CADPS functional mutations in patients with bipolar disorder increase the sensitivity to stress.

Bipolar disorder is a severe and chronic psychiatric disease resulting from a combination of genetic and environmental risk factors. Here, we identified a significant higher mutation rate in a gene encoding the calcium-dependent activator protein for secretion (CADPS) in 132 individuals with bipolar disorder, when compared to 184 unaffected controls or to 21,070 non-psychiatric and non-Finnish European subjects from the Exome Aggregation Consortium. We found that most of these variants resulted either in a lower abundance or a partial impairment in one of the basic functions of CADPS in regulating neuronal exocytosis, synaptic plasticity and vesicular transporter-dependent uptake of catecholamines. Heterozygous mutant mice for Cadps+/- revealed that a decreased level of CADPS leads to manic-like behaviours, changes in BDNF level and a hypersensitivity to stress. This was consistent with more childhood trauma reported in families with mutation in CADPS, and more specifically in mutated individuals. Furthermore, hyperactivity observed in mutant animals was rescued by the mood-stabilizing drug lithium. Overall, our results suggest that dysfunction in calcium-dependent vesicular exocytosis may increase the sensitivity to environmental stressors enhancing the risk of developing bipolar disorder.

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.

The most common way to treat schizophrenia is antipsychotic medication. However, not all antipsychotics work for all patients. The only way to find a suitable antipsychotic is to prescribe one and wait, sometimes for months, to see if it works. Finding an alternative to this trial-and-error method would help reduce patient suffering and costs for healthcare systems. The idea is to look in the DNA of our blood cells for specific marks that can change in response to our lifestyle or health condition. These marks could help us predict how patients will react to the drug. In other words, they can serve as biomarkers of antipsychotic response. The current work examined the blood of schizophrenia patients before and 4 weeks after starting medication. The patients who did not respond well to the drug had different marks on the genes involved in immune defense and nervous system functioning. Some of these genes also play roles in the development of schizophrenia, whereas others can directly affect what happens to the drug in the patient's body. Although marks that predict how patients will react were not identified with certainty, valuable targets for future research were identified.

A new genetic locus for antipsychotic-induced weight gain: A genome-wide study of first-episode psychosis patients using amisulpride (from the OPTiMiSE cohort).

BACKGROUND: Antipsychotic-induced weight gain is a common and debilitating side effect of antipsychotics. Although genome-wide association studies of antipsychotic-induced weight gain have been performed, few genome-wide loci have been discovered. Moreover, these genome-wide association studies have included a wide variety of antipsychotic compounds. AIMS: We aim to gain more insight in the genomic loci affecting antipsychotic-induced weight gain. Given the variable pharmacological properties of antipsychotics, we hypothesized that targeting a single antipsychotic compound would provide new clues about genomic loci affecting antipsychotic-induced weight gain. METHODS: All subjects included for this genome-wide association study (n=339) were first-episode schizophrenia spectrum disorder patients treated with amisulpride and were minimally medicated (defined as antipsychotic use <2 weeks in the previous year and/or <6 weeks lifetime). Weight gain was defined as the increase in body mass index from before until approximately 1 month after amisulpride treatment. RESULTS: Our genome-wide association analyses for antipsychotic-induced weight gain yielded one genome-wide significant hit (rs78310016; ß=1.05; p=3.66 × 10-08; n=206) in a locus not previously associated with antipsychotic-induced weight gain or body mass index. Minor allele carriers had an odds ratio of 3.98 (p=1.0 × 10-03) for clinically meaningful antipsychotic-induced weight gain (⩾7% of baseline weight). In silico analysis elucidated a chromatin interaction with 3-Hydroxy-3-Methylglutaryl-CoA Synthase 1. In an attempt to replicate single-nucleotide polymorphisms previously associated with antipsychotic-induced weight gain, we found none were associated with amisulpride-induced weight gain. CONCLUSION: Our findings suggest the involvement of rs78310016 and possibly 3-Hydroxy-3-Methylglutaryl-CoA Synthase 1 in antipsychotic-induced weight gain. In line with the unique binding profile of this atypical antipsychotic, our findings furthermore hint that biological mechanisms underlying amisulpride-induced weight gain differ from antipsychotic-induced weight gain by other atypical antipsychotics.

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.

Stratification and prediction of remission in first-episode psychosis patients: the OPTiMiSE cohort study.

Early response to first-line antipsychotic treatments is strongly associated with positive long-term symptomatic and functional outcome in psychosis. Unfortunately, attempts to identify reliable predictors of treatment response in first-episode psychosis (FEP) patients have not yet been successful. One reason for this could be that FEP patients are highly heterogeneous in terms of symptom expression and underlying disease biological mechanisms, thereby impeding the identification of one-size-fits-all predictors of treatment response. We have used a clustering approach to stratify 325 FEP patients into four clinical subtypes, termed C1A, C1B, C2A and C2B, based on their symptoms assessed using the Positive and Negative Syndrome Scale (PANSS) scale. Compared to C1B, C2A and C2B patients, those from the C1A subtype exhibited the most severe symptoms and were the most at risk of being non-remitters when treated with the second-generation antipsychotic drug amisulpride. Before treatment, C1A patients exhibited higher serum levels of several pro-inflammatory cytokines and inflammation-associated biomarkers therefore validating our stratification approach on external biological measures. Most importantly, in the C1A subtype, but not others, lower serum levels of interleukin (IL)-15, higher serum levels of C-X-C motif chemokine 12 (CXCL12), previous exposure to cytomegalovirus (CMV), use of recreational drugs and being younger were all associated with higher odds of being non-remitters 4 weeks after treatment. The predictive value of this model was good (mean area under the curve (AUC) = 0.73 ± 0.10), and its specificity and sensitivity were 45 ± 0.09% and 83 ± 0.03%, respectively. Further validation and replication of these results in clinical trials would pave the way for the development of a blood-based assisted clinical decision support system in psychosis.

Correction: Stratification and prediction of remission in first-episode psychosis patients: the OPTiMiSE cohort study.

The original Article did not feature the list of collaborators. This has now been corrected in the PDF and HTML versions of this Article.