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The effect of schizophrenia (SCZ) genetic risk on gene expression in brain remains elusive. A popular approach to this problem has been the application of gene co-expression network algorithms (e.g., WGCNA). To improve reliability with this method it is critical to remove unwanted sources of variance while also preserving biological signals of interest. In this WCGNA study of RNA-Seq data from postmortem prefrontal cortex (78 neurotypical donors, EUR ancestry), we tested the effects of SCZ genetic risk on co-expression networks. Specifically, we implemented a novel design in which gene expression was adjusted by linear regression models to preserve or remove variance explained by biological signal of interest (GWAS genomic scores for SCZ risk—(GS-SCZ), and genomic scores- GS of height (GS-Ht) as a negative control), while removing variance explained by covariates of non-interest. We calculated co-expression networks from adjusted expression (GS-SCZ and GS-Ht preserved or removed), and consensus between them (representative of a "background" network free of genomic scores effects). We then tested the overlap between GS-SCZ preserved modules and background networks reasoning that modules with reduced overlap would be most affected by GS-SCZ biology. Additionally, we tested these modules for convergence of SCZ risk (i.e., enrichment in PGC3 SCZ GWAS priority genes, enrichment in SCZ risk heritability and relevant biological ontologies. Our results highlight key aspects of GS-SCZ effects on brain co-expression networks, specifically: 1) preserving/removing SCZ genetic risk alters the co-expression modules; 2) biological pathways enriched in modules affected by GS-SCZ implicate processes of transcription, translation and metabolism that converge to influence synaptic transmission; 3) priority PGC3 SCZ GWAS genes and SCZ risk heritability are enriched in modules associated with GS-SCZ effects. Overall, our results indicate that gene co-expression networks that selectively integrate information about genetic risk can reveal novel combinations of biological pathways involved in schizophrenia. Author summary: Genetic risk for schizophrenia (SCZ) is linked to brain connectivity at multiple levels, from molecular interactions to coherent cognitive processing. Biological mechanisms by which SCZ genetic risk affects brain connectivity are generally unknown. In this study we sought to uncover some of these mechanisms by focusing on gene co-expression networks calculated from RNA-Seq data extracted from postmortem DLPFC. We created co-expression networks from gene expression adjusted to account for, or to remove the likely effects of genomic (polygenic) scores of SCZ risk. We minimized potential confounding effects of illness state or treatment on gene expression by using only brains from donors without a history of mental disorder. We used as a control, co-expression networks from gene expression adjusted to account for effects of genomic scores of height- a normative trait. Our results show subtle and widespread effects of SCZ genomic scores on DLPFC co-expression networks. Gene sets from co-expression modules adjusted for SCZ genetic risk harbor biological significance represented by neuronal functions, but also by interacting pathways of general cellular processes like transcription, translation and metabolism. Our findings highlight possible avenues for identifying regulatory targets of gene expression in schizophrenia. [ABSTRACT FROM AUTHOR]

Dental bleaching is a common procedure, requested and accepted by patients with aesthetic requirements. The SEM images were taken at different degrees of magnification, always looking for cracks, porosities, or other changes at this level, which could be related to the sensitivity that appeared after such a procedure. The standard bleaching procedure was applied to the labial surface of the tooth. Biolase Laser white 20 bleaching putty was used, which contains 45% hydrogen peroxide and then activated with 940 nm laser light. The microscopic SEM images of the labial faces on which the 45% concentration hydrogen peroxide type bleaching gel was applied showed that they do not present any structural damage to the enamel. [ABSTRACT FROM AUTHOR]

The widespread use of MRI has led to a wealth of structural and functional anatomical findings in patients with diverse psychiatric disorders that may represent insights into pathobiology. However, recent technical reports indicate that data from popular MRI research-particularly structural MRI, resting--state functional MRI, and diffusion tensor imaging--are highly sensitive to common artifacts (e.g., head motion and breathing effects) that may dominate the results. Because these and other important confounders of MRI data (e.g., smoking, body weight, metabolic variations, medical comorbidities, psychoactive drugs, alcohol use, mental state) tend to vary systematically between patient and control groups, the evidence that findings are neurobiologically meaningful is inconclusive and may represent artifacts or epiphenomena of uncertain value. The authors caution that uncritically accepting from study to study findings that may represent fallacies of all sorts carries the risk of misinforming practitioners and patients about biological abnormalities underlying psychiatric illness. [ABSTRACT FROM AUTHOR]

Genetic variants in GPR85 (SREB2: rs56080411 and rs56039557) have been associated with risk for schizophrenia. Here, we test the hypothesis that these variants impact on brain function in normal subjects, measured with functional magnetic resonance imaging (fMRI) paradigms that target regions with greatest SREB2 expression (hippocampal formation and amygdaloid complex). During a facial emotion recognition paradigm, a significant interaction of rs56080411 genotype by sex was found in the left amygdaloid complex (male risk allele carriers showed less activation than male homozygotes for the non-risk allele, while females showed the opposite pattern). During aversive encoding of an emotional memory paradigm, we found that risk allele carriers for rs56080411 had greater activation in the right inferior frontal gyrus. Trends in the same direction were present for rs56039557 in the right occipital cortex and right fusiform gyrus. During a working memory paradigm, a significant sex-by-genotype interaction was found with male risk allele carriers of rs56080411 having inefficient activation within the left dorsolateral prefrontal cortex (DLPFC), compared with same sex non-risk carriers, while females revealed an opposite pattern, despite similar levels of performance. These data suggest that risk-associated variants in SREB2 are associated with phenotypes similar to those found in patients with schizophrenia in the DLPFC and the amygdala of males, while the pattern is opposite in females. The findings in females and during the emotional memory paradigm are consistent with modulation by SREB2 of brain circuitries implicated in mood regulation and may be relevant to neuropsychiatric conditions other than schizophrenia. [ABSTRACT FROM AUTHOR]

Autism spectrum conditions (ASC) affect more males than females. This suggests that the neurobiology of autism: 1) may overlap with mechanisms underlying typical sex-differentiation or 2) alternately reflect sex-specificity in how autism is expressed in males and females. Here we used functional magnetic resonance imaging (fMRI) to test these alternate hypotheses. Fifteen men and fourteen women with Asperger syndrome (AS), and sixteen typically developing men and sixteen typically developing women underwent fMRI during performance of mental rotation and verbal fluency tasks. All groups performed the tasks equally well. On the verbal fluency task, despite equivalent task-performance, both males and females with AS showed enhanced activation of left occipitoparietal and inferior prefrontal activity compared to controls. During mental rotation, there was a significant diagnosis-by-sex interaction across occipital, temporal, parietal, middle frontal regions, with greater activation in AS males and typical females compared to AS females and typical males. These findings suggest a complex relationship between autism and sex that is differentially expressed in verbal and visuospatial domains. [ABSTRACT FROM AUTHOR]

Abstract: We review studies that have used diffusion imaging (DI) and magnetic resonance spectroscopy (MRS) to investigate genetic associations. A brief description of the measures obtainable with these methods and of some methodological and interpretability limitations is given. The usefulness of DI and MRS in defining intermediate phenotypes and in demonstrating the effects of common genetic variants known to increase risk for psychiatric manifestations on anatomical and metabolic phenotypes is reviewed. The main focus is on schizophrenia where the greatest amount of data has been collected. Moreover, we present an example coming from a different approach, where the genetic alteration is known (the deletion that causes Williams syndrome) and the DI phenotype can shed new light on the function of genes affected by the mutation. We conclude that, although these are still early days of this type of research and many findings remain controversial, both techniques can significantly contribute to the understanding of genetic effects in the brain and the pathophysiology of psychiatric disorders. [Copyright &y& Elsevier]

Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. 1. Samples: DLPFC gene expression (RNA-Seq) abundance was quantified (RPKM) in postmortem human brains from the LIBD Postmortem Human Brain Repository (90 controls- CTRL, 76 schizophrenia- SCZ, Caucasians, age: 16–80, RIN≥7). Common Mind Consortium (CMC) RNA-Seq postmortem DLPFC (125 CTRL, 109 SCZ, Caucasians, age, RIN as above) was used for replication of LIBD co-expression networks. 2. Expression measures/ quality control: only genes with median RPKM≥0.1 (N=23132 genes; LIBD samples) were used. Expression data was normalized by log2 transformation and adjusted for RNA quality measures (RIN, PMI, total gene assignment, proportion of mitochondrial RNA) by empirical Bayesian models. 3. Data analysis: WGCNA was applied to the adjusted expression data to construct co-expression networks, separately for LIBD- CTRL and LIBD- SCZ. Modules of co-expressed genes were detected by dynamic tree cutting method and summarized as "module eigengenes" for further analyses. 4. Modules of LIBD (CTRL; SCZ) were tested for enrichment in PGC2 genes within the 108 loci associated with the schizophrenia risk in the latest GWAS. 5. Composite module preservation statistics- median rank and Zsummary was used for assessing the preservation of LIBD SCZ modules in LIBD CTRL network and for replication of LIBD co-expression modules in the CMC independent data sets. Gene enrichment analyses for testing modules' enrichment in Gene Ontology (GO) biological processes (BP) was performed with AmiGO/ PANTHER. 17 co-expression modules were identified in each LIBD group. Module preservation analysis showed a good preservation of co-expression modules between LIBD CTRL and SCZ networks, with all but one SCZ module showing evidence for strong preservation (Zsummary≥10). PGC2 genes were overrepresented in two CTRL modules (p=0.001973, p=0.028297) enriched for GO-BP such as translation, ATP synthesis, oxidative phosphorylation, homophilic cell adhesion via plasma membrane adhesion molecules, chemical synaptic transmission, axonogenesis, and in one SCZ module (p=0.000519) enriched for RNA processing, nervous system development and modulation of synaptic transmission. 58 PGC2 genes overlapped with the SCZ module (e.g., DRD2, FURIN, TSNARE1), whereas 48 + 17 PGC2 genes were overrepresented in the two CTRL modules (e.g., CACNA1C, CHRM4, CACNA1I, TCF20). Of note, only 9 overrepresented PGC2 genes were shared by CTRL and SCZ: AMBRA1, ANKRD63, HSPA9, LRP1, PRR12, PTPRF, RERE, TOM1L2, ZDHHC5. Replication of co-expression LIBD networks in CMC data set showed evidence of weak to strong preservation (Zsummary>2, respectively ≥10) for 16/ 17 modules for each LIBD group. Our results illustrate the complexity of SCZ risk distribution within the DLPFC co-expression networks in postmortem brains of affected and unaffected individuals. Importantly, not the same PGC2 genes are members of co-expression modules in CTRL and SCZ, nor do they aggregate in similar modules. These observations may be explained by differential transcriptional regulation due to pleiotropy, epistasis, epigenetic dysregulation, or even hidden RNA quality artifacts. Future studies are necessary to elucidate the participation of SCZ risk genes in brain co-expression networks. [ABSTRACT FROM AUTHOR]

Objective: The authors sought to study the transcriptomic and genomic features of completed suicide by parsing the method chosen, to capture molecular correlates of the distinctive frame of mind of individuals who die by suicide, while reducing heterogeneity.Methods: The authors analyzed gene expression (RNA sequencing) from postmortem dorsolateral prefrontal cortex of patients who died by suicide with violent compared with nonviolent means, nonsuicide patients with the same psychiatric disorders, and a neurotypical group (total N=329). They then examined genomic risk scores (GRSs) for each psychiatric disorder included, and GRSs for cognition (IQ) and for suicide attempt, testing how they predict diagnosis or traits (total N=888).Results: Patients who died by suicide by violent means showed a transcriptomic pattern remarkably divergent from each of the other patient groups but less from the neurotypical group; consistently, their genomic profile of risk was relatively low for their diagnosed illness as well as for suicide attempt, and relatively high for IQ: they were more similar to the neurotypical group than to other patients. Differentially expressed genes (DEGs) associated with patients who died by suicide by violent means pointed to purinergic signaling in microglia, showing similarities to a genome-wide association study of Drosophila aggression. Weighted gene coexpression network analysis revealed that these DEGs were coexpressed in a context of mitochondrial metabolic activation unique to suicide by violent means.Conclusions: These findings suggest that patients who die by suicide by violent means are in part biologically separable from other patients with the same diagnoses, and their behavioral outcome may be less dependent on genetic risk for conventional psychiatric disorders and be associated with an alteration of purinergic signaling and mitochondrial metabolism. [ABSTRACT FROM AUTHOR]

Abstract: Accumulating evidence from non-human primates and computational modeling suggests that dopaminergic signals arising from the midbrain (substantia nigra/ventral tegmental area) mediate striatal gating of the prefrontal cortex during the selective updating of working memory. Using event-related functional magnetic resonance imaging, we explored the neural mechanisms underlying the selective updating of information stored in working memory. Participants were scanned during a novel working memory task that parses the neurophysiology underlying working memory maintenance, overwriting, and selective updating. Analyses revealed a functionally coupled network consisting of a midbrain region encompassing the substantia nigra/ventral tegmental area, caudate, and dorsolateral prefrontal cortex that was selectively engaged during working memory updating compared to the overwriting and maintenance of working memory content. Further analysis revealed differential midbrain-dorsolateral prefrontal interactions during selective updating between low-performing and high-performing individuals. These findings highlight the role of this meso-cortico-striatal circuitry during the selective updating of working memory in humans, which complements previous research in behavioral neuroscience and computational modeling. [Copyright &y& Elsevier]

B Background: b Genome-wide association studies (GWAS) have successfully identified a large number of genetic variants associated with psychiatric disorders, but single GWAS significant variants can only explain a small proportion of trait heritability. These approaches combine expression quantitative trait locus (eQTL) studies with GWAS to investigate gene-trait relationships by determining whether GWAS-significant variants are also enriched for eQTLs. Among these approaches, Summary-data-based Mendelian Randomization (SMR) integrates summary statistics from GWAS and eQTL studies to identify genes whose expression levels are associated with a complex trait due to pleiotropy. [Extracted from the article]

Abstract Background Previous findings suggest that differences in brain expression of a human-specific long intergenic noncoding RNA (LINC01268 ; GRCh37/hg19: LOC285758) may be linked to suicide by violent methods. We sought to replicate and extend these findings in a new sample and translate the results to the behavioral level in living healthy subjects. Methods We examined RNA sequencing data in human brains to confirm the prior postmortem association of the long intergenic noncoding RNA specifically with suicide by violent means. In addition, we used a genetic variant associated with LINC01268 expression to detect association in healthy subjects with trait aggression and with in vivo prefrontal physiology related to behavioral control. Finally, we performed weighted gene coexpression network analysis and gene ontology analysis to identify biological processes associated with a LINC01268 coexpression network. Results In the replication sample, prefrontal expression of LINC01268 was again higher in suicides by violent means (n = 65) than in both nonsuicides (n = 78; p = 1.29 × 10−6) and suicides by nonviolent means (n = 46; p = 1.4 × 10−6). In the living cohort, carriers of the minor allele of a single nucleotide polymorphism associated with increased LINC01268 expression in brain scored higher on a lifetime aggression questionnaire and show diminished engagement of prefrontal cortex (Brodmann area 10) when viewing angry faces during functional magnetic resonance imaging. Weighted gene coexpression network analysis highlighted the immune response. Conclusions These results suggest that LINC01268 influences emotional regulation, aggressive behavior, and suicide by violent means; the underlying biological dynamics may include modulation of genes potentially engaged in the immune response. [ABSTRACT FROM AUTHOR]

γ-Aminobutyric acid (GABA)-ergic transmission is critical for normal cortical function and is likely abnormal in a variety of neuropsychiatric disorders. We tested the in vivo effects of variations in two genes implicated in GABA function on GABA concentrations in prefrontal cortex of living subjects: glutamic acid decarboxylase 1 (GAD1), which encodes GAD67, and catechol-o-methyltransferase (COMT), which regulates synaptic dopamine in the cortex. We studied six single nucleotide polymorphisms (SNPs) in GAD1 previously associated with risk for schizophrenia or cognitive dysfunction and the val158met polymorphism in COMT in 116 healthy volunteers using proton magnetic resonance spectroscopy. Two of the GAD1 SNPs (rs1978340 (p=0.005) and rs769390 (p=0.004)) showed effects on GABA levels as did COMT val158met (p=0.04). We then tested three SNPs in GAD1 (rs1978340, rs11542313, and rs769390) for interaction with COMT val158met based on previous clinical results. In this model, rs11542313 and COMT val158met showed significant main effects (p=0.001 and 0.003, respectively) and a trend toward a significant interaction (p=0.05). Interestingly, GAD1 risk alleles for schizophrenia were associated with higher GABA/Cre, and Val-Val homozygotes had high GABA/Cre levels when on a GAD1 risk genotype background (N=6). These results support the importance of genetic variation in GAD1 and COMT in regulating prefrontal cortical GABA function. The directionality of the effects, however, is inconsistent with earlier evidence of decreased GABA activity in schizophrenia. [ABSTRACT FROM AUTHOR]

In recent years, Polygenic Risk Profile Scores (PRS's) are being increasingly used to indirectly measure the aggregate genetic effect of many weakly associated markers on the risk for a neuropsychiatric disorder. While the use of PRS's has supported the polygenic architecture of schizophrenia, a link between PRS's and the pathophysiology of this disorder is still missing. In this study, we analyze the association between PRS's for schizophrenia and hippocampal function during a simple declarative memory task in healthy volunteers. We then used regularized regression, a machine learning method, to further investigate the genetic structure that drives the association between schizophrenia PRS's and altered hippocampal engagement. Two hundred and five healthy volunteers underwent BOLD fMRI (3 T) during a Simple Declarative Memory Task (SDMT), which included incidental encoding and retrieval of visual scenes. For both the encoding and retrieval sessions, the scenes were presented in a blocked fashion, with 4 blocks of neutral scenes and 4 blocks of visual scenes alternating with 9 blocks of resting state (fixation cross hair). In the current study, we focused on the encoding phase for neutral scenes only (Rasetti et al. 2014). PRS's were calculated for each individual as the weighted sum of the number of reference alleles on preselected markers based on PGC GWAS study (PGC 2014), with p-value threshold at 0.05 (24,670 SNPs). Imaging space association study was conducted using multiple regressions in SPM8. Region of interest (ROI) was defined as averaged signal within a 6 mm sphere around the peak of association between PRS and right hippocampus. Regularized regression was run using ROI in R using glmnet package (Zou et al. 2005). The PRS constructed with 24,670 SNPs (with association with schizophrenia at scoring threshold of p=0.05) is significantly associated with hippocampal activation (z=4.48, p=0.004, FWE corrected in bilateral hippocampal ROI), so that higher PRS corresponds to blunted hippocampal activation. Using the regularized regression with shrinkage factor lambda=0.001, we identified 255 SNPs driving this association, so that the association between the PRS based on these 255 SNPs (PRS255) and hippocampal activation increases dramatically (z=7.14, p<0.001, FWE corrected in whole brain); PRS255 accounted for 8.9% of the variance in right hippocampal activation. Our results show that PRS's for schizophrenia are significantly associated with altered hippocampal function during a simple declarative memory task even in healthy volunteers. Using regularized regression, we are able to find a small subset of SNPs that drive the association and account for high percentage of variance in hippocampal activation. The use of machine learning techniques for dimension reduction allows disentangling the cumulative effect of risk genes on brain function. [ABSTRACT FROM AUTHOR]