Thomas W.J. Moorhead

The effects of a neuregulin 1 variant on white matter density and integrity.

Theories of abnormal anatomical and functional connectivity in schizophrenia and bipolar disorder are supported by evidence from functional magnetic resonance imaging (MRI), structural MRI and diffusion tensor imaging (DTI). The presence of similar abnormalities in unaffected relatives suggests such disconnectivity is genetically mediated, albeit through unspecified loci. Neuregulin 1 (NRG1) is a psychosis susceptibility gene with effects on neuronal migration, axon guidance and myelination that could potentially explain these findings. In the current study, unaffected subjects were genotyped at the NRG1 single nucleotide polymorphism (SNP) rs6994992 (SNP8NRG243177) locus, previously associated with increased risk for psychosis, and the effect of genetic variation at this locus on white matter density (T1-weighted MRI) and integrity (DTI) was ascertained. Subjects with the risk-associated TT genotype had reduced white matter density in the anterior limb of the internal capsule and evidence of reduced structural connectivity in the same region using DTI. We therefore provide the first imaging evidence that genetic variation in NRG1 is associated with reduced white matter density and integrity in human subjects. This finding is discussed in the context of NRG1 effects on neuronal migration, axon guidance and myelination.

A diffusion tensor MRI study of white matter integrity in subjects at high genetic risk of schizophrenia

Diffusion tensor imaging (DTI) has previously shown compromised white matter integrity in frontotemporal white matter fibers in patients with schizophrenia, as indicated by reduced fractional anisotropy (FA). In the present study we investigated whether reduced white matter FA is also present in relatives of individuals with schizophrenia who are at high risk (HR) for genetic reasons. Twenty-two HR subjects, 31 patients with schizophrenia and 51 control subjects underwent DTI. We compared FA between the three groups in the cingulum cingulate gyri, the uncinate and the arcuate fasciculi and the anterior limb of the internal capsules (ALIC). A voxel-based analysis showed lower FA in patients with schizophrenia compared to controls in left and right uncinate (p<0.03), the left arcuate (p<0.03) and left and right ALIC (p<0.01). Using an automatic region-of-interest analysis, less sensitive to potential misregistration errors, produced essentially the same results, as well as reduced FA of the ALIC in the HR group compared to controls (p<0.05). This study replicates previous findings showing lower FA in frontotemporal white matter fibers of schizophrenia patients. We also found reduced FA in the ALIC of both patients and subjects at high risk of schizophrenia when compared to controls. This may be a possible indicator of the higher vulnerability of relatives to develop the disorder.

The Impact of Substance Use on Brain Structure in People at High Risk of Developing Schizophrenia

Ventricular enlargement and reduced prefrontal volume are consistent findings in schizophrenia. Both are present in first episode subjects and may be detectable before the onset of clinical disorder. Substance misuse is more common in people with schizophrenia and is associated with similar brain abnormalities. We employ a prospective cohort study with nested case control comparison design to investigate the association between substance misuse, brain abnormality, and subsequent schizophrenia. Substance misuse history, imaging data, and clinical information were collected on 147 subjects at high risk of schizophrenia and 36 controls. Regions exhibiting a significant relationship between level of use of alcohol, cannabis or tobacco, and structure volume were identified. Multivariate regression then elucidated the relationship between level of substance use and structure volumes while accounting for correlations between these variables and correcting for potential confounders. Finally, we established whether substance misuse was associated with later risk of schizophrenia. Increased ventricular volume was associated with alcohol and cannabis use in a dose-dependent manner. Alcohol consumption was associated with reduced frontal lobe volume. Multiple regression analyses found both alcohol and cannabis were significant predictors of these abnormalities when simultaneously entered into the statistical model. Alcohol and cannabis misuse were associated with an increased subsequent risk of schizophrenia. We provide prospective evidence that use of cannabis or alcohol by people at high genetic risk of schizophrenia is associated with brain abnormalities and later risk of psychosis. A family history of schizophrenia may render the brain particularly sensitive to the risk-modifying effects of these substances.

Towards the identification of imaging biomarkers in schizophrenia, using multivariate pattern classification at a single-subject level☆

Standard univariate analyses of brain imaging data have revealed a host of structural and functional brain alterations in schizophrenia. However, these analyses typically involve examining each voxel separately and making inferences at group-level, thus limiting clinical translation of their findings. Taking into account the fact that brain alterations in schizophrenia expand over a widely distributed network of brain regions, univariate analysis methods may not be the most suited choice for imaging data analysis. To address these limitations, the neuroimaging community has turned to machine learning methods both because of their ability to examine voxels jointly and their potential for making inferences at a single-subject level. This article provides a critical overview of the current and foreseeable applications of machine learning, in identifying imaging-based biomarkers that could be used for the diagnosis, early detection and treatment response of schizophrenia, and could, thus, be of high clinical relevance. We discuss promising future research directions and the main difficulties facing machine learning researchers as far as their potential translation into clinical practice is concerned.

Prefrontal gyral folding and its cognitive correlates in bipolar disorder and schizophrenia

Objective:  We sought to address whether dorsal or ventral prefrontal gyrification is abnormal in bipolar disorder and to determine its diagnostic specificity and cognitive associations.

Human brain imaging studies of DISC1 in schizophrenia, bipolar disorder and depression: A systematic review

Disrupted-in-Schizophrenia 1 (DISC1) is a well researched candidate gene for schizophrenia and affective disorders with a range of functions relating to neurodevelopment. Several human brain imaging studies investigating correlations between common and rare variants in DISC1 and brain structure and function have shown conflicting results. A meta-analysis of case/control data showed no association between schizophrenia and any common SNP in DISC1. Therefore it is timely to review the literature to plan the direction of future studies. Twenty-two human brain imaging studies have examined the influence of DISC1 variants in health, schizophrenia, bipolar disorder or depression. The most studied common SNPs are Ser704Cys (rs821616) and Leu607Phe (rs6675281). Some imaging-genomic studies report effects on frontal, temporal and hippocampal structural indices in health and illness and a volumetric longitudinal study supports a putative role for these common SNPs in neurodevelopment. Callosal agenesis is described in association with rare deletions at 1q42 which include DISC1 and rare sequence variants at DISC1 itself. DISC1 interactions with translin-associated factor X (TRAX) and neuregulin have been shown to influence several regional volumes. In the first study involving neonates, a role for Ser704Cys (rs821616) has been highlighted in prenatal brain development with large clusters of reduced grey matter reported in the frontal lobes. Functional MRI studies examining associations between Ser704Cys (rs821616) and Leu607Phe (rs6675281) with prefrontal and hippocampal activation have also given inconsistent results. Prefrontal function was reported to be associated with interaction between DISC1 and CITRON (CIT) in health. Preliminary magnetic resonance spectroscopy and diffusion tensor data support the influence of Ser704Cys (rs821616) status on grey and white matter integrity. The glutamate system remains uninvestigated. Associations between rare sequence variants and structural changes in brain regions including the corpus callosum and effects of gene-gene interactions on brain structure and function are promising areas for future study.

Association of white matter integrity with genetic variation in an exonic DISC1 SNP

The Disrupted-in-Schizophrenia-1 (DISC1) gene was first identified at the breakpoint of a translocation between chromosomes 1 and 11 that co-segregated with a broad psychiatric phenotype in a large Scottish family,1, 2 and subsequent association studies have shown that common genetic variants in DISC1 convey susceptibility to schizophrenia, bipolar disorder and other psychiatric disorders.3 DISC1 is involved in several neurodevelopmental processes, including the development of white matter,4, 5, 6 and white matter abnormalities are well-established in schizophrenia and bipolar disorder7 and have a high genetic correlation with susceptibility to both disorders.8, 9 Here, we report an association between a common missense variant in DISC1, rs821616 (Ser704Cys), previously associated with schizophrenia,3 and white matter integrity as measured by diffusion tensor-magnetic resonance imaging.

The application of nonlinear Dynamic Causal Modelling for fMRI in subjects at high genetic risk of schizophrenia.

Nonlinear Dynamic Causal Modelling (DCM) for fMRI provides computational modelling of gating mechanisms at the neuronal population level. It allows for estimations of connection strengths with nonlinear modulation within task-dependent networks. This paper presents an application of nonlinear DCM in subjects at high familial risk of schizophrenia performing the Hayling Sentence Completion Task (HSCT). We analysed scans of 19 healthy controls and 46 subjects at high familial risk of schizophrenia, which included 26 high risk subjects without psychotic symptoms and 20 subjects with psychotic symptoms. The activity-dependent network consists of the intra parietal cortex (IPS), inferior frontal gyrus (IFG), middle temporal gyrus (MTG), anterior cingulate cortex (ACC) and the mediodorsal (MD) thalamus. The connections between the MD thalamus and the IFG were gated by the MD thalamus. We used DCM to investigate altered connection strength of these connections. Bayesian Model Selection (BMS) at the group and family level was used to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging (BMA) was used to assess the connection strengths with the gating from the MD thalamus and the IFG. The nonlinear models provided the better explanation of the data. Furthermore, the BMA analysis showed significantly lower connection strength of the thalamocortical connection with nonlinear modulation from the MD thalamus in high risk subjects with psychotic symptoms and those who subsequently developed schizophrenia. These findings demonstrate that nonlinear DCM provides a method to investigate altered connectivity at the level of neural circuits. The reduced connection strength with thalamic gating may be a neurobiomarker implicated in the development of psychotic symptoms. This study suggests that nonlinear DCM could lead to new insights into functional and effective dysconnection at the network level in subjects at high familial risk.

Impact of cannabis use on thalamic volume in people at familial high risk of schizophrenia

BACKGROUND No longitudinal study has yet examined the association between substance use and brain volume changes in a population at high risk of schizophrenia. AIMS To examine the effects of cannabis on longitudinal thalamus and amygdala-hippocampal complex volumes within a population at high risk of schizophrenia. METHOD Magnetic resonance imaging scans were obtained from individuals at high genetic risk of schizophrenia at the point of entry to the Edinburgh High-Risk Study (EHRS) and approximately 2 years later. Differential thalamic and amygdala-hippocampal complex volume change in high-risk individuals exposed (n = 25) and not exposed (n = 32) to cannabis in the intervening period was investigated using repeated-measures analysis of variance. RESULTS Cannabis exposure was associated with bilateral thalamic volume loss. This effect was significant on the left (F = 4.47, P = 0.04) and highly significant on the right (F= 7.66, P= 0.008). These results remained significant when individuals using other illicit drugs were removed from the analysis. CONCLUSIONS These are the first longitudinal data to demonstrate an association between thalamic volume loss and exposure to cannabis in currently unaffected people at familial high risk of developing schizophrenia. This observation may be important in understanding the link between cannabis exposure and the subsequent development of schizophrenia.

Temporal grey matter reductions in bipolar disorder are associated with the BDNF Val66Met polymorphism.

Temporal grey matter reductions in bipolar disorder are associated with the BDNF Val 66 Met polymorphism