Antipsychotic pharmacogenomics in first episode psychosis: a role for glutamate genes

Prediction of antipsychotics efficacy based on a polygenic risk score: a real-world cohort study

Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.

Association between genetic variants of GRM7 (rs1396409 and rs9883258) and treatment outcomes in Schizophrenic Egyptian patients

BACKGROUND AND AIM

This study evaluated the association between rs1396409 and rs9883258 and the risk of schizophrenia (SCZ) and treatment outcomes in Egyptian patients.

METHODS

This study included 88 patients with SCZ and 88 healthy controls. Lipid profile was assayed. Genotyping of rs1396409 and rs9883258 polymorphisms was analyzed using real-time PCR.

RESULTS

The rs1396409 AG genotype frequency was significantly associated with SCZ risk (p = 0.002). Also, significant increased risk of SCZ was observed under allelic (p = 0.001), dominant (p = 0.001) and overdominant (p = 0.001) genetic model of rs1396409. However, rs9883258 AA genotype revealed nonsignificant association with SCZ. Cases with the rs1396409AG genotype exhibited hypertriglyceridemia (p < 0.001) and hypercholesterolemia (p = 0.001). In total, 72.3% and 74.5% of the cases presented with rs1396409 AG have negative symptoms (p = 0.022) and exhibited poor drug response (p = 0.023), respectively; all cases with rs1396409 GG genotype attempted suicide (p = 0.002) and are drug-free (p = 0.003). SCZ patients with negative symptoms had hypercholesterolemia (p = 0.008) mainly low-density lipoproteins (LDLc) (p = 0.016), and those with cognitive symptoms presented with low level of high-density lipoprotein (HDLc) (p = 0.023). Moreover, the multivariate regression analysis revealed that both rs1396409 G allele and HDLc were predictors of SCZ (p = 0.003 and 0.001, resp.).

CONCLUSION

The current study concluded that metabotropic glutamate receptor 7 (GRM7) rs1396409 AG could be a potential biomarker for SCZ diagnosis. It also revealed an independent association between the GRM7 rs1396409 G allele, HDLc and SCZ development.

Clinical and genetic factors associated with post-operative nausea and vomiting after propofol anaesthesia

BACKGROUND

The incidence of post-operative nausea and vomiting (PONV) remains at about 30% despite all therapeutic efforts to reduce it. The clinical risk factors guiding the prophylactic treatment are well established, but genetic factors associated with PONV remain poorly known. The aim of this study was to explore clinical and genetic factors impacting PONV by performing a genome-wide association study (GWAS) together with relevant clinical factors as covariates, and systematically attempt to replicate previously reported PONV associations. Relevant clinical factors are explored with logistic regression model.

METHODS

This was an observational case control study in Helsinki University Hospital between 1 August 2006 and 31 December 2010. One thousand consenting women with elevated risk for PONV, undergoing breast cancer surgery with standardised propofol anaesthesia and antiemetics. After exclusions for clinical reasons and failed genotyping, 815 patients were included with 187 PONV cases and 628 controls. Emergence of PONV up to 7th post-operative day was recorded. PONV at 2-24 h after surgery was selected to be the primary outcome. The GWAS explored associations between PONV and 653 034 genetic variants. Replication attempts included 31 variants in 16 genes.

RESULTS

The overall incidence of PONV up to 7th post-operative day was 35%, where 3% had PONV at 0-2 h and 23% at 2-24 h after surgery. Age, American Society of Anaesthesiologists status, the amount of oxycodone used in the post-anaesthesia care unit, smoking status, previous PONV, and history of motion sickness were statistically significant predictive factors in the logistic model. The receiver operating characteristic-area under the curve of 0.75 (95% CI 0.71-0.79) was calculated for the model. The GWAS identified six variants with suggestive association to PONV (p < 1 × 10-5 ). Of the previously reported variants, association with the DRD2 variant rs18004972 (TaqIA) was replicated (p = .028).

CONCLUSIONS

Our GWAS approach did not identify any high-impact PONV susceptibility variants. The results provide some support for a role of dopamine D2 receptors in PONV.

Risperidone response in patients with schizophrenia drives DNA methylation changes in immune and neuronal systems

Background: The choice of efficient antipsychotic therapy for schizophrenia relies on a time-consuming trial-and-error approach, whereas the social and economic burdens of the disease call for faster alternatives. Material & methods: In a search for predictive biomarkers of antipsychotic response, blood methylomes of 28 patients were analyzed before and 4 weeks into risperidone therapy. Results: Several CpGs exhibiting response-specific temporal dynamics were identified in otherwise temporally stable methylomes and noticeable global response-related differences were observed between good and bad responders. These were associated with genes involved in immunity, neurotransmission and neuronal development. Polymorphisms in many of these genes were previously linked with schizophrenia etiology and antipsychotic response. Conclusion: Antipsychotic response seems to be shaped by both stable and medication-induced methylation differences.

Gene Expressions Preferentially Influence Cortical Thickness of Human Connectome Project Atlas Parcellated Regions in First-Episode Antipsychotic-Naïve Psychoses

Altered gene expressions may mechanistically link genetic factors with brain morphometric alterations. Existing gene expression studies have examined selected morphometric features using low-resolution atlases in medicated schizophrenia. We examined the relationship of gene expression with cortical thickness (CT), surface area (SA), and gray matter volume (GMV) of first-episode antipsychotic-naïve psychosis patients (FEAP = 85) and 81 controls, hypothesizing that gene expressions often associated with psychosis will differentially associate with different morphometric features. We explored such associations among schizophrenia and non-schizophrenia subgroups within FEAP group compared to controls. We mapped 360 Human Connectome Project atlas-based parcellations on brain MRI on to the publicly available brain gene expression data from the Allen Brain Institute collection. Significantly correlated genes were investigated using ingenuity pathway analysis to elucidate molecular pathways. CT but not SA or GMV correlated with expression of 1137 out of 15 633 genes examined controlling for age, sex, and average CT. Among these ≈19%, ≈39%, and 8% of genes were unique to FEAP, schizophrenia, and non-schizophrenia, respectively. Variants of 10 among these 1137 correlated genes previously showed genome-wide-association with schizophrenia. Molecular pathways associated with CT were axonal guidance and sphingosine pathways (common to FEAP and controls), selected inflammation pathways (unique to FEAP), synaptic modulation (unique to schizophrenia), and telomere extension (common to NSZ and healthy controls). We demonstrate that different sets of genes and molecular pathways may preferentially influence CT in different diagnostic groups. Genes with altered expressions correlating with CT and associated pathways may be targets for pathophysiological investigations and novel treatment designs.

Current Status of Therapeutic Drug Monitoring in Mental Health Treatment: A Review

Therapeutic drug monitoring (TDM) receives growing interest in different psychiatric clinical settings (emergency, inpatient, and outpatient services). Despite its usefulness, TDM remains underemployed in mental health. This is partly due to the need for evidence about the relationship between drug serum concentration and efficacy and tolerability, both in the general population and even more in subpopulations with atypical pharmacokinetics. This work aims at reviewing the scientific literature published after 2017, when the most recent guidelines about the use of TDM in mental health were written. We found 164 pertinent records that we included in the review. Some promising studies highlighted the possibility of correlating early drug serum concentration and clinical efficacy and safety, especially for antipsychotics, potentially enabling clinicians to make decisions on early laboratory findings and not proceeding by trial and error. About populations with pharmacokinetic peculiarities, the latest studies confirmed very common alterations in drug blood levels in pregnant women, generally with a progressive decrease over pregnancy and a very relevant dose-adjusted concentration increase in the elderly. For adolescents also, several drugs result in having different dose-related concentration values compared to adults. These findings stress the recommendation to use TDM in these populations to ensure a safe and effective treatment. Moreover, the integration of TDM with pharmacogenetic analyses may allow clinicians to adopt precise treatments, addressing therapy on an individual pharmacometabolic basis. Mini-invasive TDM procedures that may be easily performed at home or in a point-of-care are very promising and may represent a turning point toward an extensive real-world TDM application. Although the highlighted recent evidence, research efforts have to be carried on: further studies, especially prospective and fixed-dose, are needed to replicate present findings and provide clearer knowledge on relationships between dose, serum concentration, and efficacy/safety.

A polymorphism in the glutamate metabotropic receptor 7 is associated with cognitive deficits in the early phases of psychosis

Schizophrenia is an illness characterized by positive symptoms, negative symptoms, and cognitive impairments. Cognitive impairments occur before the onset of psychosis and could reflect glutamatergic dysregulation. Thus, identifying associations between genetic variations in genes coding for glutamatergic receptors and cognitive impairment in schizophrenia may help in understanding the basis of these deficits and in identifying potential drug targets. In a discovery cohort of 144 first-episode of psychosis patients (FEP), we genotyped 58 candidate Single Nucleotide Polymorphisms (SNPs) located in NMDA and metabotropic glutamatergic receptors. These SNPs were selected according to the results from the Psychiatric Genomic Consortium and were tested for association with intellectual quotient (IQ) as assessed with the Wechsler Intelligence Scales. For replication, we used the ICAAR cohort including 121 ultra-high-risk patients (UHR) with the same cognitive assessment. A polymorphism located in GRM7, rs1396409, was significantly associated with performance IQ in the discovery cohort of FEP. This association was replicated in the UHR cohort. This polymorphism is also associated with total IQ and verbal IQ in the merged dataset, with a predominant effect on the arithmetic subtest. The rs1396409 polymorphism is significantly associated with cognitive impairment during the onset of psychosis. This genetic association highlights the possible impact of glutamatergic genes in cognitive deficits in the early phases of psychosis and enforces the interest for new therapeutic interventions targeting the glutamatergic pathway.

The mGlu7 receptor in schizophrenia - An update and future perspectives

The mGlu₇ receptor belongs to the III group of metabotropic glutamatergic (mGlu) receptors and physiologically serves as an "emergency" receptor that is activated by high, almost pathological, glutamate concentrations. Of all mGlu receptors, this receptor is most highly expressed in the brain. Additionally, relatively intense expression of the receptor was found at the periphery, for example in the bowels or in the reproductive system of male mice, but this review will be focused predominantly on its role in the brain. In the CNS, the receptor is expressed presynaptically, in the center of the synaptic cleft, at the terminals of both excitatory glutamatergic and inhibitory GABAergic neurons. Thus, it may regulate the release of both glutamate and GABA. Schizophrenia is thought to develop as a consequence of a disturbed glutamatergic-GABAergic balance in different parts of the brain. Thus, the mGlu₇ receptor may be involved in the pathophysiology of schizophrenia and consequently constitute the target for antipsychotic drug discovery. In this review, we summarize the available data about mGlu₇ receptor ligands and their activity in animal models of schizophrenia. At present, only a few ligands are available, and negative allosteric modulators (NAMs) appear to exert antipsychotic-like efficacy, indicating that the inhibition of the receptor could constitute a promising target in the search for novel drugs. Additionally, the data concerning the expression of the receptor in the CNS and putative mechanisms by which its inhibition may contribute to the treatment of schizophrenia will be discussed. Finally, the polymorphisms of genes encoding the receptor in schizophrenic patients will also be provided.

Different responses to risperidone treatment in Schizophrenia: a multicenter genome-wide association and whole exome sequencing joint study

Risperidone is routinely used in the clinical management of schizophrenia, but the treatment response is highly variable among different patients. The genetic underpinnings of the treatment response are not well understood. We performed a pharmacogenomic study of the treatment response to risperidone in patients with schizophrenia by using a SNP microarray -based genome-wide association study (GWAS) and whole exome sequencing (WES)-based GWAS. DNA samples were collected from 189 patients for the GWAS and from 222 patients for the WES after quality control in multiple centers of China. Antipsychotic response phenotypes of patients who received eight weeks of risperidone treatment were quantified with percentage change on the Positive and Negative Syndrome Scale (PANSS). The GWAS revealed a significant association between several SNPs and treatment response, such as three GRM7 SNPs (rs141134664, rs57521140, and rs73809055). Gene-based analysis in WES revealed 13 genes that were associated with antipsychotic response, such as GPR12 and MAP2K3. We did not identify shared loci or genes between GWAS and WES, but association signals tended to cluster into the GPCR gene family and GPCR signaling pathway, which may play an important role in the treatment response etiology. This study may provide a research paradigm for pharmacogenomic research, and these data provide a promising illustration of our potential to identify genetic variants underlying antipsychotic responses and may ultimately facilitate precision medicine in schizophrenia.

Pharmacogenetics of Antipsychotic Treatment in Schizophrenia

Antipsychotics are the mainstay treatment for schizophrenia. There is large variability between individuals in their response to antipsychotics, both in efficacy and adverse effects of treatment. While the source of interindividual variability in antipsychotic response is not completely understood, genetics is a major contributing factor. The identification of pharmacogenetic markers that predict antipsychotic efficacy and adverse reactions is a growing area of research and holds the potential to replace the current trial-and-error approach to treatment selection in schizophrenia with a personalized medicine approach.In this chapter, we provide an overview of the current state of pharmacogenetics in schizophrenia treatment. The most promising pharmacogenetic findings are presented for both antipsychotic response and commonly studied adverse reactions. The application of pharmacogenetics to schizophrenia treatment is discussed, with an emphasis on the clinical utility of pharmacogenetic testing and directions for future research.

Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders

Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.

Toward personalized medicine in schizophrenia: Genetics and epigenetics of antipsychotic treatment

Schizophrenia is a complex psychiatric disorder where genetic, epigenetic, and environmental factors play a role in disease onset, course of illness, and treatment outcome. Pharmaco(epi)genetic research presents an important opportunity to improve patient care through prediction of medication side effects and response. In this narrative review, we discuss the current state of research and important progress of both genetic and epigenetic factors involved in antipsychotic response, over the past five years. The review is largely focused on the following frequently prescribed antipsychotics: olanzapine, risperidone, aripiprazole, and clozapine. Several consistent pharmacogenetic findings have emerged, in particular pharmacokinetic genes (primarily cytochrome P450 enzymes) and pharmacodynamic genes involving dopamine, serotonin, and glutamate neurotransmission. In addition to studies analysing DNA sequence variants, there are also several pharmacoepigenetic studies of antipsychotic response that have focused on the measurement of DNA methylation. Although pharmacoepigenetics is still in its infancy, consideration of both genetic and epigenetic factors contributing to antipsychotic response and side effects no doubt will be increasingly important in personalized medicine. We provide recommendations for next steps in research and clinical evaluation.

Gene expression and response prediction to amisulpride in the OPTiMiSE first episode psychoses

A fundamental shortcoming in the current treatment of schizophrenia is the lack of valid criteria to predict who will respond to antipsychotic treatment. The identification of blood-based biological markers of the therapeutic response would enable clinicians to identify the subgroup of patients in whom conventional antipsychotic treatment is ineffective and offer alternative treatments. As part of the Optimisation of Treatment and Management of Schizophrenia in Europe (OPTiMiSE) programme, we conducted an RNA-Seq analysis on 188 subjects with first episode psychosis, all of whom were subsequently treated with amisulpride for 4 weeks. We compared gene expression on total RNA from patients' blood before and after treatment and identified 32 genes for which the expression changed after treatment in good responders only. These findings were replicated in an independent sample of 24 patients with first episode psychosis. Six genes showed a significant difference in expression level between good and poor responders before starting treatment, allowing to predict treatment outcome with a predictive value of 93.8% when combined with clinical features. Collectively, these findings identified new mechanisms to explain symptom improvement after amisulpride medication and highlight the potential of combining gene expression profiling with clinical data to predict treatment response in first episode psychoses.

Polygenic modelling of treatment effect heterogeneity

Mendelian randomization is the use of genetic variants to assess the effect of intervening on a risk factor using observational data. We consider the scenario in which there is a pharmacomimetic (i.e., treatment-mimicking) genetic variant that can be used as a proxy for a particular pharmacological treatment that changes the level of the risk factor. If the association of the pharmacomimetic genetic variant with the risk factor is stronger in one subgroup of the population, then we may expect the effect of the treatment to be stronger in that subgroup. We test for gene-gene interactions in the associations of variants with a modifiable risk factor, where one genetic variant is treated as pharmacomimetic and the other as an effect modifier, to find genetic subgroups of the population with different predicted response to treatment. If individual genetic variants that are strong effect modifiers cannot be found, moderating variants can be combined using a random forest of interaction trees method into a polygenic response score, analogous to a polygenic risk score for risk prediction. We illustrate the application of the method to investigate effect heterogeneity in the effect of statins on low-density lipoprotein cholesterol.

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.

Variants of GRM7 as risk factor and response to antipsychotic therapy in schizophrenia

Genome-wide association study (GWAS) has determined the metabotropic glutamate receptor 7 (GRM7) gene as potential locus for schizophrenia risk variants; However, the relationship between the GRM7 variants and the risk of schizophrenia is still uncertain, and there are significant individual variations in response to the antipsychotic drugs. In order to identify susceptible gene and drug-response-related markers, 2413 subjects in our research were chosen for determining drug-response-related markers in schizophrenia. The rs1516569 variant (OR = 0.95, P < 3.47 × 10^-4) was a significant risk factor, and a single-nucleotide polymorphism of GRM7 gene- rs9883258 (OR = 0.84, P = 2.18 × 10^-3) has been determined as potential biomarkers for therapeutic responses of seven commonly used antipsychotic drugs (aripiprazole, haloperidol, olanzapine, perphenazine, quetiapine, risperidone and ziprasidone) in Chinese Han population; Significant associations with treatment response for several single-nucleotide polymorphisms in every antipsychotic drugs, such as rs779746 (OR = 1.39, P = 0.03), rs480409 (OR = 0.73, P = 0.04), rs78137319 (OR = 3.09, P = 0.04), rs1154370 (OR = 1.51, P = 0.006) have been identified in our study. Hence our research elucidates that GRM7 variants play the critical role of predicting the risk of schizophrenia and antipsychotic effect of seven common drugs.

Pharmacogenomic Characterization in Bipolar Spectrum Disorders

The holistic approach of personalized medicine, merging clinical and molecular characteristics to tailor the diagnostic and therapeutic path to each individual, is steadily spreading in clinical practice. Psychiatric disorders represent one of the most difficult diagnostic challenges, given their frequent mixed nature and intrinsic variability, as in bipolar disorders and depression. Patients misdiagnosed as depressed are often initially prescribed serotonergic antidepressants, a treatment that can exacerbate a previously unrecognized bipolar condition. Thanks to the use of the patient's genomic profile, it is possible to recognize such risk and at the same time characterize specific genetic assets specifically associated with bipolar spectrum disorder, as well as with the individual response to the various therapeutic options. This provides the basis for molecular diagnosis and the definition of pharmacogenomic profiles, thus guiding therapeutic choices and allowing a safer and more effective use of psychotropic drugs. Here, we report the pharmacogenomics state of the art in bipolar disorders and suggest an algorithm for therapeutic regimen choice.

A longitudinal magnetic resonance spectroscopy study investigating effects of risperidone in the anterior cingulate cortex and hippocampus in schizophrenia

Magnetic Resonance Spectroscopy is a popular approach to probe brain chemistry in schizophrenia (SZ), but no consensus exists as to the extent of alterations. This may be attributable to differential effects of populations studied, brain regions examined, or antipsychotic medication effects. Here, we measured neurometabolites in the anterior cingulate cortex (ACC) and hippocampus, two structurally dissimilar brain regions implicated in the SZ pathophysiology. We enrolled 61 SZ with the goal to scan them before and after six weeks of treatment with risperidone. We also scanned 31 matched healthy controls twice, six weeks apart. Using mixed effect repeated measures linear models to examine the effect of group and time on metabolite levels in each voxel, we report an increase in hippocampal glutamate + glutamine (Glx) in SZ compared to controls (p = 0.043), but no effect of antipsychotic medication (p = 0.330). In the ACC, we did not find metabolite alterations or antipsychotic medication related changes after six weeks of treatment with risperidone. The coefficients for the discriminant function (differentiating SZ from HC) in the ACC were greatest for NAA (-0.83), and in the hippocampus for Glx (0.76), the same metabolites were associated with greater treatment response in patients at trend level. Taken together, our data extends the existing literature by demonstrating regionally distinct metabolite alterations in the same patient group and suggests that antipsychotic medications may have limited effects on metabolite levels in these regions.

The ANKS1B gene and its associated phenotypes: focus on CNS drug response

The ANKS1B gene was a top finding in genome-wide association studies (GWAS) of antipsychotic drug response. Subsequent GWAS findings for ANKS1B include cognitive ability, educational attainment, body mass index, response to corticosteroids and drug dependence. We review current human association evidence for ANKS1B, in addition to functional studies that include two published mouse knockouts. The several GWAS findings in humans indicate that phenotypically relevant variation is segregating at the ANKS1B locus. ANKS1B shows strong plausibility for involvement in CNS drug response because it encodes a postsynaptic effector protein that mediates long-term changes to neuronal biology. Forthcoming data from large biobanks should further delineate the role of ANKS1B in CNS drug response.

Translational bioinformatics in mental health: open access data sources and computational biomarker discovery

Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.

Treatment-Resistant Schizophrenia: Genetic and Neuroimaging Correlates

Schizophrenia is a severe neuropsychiatric disorder that affects approximately 0.5–1% of the population. Response to antipsychotic therapy is highly variable, and it is not currently possible to predict those patients who will or will not respond to antipsychotic medication. Furthermore, a high percentage of patients, approximately 30%, are classified as treatment-resistant (treatment-resistant schizophrenia; TRS). TRS is defined as a non-response to at least two trials of antipsychotic medication of adequate dose and duration. These patients are usually treated with clozapine, the only evidence-based pharmacotherapy for TRS. However, clozapine is associated with severe adverse events. For these reasons, there is an increasing interest to identify better targets for drug development of new compounds and to establish better biomarkers for existing medications. The ability of antipsychotics to improve psychotic symptoms is dependent on their antagonist and reverse agonist activities at different neuroreceptors, and some genetic association studies of TRS have focused on different pharmacodynamic factors. Some genetic studies have shown an association between antipsychotic response or TRS and neurodevelopment candidate genes, antipsychotic mechanisms of action (such as dopaminergic, serotonergic, GABAergic, and glutamatergic) or pharmacokinetic factors (i.e., differences in the cytochrome families). Moreover, there is a growing body of literature on the structural and functional neuroimaging research into TRS. Neuroimaging studies can help to uncover the underlying neurobiological reasons for such resistance and identify resistant patients earlier. Studies examining the neuropharmacological mechanisms of antipsychotics, including clozapine, can help to improve our knowledge of their action on the central nervous system, with further implications for the discovery of biomarkers and the development of new treatments. The identification of the underlying mechanisms of TRS is a major challenge for developing personalized medicine in the psychiatric field for schizophrenia treatment. The main goal of precision medicine is to use genetic and brain-imaging information to improve the safety, effectiveness, and health outcomes of patients via more efficiently targeted risk stratification, prevention, and tailored medication and treatment management approaches. The aim of this review is to summarize the state of art of pharmacogenetic, pharmacogenomic and neuroimaging studies in TRS.

A systematic review of genome-wide association studies of antipsychotic response

Clinical symptom response to antipsychotic medications is highly variable. Genome-wide association studies (GWAS) provide a 'hypothesis-free' method of interrogating the genome for biomarkers of antipsychotic response. We performed a systematic review of GWAS findings for antipsychotic efficacy or effectiveness. 14 studies met our inclusion criteria, ten of which examined antipsychotic response using quantitative rating scales to measure symptom improvement. 15 genome-wide significant loci were identified, seven of which were replicated in other antipsychotic GWAS publications: CNTNAP5, GRID2, GRM7, 8q24 (KCNK9), PCDH7, SLC1A1 and TNIK. Notably, four replicated loci are involved in glutamatergic pathways. Additional validation and evaluation of the biological significance of these markers is warranted. These markers should also be evaluated for clinical utility, especially in the context of other validated pharmacogenomic variants (e.g., CYP450 genes). These findings may generate new avenues for development of novel antipsychotic treatments.

Dissociation of fractional anisotropy and resting-state functional connectivity alterations in antipsychotic-naive first-episode schizophrenia

Altered resting-state functional connectivity (rsFC) has been demonstrated between multiple brain regions in schizophrenia. However, whether these alterations are related to fractional anisotropy (FA) alterations in pathways that connect regions with altered rsFC remains unknown. In this study, diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed with 181 antipsychotic-naïve first-episode schizophrenia patients and 173 matched healthy controls. FA was measured using tensor-guided tractography in identifiable pathways between selected pairs of brain regions with altered rsFC as determined by prior meta-analysis. Compared with controls, patients showed significantly decreased FA between right caudate nucleus and right pallidum, right caudate nucleus and right putamen, and right hippocampus and right thalamus. Decreased rsFC was observed between right pallidum and right thalamus, and right insula and right superior temporal gyrus. No significant correlation was observed between FA and rsFC. FA between right caudate nucleus and right putamen was inversely correlated with negative symptoms while rsFC between right pallidum and right thalamus was inversely correlated with positive symptoms. The lack of robust correlations between FA and rsFC and no overlap of these abnormalities indicate that regional rsFC alterations in the early course of schizophrenia are not primarily associated with FA alterations. The observation that positive and negative symptoms are related to different functional and structural disturbances is consistent with this dissociation, and with prior work suggests that different pathophysiological mechanism may underlie positive and negative symptoms in the early course of schizophrenia.

Schizophrenia Polygenic Risk Score as a Predictor of Antipsychotic Efficacy in First-Episode Psychosis

OBJECTIVE

Pharmacogenomic studies of antipsychotics have typically examined effects of individual polymorphisms. By contrast, polygenic risk scores (PRSs) derived from genome-wide association studies (GWAS) can quantify the influence of thousands of common alleles of small effect in a single measure. The authors examined whether PRSs for schizophrenia were predictive of antipsychotic efficacy in four independent cohorts of patients with first-episode psychosis (total N=510).

METHOD

All study subjects received initial treatment with antipsychotic medication for first-episode psychosis, and all were genotyped on standard single-nucleotide polymorphism (SNP) arrays imputed to the 1000 Genomes Project reference panel. PRS was computed based on the results of the large-scale schizophrenia GWAS reported by the Psychiatric Genomics Consortium. Symptoms were measured by using total symptom rating scales at baseline and at week 12 or at the last follow-up visit before dropout.

RESULTS

In the discovery cohort, higher PRS significantly predicted higher symptom scores at the 12-week follow-up (controlling for baseline symptoms, sex, age, and ethnicity). The PRS threshold set at a p value <0.01 gave the strongest result in the discovery cohort and was used to replicate the findings in the other three cohorts. Higher PRS significantly predicted greater posttreatment symptoms in the combined replication analysis and was individually significant in two of the three replication cohorts. Across the four cohorts, PRS was significantly predictive of adjusted 12-week symptom scores (pooled partial r=0.18; 3.24% of variance explained). Patients with low PRS were more likely to be treatment responders than patients with high PRS (odds ratio=1.91 in the two Caucasian samples).

CONCLUSIONS

Patients with higher PRS for schizophrenia tended to have less improvement with antipsychotic drug treatment. PRS burden may have potential utility as a prognostic biomarker.

Response to initial antipsychotic treatment in first episode psychosis is related to anterior cingulate glutamate levels: a multicentre 1H-MRS study (OPTiMiSE)

Conventional antipsychotic medication is ineffective in around a third of patients with schizophrenia, and the nature of the therapeutic response is unpredictable. We investigated whether response to antipsychotics is related to brain glutamate levels prior to treatment. Proton magnetic resonance spectroscopy was used to measure glutamate levels (Glu/Cr) in the anterior cingulate cortex (ACC) and in the thalamus in antipsychotic-naive or minimally medicated patients with first episode psychosis (FEP, n = 71) and healthy volunteers (n = 60), at three sites. Following scanning, patients were treated with amisulpride for 4 weeks (n = 65), then ¹H-MRS was repeated (n = 46). Remission status was defined in terms of Positive and Negative Syndrome Scale for Schizophrenia (PANSS) scores. Higher levels of Glu/Cr in the ACC were associated with more severe symptoms at presentation and a lower likelihood of being in remission at 4 weeks (P < 0.05). There were longitudinal reductions in Glu/Cr in both the ACC and thalamus over the treatment period (P < 0.05), but these changes were not associated with the therapeutic response. There were no differences in baseline Glu/Cr between patients and controls. These results extend previous evidence linking higher levels of ACC glutamate with a poor antipsychotic response by showing that the association is evident before the initiation of treatment.

Is It Ethical to Use Prognostic Estimates from Machine Learning to Treat Psychosis?

Machine learning is a method for predicting clinically relevant variables, such as opportunities for early intervention, potential treatment response, prognosis, and health outcomes. This commentary examines the following ethical questions about machine learning in a case of a patient with new onset psychosis: (1) When is clinical innovation ethically acceptable? (2) How should clinicians communicate with patients about the ethical issues raised by a machine learning predictive model?

Identifying the genetic risk factors for treatment response to lurasidone by genome-wide association study: A meta-analysis of samples from three independent clinical trials

A genome-wide association study (GWAS) of response of schizophrenia patients to the atypical antipsychotic drug, lurasidone, based on two double-blind registration trials, identified SNPs from four classes of genes as predictors of efficacy, but none were genome wide significant (GWS). After inclusion of data from a third lurasidone trial, meta-analysis identified a GWS marker and other findings consistent with our first study. The primary end-point was change in Total Positive and Negative Syndrome Scale (PANSS) between baseline and last observation carried forward. rs4736253, a genetic locus near KCNK9, encoding the K_2P9.1 potassium channel, with a role in cognition and neurodevelopment, was the top marker in patients of European ancestry (EUR) (n = 264), reaching GWS (p = 4.78 × 10^-8). rs10180106 (p = 4.92 × 10^-7), located at an intron region of CTNNA2, a SCZ risk gene important for dendritic spine stabilization, was one of other best response markers for EUR patients. SNPs at STXBP5L (rs511841, p = 2.63 × 10^-7) were the top markers for patients of African ancestry (n = 158). The association between PTPRD, NRG1, and MAGI1 previously reported to be related to response to lurasidone in the first two trials, showed a trend of significant association in the third trial. None of these genetic loci showed significant associations with clinical response in the corresponding placebo groups (n = 107 for EUR; n = 58 for AFR). This meta-analysis yielded the first GWAS-based GWS biomarker for lurasidone response and additional support for the conclusion that genes related to synaptic biology and/or risk for SCZ are the strongest predictors of response to lurasidone in schizophrenia patients.

New findings in pharmacogenetics of schizophrenia

PURPOSE OF REVIEW

This review highlights recent advances in the investigation of genetic factors for antipsychotic response and side effects.

RECENT FINDINGS

Antipsychotics prescribed to treat psychotic symptoms are variable in efficacy and propensity for causing side effects. The major side effects include tardive dyskinesia, antipsychotic-induced weight gain (AIWG), and clozapine-induced agranulocytosis (CIA). Several promising associations of polymorphisms in genes including HSPG2, CNR1, and DPP6 with tardive dyskinesia have been reported. In particular, a functional genetic polymorphism in SLC18A2, which is a target of recently approved tardive dyskinesia medication valbenazine, was associated with tardive dyskinesia. Similarly, several consistent findings primarily from genes modulating energy homeostasis have also been reported (e.g. MC4R, HTR2C). CIA has been consistently associated with polymorphisms in the HLA genes (HLA-DQB1 and HLA-B). The association findings between glutamate system genes and antipsychotic response require additional replications.

SUMMARY

The findings to date are promising and provide us a better understanding of the development of side effects and response to antipsychotics. However, more comprehensive investigations in large, well characterized samples will bring us closer to clinically actionable findings.

Five novel loci associated with antipsychotic treatment response in patients with schizophrenia: a genome-wide association study

BACKGROUND

Antipsychotic drugs improve schizophrenia symptoms and reduce the frequency of relapse, but treatment response is highly variable. Little is known about the genetic factors associated with treatment response. We did a genome-wide association study of antipsychotic treatment response in patients with schizophrenia.

METHODS

The discovery cohort comprised patients with schizophrenia from 32 psychiatric hospitals in China that are part of the Chinese Antipsychotics Pharmacogenomics Consortium. Patients who met inclusion criteria were randomly assigned (1:1:1:1:1:1) to six groups (olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, and haloperidol or perphenazine; those assigned to haloperidol or perphenazine were subsequently assigned [1:1] to one or the other) for 6 weeks. Antipsychotic response was quantified with percentage change on the Positive and Negative Syndrome Scale. Single-nucleotide polymorphisms (SNPs) were tested for their association with treatment response. Linkage-disequilibrium-independent SNPs that exhibited potential associations (ie, p<1 × 10^-5) were tested in a validation cohort comprising patients from the Chinese Antipsychotics Pharmacogenetics Consortium from five collaborative hospitals, who were treated with olanzapine, risperidone, or aripiprazole for 8 weeks.

FINDINGS

The discovery cohort contained 2413 patients and the validation cohort 1379 patients. In the discovery cohort, we identified three novel SNPs (rs72790443 in MEGF10 [p=1·37 × 10^-8], rs1471786 in SLC1A1 [p=1·77 × 10^-8], and rs9291547 in PCDH7 [p=4·48 × 10^-8]) that were associated with antipsychotic treatment response at a genome-wide significance level. These associations were confirmed in the validation cohort (p<0·05). In the combined sample of the discovery and validation cohorts, we identified five novel loci showing genome-wide significant associations with general antipsychotic treatment response (rs72790443 in MEGF10 [p=1·40 × 10^-9], rs1471786 in SLC1A1 [p=2·33 × 10^-9], rs9291547 in PCDH7 [p=3·24 × 10^-9], rs12711680 in CNTNAP5 [p=2·12 × 10^-8], and rs6444970 in TNIK [p=4·85 × 10^-8]). In antipsychotic-specific groups, after the combination of results from both samples, the rs2239063 SNP in CACNA1C was associated with treatment response to olanzapine (p=1·10 × 10^-8), rs16921385 in SLC1A1 was associated with treatment response to risperidone (p=4·40 × 10^-8), and rs17022006 in CNTN4 was associated with treatment response to aripiprazole (p=2·58 × 10^-8).

INTERPRETATION

We have identified genes related to synaptic function, neurotransmitter receptors, and schizophrenia risk that are associated with response to antipsychotics. These findings improve understanding of the mechanisms underlying treatment responses, and the identified biomarkers could eventually guide choice of antipsychotic in patients with schizophrenia.

FUNDING

National Key Technology R&D Program of China, National Natural Science Foundation of China.

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.

Pleiotropic genes in psychiatry: Calcium channels and the stress-related FKBP5 gene in antidepressant resistance

A candidate gene and a genome-wide approach were combined to study the pharmacogenetics of antidepressant response and resistance. Investigated genes were selected on the basis of pleiotropic effect across psychiatric phenotypes in previous genome-wide association studies and involvement in antidepressant response. Three samples with major depressive disorder (total=671) were genotyped for 44 SNPs in 8 candidate genes (CACNA1C, CACNB2, ANK3, GRM7, TCF4, ITIH3, SYNE1, FKBP5). Phenotypes were response/remission after 4weeks of treatment and treatment-resistant depression (TRD). Genome-wide data from STAR*D were used to replicate findings for response/remission (n=1409) and TRD (n=620). Pathways including the most promising candidate genes were investigated in STAR*D for involvement in TRD. FKBP5 polymorphisms showed replicated but nominal associations with response, remission or TRD. CACNA1C rs1006737 and rs10848635 were the only polymorphisms that survived multiple-testing correction. In STAR*D the best pathway associated with TRD included CACNA1C (GO:0006942, permutated p=0.15). Machine learning models showed that independent SNPs in this pathway predicted TRD with a mean sensitivity of 0.83 and specificity of 0.56 after 10-fold cross validation repeated 100 times. FKBP5 polymorphisms appear good candidates for inclusion in antidepressant pharmacogenetic tests. Pathways including the CACNA1C gene may be involved in TRD and they may provide the base for developing multi-marker predictors of TRD.

Genetic predictors of antipsychotic response to lurasidone identified in a genome wide association study and by schizophrenia risk genes

Biomarkers which predict response to atypical antipsychotic drugs (AAPDs) increases their benefit/risk ratio. We sought to identify common variants in genes which predict response to lurasidone, an AAPD, by associating genome-wide association study (GWAS) data and changes (Δ) in Positive And Negative Syndrome Scale (PANSS) scores from two 6-week randomized, placebo-controlled trials of lurasidone in schizophrenia (SCZ) patients. We also included SCZ risk SNPs identified by the Psychiatric Genomics Consortium using a polygenic risk analysis. The top genomic loci, with uncorrected p<10^-4, include: 1) synaptic adhesion (PTPRD, LRRC4C, NRXN1, ILIRAPL1, SLITRK1) and scaffolding (MAGI1, MAGI2, NBEA) genes, both essential for synaptic function; 2) other synaptic plasticity-related genes (NRG1/3 and KALRN); 3) the neuron-specific RNA splicing regulator, RBFOX1; and 4) ion channel genes, e.g. KCNA10, KCNAB1, KCNK9 and CACNA2D3). Some genes predicted response for patients with both European and African Ancestries. We replicated some SNPs reported to predict response to other atypical APDs in other GWAS. Although none of the biomarkers reached genome-wide significance, many of the genes and associated pathways have previously been linked to SCZ. Two polygenic modeling approaches, GCTA-GREML and PLINK-Polygenic Risk Score, demonstrated that some risk genes related to neurodevelopment, synaptic biology, immune response, and histones, also contributed to prediction of response. The top hits predicting response to lurasidone did not predict improvement with placebo. This is the first evidence from clinical trials that SCZ risk SNPs are related to clinical response to an AAPD. These results need to be replicated in an independent sample.

Antipsychotic Drug Responsiveness and Dopamine Receptor Signaling; Old Players and New Prospects

Antipsychotic drugs targeting dopamine neurotransmission are still the principal mean of therapeutic intervention for schizophrenia. However, about one third of people do not respond to dopaminergic antipsychotics. Genome wide association studies (GWAS), have shown that multiple genetic factors play a role in schizophrenia pathophysiology. Most of these schizophrenia risk variants are not related to dopamine or antipsychotic drugs mechanism of action. Genetic factors have also been implicated in defining response to antipsychotic medication. In contrast to disease risk, variation of genes coding for molecular targets of antipsychotics have been associated with treatment response. Among genes implicated, those involved in dopamine signaling mediated by D2-class dopamine receptor, including DRD2 itself and its molecular effectors, have been implicated as key genetic predictors of response to treatments. Studies have also reported that genetic variation in genes coding for proteins that cross-talk with DRD2 at the molecular level, such as AKT1, GSK3B, Beta-catenin, and PPP2R2B are associated with response to antipsychotics. In this review we discuss the relative contribution to antipsychotic drug responsiveness of candidate genes and GWAS identified genes encoding proteins involved in dopamine responses. We also suggest that in addition of these older players, a deeper investigation of new GWAS identified schizophrenia risk genes such as FXR1 can provide new prospects that are not clearly engaged in dopamine function while being targeted by dopamine-associated signaling molecules. Overall, further examination of genes proximally or distally related to signaling mechanisms engaged by medications and associated with disease risk and/or treatment responsiveness may uncover an interface between genes involved in disease causation with those affecting disease remediation. Such a nexus would provide realistic targets for therapy and further the development of genetically personalized approaches for schizophrenia.

Genome-wide association study of paliperidone efficacy

Supplemental Digital Content is available in the text.

Objective

Clinical response to the atypical antipsychotic paliperidone is known to vary among schizophrenic patients. We carried out a genome-wide association study to identify common genetic variants predictive of paliperidone efficacy.

Methods

We leveraged a collection of 1390 samples from individuals of European ancestry enrolled in 12 clinical studies investigating the efficacy of the extended-release tablet paliperidone ER (n₁=490) and the once-monthly injection paliperidone palmitate (n₂=550 and n₃=350). We carried out a genome-wide association study using a general linear model (GLM) analysis on three separate cohorts, followed by meta-analysis and using a mixed linear model analysis on all samples. The variations in response explained by each single nucleotide polymorphism (h²_SNP) were estimated.

Results

No SNP passed genome-wide significance in the GLM-based analyses with suggestive signals from rs56240334 [P=7.97×10⁻⁸ for change in the Clinical Global Impression Scale-Severity (CGI-S); P=8.72×10⁻⁷ for change in the total Positive and Negative Syndrome Scale (PANSS)] in the intron of ADCK1. The mixed linear model-based association P-values for rs56240334 were consistent with the results from GLM-based analyses and the association with change in CGI-S (P=4.26×10⁻⁸) reached genome-wide significance (i.e. P<5×10⁻⁸). We also found suggestive evidence for a polygenic contribution toward paliperidone treatment response with estimates of heritability, h²_SNP, ranging from 0.31 to 0.43 for change in the total PANSS score, the PANSS positive Marder factor score, and CGI-S.

Conclusion

Genetic variations in the ADCK1 gene may differentially predict paliperidone efficacy in schizophrenic patients. However, this finding should be replicated in additional samples.

New drug developments in psychosis: Challenges, opportunities and strategies

All currently approved drugs for schizophrenia work mainly by dopaminergic antagonism. While they are efficacious for psychotic symptoms, their efficacy is limited for negative symptoms and cognitive deficits which underlie the substantive disability in this illness. Recent insights into the biological basis of schizophrenia, especially in relation to non-dopaminergic mechanisms, have raised the efforts to find novel and effective drug targets, though with relatively little success thus far. Potential impediments to novel drug discovery include the continued use of symptom based disease definitions which leads to etiological and pathophysiological heterogeneity, lack of valid preclinical models for drug testing, and design limitations in clinical trials. These roadblocks can be addressed by (i) characterizing trans-diagnostic, translational pathophysiological dimensions as potential treatment targets, (ii) efficiency, accountability and, transparency in approaches to the clinical trials process, and (iii) leveraging recent advances in genetics and in vitro phenotypes. Accomplishing these goals is urgent given the significant unmet needs in the pharmacological treatment of schizophrenia. As this happens, it is imperative that clinicians employ optimal dosing, measurement-based care, and other best practices in utilizing existing treatments to optimize outcomes for their patients today.

Evaluation of single and multiple doses of a novel mGlu2 agonist, a potential antipsychotic therapy, in healthy subjects

AIMS

The safety, tolerability, pharmacokinetics (PK) and pharmacodynamics of single and multiple doses of a novel mGlu2 agonist were assessed in healthy males.

METHODS

In two, Phase 1 investigator- and subject-blind, placebo-controlled studies, oral doses of prodrug LY2979165 were evaluated: single doses (20-150 mg, N = 30) and multiple once-daily (QD) doses (20-400 mg; N = 84), using a titration regimen. The plasma and urine PK of LY2979165 and active moiety, 2812223, were measured. Cerebrospinal fluid (CSF) was collected to determine PK and neurotransmitter levels. Safety parameters were assessed throughout.

RESULTS

Nausea and vomiting were dose limiting following single doses; dose titration allowed higher doses to be tested over 14 days. The most common adverse events related to LY2979165 were dizziness, vomiting, nausea, somnolence and headache. The plasma PK of 2812223 were approximately linear with minimal accumulation with QD dosing. Conversion of LY2979165 to 2812223 was extensive, with minimal LY2979165 measurable in plasma. There was no effect of food on the PK of LY2979165 and 2812223. After 60 mg LY2979165 single-dose, 2812223 exposure in CSF was approximately 2-6% and plasma exposure and peak concentrations were approximately four-fold higher than the mGlu2 agonist in vitro EC₅₀ value. No consistent effects were observed on CSF neurotransmitter levels.

CONCLUSIONS

Oral doses of LY2979165 up to 60 mg as a single dose and up to 400 mg given as multiple QD doses, using a titration regimen, were well tolerated with linear PK. Overall, these data support further clinical evaluation of LY2979165.

Effects of Antipsychotic Administration on Brain Glutamate in Schizophrenia: A Systematic Review of Longitudinal 1H-MRS Studies

Schizophrenia is associated with brain glutamate dysfunction, but it is currently unclear whether antipsychotic administration can reduce the extent of glutamatergic abnormality. We conducted a systematic review of proton magnetic resonance spectroscopy (¹H-MRS) studies examining the effects of antipsychotic treatment on brain glutamate levels in schizophrenia. The Medline database was searched to identify relevant articles published until December 2016. Inclusion required that studies examined longitudinal changes in brain glutamate metabolites in patients with schizophrenia before and after initiation of first antipsychotic treatment or a switch in antipsychotic treatment. The searches identified eight eligible articles, with baseline and follow-up measures in a total of 168 patients. The majority of articles reported a numerical reduction in brain glutamate metabolites with antipsychotic treatment, and the estimated overall mean reduction of 6.5% in Glx (the combined signal from glutamate and glutamine) across brain regions. Significant reductions in glutamate metabolites in at least one brain region were reported in four of the eight studies, and none of the studies reported a significant glutamatergic increase after antipsychotic administration. Relationships between the degree of change in glutamate and the degree of improvement in symptoms have been inconsistent but may provide limited evidence that antipsychotic response may be associated with lower glutamate levels before treatment and a greater extent of glutamatergic reduction during treatment. Further longitudinal, prospective studies of glutamate and antipsychotic response are required to confirm these findings.

Prediction Analysis for Transition to Schizophrenia in Individuals at Clinical High Risk for Psychosis: The Relationship of DAO, DAOA, and NRG1 Variants with Negative Symptoms and Cognitive Deficits

Schizophrenia is characterized by positive and negative symptoms and cognitive dysfunction. The glutamate hypothesis of schizophrenia has been hypothesized to explain the negative symptoms and cognitive deficits better than the dopamine hypothesis alone. Therefore, we aimed to evaluate whether glutamatergic variants such as d-amino acid oxidase (DAO), DAO activator (DAOA)/G72, and neuregulin 1 (NRG1) single-nucleotide polymorphisms (SNPs) and their mRNA levels predicted (i) transition to schizophrenia spectrum disorders and (ii) research domain criteria (RDoC) domains, mainly negative valence and cognitive systems. In a 3-year prospective study cohort of 185 individuals (age: 13-35 years) at high risk and ultra-high risk (UHR) for psychosis, we assessed DAO (rs3918347, rs4623951), DAOA (rs778293, rs3916971, rs746187), and NRG1 (rs10503929) SNPs and their mRNA expression. Furthermore, we investigated their association with RDoC domains, mainly negative valence (e.g., anxiety, hopelessness) and cognitive (e.g., perception disturbances, disorganized symptoms) systems. NRG1 rs10503929 CC + CT versus TT genotype carriers experienced significantly more disorganized symptoms. DAOA rs746187 CC versus CT + TT genotype, DAOA rs3916971 TT versus TC + CC genotype, and DAO rs3918347 GA + AA versus GG genotype carriers experienced nominally more hopelessness, visual perception disturbances, and auditory perception disturbances, respectively. The schizophrenia risk G-allele of DAO rs3918347 nominally increased risk for those UHR individuals with attenuated positive symptoms syndrome. No association between DAO, DAOA, NRG1 SNPs, and conversion to schizophrenia spectrum disorders was observed. Our findings suggest that DAO, DAOA, and NRG1 polymorphisms might influence both RDoC negative valence and cognitive systems, but not transition to schizophrenia spectrum disorders.

Precision medicine for psychopharmacology: a general introduction

INTRODUCTION

Precision medicine is an emerging medical model that can provide accurate diagnoses and tailored therapeutic strategies for patients based on data pertaining to genes, microbiomes, environment, family history and lifestyle.

AREAS COVERED

Here, we provide basic information about precision medicine and newly introduced concepts, such as the precision medicine ecosystem and big data processing, and omics technologies including pharmacogenomics, pharamacometabolomics, pharmacoproteomics, pharmacoepigenomics, connectomics and exposomics. The authors review the current state of omics in psychiatry and the future direction of psychopharmacology as it moves towards precision medicine. Expert commentary: Advances in precision medicine have been facilitated by achievements in multiple fields, including large-scale biological databases, powerful methods for characterizing patients (such as genomics, proteomics, metabolomics, diverse cellular assays, and even social networks and mobile health technologies), and computer-based tools for analyzing large amounts of data.