Search

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]

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]

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]

This Viewpoint supports using the phrase differences on MRI measurements when referring to differences representing cerebral structure as evidence of brain structural abnormalities. [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]

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]

Schizophrenia is a neurodevelopmental brain disorder whose genetic risk is associated with shifting clinical phenomena across the life span. We investigated the convergence of putative schizophrenia risk genes in brain coexpression networks in postmortem human prefrontal cortex (DLPFC), hippocampus, caudate nucleus, and dentate gyrus granule cells, parsed by specific age periods (total N  = 833). The results support an early prefrontal involvement in the biology underlying schizophrenia and reveal a dynamic interplay of regions in which age parsing explains more variance in schizophrenia risk compared to lumping all age periods together. Across multiple data sources and publications, we identify 28 genes that are the most consistently found partners in modules enriched for schizophrenia risk genes in DLPFC; twenty-three are previously unidentified associations with schizophrenia. In iPSC-derived neurons, the relationship of these genes with schizophrenia risk genes is maintained. The genetic architecture of schizophrenia is embedded in shifting coexpression patterns across brain regions and time, potentially underwriting its shifting clinical presentation.

Asperger syndrome (AS) is an Autism Spectrum Disorder (ASD) characterised by qualitative impairment in the development of emotional and social skills with relative preservation of general intellectual abilities, including verbal language. People with AS may nevertheless show atypical language, including rate and frequency of speech production. We previously observed that abnormalities in grey matter homogeneity (measured with texture analysis of structural MR images) in AS individuals when compared with controls are also correlated with the volume of caudate nucleus. Here, we tested a prediction that these distributed abnormalities in grey matter compromise the functional integrity of brain networks supporting verbal communication skills. We therefore measured the functional connectivity between caudate nucleus and cortex during a functional neuroimaging study of language generation (verbal fluency), applying psycho-physiological interaction (PPI) methods to test specifically for differences attributable to grey matter heterogeneity in AS participants. Furthermore, we used dynamic causal modelling (DCM) to characterise the causal directionality of these differences in interregional connectivity during word production. Our results revealed a diagnosis-dependent influence of grey matter heterogeneity on the functional connectivity of the caudate nuclei with right insula/inferior frontal gyrus and anterior cingulate, respectively with the left superior frontal gyrus and right precuneus. Moreover, causal modelling of interactions between inferior frontal gyri, caudate and precuneus, revealed a reliance on bottom-up (stimulus-driven) connections in AS participants that contrasted with a dominance of top-down (cognitive control) connections from prefrontal cortex observed in control participants. These results provide detailed support for previously hypothesised central disconnectivity in ASD and specify discrete brain network targets for diagnosis and therapy in ASD.