Psychiatry - Research Publications
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ItemBrain change trajectories that differentiate the major psychoses(WILEY, 2016-07)BACKGROUND: Bipolar disorder and schizophrenia are highly heritable, often chronic and debilitating psychotic disorders that can be difficult to differentiate clinically. Their brain phenotypes appear to overlap in both cross-sectional and longitudinal structural neuroimaging studies, with some evidence to suggest areas of differentiation with differing trajectories. The aim of this review was to investigate the notion that longitudinal trajectories of alterations in brain structure could differentiate the two disorders. DESIGN: Narrative review. We searched MEDLINE and Web of Science databases in May 2016 for studies that used structural magnetic resonance imaging to investigate longitudinal between-group differences in bipolar disorder and schizophrenia. Ten studies met inclusion criteria, namely longitudinal structural magnetic resonance studies comparing bipolar disorder (or affective psychosis) and schizophrenia within the same study. RESULTS: Our review of these studies implicates illness-specific trajectories of morphological change in total grey matter volume, and in regions of the frontal, temporal and cingulate cortices. The findings in schizophrenia suggest a trajectory involving progressive grey matter loss confined to fronto-temporal cortical regions. Preliminary findings identify a similar but less severely impacted trajectory in a number of regions in bipolar disorder, however, bipolar disorder is also characterized by differential involvement across cingulate subregions. CONCLUSION: The small number of available studies must be interpreted with caution but provide initial evidence supporting the notion that bipolar disorder and schizophrenia have differential longitudinal trajectories that are influenced by brain maturation.
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ItemCortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium(ELSEVIER SCIENCE INC, 2018-11-01)BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.
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ItemPredictors and consequences of health anxiety symptoms: a novel twin modeling study(WILEY, 2018-03)OBJECTIVE: The question of how to best conceptualize health anxiety (HA) from a diagnostic and etiological perspective remains debated. The aim was to examine the relationship between HA and the symptoms of anxiety and obsessive-compulsive-related disorders in a normative twin population. METHOD: Four hundred and ninety-six monozygotic adult twin pairs from the Australian Twin Registry participated in the study (age, 34.4 ± 7.72 years; 59% females). Validated scales were used to assess each domain. We applied a twin regression methodology-ICE FALCON-to determine whether there was evidence consistent with 'causal' relationships between HA and other symptoms by fitting and comparing model estimates. RESULTS: Estimates were consistent with higher levels of obsessing ('unwanted thoughts') (P = 0.008), social anxiety (P = 0.03), and body dysmorphic symptoms (P = 0.008) causing higher levels of HA symptoms, and with higher levels of HA symptoms causing higher levels of physical/somatic anxiety symptoms (P = 0.001). CONCLUSION: Obsessional thoughts, body dysmorphic concerns, and social anxiety symptoms may have a causal influence on HA. To report physical/somatic anxiety appears to be a consequence of the underlying presence of HA-related fears. Should our results be confirmed by longitudinal studies, the evaluation and treatment of HA may benefit from the consideration of these identified risk factors.
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ItemAge at first birth in women is genetically associated with increased risk of schizophrenia(NATURE PORTFOLIO, 2018-07-05)Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.
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ItemA Hierarchical Model of Inhibitory Control(FRONTIERS MEDIA SA, 2018-08-02)Inhibitory control describes the suppression of goal-irrelevant stimuli and behavioral responses. Current developmental taxonomies distinguish between Response Inhibition - the ability to suppress a prepotent motor response, and Attentional Inhibition - the ability to resist interference from distracting stimuli. Response Inhibition and Attentional Inhibition have exhibited moderately strong positive correlations in previous studies, suggesting they are closely related cognitive abilities. These results may reflect the use of cognitive tasks combining Stimulus-Stimulus- and Stimulus-Response-conflict as indicators of both constructs, which may have conflated their empirical association. Additionally, previous statistical modeling studies have not controlled for individual differences in Working Memory Capacity, which may account for some of the empirical overlap between Response Inhibition and Attentional Inhibition. The aim of the current study was to test a hierarchical model of inhibitory control that specifies Working Memory Capacity as a higher-order cognitive construct. Response Inhibition and Attentional Inhibition were conceptualized as lower-order cognitive mechanisms that should be empirically independent constructs apart from their shared reliance on Working Memory Capacity for active maintenance of goal-relevant representations. Measures of performance on modified stimulus-response compatibility tasks, complex memory span, and non-selective stopping tasks were obtained from 136 preadolescent children (M = 11 years, 10 months, SD = 8 months). Consistent with hypotheses, results from Structural Equation Modeling demonstrated that the Response Inhibition and Attentional Inhibition factors were empirically independent constructs that exhibited partial statistical dependence on the Working Memory Capacity factor. These findings have important implications for current theories and models of inhibitory control during development.
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ItemPeripheral Transcription of NRG-ErbB Pathway Genes Are Upregulated in Treatment-Resistant Schizophrenia(FRONTIERS MEDIA SA, 2017-11-06)Investigation of peripheral gene expression patterns of transcripts within the NRG-ErbB signaling pathway, other than neuregulin-1 (NRG1), among patients with schizophrenia and more specifically treatment-resistant schizophrenia (TRS) is limited. The present study built on our previous work demonstrating elevated levels of NRG1 EGFα, EGFβ, and type I(Ig2) containing transcripts in TRS by investigating 11 NRG-ErbB signaling pathway mRNA transcripts (NRG2, ErbB1, ErbB2, ErbB3, ErbB4, PIK3CD, PIK3R3, AKT1, mTOR, P70S6K, eIF4EBP1) in whole blood of TRS patients (N = 71) and healthy controls (N = 57). We also examined the effect of clozapine exposure on transcript levels using cultured peripheral blood mononuclear cells (PBMCs) from 15 healthy individuals. Five transcripts (ErbB3, PIK3CD, AKT1, P70S6K, eIF4EBP1) were significantly elevated in TRS patients compared to healthy controls but only expression of P70S6K (Pcorrected = 0.018), a protein kinase linked to protein synthesis, cell growth, and cell proliferation, survived correction for multiple testing using the Benjamini-Hochberg method. Investigation of clinical factors revealed that ErbB2, PIK3CD, PIK3R3, AKT1, mTOR, and P70S6K expression were negatively correlated with duration of illness. However, no transcript was associated with chlorpromazine equivalent dose or clozapine plasma levels, the latter supported by our in vitro PBMC clozapine exposure experiment. Taken together with previously published NRG1 results, our findings suggest an overall upregulation of transcripts within the NRG-ErbB signaling pathway among individuals with schizophrenia some of which attenuate over duration of illness. Follow-up studies are needed to determine if the observed peripheral upregulation of transcripts within the NRG-ErbB signaling pathway are specific to TRS or are a general blood-based marker of schizophrenia.
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ItemNo Preview AvailableSchizophrenia risk from complex variation of complement component 4(NATURE PUBLISHING GROUP, 2016-02-11)Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia's strongest genetic association at a population level involves variation in the major histocompatibility complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to identify. Here we show that this association arises in part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C4A. Human C4 protein localized to neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals with schizophrenia.
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ItemMulti-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2017-01-15)Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center.
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ItemNo Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study(PUBLIC LIBRARY SCIENCE, 2016-10)It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest.