identified some variants for movement-related adverse antipsychotic effects (MAAE), while how these variants confer MAAE remains unclear. We used the probabilistic Mendelian randomization (PMR) method to identify candidate proteins for MAAE by integrating MAAE GWASs and protein quantitative trait loci (pQTL) data. An independent pQTL data from the Banner project and brain-derived eQTL data were used to perform confirmatory PMR. A total of 56 proteins were identified as candidate targets for MAAE after false discovery rates (FDR) correction, such as GRIN2B, ADRA1A, and PED4B. 12 genes were replicated in the confirmatory PMR, and 18 genes had consistent evidence at the transcript level. Furthermore, we investigated the associations between candidate proteins and the motor symptoms of Parkinson's disease (PD). There were 24, 38, and 10 candidate proteins that were significantly associated with PD, PD motor subtypes, and PD motor progression, respectively. Enrichment analysis identified 34 GO terms and 17 pathways that may be involved in MAAE, such as glutamatergic synapse, glutamate receptor complex, and GABAergic synapse. Our study identified multiple candidate genes and pathways that were associated with MAAE, providing new insights into the biological mechanism of MAAE and targets for further mechanistic and therapeutic studies.

Genetic Variations Associated with Long-Term Treatment Response in Bipolar Depression

Several pharmacogenetic-based decision support tools for psychoactive medication selection are available. However, the scientific evidence of the gene-drug pairs analyzed is mainly based on pharmacogenetic studies in patients with major depression or schizophrenia, and their clinical utility is mostly assessed in major depression. This study aimed at evaluating the impact of individual genes, with pharmacogenetic relevance in other psychiatric conditions, in the response to treatment in bipolar depression. Seventy-six patients diagnosed with bipolar disorder and an index major depressive episode were included in an observational retrospective study. Sociodemographic and clinical data were collected, and all patients were genotyped using a commercial multigene pharmacogenomic-based tool (Neuropharmagen^®, AB-Biotics S.A., Barcelona, Spain). Multiple linear regression was used to identify pharmacogenetic and clinical predictors of efficacy and tolerability of medications. The pharmacogenetic variables response to serotonin-norepinephrine reuptake inhibitors (SNRIs) (ABCB1) and reduced metabolism of quetiapine (CYP3A4) predicted patient response to these medications, respectively. ABCB1 was also linked to the tolerability of SNRIs. An mTOR-related multigenic predictor was also associated with a lower number of adverse effects when including switch and autolytical ideation. Our results suggest that the predictors identified could be useful to guide the pharmacological treatment in bipolar disorder. Additional clinical studies are necessary to confirm these findings.

Alteration in the mRNA expression profile of the autophagy-related mTOR pathway in schizophrenia patients treated with olanzapine

BACKGROUND

The mammalian target of rapamycin protein (mTOR) signaling pathway is involved in the pathogenesis of schizophrenia and the mechanism of extrapyramidal adverse reactions to antipsychotic drugs, which might be mediated by an mTOR-dependent autophagy impairment. This study aimed to examine the expression of mTOR pathway genes in patients with schizophrenia treated with olanzapine, which is considered an mTOR inhibitor and autophagy inducer.

METHODS

Thirty-two patients with acute schizophrenia who had been treated with olanzapine for four weeks (average dose 14.24 ± 4.35 mg/d) and 32 healthy volunteers were recruited. Before and after olanzapine treatment, the Positive and Negative Syndrome Scale (PANSS) was used to evaluate the symptoms of patients with schizophrenia, and the mRNA expression levels of mTOR pathway-related genes, including MTOR, RICTOR, RAPTOR, and DEPTOR, were detected in fasting venous blood samples from all subjects using real-time quantitative PCR.

RESULTS

The MTOR and RICTOR mRNA expression levels in patients with acute schizophrenia were significantly decreased compared with those of healthy controls and further significantly decreased after four weeks of olanzapine treatment. The DEPTOR mRNA expression levels in patients with acute schizophrenia were not significantly different from those of healthy controls but were significantly increased after treatment. The expression levels of the RAPTOR mRNA were not significantly different among the three groups. The pairwise correlations of MTOR, DEPTOR, RAPTOR, and RICTOR mRNA expression levels in patients with acute schizophrenia and healthy controls were significant. After olanzapine treatment, the correlations between the expression levels of the DEPTOR and MTOR mRNAs and between the DEPTOR and RICTOR mRNAs disappeared.

CONCLUSIONS

Abnormalities in the mTOR pathway, especially DEPTOR and mTORC2, might play important roles in the autophagy mechanism underlying the pathophysiology of schizophrenia and effects of olanzapine treatment.

Pharmacogenetics of antipsychotics: Clinical utility and implementation

Decades of research have produced extensive evidence of the contribution of genetic factors to the efficacy and toxicity of antipsychotics. Numerous genetic variants in genes controlling drug availability or involved in antipsychotic processes have been linked to treatment variability. The complex mechanism of action and multitarget profile of most antipsychotic drugs hinder the identification of pharmacogenetic markers of clinical value. Nevertheless, the validity of associations between variants in CYP1A2, CYP2D6, CYP2C19, ABCB1, DRD2, DRD3, HTR2A, HTR2C, BDNF, COMT, MC4R genes and antipsychotic response has been confirmed in independent candidate gene studies. Genome wide pharmacogenomic studies have proven the role of the glutamatergic pathway in mediating antipsychotic activity and have reported novel associations with antipsychotic response. However, only a limited number of the findings, mainly functional variants of CYP metabolic enzymes, have been shown to be of clinical utility and translated into useful pharmacogenetic markers. Based on the currently available information, actionable pharmacogenetics should be reduced to antipsychotics' dose adjustment according to the genetically predicted metabolic status (CYPs' profile) of the patient. Growing evidence suggests that such interventions will reduce antipsychotics' side-effects and increase treatment safety. Despite this evidence, the use of pharmacogenetics in psychiatric wards is minimal. Hopefully, further evidence on the clinical and economic benefits, the development of clinical protocols based on pharmacogenetic information, and improved and cheaper genetic testing will increase the implementation of pharmacogenetic guided prescription in clinical settings.

Identifying key transcription factors for pharmacogenetic studies of antipsychotics induced extrapyramidal symptoms

INTRODUCTION

We explore the transcription factors involved in the molecular mechanism of antipsychotic (AP)-induced acute extrapyramidalsymptoms (EPS) in order to identify new candidate genes for pharmacogenetic studies.

METHODS

Protein-protein interaction (PPI) networks previously created from three pharmacogenomic models (in vitro, animal, and peripheral blood inhumans) were used to, by means of several bioinformatic tools; identify key transcription factors (TFs) that regulate each network. Once the TFs wereidentified, SNPs disrupting the binding sites (TFBS) of these TFs in the genes of each network were selected for genotyping. Finally, SNP-basedassociations with EPS were analyzed in a sample of 356 psychiatric patients receiving AP.

RESULTS

Our analysis identified 33 TFs expressed in the striatum, and 125 SNPs disrupting TFBS in 50 genes of our initial networks. Two SNPs (rs938112,rs2987902) in two genes (LSMAP and ABL1) were significantly associated with AP induced EPS (p < 0.001). These SNPs disrupt TFBS regulated byPOU2F1.

CONCLUSION

Our results highlight the possible role of the disruption of TFBS by SNPs in the pharmacological response to AP.

Pharmacogenomics of Cognitive Dysfunction and Neuropsychiatric Disorders in Dementia

Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6-10 drugs/day with the consequent risk for drug-drug interactions and adverse drug reactions (ADRs >80%) which accelerate cognitive decline. The pharmacoepigenetic machinery is integrated by pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes redundantly and promiscuously regulated by epigenetic mechanisms. CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 geno-phenotypes are involved in the metabolism of over 90% of drugs currently used in patients with dementia, and only 20% of the population is an extensive metabolizer for this tetragenic cluster. ADRs associated with anti-dementia drugs, antipsychotics, antidepressants, anxiolytics, hypnotics, sedatives, and antiepileptic drugs can be minimized by means of pharmacogenetic screening prior to treatment. These drugs are substrates, inhibitors, or inducers of 58, 37, and 42 enzyme/protein gene products, respectively, and are transported by 40 different protein transporters. APOE is the reference gene in most pharmacogenetic studies. APOE-3 carriers are the best responders and APOE-4 carriers are the worst responders; likewise, CYP2D6-normal metabolizers are the best responders and CYP2D6-poor metabolizers are the worst responders. The incorporation of pharmacogenomic strategies for a personalized treatment in dementia is an effective option to optimize limited therapeutic resources and to reduce unwanted side-effects.

Challenges and Future Prospects of Precision Medicine in Psychiatry

Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.

Pharmacogenetics of Antipsychotic Drug Treatment: Update and Clinical Implications

Numerous genetic variants have been shown to be associated with antipsychotic response and adverse effects of schizophrenia treatment. However, the clinical application of these findings is limited. The aim of this narrative review is to summarize the most recent publications and recommendations related to the genetics of antipsychotic treatment and shed light on the clinical utility of pharmacogenetics/pharmacogenomics (PGx). We reviewed the literature on PGx studies with antipsychotic drugs (i.e., antipsychotic response and adverse effects) and commonly used commercial PGx tools for clinical practice. Publications and reviews were included with emphasis on articles published between January 2015 and April 2018. We found 44 studies focusing on antipsychotic response and 45 studies on adverse effects (e.g., antipsychotic-induced weight gain, movement disorders, hormonal abnormality, and clozapine-induced agranulocytosis/granulocytopenia), albeit with mixed results. Overall, several gene variants related to antipsychotic response and adverse effects in the treatment of patients with schizophrenia have been reported, and several commercial pharmacogenomic tests have become available. However, further well-designed investigations and replication studies in large and well-characterized samples are needed to facilitate the application of PGx findings to clinical practice.

Effectiveness of a Pharmacogenetic Tool at Improving Treatment Efficacy in Major Depressive Disorder: A Meta-Analysis of Three Clinical Studies

Several pharmacogenetic tests to support drug selection in psychiatric patients have recently become available. The current meta-analysis aimed to assess the clinical utility of a commercial pharmacogenetic-based tool for psychiatry (Neuropharmagen^®) in the treatment management of depressive patients. Random-effects meta-analysis of clinical studies that had examined the effect of this tool on the improvement of depressive patients was performed. Effects were summarized as standardized differences between treatment groups. A total of 450 eligible subjects from three clinical studies were examined. The random effects model estimated a statistically significant effect size for the pharmacogenetic-guided prescription (d = 0.34, 95% CI = 0.11-0.56, p-value = 0.004), which corresponded to approximately a 1.8-fold increase in the odds of clinical response for pharmacogenetic-guided vs. unguided drug selection. After exclusion of patients with mild depression, the pooled estimated effect size increased to 0.42 (95% CI = 0.19-0.65, p-value = 0.004, n = 287), corresponding to an OR = 2.14 (95% CI = 1.40-3.27). These results support the clinical utility of this pharmacogenetic-based tool in the improvement of health outcomes in patients with depression, especially those with moderate-severe depression. Additional pragmatic RCTs are warranted to consolidate these findings in other patient populations.

Polymorphisms in Dopaminergic Genes in Schizophrenia and Their Implications in Motor Deficits and Antipsychotic Treatment

Dopaminergic system dysfunction is involved in schizophrenia (SCZ) pathogenesis and can mediate SCZ-related motor disorders. Recent studies have gradually revealed that SCZ susceptibility and the associated motor symptoms can be mediated by genetic factors, including dopaminergic genes. More importantly, polymorphisms in these genes are associated with both antipsychotic drug sensitivity and adverse effects. The study of genetic polymorphisms in the dopaminergic system may help to optimize individualized drug strategies for SCZ patients. This review summarizes the current progress about the involvement of the dopamine system in SCZ-associated motor disorders and the motor-related adverse effects after antipsychotic treatment, with a special focus on polymorphisms in dopaminergic genes. We hypothesize that the genetic profile of the dopaminergic system mediates both SCZ-associated motor deficits associated and antipsychotic drug-related adverse effects. The study of dopaminergic gene polymorphisms may help to predict drug efficacy and decrease adverse effects, thereby optimizing treatment strategies.

Improving pharmacogenetic prediction of extrapyramidal symptoms induced by antipsychotics

In previous work we developed a pharmacogenetic predictor of antipsychotic (AP) induced extrapyramidal symptoms (EPS) based on four genes involved in mTOR regulation. The main objective is to improve this predictor by increasing its biological plausibility and replication. We re-sequence the four genes using next-generation sequencing. We predict functionality "in silico" of all identified SNPs and test it using gene reporter assays. Using functional SNPs, we develop a new predictor utilizing machine learning algorithms (Discovery Cohort, N = 131) and replicate it in two independent cohorts (Replication Cohort 1, N = 113; Replication Cohort 2, N = 113). After prioritization, four SNPs were used to develop the pharmacogenetic predictor of AP-induced EPS. The model constructed using the Naive Bayes algorithm achieved a 66% of accuracy in the Discovery Cohort, and similar performances in the replication cohorts. The result is an improved pharmacogenetic predictor of AP-induced EPS, which is more robust and generalizable than the original.

MTOR Pathway-Based Discovery of Genetic Susceptibility to L-DOPA-Induced Dyskinesia in Parkinson's Disease Patients

Dyskinesia induced by L-DOPA administration (LID) is one of the most invalidating adverse effects of the gold standard treatment restoring dopamine transmission in Parkinson's disease (PD). However, LID manifestation in parkinsonian patients is variable and heterogeneous. Here, we performed a candidate genetic pathway analysis of the mTOR signaling cascade to elucidate a potential genetic contribution to LID susceptibility, since mTOR inhibition ameliorates LID in PD animal models. We screened 64 single nucleotide polymorphisms (SNPs) mapping to 57 genes of the mTOR pathway in a retrospective cohort of 401 PD cases treated with L-DOPA (70 PD with moderate/severe LID and 331 with no/mild LID). We performed classic allelic, genotypic, and epistatic analyses to evaluate the association of individual or combinations of SNPs with LID onset and with LID severity after initiation of L-DOPA treatment. As for the time to LID onset, we found significant associations with SNP rs1043098 in the EIF4EBP2 gene and also with an epistatic interaction involving EIF4EBP2 rs1043098, RICTOR rs2043112, and PRKCA rs4790904. For LID severity, we found significant association with HRAS rs12628 and PRKN rs1801582 and also with a four-loci epistatic combination involving RPS6KB1 rs1292034, HRAS rs12628, RPS6KA2 rs6456121, and FCHSD1 rs456998. These findings indicate that the mTOR pathway contributes genetically to LID susceptibility. Our study could help to identify the most susceptible PD patients to L-DOPA in order to prevent the appearance of early and/or severe LID in a future. This information could also be used to stratify PD patients in clinical trials in a more accurate way.

Recent Progress in Pharmacogenomics of Antipsychotic Drug Response

PURPOSE OF REVIEW

Pharmacogenomics (PGx) of antipsychotic drug response is an active area of research in the past few years. We reviewed recent PGx studies with an emphasis of development of new methodologies and new research directions.

RECENT FINDINGS

Traditional candidate gene approach continues to generate evidence to support the associations of antipsychotic response with genes coding for drug targets such as DRD2. Genome-wide association studies have found a few novel genes that may be associated with drug efficacy and adverse events. Recent application of polygenic risk score makes it possible to combine many genetic variants to predict clinical response. Finally, epigenetic research including DNA methylation is emerging and promises new findings that potentially can be applied in clinical practice. New methodologies may advance PGx closer to clinical application. Multiple genes and epigenomic markers can be used in prediction of clinical phenotypes.

Extrapyramidal Symptoms Probably Related to Risperidone Treatment: A Case Series

BACKGROUND

Atypical antipsychotics, like risperidone purportedly, score over their typical counterparts in terms of their lower propensity toward producing extrapyramidal symptoms (EPS). However, recent studies have furnished evidence to the contrary. Hereby, we present a case series implicating risperidone as the causative agent for EPS.

METHODS

As a part of the pharmacovigilance programme of India, the authors have assessed 10 physician-reported cases of EPS among the 1,830 patients who were prescribed risperidone within the time period of January 2012-December 2014 in a tertiary care hospital in South India. Causality, severity, and preventability assessments of adverse reaction were done as per Naranjo's, Hartwig's, and Thornton'scale respectively.

RESULTS

Of the 10 cases, a dose-dependent occurrence of EPS was noted in all and the time duration for development of EPS ranged from 1 week to 2 years. Four patients developed EPS at a dose of 6-8 mg, 4 developed at a dose of 4-6 mg, and the remaining 2 developed at 2 and 1 mg.

CONCLUSION

A strong temporal correlation between risperidone and EPS was noted in all cases. High doses produced EPS early, whereas moderate to low doses produced EPS at a later date. Thus, cautious use and close monitoring are warranted in the chronic use of risperidone.

Efficacy of prospective pharmacogenetic testing in the treatment of major depressive disorder: results of a randomized, double-blind clinical trial

BACKGROUND

A 12-week, double-blind, parallel, multi-center randomized controlled trial in 316 adult patients with major depressive disorder (MDD) was conducted to evaluate the effectiveness of pharmacogenetic (PGx) testing for drug therapy guidance.

METHODS

Patients with a CGI-S ≥ 4 and requiring antidepressant medication de novo or changes in their medication regime were recruited at 18 Spanish public hospitals, genotyped with a commercial PGx panel (Neuropharmagen®), and randomized to PGx-guided treatment (n = 155) or treatment as usual (TAU, control group, n = 161), using a computer-generated random list that locked or unlocked psychiatrist access to the results of the PGx panel depending on group allocation. The primary endpoint was the proportion of patients achieving a sustained response (Patient Global Impression of Improvement, PGI-I ≤ 2) within the 12-week follow-up. Patients and interviewers collecting the PGI-I ratings were blinded to group allocation. Between-group differences were evaluated using χ2-test or t-test, as per data type.

RESULTS

Two hundred eighty patients were available for analysis at the end of the 12-week follow-up (PGx n = 136, TAU n = 144). A difference in sustained response within the study period (primary outcome) was not observed (38.5% vs 34.4%, p = 0.4735; OR = 1.19 [95%CI 0.74-1.92]), but the PGx-guided treatment group had a higher responder rate compared to TAU at 12 weeks (47.8% vs 36.1%, p = 0.0476; OR = 1.62 [95%CI 1.00-2.61]), and this difference increased after removing subjects in the PGx-guided group when clinicians explicitly reported not to follow the test recommendations (51.3% vs 36.1%, p = 0.0135; OR = 1.86 [95%CI 1.13-3.05]). Effects were more consistent in patients with 1-3 failed drug trials. In subjects reporting side effects burden at baseline, odds of achieving a better tolerability (Frequency, Intensity and Burden of Side Effects Rating Burden subscore ≤2) were higher in the PGx-guided group than in controls at 6 weeks and maintained at 12 weeks (68.5% vs 51.4%, p = 0.0260; OR = 2.06 [95%CI 1.09-3.89]).

CONCLUSIONS

PGx-guided treatment resulted in significant improvement of MDD patient's response at 12 weeks, dependent on the number of previously failed medication trials, but not on sustained response during the study period. Burden of side effects was also significantly reduced.

TRIAL REGISTRATION

European Clinical Trials Database 2013-002228-18 , registration date September 16, 2013; ClinicalTrials.gov NCT02529462 , retrospectively registered: August 19, 2015.

Core Concepts Involving Adverse Psychotropic Drug Effects: Assessment, Implications, and Management

Adverse effects from psychiatric drugs can profoundly influence treatment adherence and outcomes. Good care involves addressing adverse effects no differently than any other component of treatment. Knowledge about adverse effect assessment and management fosters a proper context that helps clinicians not sacrifice a drug's potential therapeutic benefits because of greater concerns about its tolerability. This article provides an overview of basic concepts related to the assessment and management of suspected adverse effects from psychotropic drugs. Key points are discussed regarding clinical, pharmacogenetic, pharmacokinetic, and pharmacodynamic risk factors for treatment-emergent adverse effects, alongside recommendations for their systematic assessment.

New challenges and promises in solid organ transplantation pharmacogenetics: the genetic variability of proteins involved in the pharmacodynamics of immunosuppressive drugs

Interindividual variability in immunosuppressive drug responses might be partly explained by genetic variants in proteins involved in the immune response or associated with IS pharmacodynamics. On a general basis, the pharmacogenetics of drug target proteins is less known and understood than that of proteins involved in drug disposition pathways. The aim of this review is to facilitate research related to the pharmacodynamics of the main immunosuppressive drugs used in solid organ transplantation. We elaborated a quality of evidence grading system based on a literature review and identified 'highly recommended', 'recommended' or 'potential' candidates for further research. It is likely that a number of additional rare variants might further explain drug response phenotypes in transplantation, and particularly the most severe ones. The advent of next-generation sequencing will help to identify those variants.

Applicability of gene expression and systems biology to develop pharmacogenetic predictors; antipsychotic-induced extrapyramidal symptoms as an example

Pharmacogenetics has been driven by a candidate gene approach. The disadvantage of this approach is that is limited by our current understanding of the mechanisms by which drugs act. Gene expression could help to elucidate the molecular signatures of antipsychotic treatments searching for dysregulated molecular pathways and the relationships between gene products, especially protein-protein interactions. To embrace the complexity of drug response, machine learning methods could help to identify gene-gene interactions and develop pharmacogenetic predictors of drug response. The present review summarizes the applicability of the topics presented here (gene expression, network analysis and gene-gene interactions) in pharmacogenetics. In order to achieve this, we present an example of identifying genetic predictors of extrapyramidal symptoms induced by antipsychotic.

Network analysis of gene expression in mice provides new evidence of involvement of the mTOR pathway in antipsychotic-induced extrapyramidal symptoms

To identify potential candidate genes for future pharmacogenetic studies of antipsychotic (AP)-induced extrapyramidal symptoms (EPS), we used gene expression arrays to analyze changes induced by risperidone in mice strains with different susceptibility to EPS. We proposed a systems biology analytical approach that combined the identification of gene co-expression modules related to AP treatment, the construction of protein-protein interaction networks with genes included in identified modules and finally, gene set enrichment analysis of constructed networks. In response to risperidone, mice strain with susceptibility to develop EPS showed downregulation of genes involved in the mammalian target of rapamycin (mTOR) pathway and biological processes related to this pathway. Moreover, we also showed differences in the phosphorylation pattern of the ribosomal protein S6 (rpS6), which is a major downstream effector of mTOR. The present study provides new evidence of the involvement of the mTOR pathway in AP-induced EPS and offers new and valuable markers for pharmacogenetic studies.

Network analysis of gene expression in peripheral blood identifies mTOR and NF-κB pathways involved in antipsychotic-induced extrapyramidal symptoms

To identify the candidate genes for pharmacogenetic studies of antipsychotic (AP)-induced extrapyramidal symptoms (EPS), we propose a systems biology analytical approach, based on protein-protein interaction network construction and functional annotation analysis, of changes in gene expression (Human Genome U219 Array Plate) induced by treatment with risperidone or paliperidone in peripheral blood. 12 AP-naïve patients with first-episode psychosis participated in the present study. Our analysis revealed that, in response to AP treatment, constructed networks were enriched for different biological processes in patients without EPS (ubiquitination, protein folding and adenosine triphosphate (ATP) metabolism) compared with those presenting EPS (insulin receptor signaling, lipid modification, regulation of autophagy and immune response). Moreover, the observed differences also involved specific pathways, such as anaphase promoting complex /cdc20, prefoldin/CCT/triC and ATP synthesis in no-EPS patients, and mammalian target of rapamycin and NF-κB kinases in patients with EPS. Our results showing different patterns of gene expression in EPS patients, offer new and valuable markers for pharmacogenetic studies.