Psychiatry - Research Publications

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    Plasma neurofilament light chain is not elevated in people with first-episode psychosis or those at ultra-high risk for psychosis
    Kang, MJY ; Eratne, D ; Wannan, C ; Santillo, AF ; Velakoulis, D ; Pantelis, C ; Cropley, V (ELSEVIER, 2024-05)
    INTRODUCTION: Neurofilament light chain (NfL), a blood biomarker of neuronal injury, shows promise in distinguishing neurodegenerative disorders from psychiatric conditions. This is especially relevant in psychosis, given neurological conditions such as autoimmune encephalitis and Niemann Pick Type C disease (NPC) may initially present with psychotic symptoms. Whilst NfL levels have been studied in established schizophrenia cases, their levels in first-episode psychosis (FEP) and ultra-high risk (UHR) for psychosis individuals remain largely unexplored. This study aimed to compare plasma NfL in people with FEP or UHR with healthy controls, as well as explore its associations with clinical data. METHOD: We retrospectively analysed plasma NfL in 63 participants, consisting of 29 individuals with FEP, 10 individuals with UHR, and 24 healthy controls. We used general linear models (GLM), which were bootstrapped, to compute bias-corrected and accelerated (BCa) 95 % confidence intervals (CIs). RESULTS: Mean NfL levels were 5.2 pg/mL in FEP, 4.9 pg/mL in UHR, and 5.9 pg/mL in healthy controls. Compared to healthy controls, there were no significant differences in NfL levels in the FEP group (β = -0.22, 95 % CI [-0.86, 0.39], p = 0.516) nor UHR group (β = -0.37, 95 % CI [-0.90, 0.19], p = 0.182). There were no significant associations between NfL levels and clinical variables in the FEP group. DISCUSSION: Our study is the first to demonstrate that plasma NfL levels are not significantly elevated in individuals at UHR for psychosis compared to healthy controls, a finding also observed in the FEP cohort. These findings bolster the potential diagnostic utility of NfL in differentiating between psychiatric and neurodegenerative disorders.
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    Public support for proposed government policies to optimise the social benefits of autonomous vehicles
    Pettigrew, S ; Booth, L ; Farrar, V ; Brown, J ; Karl, C ; Godic, B ; Vidanaarachchi, R ; Thompson, J (ELSEVIER SCI LTD, 2024-04)
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    Predictors of the placebo response in a nutraceutical randomizedcontrolled trial for depression
    Arnold, R ; Murphy-Smith, J ; Ng, CH ; Mischoulon, D ; Byrne, GJ ; Bousman, CA ; Stough, C ; Berk, M ; Sarris, J (ELSEVIER, 2024-01)
    OBJECTIVE: The placebo response in depression studies is the change in symptoms amongst those who receive an inactive treatment. Many well-designed randomized controlled trials (RCTs) of depression have a high proportion of placebo responders, with little understanding as to why. The present study assesses characteristics associated with the placebo response in a nutraceutical trial with a large proportion of placebo responders. METHODS: This is a secondary analysis of a nutraceutical depression RCT which identified no overall treatment benefit relative to placebo (n = 69 in placebo group). We investigated participant characteristics such as socio-demographics, clinical features, and recruitment methods, and their association with the placebo response. Monoaminergic genetic polymorphisms were also assessed. Placebo response was measured based on change in Montgomery-Asberg Depression Rating Scale score. The association of these hypothesis-driven variables of interest and the placebo response was examined using linear mixed effects models. RESULTS: Greater levels of education, particularly pursuing post-high school education, better self-reported general health, marriage/de facto, greater improvement in the first trial week, and more failed antidepressant therapies in the current depressive episode were associated with greater placebo response. An increased placebo response was not found in those recruited via social media nor in those with concomitant antidepressant therapy. Single nucleotide polymorphisms from the tryptophan hydroxylase 1 (TPH1) gene (A779C and A218C) were weakly associated with greater placebo response, although the evidence was attenuated after accounting for multiple comparisons. CONCLUSION: This is, to our knowledge, the first study within nutraceutical research for depression to assess the association between participant characteristics and variation in the placebo response. Several variables appeared to predict the placebo response. Such findings may encourage future trial designs which could dampen placebo response, improve assay sensitivity, and allow for treatment effects to be potentially more detectable. Please cite this article as: Arnold R, Murphy-Smith J, Ng CH, Mischoulon D, Byrne GJ, Bousman CA, Stough C, Berk M, Sarris J. Predictors of the placebo response in a nutraceutical randomized controlled trial for depression. J Integr Med. 2024; 22(1): 46-53.
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    A comparison of content from across contemporary Australian population health surveys
    Godic, B ; Akaraci, S ; Vidanaarachchi, R ; Nice, K ; Seneviratne, S ; Mavoa, S ; Hunter, R ; Garcia, L ; Stevenson, M ; Wijnands, J ; Thompson, J (Wiley, 2024-06)
    Objective: Associations between place and population health are of interest to researchers and policymakers. The objective of this paper is to explore, summarise and compare content across contemporary Australian geo-referenced population health survey data sets. Methods: A search for recent (2015 or later) population health surveys from within Australia containing geographic information from participants was conducted. Survey response frames were analysed and categorised based on demographic, risk factor and disease-related characteristics. Analysis using interactive Sankey diagrams shows the extent of content overlap and differences between population health surveys in Australia. Results: Thirteen Australian geo-referenced population health survey data sets were identified. Information captured across surveys was inconsistent as was the spatial granularity of respondent information. Health and demographic features most frequently captured were symptoms, signs and clinical findings from the International Statistical Classification of Diseases and Related Health Problems version 11, employment, housing, income, self-rated health and risk factors, including alcohol consumption, diet, medical treatments, physical activity and weight-related questions. Sankey diagrams were deployed online for use by public health researchers. Conclusions: Identifying the relationship between place and health in Australia is made more difficult by inconsistencies in information collected across surveys deployed in different regions in Australia. Implications for Public Health: Public health research investigating place and health involves a vast and inconsistent patchwork of information within and across states, which may impact broad-scale research questions. The tools developed here assist public health researchers to identify surveys suitable for their research queries related to place and health.
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    Trajectory of adjustment difficulties following disaster: 10-year longitudinal cohort study
    Pacella, BJ ; Cowlishaw, S ; Gibbs, L ; Bryant, RA ; Brady, K ; Gallagher, C ; Molyneaux, R ; Gibson, K ; Block, K ; Harms, L ; Forbes, D ; ODonnell, ML (Cambridge University Press, 2024-03)
    BACKGROUND: Although much is known about psychopathology such as post-traumatic stress disorder (PTSD) and depression following bushfire (also known as wildfire), little is known about prevalence, trajectory and impacts for those experiencing general adjustment difficulties following exposure to these now-common events. AIMS: This was an exploratory analysis of a large cohort study that examined the prevalence, trajectory and risk factors of probable adjustment disorder over a 10-year period following bushfire exposure. METHOD: The Beyond Bushfires study assessed individuals exposed to a large and deadly bushfire across three time points spanning 10 years. Self-report survey data from participants from areas with moderate and high levels of fire-affectedness were analysed: n = 802 participants at Wave 1 (3-4 years post-fires), n = 596 at Wave 2 (5 years post-fires) and n = 436 at Wave 3 (10 years post-fires). Surveys indexed fire-related experiences and post-fire stressors, and comprised the six-item Kessler Psychological Distress Scale (probable adjustment disorder index), four-item Posttraumatic Stress Disorder Checklist (probable fire-related PTSD) and nine-item Patient Health Questionnaire (probable major depressive episode). RESULTS: Prevalence of probable adjustment disorder was 16% (Wave 1), 15% (Wave 2) and 19% (Wave 3). Probable adjustment disorder at 3-4 years post-fires predicted a five-fold increase in risk for escalating to severe psychiatric disorder (i.e. probable fire-related PTSD/major depressive episode) at 10 years post-fires, and was associated with post-fire income and relationship stressors. CONCLUSIONS: Adjustment difficulties are prevalent post-disaster, many of which are maintained and exacerbated over time, resulting in increased risk for later disorder and adaptation difficulties. Psychosocial interventions supporting survivors with adjustment difficulties may prevent progression to more severe disorder.
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    Neuroimaging Insights: Kava's (Piper methysticum) Effect on Dorsal Anterior Cingulate Cortex GABA in Generalized Anxiety Disorder.
    Savage, K ; Sarris, J ; Hughes, M ; Bousman, CA ; Rossell, S ; Scholey, A ; Stough, C ; Suo, C (MDPI AG, 2023-10-28)
    Generalised Anxiety Disorder (GAD) is a prevalent, chronic mental health disorder. The measurement of regional brain gamma-aminobutyric acid (GABA) offers insight into its role in anxiety and is a potential biomarker for treatment response. Research literature suggests Piper methysticum (Kava) is efficacious as an anxiety treatment, but no study has assessed its effects on central GABA levels. This study investigated dorsal anterior cingulate (dACC) GABA levels in 37 adult participants with GAD. GABA was measured using proton magnetic resonance spectroscopy (1H-MRS) at baseline and following an eight-week administration of Kava (standardised to 120 mg kavalactones twice daily) (n = 20) or placebo (n = 17). This study was part of the Kava for the Treatment of GAD (KGAD; ClinicalTrials.gov: NCT02219880), a 16-week intervention study. Compared with the placebo group, the Kava group had a significant reduction in dACC GABA (p = 0.049) at eight weeks. Baseline anxiety scores on the HAM-A were positively correlated with GABA levels but were not significantly related to treatment. Central GABA reductions following Kava treatment may signal an inhibitory effect, which, if considered efficacious, suggests that GABA levels are modulated by Kava, independent of reported anxiety symptoms. dACC GABA patterns suggest a functional role of higher levels in clinical anxiety but warrants further research for symptom benefit. Findings suggest that dACC GABA levels previously un-examined in GAD could serve as a biomarker for diagnosis and treatment response.
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    Cumulative trauma load and timing of trauma prior to military deployment differentially influences inhibitory control processing across deployment
    Miller, LN ; Forbes, D ; Mcfarlane, AC ; Lawrence-Wood, E ; Simmons, JG ; Felmingham, K (NATURE PORTFOLIO, 2023-12-05)
    Military personnel experience high trauma load that can change brain circuitry leading to impaired inhibitory control and posttraumatic stress disorder (PTSD). Inhibitory control processing may be particularly vulnerable to developmental and interpersonal trauma. This study examines the differential role of cumulative pre-deployment trauma and timing of trauma on inhibitory control using the Go/NoGo paradigm in a military population. The Go/NoGo paradigm was administered to 166 predominately male army combat personnel at pre- and post-deployment. Linear mixed models analyze cumulative trauma, trauma onset, and post-deployment PTSD symptoms on NoGo-N2 and NoGo-P3 amplitude and latency across deployment. Here we report, NoGo-N2 amplitude increases and NoGo-P3 amplitude and latency decreases in those with high prior interpersonal trauma across deployment. Increases in NoGo-P3 amplitude following adolescent-onset trauma and NoGo-P3 latency following childhood-onset and adolescent-onset trauma are seen across deployment. Arousal symptoms positively correlated with conflict monitoring. Our findings support the cumulative trauma load and sensitive period of trauma exposure models for inhibitory control processing in a military population. High cumulative interpersonal trauma impacts conflict monitoring and response suppression and increases PTSD symptoms whereas developmental trauma differentially impacts response suppression. This research highlights the need for tailored strategies for strengthening inhibitory control, and that consider timing and type of trauma in military personnel.
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    Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.
    Belov, V ; Erwin-Grabner, T ; Aghajani, M ; Aleman, A ; Amod, AR ; Basgoze, Z ; Benedetti, F ; Besteher, B ; Bülow, R ; Ching, CRK ; Connolly, CG ; Cullen, K ; Davey, CG ; Dima, D ; Dols, A ; Evans, JW ; Fu, CHY ; Gonul, AS ; Gotlib, IH ; Grabe, HJ ; Groenewold, N ; Hamilton, JP ; Harrison, BJ ; Ho, TC ; Mwangi, B ; Jaworska, N ; Jahanshad, N ; Klimes-Dougan, B ; Koopowitz, S-M ; Lancaster, T ; Li, M ; Linden, DEJ ; MacMaster, FP ; Mehler, DMA ; Melloni, E ; Mueller, BA ; Ojha, A ; Oudega, ML ; Penninx, BWJH ; Poletti, S ; Pomarol-Clotet, E ; Portella, MJ ; Pozzi, E ; Reneman, L ; Sacchet, MD ; Sämann, PG ; Schrantee, A ; Sim, K ; Soares, JC ; Stein, DJ ; Thomopoulos, SI ; Uyar-Demir, A ; van der Wee, NJA ; van der Werff, SJA ; Völzke, H ; Whittle, S ; Wittfeld, K ; Wright, MJ ; Wu, M-J ; Yang, TT ; Zarate, C ; Veltman, DJ ; Schmaal, L ; Thompson, PM ; Goya-Maldonado, R ; ENIGMA Major Depressive Disorder working group, (Springer Science and Business Media LLC, 2024-01-11)
    Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.
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    Major depressive disorder associated alterations in the effective connectivity of the face processing network: a systematic review
    Jamieson, AJ ; Leonards, CA ; Davey, CG ; Harrison, BJ (SPRINGERNATURE, 2024-01-25)
    Major depressive disorder (MDD) is marked by altered processing of emotional stimuli, including facial expressions. Recent neuroimaging research has attempted to investigate how these stimuli alter the directional interactions between brain regions in those with MDD; however, methodological heterogeneity has made identifying consistent effects difficult. To address this, we systematically examined studies investigating MDD-associated differences present in effective connectivity during the processing of emotional facial expressions. We searched five databases: PsycINFO, EMBASE, PubMed, Scopus, and Web of Science, using a preregistered protocol (registration number: CRD42021271586). Of the 510 unique studies screened, 17 met our inclusion criteria. These studies identified that compared with healthy controls, participants with MDD demonstrated (1) reduced connectivity from the dorsolateral prefrontal cortex to the amygdala during the processing of negatively valenced expressions, and (2) increased inhibitory connectivity from the ventromedial prefrontal cortex to amygdala during the processing of happy facial expressions. Most studies investigating the amygdala and anterior cingulate cortex noted differences in their connectivity; however, the precise nature of these differences was inconsistent between studies. As such, commonalities observed across neuroimaging modalities warrant careful investigation to determine the specificity of these effects to particular subregions and emotional expressions. Future research examining longitudinal connectivity changes associated with treatment response may provide important insights into mechanisms underpinning therapeutic interventions, thus enabling more targeted treatment strategies.
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    Extreme deviations from the normative model reveal cortical heterogeneity and associations with negative symptom severity in first-episode psychosis from the OPTiMiSE and GAP studies
    Worker, A ; Berthert, P ; Lawrence, AJ ; Kia, SM ; Arango, C ; Dinga, R ; Galderisi, S ; Glenthoj, B ; Kahn, RS ; Leslie, A ; Murray, RM ; Pariante, CM ; Pantelis, C ; Weiser, M ; Winter-van Rossum, I ; Mcguire, P ; Dazzan, P ; Marquand, AF (SPRINGERNATURE, 2023-12-02)
    There is currently no quantifiable method to predict long-term clinical outcomes in patients presenting with a first episode of psychosis. A major barrier to developing useful markers for this is biological heterogeneity, where many different pathological mechanisms may underly the same set of symptoms in different individuals. Normative modelling has been used to quantify this heterogeneity in established psychotic disorders by identifying regions of the cortex which are thinner than expected based on a normative healthy population range. These brain atypicalities are measured at the individual level and therefore potentially useful in a clinical setting. However, it is still unclear whether alterations in individual brain structure can be detected at the time of the first psychotic episode, and whether they are associated with subsequent clinical outcomes. We applied normative modelling of cortical thickness to a sample of first-episode psychosis patients, with the aim of quantifying heterogeneity and to use any pattern of cortical atypicality to predict symptoms and response to antipsychotic medication at timepoints from baseline up to 95 weeks (median follow-ups = 4). T1-weighted brain magnetic resonance images from the GAP and OPTiMiSE samples were processed with Freesurfer V6.0.0 yielding 148 cortical thickness features. An existing normative model of cortical thickness (n = 37,126) was adapted to integrate data from each clinical site and account for effects of gender and site. Our test sample consisted of control participants (n = 149, mean age = 26, SD = 6.7) and patient data (n = 295, mean age = 26, SD = 6.7), this sample was used for estimating deviations from the normative model and subsequent statistical analysis. For each individual, the 148 cortical thickness features were mapped to centiles of the normative distribution and converted to z-scores reflecting the distance from the population mean. Individual cortical thickness metrics of +/- 2.6 standard deviations from the mean were considered extreme deviations from the norm. We found that no more than 6.4% of psychosis patients had extreme deviations in a single brain region (regional overlap) demonstrating a high degree of heterogeneity. Mann-Whitney U tests were run on z-scores for each region and significantly lower z-scores were observed in FEP patients in the frontal, temporal, parietal and occipital lobes. Finally, linear mixed-effects modelling showed that negative deviations in cortical thickness in parietal and temporal regions at baseline are related to more severe negative symptoms over the medium-term. This study shows that even at the early stage of symptom onset normative modelling provides a framework to identify individualised cortical markers which can be used for early personalised intervention and stratification.