Pharmacogenetics and schizophrenia

[Pharmacogenetic-based risk assessment of antipsychotic-induced extrapyramidal symptoms]

"Typical" antipsychotics remain the wide-prescribed drugs in modern psychiatry. But these drugs are associated with development of extrapyramidal symptoms (EPS). Preventive methods of EPS are actively developed and they concentrate on personalized approach. The method of taking into account genetic characteristics of patient for prescribing of treatment was proven as effective in cardiology, oncology, HIV-medicine. In this review the modern state of pharmacogenetic research of antipsychotic-induced EPS are considered. There are pharmacokinetic and pharmacodynamic factors which impact on adverse effects. Pharmacokinetic factors are the most well-studied to date, these include genetic polymorphisms of genes of cytochrome P450. However, evidence base while does not allow to do the significant prognosis of development of EPS based on genetic testing of CYP2D6 and CYP7A2 polymorphisms. Genes of pharmacodynamics factors, which realize the EPS during antipsychotic treatment, are the wide field for research. In separate part of review research of such systems as dopaminergic, serotonergic, adrenergic, glutamatergic, GABAergic, BDNF were analyzed. The role of oxidative stress factors in the pathogenesis of antipsychotic-induced EPS was enough detailed considered. The system of those factors may be used for personalized risk assessment of antipsychotics' safety in the future. Although there were numerous studies, the pharmacogenetic-based prevention of EPS before prescribing of antipsychotics was not introduced. However, it is possible to distinguish the most perspectives markers for further research. Furthermore, brief review of new candidate genes provides here, but only preliminary results were published. The main problem of the field is the lack of high- quality studies. Moreover, the several results were not replicated in repeat studies. The pharmacogenetic-based research must be standardized by ethnicity of patients. But there is the ethnical misbalance in world literature. These facts explain why the introduction of pharmacogenetic testing for risk assessment of antipsychotic-induced EPS is so difficult to achieve.

Tying comparative effectiveness information to decision-making and the future of comparative effectiveness research designs: the case for antipsychotic drugs

The outcome of comparative effectiveness research on antipsychotic drugs, specifically the National Institute of Mental Health-funded CATIE trial, has raised questions regarding the value of second-generation antipsychotic drugs and has sparked a debate regarding their accessibility through public insurance. We reviewed the evidence on the impact of access restrictions for antipsychotic drugs in Medicaid programs and found that such restrictions resulted in increases in overall costs and a possible decline in the quality of care. We attribute this unwanted outcome to limitations in comparative effectiveness research designs that fail to inform either clinical or policy decision-making. We enumerate these limitations and illustrate the potential for more innovative comparative effectiveness research designs that may be in line with clinical decision-making using an original analysis of the CATIE trial data. The value of genomic information in enabling better trial design is also discussed.

Personalized Medicine in the Context of Comparative Effectiveness Research

The world of patient-centered outcomes research (PCOR) seems to bridge the previously disjointed worlds of comparative effectiveness research (CER) and personalized medicine (PM). Indeed, theoretical reasoning on how information on medical quality should inform decision making, both at the individual and the policy level, reveals that personalized information on the value of medical products is critical for improving decision making at all levels. However, challenges to generating, evaluating and translating evidence that might lead to personalization need to be critically assessed. In this paper, I discuss two different concepts of personalized medicine - passive personalization (PPM) and active personalization (APM) that are important to distinguish in order to invest efficiently in PCOR and develop objective evidence on the value of personalization that will aid in its translation. APM constitutes the process of actively seeking identifiers, which can be genotypical, phenotypical or even environmental, that can be used to differentiate between the marginal benefits of treatment across patients. In contrast, PPM involves a passive approach to personalization where, in the absence of explicit research to discover identifiers, patients and physicians "learn by doing" mostly due to the repeated use of similar products on similar patients. Benchmarking the current state of PPM sets the bar to which the expected value of any new APM agenda should be evaluated. Exploring processes that enable PPM in practice can help discover new APM agendas, such as those based on developing predictive algorithms based on clinical, phenotypical and preference data, which may be more efficient that trying to develop expensive genetic tests. It can also identify scenarios or subgroups of patients where genomic research would be most valuable since alternative prediction algorithms were difficult to develop in those settings. Two clinical scenarios are discussed where PPM was explored through novel econometric methods. Related discussions around exploring PPM processes, multi-dimensionality of outcomes, and a balanced agenda for future research on personalization follow.

Personalized medicine in psychiatry: problems and promises

The central theme of personalized medicine is the premise that an individual's unique physiologic characteristics play a significant role in both disease vulnerability and in response to specific therapies. The major goals of personalized medicine are therefore to predict an individual's susceptibility to developing an illness, achieve accurate diagnosis, and optimize the most efficient and favorable response to treatment. The goal of achieving personalized medicine in psychiatry is a laudable one, because its attainment should be associated with a marked reduction in morbidity and mortality. In this review, we summarize an illustrative selection of studies that are laying the foundation towards personalizing medicine in major depressive disorder, bipolar disorder, and schizophrenia. In addition, we present emerging applications that are likely to advance personalized medicine in psychiatry, with an emphasis on novel biomarkers and neuroimaging.

Outcome definitions and clinical predictors influence pharmacogenetic associations between HTR3A gene polymorphisms and response to clozapine in patients with schizophrenia

RATIONALE

Pharmacogenetics of schizophrenia has not yet delivered anticipated clinical dividends. Clinical heterogeneity of schizophrenia contributes to the poor replication of the findings of pharmacogenetic association studies. Functionally important HTR3A gene single-nucleotide polymorphisms (SNPs) were reported to be associated with response to clozapine.

OBJECTIVE

The aim of this study was to investigate how the association between HTR3A gene SNP and response to clozapine is influenced by various clinical predictors and by differing outcome definitions in patients with treatment-resistant schizophrenia (TRS).

METHODS

We recruited 101 consecutive patients with TRS, on stable doses of clozapine, and evaluated their HTR3A gene SNP (rs1062613 and rs2276302), psychopathology, and serum clozapine levels. We assessed their socio-demographic and clinical profiles, premorbid adjustment, traumatic events, cognition, and disability using standard assessment schedules. We evaluated their response to clozapine, by employing six differing outcome definitions. We employed appropriate multivariate statistics to calculate allelic and genotypic association, accounting for the effects of various clinical variables.

RESULTS

T allele of rs1062613 and G allele of rs2276302 were significantly associated with good clinical response to clozapine (p = 0.02). However, varying outcome definitions make these associations inconsistent. rs1062613 and rs2276302 could explain only 13.8 % variability in the responses to clozapine, while combined clinical predictors and HTR3A pharmacogenetic association model could explain 38 % variability.

CONCLUSIONS

We demonstrated that the results of pharmacogenetic studies in schizophrenia depend heavily on their outcome definitions and that combined clinical and pharmacogenetic models have better predictive values. Future pharmacogenetic studies should employ multiple outcome definitions and should evaluate associated clinical variables.

Genomics and pharmacogenomics of schizophrenia

Schizophrenia (SCZ) is among the most disabling of mental disorders. Several neurobiological hypotheses have been postulated as responsible for SCZ pathogenesis: polygenic/multifactorial genomic defects, intrauterine and perinatal environment-genome interactions, neurodevelopmental defects, dopaminergic, cholinergic, serotonergic, gamma-aminobutiric acid (GABAergic), neuropeptidergic and glutamatergic/N-Methyl-D-Aspartate (NMDA) dysfunctions, seasonal infection, neuroimmune dysfunction, and epigenetic dysregulation. SCZ has a heritability estimated at 60-90%. Genetic studies in SCZ have revealed the presence of chromosome anomalies, copy number variants, multiple single-nucleotide polymorphisms of susceptibility distributed across the human genome, aberrant single nucleotide polymorphisms (SNPs) in microRNA genes, mitochondrial DNA mutations, and epigenetic phenomena. Pharmacogenetic studies of psychotropic drug response have focused on determining the relationship between variation in specific candidate genes and the positive and adverse effects of drug treatment. Approximately, 18% of neuroleptics are major substrates of CYP1A2 enzymes, 40% of CYP2D6, and 23% of CYP3A4; 24% of antidepressants are major substrates of CYP1A2 enzymes, 5% of CYP2B6, 38% of CYP2C19, 85% of CYP2D6, and 38% of CYP3A4; 7% of benzodiazepines are major substrates of CYP2C19 enzymes, 20% of CYP2D6, and 95% of CYP3A4. About 10-20% of Western populations are defective in genes of the CYP superfamily. Only 26% of Southern Europeans are pure extensive metabolizers for the trigenic cluster integrated by the CYP2D6+CYP2C19+CYP2C9 genes. The pharmacogenomic response of SCZ patients to conventional psychotropic drugs also depends on genetic variants associated with SCZ-related genes. Consequently, the incorporation of pharmacogenomic procedures both to drugs in development and drugs on the market would help to optimize therapeutics in SCZ and other central nervous system (CNS) disorders.

Pharmacogenomics of antipsychotics efficacy for schizophrenia

Central nervous system disorders are the third greatest health problem in developed countries, and schizophrenia represents some of the most disabling ailments in young individuals. There is an abuse and/or misuse of antipsychotics, and recent advances in pharmacogenomics pose new challenges for the clinical management of this complex disorder. Schizophrenia is a multi-factorial/polygenic complex disorder in which hundreds of different genes are potentially involved, leading to the phenotypic expression of the disease in conjunction with epigenetic and environmental phenomena. Consequently, structural and functional genomic changes induce proteomic and metabolomic defects associated with the disease phenotype. Disease-related genomic profiles and genetic variants in genes involved in drug metabolism are responsible for drug efficacy and safety. About 20% of Caucasians are defective in CYP2D6 enzymes, which participate in the metabolism of 25-30% of central nervous system drugs. Approximately 40% of antipsychotics are substrates of CYP2D6 enzymes, 23% are substrates of CYP3A4, and 18% are substrates of CYP1A2. In order to achieve a mature discipline of pharmacogenomics of schizophrenia it would be effective to accelerate: (i) the education of physicians and the public in the use of genomic screening in daily clinical practice; (ii) the standardization of genetic testing for major categories of drugs; (iii) the validation of pharmacogenomic procedures according to drug category and pathology; (iv) the regulation of ethical, social, and economic issues; and (v) the incorporation of pharmacogenomic procedures of drugs in development and drugs on the market in order to optimize therapeutics.

Future Trends in the Pharmacogenomics of Brain Disorders and Dementia: Influence of APOE and CYP2D6 Variants

About 80% of functional genes in the human genome are expressed in the brain and over 1,200 different genes have been associated with the pathogenesis of CNS disorders and dementia. Pharmacogenetic studies of psychotropic drug response have focused on determining the relationship between variations in specific candidate genes and the positive and adverse effects of drug treatment. Approximately, 18% of neuroleptics are substrates of CYP1A2 enzymes, 40% of CYP2D6, and 23% of CYP3A4; 24% of antidepressants are substrates of CYP1A2 enzymes, 5% of CYP2B6, 38% of CYP2C19, 85% of CYP2D6, and 38% of CYP3A4; 7% of benzodiazepines are substrates of CYP2C19 enzymes, 20% of CYP2D6, and 95% of CYP3A4. 10-20% of Western populations are defective in genes of the CYP superfamily; and the pharmacogenomic response of psychotropic drugs also depends on genetic variants associated with dementia. Prospective studies with anti-dementia drugs or with multifactorial strategies have revealed that the therapeutic response to conventional drugs in Alzheimer’s disease is genotype-specific. The disease-modifying effects (cognitive performance, biomarker modification) of therapeutic intervention are APOE-dependent, with APOE-4 carriers acting as the worst responders (APOE-3/3 > APOE-3/4 > APOE-4/4). APOE-CYP2D6 interactions also influence the therapeutic outcome in patients with dementia.

Pharmacogenomic Biomarkers in Neuropsychiatry: The Path to Personalized Medicine in Mental Disorders

Neuropsychiatric disorders and dementia represent a major cause of disability and high cost in developed societies. Most disorders of the central nervous system (CNS) share some common features, such as a genomic background in which hundreds of genes might be involved, genome-environment interactions, complex pathogenic pathways, poor therapeutic outcomes, and chronic disability.

Recent advances in genomic medicine can contribute to accelerate our understanding on the pathogenesis of CNS disorders, improve diagnostic accuracy with the introduction of novel biomarkers, and personalize therapeutics with the incorporation of pharmacogenetic and pharmacogenomic procedures to drug development and clinical practice.

The pharmacological treatment of CNS disorders, in general, accounts for 10–20% of direct costs, and less than 30–40% of the patients are moderate responders to conventional drugs, some of which may cause important adverse drugs reactions (ADRs). Pharmacogenetic and pharmacogenomic factors may account for 60–90% of drug variability in drug disposition and pharmacodynamics. Approximately 60–80% of CNS drugs are metabolized via enzymes of the CYP gene superfamily; 18% of neuroleptics are major substrates of CYP1A2 enzymes, 40% of CYP2D6, and 23% of CYP3A4; 24% of antidepressants are major substrates of CYP1A2 enzymes, 5% of CYP2B6, 38% of CYP2C19, 85% of CYP2D6, and 38% of CYP3A4; 7% of benzodiazepines are major substrates of CYP2C19 enzymes, 20% of CYP2D6, and 95% of

CYP3A4. About 10–20% of Caucasians are carriers of defective CYP2D6 polymorphic variants that alter the metabolism of many psychotropic agents. Other 100 genes participate in the efficacy and safety of psychotropic drugs. The incorporation of pharmacogenetic/ pharmacogenomic protocols to CNS research and clinical practice can foster therapeutics optimization by helping to develop cost-effective pharmaceuticals and improving drug efficacy and safety. To achieve this goal several measures have to be taken, including: (a) educate physicians and the public on the use of genetic/ genomic screening in the daily clinical practice; (b) standardize genetic testing for major categories of drugs; (c) validate pharmacogenetic and pharmacogenomic procedures according to drug category and pathology; (d) regulate ethical, social, and economic issues; and (e) incorporate pharmacogenetic and pharmacogenomic procedures to both drugs in development and drugs in the market to optimize therapeutics.