Psychiatry - Research Publications
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ItemGenetic Influences on Cost-Efficient Organization of Human Cortical Functional Networks(SOC NEUROSCIENCE, 2011-03-02)The human cerebral cortex is a complex network of functionally specialized regions interconnected by axonal fibers, but the organizational principles underlying cortical connectivity remain unknown. Here, we report evidence that one such principle for functional cortical networks involves finding a balance between maximizing communication efficiency and minimizing connection cost, referred to as optimization of network cost-efficiency. We measured spontaneous fluctuations of the blood oxygenation level-dependent signal using functional magnetic resonance imaging in healthy monozygotic (16 pairs) and dizygotic (13 pairs) twins and characterized cost-efficient properties of brain network functional connectivity between 1041 distinct cortical regions. At the global network level, 60% of the interindividual variance in cost-efficiency of cortical functional networks was attributable to additive genetic effects. Regionally, significant genetic effects were observed throughout the cortex in a largely bilateral pattern, including bilateral posterior cingulate and medial prefrontal cortices, dorsolateral prefrontal and superior parietal cortices, and lateral temporal and inferomedial occipital regions. Genetic effects were stronger for cost-efficiency than for other metrics considered, and were more clearly significant in functional networks operating in the 0.09-0.18 Hz frequency interval than at higher or lower frequencies. These findings are consistent with the hypothesis that brain networks evolved to satisfy competitive selection criteria of maximizing efficiency and minimizing cost, and that optimization of network cost-efficiency represents an important principle for the brain's functional organization.
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ItemCortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study(SPRINGERNATURE, 2022-02)Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.
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ItemTranscriptional signatures of connectomic subregions of the human striatum(WILEY, 2017-09)Functionally distinct regions of the brain are thought to possess a characteristic connectional fingerprint - a profile of incoming and outgoing connections that defines the function of that area. This observation has motivated efforts to subdivide brain areas using their connectivity patterns. However, it remains unclear whether these connectomically-defined subregions can be distinguished at the molecular level. Here, we combine high-resolution diffusion-weighted magnetic resonance imaging with transcriptomic data to show that connectomically-defined subregions of the striatum carry distinct transcriptional signatures. Using data-driven clustering of diffusion tractography, seeded from the striatum in 100 healthy individuals, we identify a tripartite organization of the caudate and putamen that comprises ventral, dorsal and caudal subregions. We then use microarray data of gene expression levels in 19 343 genes, taken from 98 tissue samples distributed throughout the striatum, to accurately discriminate the three connectomically-defined subregions with 80-90% classification accuracy using linear support vector machines. This classification accuracy was robust at the group and individual level and was superior for our parcellation of the striatum when compared with parcellations based on anatomical boundaries or other criteria. Genes contributing strongly to classification were enriched for gene ontology categories including dopamine signaling, glutamate secretion, response to amphetamine and metabolic pathways, and were implicated in risk for disorders such as schizophrenia, autism and Parkinson's disease. Our findings highlight a close link between regional variations in transcriptional activity and inter-regional connectivity in the brain, and suggest that there may be a strong genomic signature of connectomically-defined subregions of the brain.
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ItemStaged treatment and acceptability guidelines in early psychosis study (STAGES): A randomized placebo controlled trial of intensive psychosocial treatment plus or minus antipsychotic medication for first-episode psychosis with low-risk of self-harm or aggression. Study protocol and baseline characteristics of participants(WILEY, 2019-08)AIM: It is now necessary to investigate whether recovery in psychosis is possible without the use of antipsychotic medication. This study will determine (1) whether a first-episode psychosis (FEP) group receiving intensive psychosocial interventions alone can achieve symptomatic remission and functional recovery; (2) whether prolonging the duration of untreated psychosis (DUP) in a sub-group according to randomisation will be associated with a poorer outcome and thereby establish whether the relationship between DUP and outcome is causative; and (3) whether neurobiological changes observed in FEP are associated with the psychotic disorder or antipsychotic medication. Baseline characteristics of participants will be presented. METHODS: This study is a triple-blind randomized placebo-controlled non-inferiority trial. The primary outcome is the level of functioning measured by the Social and Occupational Functioning Assessment Scale at 6 months. This study is being conducted at the Early Psychosis Prevention and Intervention Centre, Melbourne and includes young people aged 15 to 24 years with a DSM-IV psychotic disorder, a DUP less than 6 months and not high risk for suicide or harm to others. Strict discontinuation criteria are being applied. Participants are also undergoing three 3-Tesla-MRI scans. RESULTS: Ninety participants have been recruited and baseline characteristics are presented. CONCLUSIONS: Staged treatment and acceptability guidelines in early psychosis will determine whether antipsychotic medications are indicated in all young people with a FEP and whether antipsychotic medication can be safely delayed. Furthermore, the relative contribution of psychotic illness and antipsychotic medication in terms of structural brain changes will also be elucidated. The findings will inform clinical practice guidelines.
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ItemS166. EFFECTIVE CONNECTIVITY OF FRONTOSTRIATAL SYSTEMS IN FIRST-EPISODE PSYCHOSIS(Oxford University Press (OUP), 2020-05-18)Abstract Background Neuroimaging studies have found dysconnectivity of frontostriatal circuits across a broad spectrum of psychotic symptoms. However, it is unknown whether dysconnectivity within frontostriatal circuits originates from disrupted bottom-up or top-down control signaling within these systems. Here, we used dynamic causal modelling (DCM) to examine the effective connectivity of frontostriatal systems in first-episode psychosis (FEP). Methods A total of 55 FEP patients (26 males; mean [SD] age = 19.24 [2.89]) and 24 healthy controls (15 males; mean [SD] age = 21.83 [1.93]) underwent a resting-state functional magnetic resonance imaging protocol. Biologically plausible connections between eight left hemisphere regions encompassing the dorsal and ventral frontostriatal systems were modelled using spectral DCM. The regions comprise dorsolateral prefrontal cortex, ventromedial prefrontal cortex, anterior hippocampus, amygdala, dorsal caudate, nucleus accumbens, thalamus, and the midbrain. Effective connectivity between groups were assessed using a parametric Bayesian model. Associations between effective connectivity parameters and positive symptoms, measured by the Brief Psychiatric Rating Scale positive subscale, was assessed in the patient group in a separate Bayesian general linear model. Results DCM shows evidence for differences in effective connectivity between patients and healthy controls, namely in the bottom-down connections distributed in the frontostriatal system encompassing the hippocampus, amygdala, striatum, and midbrain. Compared to healthy controls, patients also demonstrated increased disinhibition of the midbrain. In patients, positive symptoms are associated with increased top-down connections to the midbrain. Outgoing connection from the midbrain to the nucleus accumbens is also increased in association with positive symptoms. Discussion Aberrant top-down connectivity in the frontostriatal system in patients is consistent with top-down dysregulation of dopamine function in FEP, as dopaminergic activity in the midbrain is proposed to be under the control of higher brain areas. In patients, increased self-inhibition of the midbrain, as well as symptom associations in both ingoing and outgoing connections of this region, are congruous with hyperactivity of the midbrain as proposed by the dopamine dysregulation hypothesis. Here, we demonstrate that mathematical models of brain imaging signals can be used to identify the key disruptions driving brain circuit dysfunction, identifying new targets for treatment.
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ItemT162. THICKER PREFRONTAL CORTEX IS ASSOCIATED WITH SUBCLINICAL NEGATIVE SYMPTOMS IN SCHIZOTYPY - AN ENIGMA CONSORTIUM META-ANALYSIS(Oxford University Press (OUP), 2020-05-18)Abstract Background Negative symptoms can be seen to represent a continuum from subclinical manifestations in the general population to severe symptoms in schizophrenia. Neuroanatomical studies show evidence of fronto-striatal structural abnormalities linked to negative symptoms in patients with schizophrenia (Walton et al. 2018). However, it remains an open question whether these structural associations are also observed in ostensibly healthy individuals reporting subclinical negative symptoms. The present study used structural T1-weighted brain imaging data from the ENIGMA Schizotypy Working Group to investigate the relationship between subclinical negative symptoms and fronto-striatal structural measures. Methods We included 2,235 healthy unmedicated individuals with varying levels of schizotypy from 17 centers around the world. The complete sample had a weighted mean (range) age of 29.2 (15.9–39.6) and 59.4% (51–100) were male. Subclinical negative symptoms were assessed at each site separately using factor scores from self-report schizotypy questionnaires (i.e., the Community Assessment of Psychic Experiences, the Oxford-Liverpool Inventory of Feelings and Experiences, or the Schizotypal Personality Questionnaire). Based on prior studies in schizophrenia, we obtained cortical thickness from 22 frontal regions-of-interest (ROIs) and subcortical volumes from 6 striatal ROIs using FreeSurfer. We performed meta-analyses of effect sizes (standardized regression coefficients) from a model predicting mean cortical thickness by subclinical negative symptom scores, adjusting for age, sex, and site. The same analysis was repeated for subcortical volumes including intracranial volume as additional covariate. Results Meta-analyses revealed significant positive associations between subclinical negative symptoms and cortical thickness of the left frontal pole (βstd=0.091; pFDR=0.009), right medial orbitofrontal cortex (βstd=0.083; pFDR=0.009) and right anterior cingulate cortex (βstd=0.07; pFDR=0.011). Discussion Using a large sample of healthy unmedicated individuals with varying levels of schizotypal personality traits, this ENIGMA meta-analysis showed that subclinical negative symptoms are associated with thicker prefrontal cortex. The present data are contrary to previous findings in schizophrenia, which demonstrates a relationship between negative symptoms and lower prefrontal cortical thickness (Walton et al. 2018). These divergent neural correlates suggest that thicker cortex could be a potential compensatory mechanism preventing individuals with schizotypy from the clinical manifestation of severe negative symptoms. Alternatively, greater prefrontal cortical thickness could also be associated with pathological processes along the negative symptom continuum prior to clinical manifestation.
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ItemGenome-wide association study reveals novel genetic locus associated with intra- individual variability in response time(NATURE PUBLISHING GROUP, 2018-10-04)Intra-individual response time variability (IIRTV) is proposed as a viable endophenotype for many psychiatric disorders, particularly attention-deficit hyperactivity disorder (ADHD). Here we assessed whether IIRTV was associated with common DNA variation genome-wide and whether IIRTV mediated the relationship between any associated loci and self-reported ADHD symptoms. A final data set from 857 Australian young adults (489 females and 368 males; Mage = 22.14 years, SDage = 4.82 years) who completed five response time tasks and self-reported symptoms of ADHD using the Conners' Adult ADHD Rating Scale was used. Principal components analysis (PCA) on these response time measures (standard deviation of reaction times and the intra-individual coefficient of variation) produced two variability factors (labelled response selection and selective attention). To understand the genetic drivers of IIRTV we performed a genome-wide association analysis (GWAS) on these PCA-derived indices of IIRTV. For the selective attention variability factor, we identified one single-nucleotide polymorphism (SNP) attaining genome-wide significance; rs62182100 in the HDAC4 gene located on chromosome 2q37. A bootstrapping mediation analysis demonstrated that the selective attention variability factor mediated the relationship between rs62182100 and self-reported ADHD symptoms. Our findings provide the first evidence of a genome-wide significant SNP association with IIRTV and support the potential utility of IIRTV as a valid endophenotype for ADHD symptoms. However, limitations of this study suggest that these observations should be interpreted with caution until replication samples become available.
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ItemNo Preview AvailableNetwork scaling effects in graph analytic studies of human resting-state fMRI data(FRONTIERS MEDIA SA, 2010)Graph analysis has become an increasingly popular tool for characterizing topological properties of brain connectivity networks. Within this approach, the brain is modeled as a graph comprising N nodes connected by M edges. In functional magnetic resonance imaging (fMRI) studies, the nodes typically represent brain regions and the edges some measure of interaction between them. These nodes are commonly defined using a variety of regional parcellation templates, which can vary both in the volume sampled by each region, and the number of regions parcellated. Here, we sought to investigate how such variations in parcellation templates affect key graph analytic measures of functional brain organization using resting-state fMRI in 30 healthy volunteers. Seven different parcellation resolutions (84, 91, 230, 438, 890, 1314, and 4320 regions) were investigated. We found that gross inferences regarding network topology, such as whether the brain is small-world or scale-free, were robust to the template used, but that both absolute values of, and individual differences in, specific parameters such as path length, clustering, small-worldness, and degree distribution descriptors varied considerably across the resolutions studied. These findings underscore the need to consider the effect that a specific parcellation approach has on graph analytic findings in human fMRI studies, and indicate that results obtained using different templates may not be directly comparable.
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ItemNo Preview AvailableHierarchical modularity in human brain functional networks.(Frontiers Media SA, 2009)The idea that complex systems have a hierarchical modular organization originated in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I = 0.63. The largest five modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.