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Background: Psychiatric disorders are complex, multifactorial illnesses with a demonstrated biological component in their etiopathogenesis. Epigenetic modifications, through the modulation of DNA methylation, histone modifications and RNA interference, tune tissue-specific gene expression patterns and play a relevant role in the etiology of psychiatric illnesses. Objective: This review aims to discuss the epigenetic mechanisms involved in psychiatric disorders, their modulation by environmental factors and their interactions with genetic variants, in order to provide a comprehensive picture of their mutual crosstalk. Methods: In accordance with the PRISMA guidelines, systematic searches of Medline, EMBASE, PsycINFO, Web of Science, Scopus, and the Cochrane Library were conducted. Results: Exposure to environmental factors, such as poor socio-economic status, obstetric complications, migration, and early life stressors, may lead to stable changes in gene expression and neural circuit function, playing a role in the risk of psychiatric diseases. The most replicated genes involved by studies using different techniques are discussed. Increasing evidence indicates that these sustained abnormalities are maintained by epigenetic modifications in specific brain regions and they interact with genetic variants in determining the risk of psychiatric disorders. Conclusion: An increasing amount of evidence suggests that epigenetics plays a pivotal role in the etiopathogenesis of psychiatric disorders. New therapeutic approaches may work by reversing detrimental epigenetic changes that occurred during the lifespan.

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Polymorphisms in cytochrome P450 genes (CYP450) were demonstrated to play a significant role in antidepressant response and side effects, but their effect in real-world clinical practice is poorly known. We determined the metabolic status of CYP2C19 based on the combination of *1, *2, *3 and *17 alleles extracted from genome-wide data in 1239 patients with MDD, pharmacologically treated in a naturalistic setting. Symptom improvement and side effects were assessed using the Montgomery and Åsberg Depression Rating Scale and the Udvalg for Kliniske Undersøgelse scale, respectively. We tested if symptom improvement, response and side effects were associated with CYP2C19 metabolic status adjusting for potential confounders. We considered patients treated with drugs for depression having CYP2C19 genotyping recommended by guidelines (T1 Drugs); secondarily, with all psychotropic drugs having CYP2C19 as relevant metabolic path (T2 Drugs). In the group treated with T1 drugs (n = 540), poor metabolizers (PMs) showed higher response and higher symptom improvement compared to normal metabolizers (p = 0.023 and p = 0.009, respectively), but also higher risk of autonomic and neurological side effects (p = 0.022 and p = 0.022 respectively). In patients treated with T2 drugs (n = 801), similar results were found. No associations between metabolizer status and other types of side effects were found (psychic and other side effects). Our study suggests potential advantages of CYP2C19 pharmacogenetic testing to guide treatment prescription, that may not be limited to the drugs currently recommended by guidelines.

About two-thirds of patients with major depressive disorder (MDD) fail to achieve symptom remission after the initial antidepressant treatment. Despite a role of genetic factors was proven, the specific underpinnings are not fully understood yet. Polygenic risk scores (PRSs), which summarise the additive effect of multiple risk variants across the genome, might provide insights into the underlying genetics. This study aims to investigate the possible association of PRSs for bipolar disorder, MDD, neuroticism, and schizophrenia (SCZ) with antidepressant non-response or non-remission in patients with MDD. PRSs were calculated at eight genome-wide P-thresholds based on publicly available summary statistics of the largest genome-wide association studies. Logistic regressions were performed between PRSs and non-response or non-remission in six European clinical samples, adjusting for age, sex, baseline symptom severity, recruitment sites, and population stratification. Results were meta-analysed across samples, including up to 3,637 individuals. Bonferroni correction was applied. In the meta-analysis, no result was significant after Bonferroni correction. The top result was found for MDD-PRS and non-remission (p = 0.004), with patients in the highest vs. lowest PRS quintile being more likely not to achieve remission (OR=1.5, 95% CI=1.11–1.98, p = 0.007). Nominal associations were also found between MDD-PRS and non-response (p = 0.013), as well as between SCZ-PRS and non-remission (p = 0.035). Although PRSs are still not able to predict non-response or non-remission, our results are in line with previous works; methodological improvements in PRSs calculation may improve their predictive performance and have a meaningful role in precision psychiatry.

Depression is a leading cause of disability worldwide and, despite the availability of numerous antidepressants, the lack of standardized criteria to apply personalized prescription is still a major issue. Pharmacogenetic (PGx) markers in cytochrome P450 (CYP450) genes are already usable to guide antidepressant choice/titration according to clinical guidelines; they are an important step toward personalized psychiatry as they can reduce the time to identify an effective and tolerated treatment. Clinical application is still limited due to the financial and organizational challenges, but the number of services providing genotyping of pharmacogenes is increasing, with encouraging projections of cost-effectiveness. Critical aspects that emerged from the available studies are the importance of integration of genotyping results in electronic medical records, standardization, and regular updates of decision support systems, training and collaboration of different professionals, need of longer follow-ups to estimate cost-effectiveness, and importance of avoiding inequalities in access to genotyping. Diversities exist among the groups of patients to whom genotyping is offered (pre-emptive or reactive testing) and the type of clinical services (e.g., hospitals and primary care), currently without a consensus on which is the best approach. Future studies should aim to clarify these issues, as well as consider and compare PGx applications among different countries and healthcare systems. Finally, the extension of genotyping outside pharmacokinetic genes should be considered as a key step to improve the clinical impact of PGx, as this could significantly increase the variance explained in treatment outcomes.

Over 20 years after the initial report of gene variants within the central nervous system modulating antidepressant response, we are now facing for the first time routine clinical pharmacogenetic applications. The scientific community is divided between enthusiasm and skepticism. It seems clear that the benefit of existing tools is not huge, at least for the central nervous system gene variants, while it is generally accepted for the metabolic gene variants. Findings from large international consortia suggest for the first time in psychiatric genetic research history that cumulative scores comprising many variants across the whole genome may reliably constitute liability factors for psychiatric disorders, this approach will most likely improve also present pharmacogenetic tools. A composite genetic score complemented with clinical risk factors for each patient is the most promising approach for a more effective method of targeted treatment for patients with depression.

BACKGROUND: The present multicenter study aimed at defining the clinical profile of patients with major depressive disorder (MDD) and comorbid migraine. METHODS: Demographic and clinical information for 1410 MDD patients with vs without concurrent migraine were compared by descriptive statistics, analyses of covariance, and binary logistic regression analyses. RESULTS: The point prevalence rate for comorbid migraine was 13.5% for female and 6.2% for male patients. MDD + migraine patients were significantly younger, heavier, more likely female, of non-Caucasian origin, outpatient, and suffering from asthma. The presence of MDD + migraine resulted in a significantly higher functional disability. First-line antidepressant treatment strategy revealed a trend towards agomelatine. Second-generation antipsychotics were significantly less often administered for augmentation treatment in migraineurs. Overall, MDD + migraine patients tended to respond worse to their pharmacotherapy. CONCLUSION: Treatment guidelines for comorbid depression and migraine are warranted to ensure optimal efficacy and avoid possible pitfalls in psychopharmacotherapy, including serotonin syndrome., SCOPUS: ar.j, DecretOANoAutActif, info:eu-repo/semantics/published

Background Augmentation with second-generation antipsychotics (SGAs) represents an evidence-based psychopharmacotherapeutic strategy recommended in case of insufficient response to the first-line antidepressant (AD) treatment in major depressive disorder (MDD). Comparative evidence regarding efficacy and prescription preferences of the individual SGAs is scarce. Methods In the scope of this European, multi-site, naturalistic cross-sectional investigation with retrospective assessment of treatment outcome, we compared sociodemographic and clinical characteristics of 187 MDD patients receiving either quetiapine (n = 150) or aripiprazole (n = 37) as augmentation of their first-line AD psychopharmacotherapy. Results Comorbid posttraumatic stress disorder and diabetes were significantly associated with aripiprazole augmentation in our primary and post-hoc binary logistic regression analyses. Furthermore, we identified an association between aripiprazole co-administration and the presence of additional psychotic features, higher rates of AD combination treatment, and a longer duration of psychiatric hospitalizations during the lifetime, which, however, lost significance after correcting for multiple comparisons. Regarding treatment outcome, we found a trend of higher response rates and greater reductions in severity of depressive symptoms in MDD patients dispensed quetiapine. Conclusions Factors associated with a more chronic and severe profile of MDD seem to encourage clinicians to choose aripiprazole over quetiapine, that was, however, administered in the majority of our MDD patients, which might reflect the current approval situation allowing to prescribe exclusively quetiapine as on-label augmentation in MDD in Europe. Given the retrospective assessment of treatment response, the markedly smaller proportion of patients receiving aripiprazole augmentation generally showing an unfavorable disease profile, and the partially heterogeneous statistical robustness of our findings, further studies are required to elaborate on our observation and to generate unambiguous recommendations regarding the choice of first-line SGA augmentation in MDD.

About two thirds of the patients with major depressive disorder (MDD) do not sufficiently respond to monotherapy with antidepressants (ADs) which makes them reliant on further treatment approaches. Hereby, combination of different ADs and augmentation with second-generation antipsychotics (SGAs) are widely used and recommended psychopharmacotherapeutic strategies. The present secondary analyses are based on an international, naturalistic, cross-sectional multicenter study conducted by the European Group for the Study of Resistant Depression. Comparing socio-demographic and clinical characteristics of 436 adult MDD patients receiving either SGAs (N = 191, 43.8%) or ADs (N = 245, 56.2%), that were additionally administered to their first-line AD psychopharmacotherapy, we aimed to identify possible trajectories of decision-making for clinicians regarding which treatment option to prefer in individual patients. Our most robust findings represent an association of SGA augmentation with the presence of psychotic symptoms, longer mean duration of lifetime psychiatric hospitalizations, employment of further augmentation strategies with mood-stabilizers and benzodiazepines, and a trend towards higher mean daily dosages of their first-line ADs and current suicidal risk. Treatment outcome was not significantly different between patients receiving either SGA augmentation or AD combination. Being aware of limitations inherent to the cross-sectional study design and the lack of randomization, more severe and rather chronic conditions in MDD seemed to encourage clinicians to choose SGA augmentation over AD combination. The fact that mood-stabilizers and/or benzodiazepines were more frequently co-administered with SGAs may represent a requirement of an overall refined psychopharmacotherapy including additional fast-acting agents with potent AD, tranquilizing and anti-suicidal effects in MDD patients experiencing challenging clinical manifestations. New glutamatergic substances seem to be promising in this regard.

Major depressive disorder (MDD) is the single largest contributor to global disability and up to 20–30% of patients do not respond to at least two antidepressants (treatment-resistant depression, TRD). This study leveraged imputed gene expression in TRD to perform a drug repurposing analysis. Among those with MDD, we defined TRD as having at least two antidepressant switches according to primary care records in UK Biobank (UKB). We performed a transcriptome-wide association study (TWAS) of TRD (n = 2165) vs healthy controls (n = 11,188) using FUSION and gene expression levels from 21 tissues. We identified compounds with opposite gene expression signatures (ConnectivityMap data) compared to our TWAS results using the Kolmogorov-Smirnov test, Spearman and Pearson correlation. As symptom patterns are routinely assessed in clinical practice and could be used to provide targeted treatments, we identified MDD subtypes associated with TRD in UKB and analysed them using the same pipeline described for TRD. Anxious MDD (n = 14,954) and MDD with weight gain (n = 4697) were associated with TRD. In the TWAS, two genes were significantly dysregulated (TMEM106B and ATP2A1 for anxious and weight gain MDD, respectively). A muscarinic receptor antagonist was identified as top candidate for repurposing in TRD; inhibition of heat shock protein 90 was the main mechanism of action identified for anxious MDD, while modulators of metabolism such as troglitazone showed promising results for MDD with weight gain. This was the first TWAS of TRD and associated MDD subtypes. Our results shed light on possible pharmacological approaches in individuals with difficult-to-treat depression.

Contains fulltext : 237832.pdf (Publisher’s version ) (Open Access) Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h(2) of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability.

Background: Major Depressive Disorder(MDD) and its frequent partial response to antidepressants are a major health concern and therefore an important focus of research. Despite the efforts, MDD pathogenesis and the mechanisms of antidepressant action are only partially understood. In the last few years, the need of rethinking the classification of depressive disorders and psychiatric disorders, in general, has been suggested, in order to provide a nosology that reflects more closely the biological background associated with disease pathogenesis and its role/significance in treatment. The classification proposed by the National Institute of Mental Health (NIMH), namely the research domain criteria (RDoC), may represent a key framework to guide research in this direction. Methods: A literature search was performed on PubMed and Google Scholar databases in order to retrieve data regarding Antidepressants effects on specific RDoC constructs. Further, the targets of drugs of interest were identified through the Drug bank database, and their possible function within RDoC constructs was discussed. Discussion: In this review, we summarize and discuss the significance of the results of pre-clinical and clinical studies investigating specific RDoC paradigms relevant to depressive phenotypes and antidepressant effects. Conclusion: The RDoC framework may facilitate a more specific use of antidepressants based on the individual’s spectrum of symptoms and the development of new compounds that target specific depressive symptoms.

There is still a debate, if melancholic symptoms can be seen rather as a more severe subtype of major depressive disorder (MDD) or as a separate diagnostic entity. The present European multicenter study comprising altogether 1410 MDD in- and outpatients sought to investigate the influence of the presence of melancholic features in MDD patients. Analyses of covariance, chi-squared tests, and binary logistic regression analyses were accomplished to determine differences in socio-demographic and clinical variables between MDD patients with and without melancholia. We found a prevalence rate of 60.71% for melancholic features in MDD. Compared to non-melancholic MDD patients, they were characterized by a significantly higher likelihood for higher weight, unemployment, psychotic features, suicide risk, inpatient treatment, severe depressive symptoms, receiving add-on medication strategies in general, and adjunctive treatment with antidepressants, antipsychotics, benzodiazepine (BZD)/BZD-like drugs, low-potency antipsychotics, and pregabalin in particular. With regard to the antidepressant pharmacotherapy, we found a less frequent prescription of selective serotonin reuptake inhibitors (SSRIs) in melancholic MDD. No significant between-group differences were found for treatment response, non-response, and resistance. In summary, we explored primarily variables to be associated with melancholia which can be regarded as parameters for the presence of severe/difficult-to treat MDD conditions. Even if there is no evidence to realize any specific treatment strategy in melancholic MDD patients, their prescribed medication strategies were different from those for patients without melancholia.

In clinical practice, an antidepressant prescription is a trial and error approach, which is time consuming and discomforting for patients. This study investigated an in silico approach for ranking antidepressants based on their hypothetical likelihood of efficacy. We predicted the transcriptomic profile of citalopram remitters by performing an in silico transcriptomic-wide association study on STAR*D GWAS data (N = 1163). The transcriptional profile of remitters was compared with 21 antidepressant-induced gene expression profiles in five human cell lines available in the connectivity-map database. Spearman correlation, Pearson correlation, and the Kolmogorov–Smirnov test were used to determine the similarity between antidepressant-induced profiles and remitter profiles, subsequently calculating the average rank of antidepressants across the three methods and a p value for each rank by using a permutation procedure. The drugs with the top ranks were those having a high positive correlation with the expression profiles of remitters and that may have higher chances of efficacy in the tested patients. In MCF7 (breast cancer cell line), escitalopram had the highest average rank, with an average rank higher than expected by chance (p = 0.0014). In A375 (human melanoma) and PC3 (prostate cancer) cell lines, escitalopram and citalopram emerged as the second-highest ranked antidepressants, respectively (p = 0.0310 and 0.0276, respectively). In HA1E (kidney) and HT29 (colon cancer) cell types, citalopram and escitalopram did not fall among top antidepressants. The correlation between citalopram remitters’ and (es)citalopram-induced expression profiles in three cell lines suggests that our approach may be useful and with future improvements, it can be applicable at the individual level to tailor treatment prescription.

BackgroundUp to 60% of patients with major depressive disorder (MDD) do not respond to the first treatment with antidepressants. Response to antidepressants is a polygenic trait, although its underpinning genetics has not been fully clarified. This study aimed to investigate if Polygenic Risk Scores (PRSs) for major psychiatric disorders and neuroticism were associated with non-response or resistance to antidepressants in MDD.MethodsPRSs for bipolar disorder, MDD, neuroticism, and schizophrenia (SCZ) were computed in 1148 MDD patients recruited by the European Group for the Study of Resistant Depression. Summary statistics from largest meta-analyses of genome-wide association studies were used as base data. Patients were classified as responders, non-responders to one treatment, non-responders to two or more treatments (treatment-resistant depression or TRD). Regression analyses were adjusted for population stratification and recruitment sites.ResultsPRSs did not predict either non-response or TRD after Bonferroni correction. However, SCZ-PRS was nominally associated with non-response (p=0.003). Patients in the highest SCZ-PRS quintile were more likely to be non-responders than those in the lowest quintile (OR=2.23, 95% CI=1.21-4.10, p=0.02). Patients in the lowest SCZ-PRS quintile showed higher response rates when they did not receive augmentation with second-generation antipsychotics (SGAs), while those in the highest SCZ-PRS quintile had a poor response independently from the treatment strategy (p=0.009).ConclusionsA higher genetic liability to SCZ may reduce responsiveness to pharmacological treatment in MDD. From a clinical point of view, our results suggest that MDD patients with low SCZ-PRS do not benefit from augmentation with SGAs.

Since many patients with major depressive disorder (MDD) do not satisfactorily respond to initial antidepressant monotherapy, add-on treatment strategies with other psychiatric compounds are often established. The present European multicenter cross-sectional study comprising 1410 MDD in- and outpatients investigated the prescription pattern of benzodiazepines as add-on treatment in the psychopharmacotherapy of MDD. Analyses of variance, chi-squared tests, and logistic regression analyses were conducted to examine differences in socio-demographic, clinical, and treatment characteristics between benzodiazepine users and non-users. The prescription rate for adjunctive benzodiazepine treatment amounted to 31.35%. The most often administered benzodiazepines were lorazepam (11.13%), clonazepam (6.74%), and alprazolam (6.60%). Benzodiazepine users exhibited more severe depressive symptoms expressed by a higher mean Montgomery and Åsberg Depression Rating Scale total score at study entry (26.92 ± 11.07 vs 23.55 ± 11.23, p

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects.CYP2C19 phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was percentage symptom improvement and remission. Side effect data were available at weeks 2–4, 6 and 9 in three of the investigated samples. A fixed-effects meta-analysis was performed using EM as the reference group.Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD=0.43, CI=0.19–0.66) and higher remission rates (OR=1.55, CI=1.23–1.96) compared to EMs. At weeks 2–4, PMs showed higher risk of gastro-intestinal (OR=1.26, CI=1.08–1.47), neurological (OR=1.28, CI=1.07–1.53) and sexual side effects (OR=1.52, CI=1.23–1.87; week 6 values similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups.CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs are relatively rare among Caucasians (~2%).

Background: One-third of depressed patients develop treatment-resistant depression with the related sequelae in terms of poor functionality and worse prognosis. Solid evidence suggests that genetic variants are potentially valid predictors of antidepressant efficacy and could be used to provide personalized treatments. Methods: The present review summarizes genetic findings of treatment-resistant depression including results from candidate gene studies and genome-wide association studies. The limitations of these approaches are discussed, and suggestions to improve the design of future studies are provided. Results: Most studies used the candidate gene approach, and few genes showed replicated associations with treatment-resistant depression and/or evidence obtained through complementary approaches (e.g. gene expression studies). These genes included GRIK4, BDNF, SLC6A4, and KCNK2, but confirmatory evidence in large cohorts was often lacking. Genome-wide association studies did not identify any genome-wide significant association at variant level, but pathways including genes modulating actin cytoskeleton, neural plasticity, and neurogenesis may be associated with treatment-resistant depression, in line with results obtained by genome-wide association studies of antidepressant response. The improvement of aggregated tests (e.g. polygenic risk scores), possibly using variant/gene prioritization criteria, the increase in the covering of genetic variants, and the incorporation of clinical-demographic predictors of treatment-resistant depression are proposed as possible strategies to improve future pharmacogenomic studies. Conclusions: Genetic biomarkers to identify patients with higher risk of treatment-resistant depression or to guide treatment in these patients are not available yet. Methodological improvements of future studies could lead to the identification of genetic biomarkers with clinical validity., SCOPUS: ar.j, info:eu-repo/semantics/published

Background Schizophrenia is a highly heritable disorder and the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) identified 108 loci with genome-wide association with broad schizophrenia diagnosis. Schizophrenia is a clinically complex entity and the role of these 108 loci in modulating specific clinical features of the disease is still unknown. This study investigated which symptom dimensions may be affected by these loci in schizophrenia and bipolar disorder. Methods Positive, negative and depressive symptoms, suicidal ideation, cognition, violent behaviors, quality of life and early onset were investigated in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) samples. Only white subjects were included to avoid possible confounding from ancestry stratification. Imputation of genotypes was carried out after standard quality control using the Haplotype Reference Consortium panel as reference. Individual loci were investigated using linear or logistic regression, then genes within 50 Kbp from polymorphisms with p Results 89 polymorphisms among the 108 of interest were available in both samples, 479 and 810 white subjects were included from CATIE and STEP-BD, respectively. rs75059851 (IGSF9B gene) was associated with negative symptoms in CATIE (p=0.00048); no other variants survived after multiple-testing correction. rs1023500 (CENPM gene) showed a trend of association with early onset with consistent direction in both samples (p=0.033 in STEP-BD and p=0.073 in CATIE). GeneMania analysis showed that negative symptoms and suicidal ideation had a relevant enrichment of Gene Ontology (GO) terms related to acetylcholine neurotransmission, monoamines and ion channel activity while pyridoxal phosphate binding and fucose metabolism showed enrichment for cognition. GO terms referred to processes involved in extracellular matrix structure were found enriched for early onset. PRS showed nominal associations with violent behaviors (p=0.034, Nagelkerke's R2=0.014) and depressive symptoms (p=0.04, R2=0.009). Discussion This study provided preliminary evidence that a schizophrenia-associated variant in the IGSF9B (immunoglobulin superfamily member 9B) gene may modulate negative symptoms. IGSF9B is involved in GABAergic signaling and it may mediate negative symptoms by affecting depression and cognition. A polymorphism in the CENPM (centromere protein M) gene showed an interesting trend of association with early onset. CENPM encodes for an inner protein of the kinetochore, the multi-protein complex that binds spindle microtubules to regulate chromosome segregation during cell division. Multi-locus models may provide interesting insights about the biological mechanisms that medicate specific symptom domains and the genetic overlap between schizophrenia and bipolar disorder.

Genes belonging to neuroplasticity, monoamine, circadian rhythm, and transcription factor pathways were investigated as modulators of antidepressant efficacy. The present study aimed (1) to replicate previous findings in an independent sample with treatment-resistant depression (TRD), and (2) to perform a pathway analysis to investigate the possible molecular mechanisms involved. 220 patients with major depressive disorder who were non-responders to a previous antidepressant were treated with venlafaxine for 4–6 weeks and in case of non-response with escitalopram for 4–6 weeks. Symptoms were assessed using the Montgomery Asberg Depression Rating Scale. The phenotypes were response and remission to venlafaxine, non-response (TRDA) and non-remission (TRDB) to neither venlafaxine nor escitalopram. 50 tag SNPs in 14 genes belonging to the pathways of interest were tested for association with phenotypes. Molecular pathways (KEGG database) that included one or more of the genes associated with the phenotypes were investigated also in the STAR*D sample. The associations between ZNF804A rs7603001 and response, CREB1 rs2254137 and remission were replicated, as well as CHL1 rs2133402 and lower risk of TRD. Other CHL1 SNPs were potential predictors of TRD (rs1516340, rs2272522, rs1516338, rs2133402). The MAPK1 rs6928 SNP was consistently associated with all the phenotypes. The protein processing in endoplasmic reticulum pathway (hsa04141) was the best pathway that may explain the mechanisms of MAPK1 involvement in antidepressant response. Signals in genes previously associated with antidepressant efficacy were confirmed for CREB1, ZNF804A and CHL1. These genes play pivotal roles in synaptic plasticity, neural activity and connectivity.

none 11 no Several antipsychotics and antidepressants have been associated with QTc prolongation or other electrocardiogram (ECG) alterations, but their impact is still debated and other risk factors are known to affect QTc. We investigated the effect of antidepressants and antipsychotics on QTc and other ECG intervals/waves in three samples. Two discovery samples (cross-sectional sample n = 145 and prospective sample n = 68, naturalistic treatment) and a replication prospective sample (Clinical Antipsychotic Trials of Intervention Effectiveness, n = 515, randomized treatment) were analysed. In both prospective samples, baseline/follow-up changes in ECG parameters were analysed in relation to the number of psychotropic drugs stratified according to their known cardiovascular risk. In the cross-sectional sample, ECG parameters were compared among drugs with different risk profile. The possible effect of single nucleotide polymorphisms (SNPs) in the CACNA1C gene on QTc was also investigated. There was no evidence of mean QTc prolongation or increased risk of clinically relevant QTc prolongation (≥20 msec.) in association with psychotropic drugs stratified according to their known cardiovascular risk. The prescription of drugs with cardiovascular risk was less common in older individuals or individuals with cardiovascular comorbidities. Other factors (gender, baseline QTc, renal function) affected QTc. rs1006737 and SNPs in linkage disequilibrium with it modulated QTc duration/changes in all samples. An association between risk drugs and shorter RR interval or higher heart rate was found in all samples. A relevant effect of psychotropic drugs with cardiovascular risk on QTc duration was not observed. A number of factors other than psychotropic drugs may influence QTc. CACNA1C rs1006737 may modulate QTc in patients treated with psychotropic drugs. none Fabbri, Chiara; Boriani, Giuseppe; Diemberger, Igor; Filippi, Maria Giulia; Ravegnini, Gloria; Hrelia, Patrizia; Minarini, Alessandro; Albani, Diego; Forloni, Gianluigi; Angelini, Sabrina; Serretti, Alessandro Fabbri, Chiara; Boriani, Giuseppe; Diemberger, Igor; Filippi, Maria Giulia; Ravegnini, Gloria; Hrelia, Patrizia; Minarini, Alessandro; Albani, Diego; Forloni, Gianluigi; Angelini, Sabrina; Serretti, Alessandro

Second generation antipsychotics (SGAs) are effective options in the treatment of schizophrenia and mood disorders, each with characteristic efficacy and safety features. In order to optimize the balance between efficacy and side effects, it is of upmost importance to match compound specificity against patient clinical profile. As the number of SGAs increased, this review can assist physicians in the prescription of three novel SGAs already on the market, namely lurasidone, brexpiprazole, cariprazine, and lumateperone, which is in the approval phase for schizophrenia treatment at the FDA. Besides schizophrenia, EMA and/or FDA approved lurasidone for bipolar depression, brexpiprazole as augmentation in major depressive disorder and cariprazine for the acute treatment of manic or mixed episodes associated with bipolar I disorder. These new antipsychotics were developed with the aim of improving efficacy on negative and depressive symptoms and reducing metabolic and cardiovascular side effects compared to prior SGAs, while keeping the risk of extrapyramidal symptoms low. They succeeded quite well in containing these side effects, despite weight gain during acute treatment remains a possible concern for brexpiprazole, while cariprazine and lurasidone show higher risk of akathisia compared to placebo and other SGAs such as olanzapine. The available studies support the expected benefits on negative symptoms, cognitive dysfunction and depressive symptoms, while the overall effect on acute psychotic symptoms may be similar to other SGAs such as quetiapine, aripiprazole and ziprasidone. The discussed new antipsychotics represent useful therapeutic options but their efficacy and side effect profiles should be considered to personalize prescription.

Shared genetic vulnerability between schizophrenia (SCZ) and bipolar disorder (BP) was demonstrated, but the genetic underpinnings of specific symptom domains are unclear. This study investigated which genes and gene sets may modulate specific psychopathological domains and if genome-wide significant loci previously associated with SCZ or BP may play a role. Genome-wide data were available in patients with SCZ (n = 226) or BP (n = 228). Phenotypes under investigation were depressive and positive symptoms severity, suicidal ideation, onset age and substance use disorder comorbidity. Genome-wide analyses were performed at gene and gene set level, while 148 genome-wide significant loci previously associated with SCZ and/or BP were investigated. Each sample was analyzed separately then a meta-analysis was performed. SH3GL2 and CLVS1 genes were associated with suicidal ideation in SCZ (p = 5.62e-08 and 0.01, respectively), the former also in the meta-analysis (p = .01). SHC4 gene was associated with depressive symptoms severity in BP (p = .003). A gene set involved in cellular differentiation (GO:0048661) was associated with substance disorder comorbidity in the meta-analysis (p = .03). Individual loci previously associated with SCZ or BP did not modulate the phenotypes of interest. This study provided confirmatory and new findings. SH3GL2 (endophilin A1) showed a role in suicidal ideation that may be due to its relevance to the glutamate system. SHC4 regulates BDNF-induced MAPK activation and was previously associated with depression. CLVS1 is involved in lysosome maturation and was for the first time associated with a psychiatric trait. GO:0048661 may mediate the risk of substance disorder through an effect on neurodevelopment/neuroplasticity.

About 20–30% of patients with major depressive disorder (MDD) develop treatment-resistant depression (TRD) and finding new effective treatments for TRD has been a challenge. This study aimed to identify new possible pharmacological options for TRD. Genes in pathways included in predictive models of TRD in a previous whole exome sequence study were compared with those coding for targets of drugs in any phase of development, nutraceuticals, proteins and peptides from Drug repurposing Hub, Drug-Gene Interaction database and DrugBank database. We tested if known gene targets were enriched in TRD-associated genes by a hypergeometric test. Compounds enriched in TRD-associated genes after false-discovery rate (FDR) correction were annotated and compared with those showing enrichment in genes associated with MDD in the last Psychiatric Genomics Consortium genome-wide association study. Among a total of 15,475 compounds, 542 were enriched in TRD-associated genes (FDR p < .05). Significant results included drugs which are currently used in TRD (e.g. lithium and ketamine), confirming the rationale of this approach. Interesting molecules included modulators of inflammation, renin-angiotensin system, proliferator-activated receptor agonists, glycogen synthase kinase 3 beta inhibitors and the rho associated kinase inhibitor fasudil. Nutraceuticals, mostly antioxidant polyphenols, were also identified. Drugs showing enrichment for TRD-associated genes had a higher probability of enrichment for MDD-associated genes compared to those having no TRD-genes enrichment (p = 6.21e-55). This study suggested new potential treatments for TRD using a in silico approach. These analyses are exploratory only but can contribute to the identification of drugs to study in future clinical trials.

Major depressive disorder (MDD) is a heritable disease with a heavy personal and socio-economic burden. Antidepressants of different classes are prescribed to treat MDD, but reliable and reproducible markers of efficacy are not available for clinical use. Further complicating treatment, the diagnosis of MDD is not guided by objective criteria, resulting in the risk of under- or overtreatment. A number of markers of MDD and antidepressant response have been investigated at the genetic, epigenetic, gene expression and protein levels. Polymorphisms in genes involved in antidepressant metabolism (cytochrome P450 isoenzymes), antidepressant transport (ABCB1), glucocorticoid signalling (FKBP5) and serotonin neurotransmission (SLC6A4 and HTR2A) were among those included in the first pharmacogenetic assays that have been tested for clinical applicability. The results of these investigations were encouraging when examining patient-outcome improvement. Furthermore, a nine-serum biomarker panel (including BDNF, cortisol and soluble TNF-α receptor type II) showed good sensitivity and specificity in differentiating between MDD and healthy controls. These first diagnostic and response-predictive tests for MDD provided a source of optimism for future clinical applications. However, such findings should be considered very carefully because their benefit/cost ratio and clinical indications were not clearly demonstrated. Future tests may include combinations of different types of biomarkers and be specific for MDD subtypes or pathological dimensions.

Background Large sample sizes are often required to detect statistically significant associations between pharmacogenetic markers and treatment response. Meta-analysis may be performed to synthesize data from several studies, increasing sample size and, consequently, power to detect significant genetic effects. However, performing robust synthesis of data from pharmacogenetic studies is often challenging because of poor reporting of key data in study reports. There is currently no guideline for the reporting of pharmacogenetic studies that has been developed using a widely accepted robust methodology. The objective of this project was to develop the STrengthening the Reporting Of Pharmacogenetic Studies (STROPS) guideline. Methods and findings We established a preliminary checklist of reporting items to be considered for inclusion in the guideline. We invited representatives of key stakeholder groups to participate in a 2-round Delphi survey. A total of 52 individuals participated in both rounds of the survey, scoring items with regards to their importance for inclusion in the STROPS guideline. We then held a consensus meeting, at which 8 individuals considered the results of the Delphi survey and voted on whether each item ought to be included in the final guideline. The STROPS guideline consists of 54 items and is accompanied by an explanation and elaboration document. The guideline contains items that are particularly important in the field of pharmacogenetics, such as the drug regimen of interest and whether adherence to treatment was accounted for in the conducted analyses. The guideline also requires that outcomes be clearly defined and justified, because in pharmacogenetic studies, there may be a greater number of possible outcomes than in other types of study (for example, disease–gene association studies). A limitation of this project is that our consensus meeting involved a small number of individuals, the majority of whom are based in the United Kingdom. Conclusions Our aim is for the STROPS guideline to improve the transparency of reporting of pharmacogenetic studies and also to facilitate the conduct of high-quality systematic reviews and meta-analyses. We encourage authors to adhere to the STROPS guideline when publishing pharmacogenetic studies., Marty Chaplin and co-authors recount the development of a guideline for reporting pharmacogenetic studies.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.The Pharmacogenomics Journal advance online publication, 21 November 2017; doi:10.1038/tpj.2017.44.

Mental illness represents a major health issue both at the individual and at the socioeconomical level. This is partly due to the current suboptimal treatment options: existing psychotropic medications, including antidepressants, antipsychotics, and mood stabilizers, are effective only in a subset of patients or produce partial response and they are often associated with debilitating side effects that discourage adherence. Pharmacogenetics is the study of how genetic information impacts on drug response/side effects with the goal to provide tailored treatments, thereby maximizing efficacy and tolerability. The first pharmacogenetic studies focused on candidate genes, previously known to be relevant to the pharmacokinetics and pharmacodynamics of psychotropic drugs. Results were mainly inconclusive, but some replicated candidates were identified and included as pharmacogenetic biomarkers in drug labeling and in some commercial kits. With the advent of the genomic revolution, it became possible to study the genetic variation on an unprecedented scale, throughout the whole genome with no need of a priori hypothesis. This may lead to the personalized prescription of existing medications and potentially to the development of innovative ones, thanks to new insights into the genetics of mental illness. Promising findings were obtained, but methods for the generation and analysis of genome-wide and sequencing data are still in evolution. Future pharmacogenetic tests may consist of hundreds/thousands of polymorphisms throughout the genome or selected pathways in order to take into account the complex interactions across variants in a number of genes.

Major depressive disorder is one of the most prevalent and life-threatening forms of mental illnesses and a major cause of morbidity worldwide. Currently available antidepressants are effective for most patients, although around 30% are considered treatment resistant (TRD), a condition that is associated with a significant impairment of cognitive function and poor quality of life. In this respect, the identification of the molecular mechanisms contributing to TRD represents an essential step for the design of novel and more efficacious drugs able to modify the clinical course of this disorder and increase remission rates in clinical practice. New insights into the neurobiology of TRD have shed light on the role of a number of different mechanisms, including the glutamatergic system, immune/inflammatory systems, neurotrophin function, and epigenetics. Advances in drug discovery processes in TRD have also influenced the classification of antidepressant drugs and novel classifications are available, such as the neuroscience-based nomenclature that can incorporate such advances in drug development for TRD. This review aims to provide an up-to-date description of key mechanisms in TRD and describe current therapeutic strategies for TRD before examining novel approaches that may ultimately address important neurobiological mechanisms not targeted by currently available antidepressants. All in all, we suggest that drug targeting different neurobiological systems should be able to restore normal function but must also promote resilience to reduce the long-term vulnerability to recurrent depressive episodes.

The empirical approach to drug choice and dosing in depression often results into inadequate response and side effects. Pharmacogenetic (PGx) testing appears a promising way to implement personalized treatments. A systematic review was performed to identify available PGx tests, compare the genes they include with clinical guidelines and drug labels, and assess the quality of published clinical studies. ~40 commercial PGx tests are available and potential benefits were estimated for nine of them by clinical studies. The most part of studies are observational (9/21) or non-randomized case-control trials that compared standard care with PGx-guided treatment (6/21), six randomized controlled trials (RCTs) are available. The only genes included in all the available PGx tests and with recommendations in current clinical guidelines and drug labels are CYP2D6 and CYP2C19. There is heterogeneity among outcome measures across studies (response, remission, improvement, health care utilization, medication tolerability), as well as in trial design. Relatively weak clinical benefits were reported by RCTs and higher clinical benefits by non-RCTs, but the last group showed greater risk of bias. Lack of patient and rater's blindness, retrospective design and possible confounders (concomitant medications and medical diseases, lack of wash out prior to inclusion, no assessment of compliance etc.) were the main issues. Estimations of cost savings provided heterogeneous findings. Variants in CYP2D6 and CYP2C19 have already adequate support for clinical application. The development of future PGx tests should include best practices for clinical evidence development and for health economic assessment.