Genetics of suicide ideation. A role for inflammation and neuroplasticity?

Suicide is a leading cause of death worldwide. Suicide ideation (SI) is a known risk factor for suicide behaviour (SB). The current psychobiology and genetic predisposition to SI and SB are poorly defined. Despite convincing relevance of a genetic background for SI, there is no current implementable knowledge about the genetic makeup that identifies subjects at risk for it. One of the possible reasons for the absence of a clear-cut evidence is the polygenetic nature of SI along with the very large sample sizes that are needed to observe significant genetic association result. The CATIE sample was instrumental to the analysis. SI was retrieved as measured by the Calgary test. Clinical possible covariates were identified by a nested regression model. A principal component analysis helped in defining the possible genetic stratification factors. A GWAS analysis, polygenic risk score associated with a random forest analysis and a molecular pathway analysis were undertaken to identify the genetic contribution to SI. As a result, 741 Schizophrenic individuals from the CATIE were available for the genetic analysis, including 166,325 SNPs after quality control and pruning. No GWAS significant result was found. The random forest analysis conducted by combining the polygenic risk score and several clinical variables resulted in a possibly overfitting model (OOB error rate < 1%). The molecular pathway analysis revealed several molecular pathways possibly involved in SI, of which those involved in microglia functioning were of particular interest. A medium-small sample of SKZ individuals was analyzed to shed a light on the genetic of SI. As an expected result from the underpowered sample, no GWAS positive result was retrieved, but the molecular pathway analysis indicated a possible role of microglia and neurodevelopment in SI.

Genetic signatures of suicide attempt behavior: insights and applications.

INTRODUCTION: Every year about 800,000 complete suicide events occur. The identification of biologic markers to identify subjects at risk would be helpful in targeting specific support treatments. AREA COVERED: A narrative review defines the meta-analytic level of current evidence about the biologic markers of suicide behavior (SB). The meta-analytic evidence gathered so far indicates that the hypothesis-driven research largely failed to identify the biologic markers of suicide. The most consistent and replicated result was reported for: 1) 5-HTR2A T102C, associated with SB in patients with schizophrenia (OR = 1.73 (1.11-2.69)) and 2) BDNF Val66Met (rs6265), with the Met-Val + Val-Val carriers found to be at risk for suicide in the Caucasian population (OR: 1.96 (1.58-2.43)), while Val-Val vs. Val-Met + Met carriers found to be at risk for suicide in the Asian populations (OR: 1.36 (1.04-1.78)). GWAS-based meta-analyses indicate some positive replicated findings regarding the DRD2, Neuroligin gene, estrogen-related genes, and genes involved in gene expression. EXPERT OPINION: Most consistent results were obtained when analyzing sub-samples of patients. Some promising results come from the implementation of the polygenic risk score. There is no current consensus about an implementable biomarker for SB.

Music to improve sleep quality in adults with depression-related insomnia (MUSTAFI): randomized controlled trial.

BACKGROUND: Insomnia in depression is common and difficult to resolve. Unresolved depression-related sleep disturbances increase risk of relapse at high costs for individuals and society. Trials have suggested music for insomnia in various populations, but there is little research on the effectiveness of music for depression-related insomnia. METHODS: We examined the efficacy of a music intervention on insomnia, depression symptoms and quality of life in adults with depression-related insomnia. A two-armed randomized controlled trial was conducted, including depression outpatients with insomnia (n = 112) in a 1:1 ratio to music intervention and waitlist control group. The intervention group listened to music at bedtime for 4 weeks. Participants received treatment as usual during 8 weeks with assessments at baseline, at 4 and 8 weeks. The primary outcome measure was Pittsburgh Sleep Quality Index (PSQI), secondary outcomes comprised Actigraphy, the Hamilton Depression Rating Scale (HAMD-17) and World Health Organisation well-being questionnaires (WHO-5, WHOQOL-BREF). RESULTS: The music intervention group experienced significant improvements in sleep quality and well-being at 4 weeks according to global PSQI scores (effect size = -2.1, 95%CI -3.3; -0.9) and WHO-5 scores (effect size 8.4, 95%CI 2.7;14.0). At 8 weeks, i.e. 4 weeks after termination of the music intervention, the improvement in global PSQI scores had decreased (effect size = -0.1, 95%CI -1.3; 1.1). Actigraphy sleep assessments showed no changes and there was no detection of change in depression symptoms. CONCLUSIONS: Music intervention is suggested as a safe and moderately effective sleep aid in depression-related insomnia. Trial registration: Clinicaltrials.gov. ID NCT03676491.

Body weight changes and bipolar disorder: a molecular pathway analysis.

BACKGROUND: There is evidence suggesting a link between weight-related disorders and bipolar disorder (BD). The pathophysiology of the association includes psychological, social and psychotropic treatment-related variables, together with psychiatric comorbidity. Weight changes during BD may influence compliance to the treatment, quality of life and prognosis, and can modulate risk of death associated with, for example, diabetes or cardiovascular disorders. METHODS: The STEP-BD sample is analyzed through a hypothesis-free molecular pathway analysis in order to detect the molecular pathways that distinguish individuals who experience weight change during BD treatment from those who do not. A total of 618 individuals were available for the analysis, mean age = 41.19 ± 12.58, females = 351 (56.8%). Socioeconomic variables and treatment-related variables were included as clinical covariates. A cluster analysis in the genetic dataset provided the genetic covariate input to the study to avoid stratification factors. RESULT: After applying the quality analysis that is typical for this kind of investigation, no Genome Wide Association Study significant finding was retrieved. Six molecular pathways were found to be significantly associated with weight change during the first 3 months of treatment after correction for multiple testing. Of those, CDC42 (R-HSA-9013148) participates in insulin synthesis and secretion and contributes to the pathogenesis of insulin resistance and Rac Family Small GTPase 1 (R-HSA-9013149) is involved in metabolic regulation of pancreatic islet ß-cells and in diabetes pathophysiology. DISCUSSION: Pathways that are central in energy homeostasis may play a role to separate individuals with BD that will experience weight changes during treatment from those who will not. If confirmed, such finding can be instrumental in the identification of the correct preventive strategies and most correct treatment to increase compliance and efficacy in the treatment of BD.

Suicide Related Phenotypes in a Bipolar Sample: Genetic Underpinnings.

Suicide in Bipolar Disorder (BD) is a relevant clinical concern. Genetics may shape the individual risk for suicide behavior in BD, together with known clinical factors. The lack of consistent replication in BD may be associated with its multigenetic component. In the present contribution we analyzed a sample of BD individuals (from STEP-BD database) to identify the genetic variants potentially associated with three different suicide-related phenotypes: (1) a feeling that the life was not worth living; (2) fantasies about committing a violent suicide; (3) previous attempted suicide. The sample under analysis included 1115 BD individuals. None of the SNPs reached genome-wide significance. However, a trend of association was evidenced for rs2767403, an intron variant of AOPEP gene, in association with phenotype #1 (p = 5.977 × 10-6). The molecular pathway analysis showed a significant enrichment in all the investigated phenotypes on pathways related to post synaptic signaling, neurotransmission and neurodevelopment. Further, NOTCH signaling or the γ-aminobutyric acid (GABA)-ergic signaling were found to be associated with specific suicide-related phenotypes. The present investigation contributes to the hypothesis that the genetic architecture of suicide behaviors in BD is related to alteration of entire pathways rather than single genes. In particular, our molecular pathway analysis points on some specific molecular events that could be the focus of further research in this field.

Molecular pathway analysis associates alterations in obesity-related genes and antipsychotic-induced weight gain.

OBJECTIVE: Antipsychotics often induce excessive weight gain. We hypothesised that individuals with genetic variations related to known obesity-risk genes have an increased risk of excessive antipsychotic-induced weight gain (AIWG). This hypothesis was tested in a subset of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) trial data set. METHODS: The CATIE trial compared effects and side effects of five different antipsychotics through an 18-month period. Based on the maximum weight gain recorded, excessive weight gain was defined as >7% weight gain. Cytoscape and GeneMANIA were instrumental in composing a molecular pathway from eight selected genes linked to obesity. Genetic information on a total of 495.172 single-nucleotide polymorphisms (SNPs) were available from 765 (556 males) individuals. Enrichment test was conducted through ReactomePA and Bioconductor. A permutation test was performed, testing the generated pathway against 105 permutated pathways (p ≤ 0.05). In addition, a standard genome-wide association study (GWAS) analysis was performed. RESULT: GWAS analysis did not detect significant differences related to excessive weight gain. The pathway generated contained 28 genes. A total of 2067 SNPs were significantly expressed (p < 0.01) within this pathway when comparing excessive weight gainers to the rest of the sample. Affected genes including PPARG and PCSK1 were not previously related to treatment-induced weight gain. CONCLUSIONS: The molecular pathway composed from high-risk obesity genes was shown to overlap with genetics of patients who gained >7% weight gain during the CATIE trial. This suggests that genes related to obesity compose a pathway of increased risk of excessive AIWG. Further independent analyses are warranted that may confirm or clarify the possible reasoning behind.

Enriched developmental biology molecular pathways impact on antipsychotics-induced weight gain.

Psychotropic-induced weight gain (PIWG) may lead to increased risk for cardiovasculardiseases, metabolic disorders and treatment discontinuation. PIWG may be genetically driven. The analysis of complete molecular pathways may grant suffcient power to tackle the biologic variance of PIWG. Such identifcation would help to move a step forward in the direction of personalized treatment in psychiatry. A genetic sample from the CATIE trial (n = 765; M = 556, mean age = 40.93 ± 11.03) treated with diverse antipsychotic drugs was investigated. A molecular pathway analysis was conducted for the identifcation of the molecular pathways enriched in variations associated with PIWG. The developmental biology molecular pathway was signifcantly (P.adj = 0.018) enriched in genetic variations signifcantly (P < 0.01) associated with PIWG. A total of 18 genes were identifed and discussed. The developmental biology molecular pathway is involved in the regulation of ß-cell development, and the transcriptional regulation of white adipocyte differentiation. Results from the current contribution correlate with previous evidence and it is consistent with our earlier result on the STAR*D sample. Furthermore, the involvement of the ß-cell development and the transcriptional regulation of white adipocyte differentiation pathways stress the relevance of the peripheral tissue rearrangement, rather than increased food intake, in the biologic modifcations that follow psychotropic treatment and may lead to PIWG. Further research is warranted.

A molecular pathway analysis informs the genetic risk for arrhythmias during antipsychotic treatment.

Arrhythmias are a frequent and potentially fatal side effect of antipsychotic treatment. Strict ECG monitoring and clinical interviews are the standards used to prevent arrhythmias. A biologic predictive tool is missing. The identification of a genetic makeup at risk of antipsychotic-induced arrhythmias is the aim of the present investigation. The aim of this study was to identify a molecular pathway enriched in single nucleotide polymorphisms associated with antipsychotic-induced QTc modifications. In total, 661 schizophrenic individuals from the CATIE study, M=486 (73.52%), mean age=40.92±11.02, were included. QTc variation was measured as a phase-specific change-created variable. A nested mixed regression for a repeated-measures model served in R for the analysis of the clinical and treatment-related covariates and molecular pathway analysis. Plink was used for the genetic genome-wide analysis. Quality checking was the standard (genotype call rate>0.95; minor allele frequency>0.01; Hardy-Weinberg equilibrium<0.0001) and the inflation factor was controlled by λ values. Quetiapine and perphenazine were associated with QTc variation during phase 1. No other significant association was detected. No significant inflation was detected. A number of molecular pathways were associated with QT variation at a conservative (adjusted) P value less than 0.05, including pathways related to neuronal wiring and collagen biosynthesis, along with pathways related to K+ currents and cardiac contraction. Pathways related to neuronal wiring, collagen biosynthesis, and ion currents were identified as possibly involved in QTc modifications during antispsychotic treatment in SKZ patients.

A molecular pathway analysis stresses the role of inflammation and oxidative stress towards cognition in schizophrenia.

Cognitive processes have a genetic component and are impaired in Schizophrenia (SKZ). The exact nature of such impairment escapes definition. The aim of the present contribution was the identification of the molecular pathways enriched with mutations (SNPs) associated with cognitive performance during antipsychotic treatment. 765 individuals from the CATIE study, males = 559, mean age 40.93 ± 11.03 were included. Working memory and the verbal memory were the evaluated outcomes. A mixed regression model for repeated measures served in R for clinical and molecular pathway analysis. The analysis of quality was conducted under the following criteria: minor allele frequency >0.01, genotype call rate >95%, missing data frequency <5%, Hardy-Weimberg equilibrium threshold >0.0001. The inflation factor was controlled by lambda values. Input for the pathway analysis was SNPs at a p level <0.05 of association genome-wide. Gender, age, education and the duration of the disease were the clinical and socio-demographic variables associated with the cognitive performance. 4268977 SNPs were available after imputation and quality analysis. Pathways related to inflammation and oxidation were the most strongly associated with verbal memory and working memory at a conservative adjusted p value < 0.01. We report that inflammation and in particular the pathway associated with arachidonic acid was enriched in mutations associated with poorer performance at the verbal memory and working memory tasks in SKZ patients.

Insight gained from genome-wide interaction and enrichment analysis on weight gain during citalopram treatment.

Weight gain is a possible side effect of the pharmacological antidepressant treatments. Defining antidepressant prescriptions based on personal genetic makeups would decrease the risk of weight gain and increase the quality of the current antidepressant pharmacological treatments. 643 depressed, citalopram treated individuals with available clinical and genome-wide genetic information were investigated to identify the molecular pathways associated with weight gain. 111 individuals experienced weight gain during citalopram treatment. The axon guidance (p.adjust=0.005) and the developmental biology pathway (p.adjust=0.01) were enriched in variations associated with weight gain. The developmental biology pathway includes molecular cascades involved in the regulation of beta-cell development, and the transcriptional regulation of white adipocyte differentiation. A number of variations were harbored by genes whose products are involved in the synthesis of collagen (COL4A3, COL5A1 and ITGA1), activity of the thyroid-hormones (NCOR1 and NCOR2), energy metabolism (ADIPOQ, PPARGC1A) and myogenic differentiation (CDON). A molecular pathway analysis conducted in a sample of depressed patients identified new candidate genes whose future investigation may provide insights in the molecular events that drive weight gain during antidepressant treatment.

The microtubule-associated molecular pathways may be genetically disrupted in patients with Bipolar Disorder. Insights from the molecular cascades.

Bipolar Disorder is a severe disease characterized by pathological mood swings from major depressive episodes to manic ones and vice versa. The biological underpinnings of Bipolar Disorder have yet to be defined. As a consequence, pharmacological treatments are suboptimal. In the present paper we test the hypothesis that the molecular pathways involved with the direct targets of lithium, hold significantly more genetic variations associated with BD. A molecular pathway approach finds its rationale in the polygenic nature of the disease. The pathways were tested in a sample of ∼ 7,000 patients and controls. Data are available from the public NIMH database. The definition of the pathways was conducted according to the National Cancer Institute (http://pid.nci.nih.gov/). As a result, 3 out of the 18 tested pathways related to lithium action resisted the permutation analysis and were found to be associated with BD. These pathways were related to Reelin, Integrins and Aurora. A pool of genes selected from the ones linked with the above pathways was further investigated in order to identify the fine molecular mechanics shared by our significant pathways and also their link with lithium mechanism of action. The data obtained point out to a possible involvement of microtubule-related mechanics.

Hippocampal Pruning as a New Theory of Schizophrenia Etiopathogenesis.

Pruning in neurons has been suggested to be strongly involved in Schizophrenia's (SKZ) etiopathogenesis in recent biological, imaging, and genetic studies. We investigated the impact of protein-coding genes known to be involved in pruning, collected by a systematic literature research, in shaping the risk for SKZ in a case-control sample of 9,490 subjects (Psychiatric Genomics Consortium). Moreover, their modifications through evolution (humans, chimpanzees, and rats) and subcellular localization (as indicative of their biological function) were also investigated. We also performed a biological pathways (Gene Ontology) analysis. Genetics analyses found four genes (DLG1, NOS1, THBS4, and FADS1) and 17 pathways strongly involved in pruning and SKZ in previous literature findings to be significantly associated with the sample under analysis. The analysis of the subcellular localization found that secreted genes, and so regulatory ones, are the least conserved through evolution and also the most associated with SKZ. Their cell line and regional brain expression analysis found that their areas of primary expression are neuropil and the hippocampus, respectively. At the best of our knowledge, for the first time, we were able to describe the SKZ neurodevelopmental hypothesis starting from a single biological process. We can also hypothesize how alterations in pruning fine regulation and orchestration, strongly related with the evolutionary newest (and so more sensitive) secreted proteins, may be of particular relevance in the hippocampus. This early alteration may lead to a mis-structuration of neural connectivity, resulting in the different brain alteration that characterizes SKZ patients.

Genes involved in pruning and inflammation are enriched in a large mega-sample of patients affected by Schizophrenia and Bipolar Disorder and controls.

A molecular pathway analysis has been performed in order to complement previous genetic investigations on Schizophrenia. 4486 Schizophrenic patients and 4477 controls served as the investigation sample. 3521 Bipolar patients and 3195 controls served as replication sample. A molecular pathway associated with the neuronal pruning activity was found to be enriched in subjects with Schizophrenia compared to controls. HLA-C and HLA-DRA had more SNPs associated with both Schizophrenia and Bipolar Disorder than expected by chance.

Enrichment pathway analysis. The inflammatory genetic background in Bipolar Disorder.

INTRODUCTION: The pathophysiology of Bipolar Disorder (BD) is yet to be fully characterized. In the last years attention was focused on neurodevelopment or neurodegenerative events. In this context, hyper- and hypo- activation of inflammatory cascades may play a role in modulating the architecture and function of neuronal tissues. In the present paper we tested the enrichment of molecular pathways related to inflammatory cascades (IL-1, IL-2, IL-6, IL-8, TNF and INF) testing whether genes related to these systems hold more variations associated with the risk for BD than expected. METHODS: ~7000 bipolar patients and controls with genome-wide data available from NIMH dataset were analyzed. SNPs were imputed, checked for quality control, pruned and tested for association (0.01

CRY1 Variations Impacts on the Depressive Relapse Rate in a Sample of Bipolar Patients.

OBJECTIVE: A relevant part of the social and personal burden caused by Bipolar Disorder (BD) is related to depressive phases. Authors investigated the genetic impact of a set of variations located in CRY1, a gene involved in the control of the circadian rhythms, towards depressive episodes in a sample of bipolar patients from the STEP-BD sample. As a secondary analysis, CYR1 variations were analyzed as predictors of sleep disruption. METHODS: 654 bipolar patients were included in the analysis. Data were available genome-wide. The part of the genome coding for the CRY1 was imputed and pruned according to standards in the field. 7 SNPs were available for the analysis. A correction for multitesting was applied and we had sufficient power (0.80) to detect a small-medium effect size (0.22) between two allelic frequencies each one represented by at least 300 subjects. RESULTS: Intronic rs10861688 was associated with the number of depressive events corrected for the times patients were assessed during the period of observation. In particular, AA subjects (n=21) had 4.46±3.15 events, AG (n=141) had 3.08±3.17 and GG (n=342) 2.65±2.97 (p=0.0048, beta=-0.22). No other significant associations were reported. CONCLUSION: We bring further evidence that genes involved in the regulation of circadian rhythms may be relevant to depressive bipolar phases. Independent confirmation analyses are mandatory.

A molecular pathway analysis informs the genetic background at risk for schizophrenia.

BACKGROUND: Schizophrenia is a complex mental disorder marked by severely impaired thinking, delusional thoughts, hallucinations and poor emotional responsiveness. The biological mechanisms that lead to schizophrenia may be related to the genetic background of patients. Thus, a genetic perspective may help to unravel the molecular pathways disrupted in schizophrenia. METHODS: In the present work, we used a molecular pathway analysis to identify the molecular pathways associated with schizophrenia. We collected data of genetic loci previously associated with schizophrenia, identified the genes located in those positions and created the metabolic pathways that are related to those genes' products. These pathways were tested for enrichment (a number of SNPs associated with the phenotype significantly higher than expected by chance) in a sample of schizophrenic patients and controls (4486 and 4477, respectively). RESULTS: The molecular pathway that resulted from the identification of all the genes located in the loci previously found to be associated with schizophrenia was found to be enriched, as expected (permutated p(10(6))=9.9999e-06).We found 60 SNPs amongst 30 different genes with a strong association with schizophrenia. The genes are related to the pathways related to neurodevelopment, apoptosis, vesicle traffic, immune response and MAPK cascade. CONCLUSIONS: The pathway related to the toll-like receptor family seemed to play a central role in the modulation/connection of various pathways whose disruption leads to schizophrenia. This pathway is related to the innate immune system, further stressing the role of immunological-related events in increasing the risk to schizophrenia.

A model to investigate SNPs' interaction in GWAS studies.

Genome-wide association studies (GWAS) are able to identify the role of individual SNPs in influencing a phenotype. Nevertheless, such analysis is unable to explain the biological complexity of several diseases. We elaborated an algorithm that starting from genes in molecular pathways implicated in a phenotype is able to identify SNP-SNP interaction's role in association with the phenotype. The algorithm is based on three steps. Firstly, it identifies the biological pathways (gene ontology) in which the genes under analysis play a role (GeneMANIA). Secondly, it identifies the group of SNPs that best fits the phenotype (and covariates) under analysis, not considering individual SNP regression coefficients but fitting the regression for the group itself. Finally, it operates an analysis of SNP interactions for each possible couple of SNPs within the group. The sensitivity and specificity of our algorithm was validated in simulated datasets (HapGen and Simulate Phenotypes programs). The impact on efficiency deriving from changes in the number of SNPs/patients under analysis, linkage disequilibrium and minor allele frequency thresholds was analyzed. Our algorithm showed a strong stability throughout all analysis operated, resulting in an overall sensitivity of 81.67 % and a specificity of 98.35 %. We elaborated a stable algorithm that may detect SNPs interactions, especially those effects that pass undetected in classical GWAS. This method may contribute to face the two relevant limitations of GWAS: lack of biological informative power and amount of time needed for the analysis.

A molecular pathway analysis of the glutamatergic-monoaminergic interplay serves to investigate the number of depressive records during citalopram treatment.

The efficacy of current antidepressant (AD) drugs for the treatment of major depressive disorder (MDD) lays behind expectations. The correct genetic differentiation between severe and less severe cases before treatment may pave the way to the most correct clinical choices in clinical practice. Genetics may pave the way such identification, which in turns may provide perspectives for the synthesis of new ADs by correcting the molecular unbalances that differentiate severe and less severe depressive patients. We investigated 1,903 MDD patients from the STAR*D study. Outcome was the number of severe depressive records, defined as a Quick Inventory of Depressive Symptomatology (QIDS)-Clinician rated (C) total score >15, corrected for the number of observations for each patient during the first 14 weeks of citalopram treatment. Predictors were the genetic variations harbored by genes involved in the glutamatergic-monoaminergic interplay as defined in a previous work published by our group. Clinical and socio-demographic stratification factor analyses were taken in cases and controls. Covariated linear regression was the statistical model for the analysis. SNPs were analyzed in groups (molecular pathway analysis) testing the hypothesis that the distribution of significant (p < 0.05) associations between SNPs and the outcome segregates within each pathway/gene subset. The best associated results are relative to two signle SNPs, (rs7744492 in AKAP12 p = 0.0004 and rs17046113 in CAMK2D p = 0.0006) and a molecular pathway (cAMP biosynthetic process p = 0.005). After correction for multitesting, none of them resulted to be significantly associated. These results are consistent with previous findings in literature and further stress that the molecular mechanisms targeted by current ADs may not be the key biological variables that differentiate severe from mild depression.

DISC1-TSNAX and DAOA genes in major depression and citalopram efficacy.

BACKGROUND: Major depressive disorder (MDD) is a common disease with high morbidity and still unsatisfying treatment response. Both MDD pathogenesis and antidepressant effect are supposed to be strongly affected by genetic polymorphisms. Among promising candidate genes, distrupted in schizophrenia 1 (DISC1), translin-associated factor X (TSNAX) and D-amino acid oxidase activator (DAOA) were suggested since their regulator role in neurodevelopment, neuroplasticity and neurotransmission, and previous evidence of cross-involvement in major psychiatric diseases. METHODS: The present paper investigated the role of 13 SNPs within the reported genes in MDD susceptibility through a case-control (n=320 and n=150, respectively) study and in citalopram efficacy (n=157). Measures of citalopram efficacy were response (4th week) and remission (12th week). Pharmacogenetic findings were tested in the STAR(⁎)D genome-wide dataset (n=1892) for replication. RESULTS: Evidence of association among rs3738401 (DISC1), rs1615409 and rs766288 (TSNAX) and MDD was found (p=0.004, p=0.0019, and p=0.008, respectively). A trend of association between remission and DISC1 rs821616 and DAOA rs778294 was detected, and confirmation was found for rs778294 by repeated-measure ANOVA (p=0.0008). In the STAR(⁎)D a cluster of SNPs from 20 to 40Kbp from DISC1 findings in the original sample was associated with citalopram response, as well as rs778330 (12,325bp from rs778294). LIMITATIONS: Relatively small size of the original sample and focus on only three candidate genes. CONCLUSIONS: The present study supported a role of DISC1-TSNAX variants in MDD susceptibility. On the other hand, genetic regions around DAOA rs778294 and DISC1 rs6675281-rs1000731 may influence citalopram efficacy.

Genome-wide association study supports the role of the immunological system and of the neurodevelopmental processes in response to haloperidol treatment.

AIM: The aim of the study was to detect the genetic predictors of reseponse to haloperidol. BACKGROUND: Haloperidol is a benchmark drug for the pharmacological treatment of schizophrenia, but the genetics of its efficacy is yet to be elucidated. METHODS: A genome-wide association analysis was carried out in a small sample of patients treated with haloperidol (n=96) and the results were replicated in a larger sample of patients treated with second-generation antipsychotics or perphenazine (final n=169, available from the Clinical Antipsychotic Trials for Intervention Effectiveness study). The Positive and Negative Symptom Scale % score decrease was the outcome in both samples. The period of observation was restricted to 1 month in the replication sample and the most severe cases were included to best balance the replication. The quality control (QC) for the investigation and replication sample included a minor allele frequency at least 0.01, call rate at least 0.95, and Hardy-Weinberg equilibrium P at least 0.0001. The source for imputation was the 1000 Genomes Pilot+HapMap 3 dataset. In total 1 080 870 single nucleotide polymorphisms (SNPs) were available after imputation and QC in the investigation sample. After QC of real genotypes, locus-targeted imputations were restricted to windows of 10 kb on either side of the sentinel SNP in the replication sample. Sentinel SNPs were the most significant findings in the investigation sample. Analysis of variance was the test of choice, PLINK, SNPTEST, and GTOOL were used in the analysis. RESULTS: Two SNPs (rs7912580 and rs2412459) were associated with response in both samples, respectively, located in an intergenic region between the AT-rich interactive domain 5B (ARID5B, MRF1-like) gene and rhotekin 2 (RTKN2) gene, an intronic region located in the eukaryotic translation initiation factor 2α kinase 4 (EIF2AK4) gene (P=1.358e-06 and 0.015 for the Positive and Negative Symptom Scale % total score decrease in the investigation and replication samples, respectively). The direction of association was opposite in the two samples, a finding that is sometimes reported as a flip-flop association. CONCLUSION: Heterozygosis for the ancestral allele was associated with the best improvement in the investigation sample and with poorer outcome in the replication sample. This discrepancy can be because of differences in the replication and investigation sample including the drugs used and the severity at baseline. Nevertheless, this finding is in line with two relevant hypothesis of schizophrenia, related to alterations in the immunological system (RTKN2) and in the neurodevelopment of the central nervous system (EIF2AK4). More studies are warranted to further investigate these associations.