Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the train- ing set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our under- standing of the neurobiological basis of the disorder

SiNoPsis: single nucleotide polymorphisms selection and promoter profiling

Motivation: The selection of a single nucleotide polymorphism (SNP) using bibliographic methods can be a very time-consuming task. Moreover, a SNP selected in this way may not be easily visualized in its genomic context by a standard user hoping to correlate it with other valuable information. Here we propose a web form built on top of Circos that can assist SNP-centered screening, based on their location in the genome and the regulatory modules they can disrupt. Its use may allow researchers to prioritize SNPs in genotyping and disease studies. Results: SiNoPsis is bundled as a web portal. It focuses on the different structures involved in the genomic expression of a gene, especially those found in the core promoter upstream region. These structures include transcription factor binding sites (for promoter and enhancer signals), histones and promoter flanking regions. Additionally, the tool provides eQTL and linkage disequilibrium (LD) properties for a given SNP query, yielding further clues about other indirectly associated SNPs. Possible disruptions of the aforementioned structures affecting gene transcription are reported using multiple resource databases. SiNoPsis has a simple user-friendly interface, which allows single queries by gene symbol, genomic coordinates, Ensembl gene identifiers, RefSeq transcript identifiers and SNPs. It is the only portal providing useful SNP selection based on regulatory modules and LD with functional variants in both textual and graphic modes (by properly defining the arguments and parameters needed to run Circos). Availability and implementation: SiNoPsis is freely available at https://compgen.bio.ub.edu/SiNoPsis/ Supplementary information: Supplementary data are available at Bioinformatics online

Different modulation of RPS6 phosphorylation by risperidone in striatal cells sub populations: involvement of the mTOR pathway in antipsychotic-induced extrapyramidal symptoms in mice

Objective: Acute extrapyramidal symptoms (EPS) are frequent and serious adverse reactions to antipsychotic (AP) drugs. Although the proposed mechanism is an excessive blockade of dopamine D2 receptors in the striatopallidal pathway of the striatum, previous studies implicated the mTOR pathway in the susceptibility to EPS. The objective of the present study is to analyze the mTOR-mediated response to risperidone in subpopulations of striatal neurons and its relationship to risperidone-induced motor side effects. Methods: Two mouse strains (A/J and DBA/2J) with different susceptibility to developing EPS were treated with risperidone 1 mg/kg for three consecutive days. Here we monitored, by double labeling immunohistochemistry, ribosomal protein S6 (rpS6) phosphorylation (Ser235/236 and Ser244/247 sites), a marker of mTOR signaling, in the striatonigral pathway (D1-medium spiny neurons (MSNs)), the striatopallidal pathway (D2-MSNs) and striatal cholinergic interneurons. Results: We found that EPS-resistant DBA/2J mice show higher baseline levels of phosphoactivated rpS6 protein in striatal MSNs, compared with EPS-prone A/J mice. Moreover, risperidone differentially targeted rpS6 phosphorylation in direct and indirect pathway neurons in a strain-specific manner: a significant decrease in the phosphorylation of rpS6 at Ser235/236 and Ser240/244 in DRD1-MSNs EPS-resistant DBA/2J mice after; and a significant increase of phospho-Ser235/236-rpS6 in the striatopallidal pathway of the EPS-prone A/J mice in response to risperidone. Conclusions: Our results reveal the vital role of genetic background in the response to risperidone, and point to the mTOR pathway as an important factor in EPS susceptibility. Keywords: Schizophrenia, Antipsychotic, Risperidone, Extrapyramidal symptoms. mTOR pathway, Striatum, Medium spiny neuron

Inflammatory dysregulation of monocytes in pediatric patients with obsessive-compulsive disorder

BACKGROUND: Although the exact etiology of obsessive-compulsive disorder (OCD) is unknown, there is growing evidence of a role for immune dysregulation in the pathophysiology of the disease, especially in the innate immune system including the microglia. To test this hypothesis, we studied inflammatory markers in monocytes from pediatric patients with OCD and from healthy controls. METHODS: We determined the percentages of total monocytes, CD16+ monocytes, and classical (CD14highCD16-), intermediate (CD14highCD16low), and non-classical (CD14lowCD16high) monocyte subsets in 102 patients with early-onset OCD and in 47 healthy controls. Moreover, proinflammatory cytokine production (GM-CSF, IL-1β, IL-6, IL-8, and TNF-α) was measured by multiplex Luminex analysis in isolated monocyte cultures, in basal conditions, after exposure to lipopolysaccharide (LPS) to stimulate immune response or after exposure to LPS and the immunosuppressant dexamethasone. RESULTS: OCD patients had significantly higher percentages of total monocytes and CD16+ monocytes than healthy controls, mainly due to an increase in the intermediate subset but also in the non-classical monocytes. Monocytes from OCD patients released higher amounts of GM-CSF, IL-1β, IL-6, IL-8, and TNF-α than healthy controls after exposure to LPS. However, there were no significant differences in basal cytokine production or the sensitivity of monocytes to dexamethasone treatment between both groups. Based on monocyte subset distribution and cytokine production after LPS stimulation, patients receiving psychoactive medications seem to have an intermediate inflammatory profile, that is, lower than non-medicated OCD individuals and higher than healthy controls. CONCLUSIONS: These results strongly support the involvement of an enhanced proinflammatory innate immune response in the etiopathogenesis of early-onset OCD

Response to fluoxetine in children and adolescents: a weighted gene co-expression network analysis of peripheral blood

The inconclusive and non-replicated results of pharmacogenetic studies of antidepressant response could be related to the lack of acknowledgement of its mechanism of action. In this scenario, gene expression studies provide and interesting framework to reveal new candidate genes for pharmacogenetic studies or peripheral biomarkers of fluoxetine response. We propose a system biology approach to analyse changes in gene expression induced by eight weeks of treatment with fluoxetine in peripheral blood. 21 naïve child and adolescents participated in the present study. Our analysis include the identification of gene co-expression modules, using Weighted Gene Co-expression Network Analysis (WGCNA), followed by protein-protein interaction (PPi) network construction coupled with functional annotation. Our results revealed two modules of co-expression genes related to fluoxetine treatment. The constructed networks from these modules were enriched for biological processes related to cellular and metabolic processes, cell communication, immune system processes, cell death, response to stimulus and neurogenesis. Some of these processes, such as immune system, replicated previous findings in the literature, whereas, neurogenesis, a mechanism proposed to be involved in fluoxetine response, had been identified for first time using peripheral tissues. In conclusion, our study identifies several biological processes in relation to fluoxetine treatment in peripheral blood, offer new candidate genes for pharmacogenetic studies and valuable markers for peripheral moderator biomarkers discovery

Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data

Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs. Keywords: EP300; antipsychotics; gene; gene expression; metabolic syndrome; microarray; pharmacogenetics; weight gain

Evidence of activation of the Toll-like receptor-4 proinflammatory pathway in patients with schizophrenia

BACKGROUND: Alterations in the innate immune/inflammatory system may underlie the pathophysiology of schizophrenia, but we do not understand the mechanisms involved. The main agents of innate immunity are the Toll-like receptors (TLRs), which detect molecular patterns associated with damage and pathogens. The TLR first reported was TLR4, and it is still the most studied one. METHODS: We aimed to describe putative modifications to the TLR4 proinflammatory pathway using 2 different strategies in 2 cohorts of patients with schizophrenia and matched controls: 1) quantification of protein and mRNA expression in postmortem prefrontal cortex samples from 30 patients with schizophrenia and 30 controls, and 2) identification of single nucleotide polymorphisms associated with the risk of schizophrenia using whole blood samples from 214 patients with schizophrenia and 216 controls. RESULTS: We found evidence of alterations in the expression of the initial elements of the TLR4 signalling pathway (TLR4, Myeloid differentiation primary response gene 88 [MyD88] and nuclear factor-κ B [NF-κB]) in the PFC of patients with schizophrenia. These alterations seem to depend on the presence/absence of antipsychotic treatment at death. Moreover, a polymorphism within the MyD88 gene was significantly associated with schizophrenia risk. LIMITATIONS: The use of 2 different approaches in 2 different cohorts, the lack of a complementary neuropsychiatric group, the possible confounding effects of antipsychotic treatment and suicide are the main limitations of our study. CONCLUSION: The evidence from this dual approach suggests there is an altered innate immune response in patients with chronic schizophrenia in which the TLR4 proinflammatory pathway could be affected. Improved understanding of the stimuli and mechanisms responsible for this response could lead to improved schizophrenia treatment and better control of the side effects of current antipsychotics

A longitudinal study of gene expression in first-episode schizophrenia; exploring relapse mechanisms by co-expression analysis in peripheral blood.

Little is known about the pathophysiological mechanisms of relapse in first-episode schizophrenia, which limits the study of potential biomarkers. To explore relapse mechanisms and identify potential biomarkers for relapse prediction, we analyzed gene expression in peripheral blood in a cohort of first-episode schizophrenia patients with less than 5 years of evolution who had been evaluated over a 3-year follow-up period. A total of 91 participants of the 2EPs project formed the sample for baseline gene expression analysis. Of these, 67 provided biological samples at follow-up (36 after 3 years and 31 at relapse). Gene expression was assessed using the Clariom S Human Array. Weighted gene co-expression network analysis was applied to identify modules of co-expressed genes and to analyze their preservation after 3 years of follow-up or at relapse. Among the 25 modules identified, one module was semi-conserved at relapse (DarkTurquoise) and was enriched with risk genes for schizophrenia, showing a dysregulation of the TCF4 gene network in the module. Two modules were semi-conserved both at relapse and after 3 years of follow-up (DarkRed and DarkGrey) and were found to be biologically associated with protein modification and protein location processes. Higher expression of DarkRed genes was associated with higher risk of suffering a relapse and early appearance of relapse (p = 0.045). Our findings suggest that a dysregulation of the TCF4 network could be an important step in the biological process that leads to relapse and suggest that genes related to the ubiquitin proteosome system could be potential biomarkers of relapse