The Gut Microbiome and Treatment-Resistance in Schizophrenia

The effect of antipsychotic medication is poor in 30-40% of patients with schizophrenia; treatment resistance is usually met with shifts to new drugs or drug augmentation strategies or a trial of clozapine. The purpose of this review was to examine the potential role of intestinal bacteria in the bioavailability of antipsychotic medication and the possibility that parenterally administered antipsychotics might be able to overcome treatment resistance. Databases were searched with appropriate terms to locate relevant papers dealing with the effect of antipsychotic drugs on the gut microbiome and the effect of bacterial metabolizing enzymes on antipsychotic drugs. Also searched were papers addressing the various current parenteral formulations of antipsychotic drugs. Sixty-five recent pertinent papers were reviewed and the results are suggestive of the premise that there is a drug refractory form of psychosis for which the composition of gut bacteria is responsible, and that parenteral drug administration could overcome the problem.

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.

The current and potential impact of genetics and genomics on neuropsychopharmacology

One justification for the major scientific and financial investments in genetic and genomic studies in medicine is their therapeutic potential, both for revealing novel targets for drugs which treat the disease process, as well as allowing for more effective and safe use of existing medications. This review considers the extent to which this promise has yet been realised within psychopharmacology, how things are likely to develop in the foreseeable future, and the key issues involved. It draws primarily on examples from schizophrenia and its treatments. One observation is that there is evidence for a range of genetic influences on different aspects of psychopharmacology in terms of discovery science, but far less evidence that meets the standards required before such discoveries impact upon clinical practice. One reason is that results reveal complex genetic influences that are hard to replicate and usually of very small effect. Similarly, the slow progress being made in revealing the genes that underlie the major psychiatric syndromes hampers attempts to apply the findings to identify novel drug targets. Nevertheless, there are some intriguing positive findings of various kinds, and clear potential for genetics and genomics to play an increasing and major role in psychiatric drug discovery.

SULT4A1 haplotype: conflicting results on its role as a biomarker of antipsychotic response

Aim: Based on previous pharmacogenetic findings, we investigated the possible association between SULT4A1-1 haplotype and antipsychotic treatment response. Materials & methods: Using Mixed Model Repeated Measures, we tested the relationship between SULT4A1-1 status (+ carrier, - noncarrier) and clinical improvement (in Positive and Negative Syndrome Scale total score) among European ancestry patients treated with paliperidone extended release (n = 937), paliperidone palmitate (n = 990), risperidone (n = 507) and olanzapine (n = 381) in 12 schizophrenia, two schizoaffective disorder and three bipolar I disorder trials. SULT4A1-1 haplotype was determined using tagging SNP rs763120. Results: There was no significant difference between SULT4A1-1(+) and SULT4A1-1(-) patients for treatment response to paliperidone or olanzapine. SULT4A1-1(-) patients had better treatment response to risperidone in one schizophrenia trial, but not in another schizophrenia trial or bipolar mania trial. Conclusion: Across three psychiatric disorders (n = 2815 patients), we observed no consistent association between SULT4A1-1 status and atypical antipsychotic effect.

Original submitted 11 February 2014; Revision submitted 2 July 2014

Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia

Schizophrenia is a severe mental disorder characterized by cognitive deficits, and positive and negative symptoms. The development of effective pharmacological compounds for the treatment of schizophrenia has proven challenging and costly, with many compounds failing during clinical trials. Many failures occur due to disease heterogeneity and lack of predictive preclinical models and biomarkers that readily translate to humans during early characterization of novel antipsychotic compounds. Traditional early-phase trials consist of single- or multiple-dose designs aimed at determining the safety and tolerability of an investigational compound in healthy volunteers. However, by incorporating a translational approach employing methodologies derived from preclinical studies, such as EEG measures and imaging, into the traditional Phase I program, critical information regarding a compound's dose-response effects on pharmacodynamic biomarkers can be acquired. Furthermore, combined with the use of patients with stable schizophrenia in early-phase clinical trials, significant 'de-risking' and more confident 'go/no-go' decisions are possible.

The pharmacogenetics of antipsychotic-induced adverse events

PURPOSE OF REVIEW

Antipsychotic drugs are effective in alleviating a variety of symptoms and are medication of first choice in schizophrenia. However, a substantial interindividual variability in side effects often requires a lengthy 'trial-and-error' approach until the right medication is found for the right patient. Genetic factors have long been hypothesized to be involved and identification of related gene variants could be used to predict and tailor drug treatment.

RECENT FINDINGS

This review highlighting the most recent genetic findings was conducted on the two most common and most well-studied side effects: antipsychotic-induced weight gain and tardive dyskinesia.

SUMMARY

Regarding weight gain, most promising and most consistent findings were obtained in the serotonergic system (HTR2C) and with hypothalamic leptin-melanocortin genes, in particular with one variant close to the melanocortin-4-receptor (MC4R) gene. With respect to tardive dyskinesia, most interesting findings were generally obtained in genes related to the dopaminergic system (dopamine receptors D2 and D3), and more recently with glutamatergic system genes. Overall, genetic studies have been successful in identifying strong findings, in particular for antipsychotic-induced weight gain and to some extent for tardive dyskinesia. Apart from the need for replication studies in larger and well-characterized samples, the next challenge will be to create predictive algorithms that can be used for clinical practice.