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The social and emotional wellbeing of young Aboriginal and Torres Strait Islander peoples should be supported through an Indigenous-led and community empowering approach. Applying systems thinking via participatory approaches is aligned with Aboriginal and Torres Strait Islander research paradigms and can be an effective method to deliver a decision support tool for mental health systems planning for Indigenous communities. Evaluations are necessary to understand the effectiveness and value of such methods, uncover protective and healing factors of social and emotional wellbeing, as well as to promote Aboriginal and Torres Strait Islander self-determination over allocation of funding and resources. This paper presents modifications to a published evaluation protocol for participatory systems modelling to align with critical Aboriginal and Torres Strait Islander guidelines and recommendations to support the social and emotional wellbeing of young people. This paper also presents a culturally relevant participatory systems modelling evaluation framework. Recognizing the reciprocity, strengths, and expertise Aboriginal and Torres Strait Islander methodologies can offer to broader research and evaluation practices, the amended framework presented in this paper facilitates empowering evaluation practices that should be adopted when working with Aboriginal and Torres Strait Islander peoples as well as when working with other diverse, non-Indigenous communities.

A rate-limiting step in the prevention and early intervention of depressive disorders in young people is our insufficient understanding of causal mechanisms. One plausible pathophysiological pathway is disturbance in the 24 h sleep-wake cycle and the underlying circadian system. Abnormalities in circadian rhythms are well documented in adults with various depressive disorders and have been linked to core clinical features, including unstable mood, daytime fatigue, non-restorative sleep, reduced motor activity, somatic symptoms, and appetite and weight change. In this Review, we summarise four areas of research: basic circadian biology and animal models of circadian disturbances; developmental changes in circadian rhythms during adolescence and implications for the emergence of adolescent-onset depressive syndromes; community and clinical studies linking 24 h sleep-wake cycle disturbances and depressive disorders; and clinical trials of circadian-based treatments. We present recommendations based on a highly personalised, early intervention model for circadian-linked depression in young people.

GABA is the primary inhibitory neurotransmitter in the brain, and is essential to the balance of cortical excitation and inhibition. Reductions in GABA are proposed to result in an overly excitatory cortex that may cause, or contribute to, symptoms of autism spectrum disorder (ASD). This study employed a cross-sectional design to explore GABA+ differences in ASD and the impact of age, comparing 4-12 year olds with ASD (N = 24) to typically developing children (N = 35). GABA+ concentration was measured using edited magnetic resonance spectroscopy in the left parietal lobe. This study used a mixed model to investigate group differences between children with ASD and typically developing children. There was a significant difference in GABA+ levels between the groups, a significant effect of age and interaction between age and diagnostic group. The ASD group showed an association between GABA+ and age, with GABA+ levels gradually increasing with age (r = 0.59, p = 0.003). Typically developing children did not show age-related change in GABA+ concentration (r = 0.09, p = 0.60). By the age of 9, children with ASD showed GABA+ levels that were comparable to their typically developing peers. This study suggests that children with ASD have initially lower levels of GABA+ in the left parietal lobe compared to typically developing children, and that these initially lower levels of GABA+ increase with age in ASD within this region. It is suggested that this developmental shift of GABA+ levels within the left parietal lobe provides a possible explanation for the previously found reductions in childhood that does not persist in adults. LAY SUMMARY: This study measured levels of GABA in the left parietal lobe using magnetic resonance spectroscopy in children with ASD and typically developing children. GABA levels were initially lower in the ASD group, and increased with age, while GABA did not change with age in the typically developing group. This suggests that alterations in GABA signaling may be associated with ASD in childhood. Autism Res 2021, 14: 859-872. © 2021 International Society for Autism Research, Wiley Periodicals LLC.

The ongoing COVID-19 pandemic has impacted the mental health of populations and highlighted the limitations of mental health care systems. As the trajectory of the pandemic and the economic recovery are still uncertain, decision tools are needed to help evaluate the best interventions to improve mental health outcomes. We developed a system dynamics model that captures causal relationships among population, demographics, post-secondary education, health services, COVID-19 impact, and mental health outcomes. The study was conducted in the Australian state of Victoria. The model was calibrated using historical data and was stratified by age group and by geographic remoteness. Findings demonstrate that the most effective intervention combination includes economic, social, and health sector initiatives. Assertive post-suicide attempt care is the most impactful health sector intervention, but delaying implementation reduces the potency of its impact. Some evidence-based interventions, such as population-wide community awareness campaigns, are projected to worsen mental health outcomes when implemented on their own. Systems modelling offers a powerful decision-support tool to test alternative strategies for improving mental health outcomes in the Victorian context.

The COVID-19 pandemic demonstrated the significant value of systems modelling in supporting proactive and effective public health decision making despite the complexities and uncertainties that characterise an evolving crisis. The same approach is possible in the field of mental health. However, a commonly levelled (but misguided) criticism prevents systems modelling from being more routinely adopted, namely, that the presence of uncertainty around key model input parameters renders a model useless. This study explored whether radically different simulated trajectories of suicide would result in different advice to decision makers regarding the optimal strategy to mitigate the impacts of the pandemic on mental health. Using an existing system dynamics model developed in August 2020 for a regional catchment of Western Australia, four scenarios were simulated to model the possible effect of the COVID-19 pandemic on levels of psychological distress. The scenarios produced a range of projected impacts on suicide deaths, ranging from a relatively small to a dramatic increase. Discordance in the sets of best-performing intervention scenarios across the divergent COVID-mental health trajectories was assessed by comparing differences in projected numbers of suicides between the baseline scenario and each of 286 possible intervention scenarios calculated for two time horizons; 2026 and 2041. The best performing intervention combinations over the period 2021–2041 (i.e., post-suicide attempt assertive aftercare, community support programs to increase community connectedness, and technology enabled care coordination) were highly consistent across all four COVID-19 mental health trajectories, reducing suicide deaths by between 23.9–24.6% against the baseline. However, the ranking of best performing intervention combinations does alter depending on the time horizon under consideration due to non-linear intervention impacts. These findings suggest that systems models can retain value in informing robust decision making despite uncertainty in the trajectories of population mental health outcomes. It is recommended that the time horizon under consideration be sufficiently long to capture the full effects of interventions, and efforts should be made to achieve more timely tracking and access to key population mental health indicators to inform model refinements over time and reduce uncertainty in mental health policy and planning decisions.

BackgroundMental illness costs the world economy over US2.5 Bn each year, including premature mortality, morbidity, and productivity losses. Multisector approaches are required to address the systemic drivers of mental health and ensure adequate service provision. There is an important role for economics to support priority setting, identify best value investments and inform optimal implementation. Mental health can be defined as a complex dynamic system where decision makers are challenged to prospectively manage the system over time. This protocol describes the approach to equip eight system dynamics (SD) models across Australia to support priority setting and guide portfolio investment decisions, tailored to local implementation context.MethodsAs part of a multidisciplinary team, three interlinked protocols are developed; (i) the participatory process to codesign the models with local stakeholders and identify interventions for implementation, (ii) the technical protocol to develop the SD models to simulate the dynamics of the local population, drivers of mental health, the service system and clinical outcomes, and (iii) the economic protocol to detail how the SD models will be equipped to undertake a suite of economic analysis, incorporating health and societal perspectives. Models will estimate the cost of mental illness, inclusive of service costs (health and other sectors, where necessary), quality-adjusted life years (QALYs) lost, productivity costs and carer costs. To assess the value of investing (disinvesting) in interventions, economic analysis will include return-on-investment, cost-utility, cost benefit, and budget impact to inform affordability. Economic metrics are expected to be dynamic, conditional upon changing population demographics, service system capacities and the mix of interventions when synergetic or antagonistic interactions. To support priority setting, a portfolio approach will identify best value combinations of interventions, relative to a defined budget(s). User friendly dashboards will guide decision makers to use the SD models to inform resource allocation and generate business cases for funding.DiscussionEquipping SD models to undertake economic analysis is intended to support local priority setting and help optimise implementation regarding the best value mix of investments, timing and scale. The objectives are to improve allocative efficiency, increase mental health and economic productivity.

Background The right to the highest attainable standard of mental health remains a distant goal worldwide. The Report of the UN Special Rapporteur on the right of all people to enjoyment of the highest attainable standard of physical and mental health pleaded the urgent need for governments to act through appropriate laws and policies. We argue that Australia is in breach of international obligations, with inadequate access to mental health services, inconsistent mental health legislation across jurisdictions and ongoing structural (systematic) and individual discrimination. Discussion Inadequate access to mental health services is a worldwide phenomenon. Australia has committed to international law obligations under the Convention on the Rights of Persons with Disabilities (CRPD) to ‘promote, protect and ensure the full and equal enjoyment of all human rights and fundamental freedoms by all persons with disability, with respect to their inherent dignity’. This includes people with mental health impairment and this convention includes the right to ‘the highest attainable standard of mental health’. Under the Australian Constitution, ratification of this convention enables the national government to pass laws to implement the convention obligations, and such national laws would prevail over any inconsistent state (or territory) laws governing mental health service provision. Summary The authors argue that enabling positive rights through legislation and legally binding mental health service standards may facilitate enhanced accountability and enforcement of such rights. These steps may support critical key stakeholders to improve the standards of mental health service provision supported by the implementation of international obligations, thereby accelerating mental health system reform. Improved legislation would encourage better governance and the evolution of better services, making mental health care more accessible, without structural or individual discrimination, enabling all people to enjoy the highest attainable standard of health.

Background Despite significant investment, mental health issues remain a leading cause of death among young people globally. Sophisticated decision analysis methods are needed to better understand the dynamic and multisector drivers of youth mental health. System modeling can help explore complex issues such as youth mental health and inform strategies to effectively respond to local needs and achieve lasting improvements. The advantages of engaging stakeholders in model development processes have long been recognized; however, the methods for doing so are often not well-described. Objective This paper aims to describe the participatory procedures that will be used to support systems modeling for national multisite implementation. The Right Care, First Time, Where You Live research program will focus on regional youth mental health applications of systems modeling in 8 different sites across Australia. Methods The participatory model development approach involves an iterative process of engaging with a range of participants, including people with lived experience of mental health issues. Their knowledge of the local systems, pathways, and drivers is combined with the academic literature and data to populate the models and validate their structure. The process centers around 3 workshops where participants interact and actively engage in group model-building activities to define, refine, and validate the systems models. This paper provides a detailed blueprint for the implementation of this process for mental health applications. Results The participatory modeling methods described in this paper will be implemented at 2 sites per year from 2022 to 2025. The 8 selected sites have been chosen to capture variations in important factors, including determinants of mental health issues and access to services. Site engagement commenced in August 2021, and the first modeling workshops are scheduled to commence in February 2022. Conclusions Mental health system decision makers require tools to help navigate complex environments and leverage interdisciplinary problem-solving. Systems modeling can mobilize data from diverse sources to explore a range of scenarios, including the impact of interventions in different combinations and contexts. Involving stakeholders in the model development process ensures that the model findings are context-relevant and fit-for-purpose to inform decision-making. International Registered Report Identifier (IRRID) PRR1-10.2196/32988

BACKGROUND Despite significant investment, mental health issues remain a leading cause of death among young people globally. Sophisticated decision analysis methods are needed to better understand the dynamic and multisector drivers of youth mental health. System modeling can help explore complex issues such as youth mental health and inform strategies to effectively respond to local needs and achieve lasting improvements. The advantages of engaging stakeholders in model development processes have long been recognized; however, the methods for doing so are often not well-described. OBJECTIVE This paper aims to describe the participatory procedures that will be used to support systems modeling for national multisite implementation. The Right Care, First Time, Where You Live research program will focus on regional youth mental health applications of systems modeling in 8 different sites across Australia. METHODS The participatory model development approach involves an iterative process of engaging with a range of participants, including people with lived experience of mental health issues. Their knowledge of the local systems, pathways, and drivers is combined with the academic literature and data to populate the models and validate their structure. The process centers around 3 workshops where participants interact and actively engage in group model-building activities to define, refine, and validate the systems models. This paper provides a detailed blueprint for the implementation of this process for mental health applications. RESULTS The participatory modeling methods described in this paper will be implemented at 2 sites per year from 2022 to 2025. The 8 selected sites have been chosen to capture variations in important factors, including determinants of mental health issues and access to services. Site engagement commenced in August 2021, and the first modeling workshops are scheduled to commence in February 2022. CONCLUSIONS Mental health system decision makers require tools to help navigate complex environments and leverage interdisciplinary problem-solving. Systems modeling can mobilize data from diverse sources to explore a range of scenarios, including the impact of interventions in different combinations and contexts. Involving stakeholders in the model development process ensures that the model findings are context-relevant and fit-for-purpose to inform decision-making. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/32988

Early life social experiences shape neural pathways in infants to develop lifelong social skills. This review presents the first unified circuit-based model of social learning that can be applied to early life social development, drawing together unique human developmental milestones, sensitive learning periods, and behavioral and neural scaffolds. Circuit domains for social learning are identified governing Activation, Integration, Discrimination, Response and Reward (AIDRR) to sculpt and drive human social learning. This unified model can be used to identify social delays earlier in development. We propose social impairments observed in Autism Spectrum Disorder are underpinned by early mistimed sensitive periods in brain development and alterations in amygdala development to disrupt the AIDRR circuits. This model directs how interventions can target neural circuits for social development and be applied early in life. To illustrate, the role of oxytocin and its use as an intervention is explored. The AIDRR model shifts focus away from delivering broad treatments based only on diagnostic classifications, to specifying and targeting the relevant circuits, at the right time of development, to optimize social learning.

The World Health Organization Disability Assessment Schedule II (WHODAS-II) is one of the most widely used generic assessments for measuring disability levels in both clinical and nonclinical populations, with sound psychometrics that is also aligned with the International Classification of Functioning framework. However, its psychometric properties have not been explored extensively in individuals with autism spectrum disorder (ASD). This study examined the psychometric properties of the 36-item and 12-item Self-Report WHODAS-II from 109 individuals diagnosed with ASD and without intellectual disability (IQ ≥ 70). Participants were consecutively recruited from the Brain and Mind Centre in New South Wales, Australia. The WHODAS-II showed adequate internal consistency for all domain scores (α = 0.78-0.97 for 36-item) and for the summary scale (α = 0.95 for 36-item; 0.86 for 12-item). All items also exhibited satisfactory correlations with their respective domain (r = 0.39-0.94 for 36-item) and summary scores (r = 0.42-0.71 for 36-item; 0.42-0.67 for 12-item), except item 4.5 "sexual activity" from the 36-item WHODAS-II (r = 0.19). Concurrent validity was shown by moderate correlations between similar constructs across the WHODAS-II and the World Health Organization Quality of Life BREF (Ps < 0.05). The second-order 7-factor model showed the best fit for the 36-item WHODAS-II, while the second-order 6-factor model demonstrated an acceptable fit for the 12-item WHODAS-II. The model fit could be improved with some modifications. The Schmid-Leiman transformation further confirmed the appropriateness of the second-order factor structure. Overall, the results indicated that the WHODAS-II is a viable generic self-report measure for disability in autistic individuals without ID. Autism Res 2019, 12: 1101-1111. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The majority of autistic people have a disability with a profound or severe limitation in their core activities. However, there is currently limited research identifying reliable and valid self-report measures for disability in the autistic population. This study examined the psychometric properties of the World Health Organization Disability Assessment Schedule II (WHODAS-II) from 109 autistic individuals without intellectual disability. Our results suggest that the WHODAS-II is a viable generic self-report measure for disability in autistic individuals.

BACKGROUND Australia’s mental health care system has long been fragmented and under-resourced, with services falling well short of demand. In response, the World Economic Forum has recently called for the rapid deployment of smarter, digitally enhanced health services to facilitate effective care coordination and address issues of demand. The University of Sydney’s Brain and Mind Centre (BMC) has developed an innovative digital health solution that incorporates 2 components: a highly personalized and measurement-based (data-driven) model of youth mental health care and a health information technology (HIT) registered on the Australian Register of Therapeutic Goods. Importantly, research into implementation of such solutions considers education and training of clinicians to be essential to adoption and optimization of use in standard clinical practice. The BMC’s Youth Mental Health and Technology Program has subsequently developed a comprehensive education and training program to accompany implementation of the digital health solution. OBJECTIVE This paper describes the protocol for an evaluation study to assess the effectiveness of the education and training program on the adoption and optimization of use of the digital health solution in service delivery. It also describes the proposed tools to assess the impact of training on knowledge and skills of mental health clinicians. METHODS The evaluation study will use the Kirkpatrick Evaluation Model as a framework with 4 levels of analysis: Reaction (to education and training), Learning (knowledge acquired), Behavior (practice change), and Results (client outcomes). Quantitative and qualitative data will be collected using a variety of tools, including evaluation forms, pre- and postknowledge questionnaires, skill development and behavior change scales, as well as a real-time clinical practice audit. RESULTS This project is funded by philanthropic funding from Future Generation Global. Ethics approval has been granted via Sydney Local Health District’s Human Research Ethics Committee. At the time of this publication, clinicians and their services were being recruited to this study. The first results are expected to be submitted for publication in 2021. CONCLUSIONS The education and training program teaches clinicians the necessary knowledge and skills to assess, monitor, and manage complex needs; mood and psychotic syndromes; and trajectories of youth mental ill-health using a HIT that facilitates a highly personalized and measurement-based model of care. The digital health solution may therefore guide clinicians to help young people recover low functioning associated with subthreshold diagnostic presentations and prevent progression to more serious mental ill-health. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/24697

Background Australia’s mental health care system has long been fragmented and under-resourced, with services falling well short of demand. In response, the World Economic Forum has recently called for the rapid deployment of smarter, digitally enhanced health services to facilitate effective care coordination and address issues of demand. The University of Sydney’s Brain and Mind Centre (BMC) has developed an innovative digital health solution that incorporates 2 components: a highly personalized and measurement-based (data-driven) model of youth mental health care and a health information technology (HIT) registered on the Australian Register of Therapeutic Goods. Importantly, research into implementation of such solutions considers education and training of clinicians to be essential to adoption and optimization of use in standard clinical practice. The BMC’s Youth Mental Health and Technology Program has subsequently developed a comprehensive education and training program to accompany implementation of the digital health solution. Objective This paper describes the protocol for an evaluation study to assess the effectiveness of the education and training program on the adoption and optimization of use of the digital health solution in service delivery. It also describes the proposed tools to assess the impact of training on knowledge and skills of mental health clinicians. Methods The evaluation study will use the Kirkpatrick Evaluation Model as a framework with 4 levels of analysis: Reaction (to education and training), Learning (knowledge acquired), Behavior (practice change), and Results (client outcomes). Quantitative and qualitative data will be collected using a variety of tools, including evaluation forms, pre- and postknowledge questionnaires, skill development and behavior change scales, as well as a real-time clinical practice audit. Results This project is funded by philanthropic funding from Future Generation Global. Ethics approval has been granted via Sydney Local Health District’s Human Research Ethics Committee. At the time of this publication, clinicians and their services were being recruited to this study. The first results are expected to be submitted for publication in 2021. Conclusions The education and training program teaches clinicians the necessary knowledge and skills to assess, monitor, and manage complex needs; mood and psychotic syndromes; and trajectories of youth mental ill-health using a HIT that facilitates a highly personalized and measurement-based model of care. The digital health solution may therefore guide clinicians to help young people recover low functioning associated with subthreshold diagnostic presentations and prevent progression to more serious mental ill-health. International Registered Report Identifier (IRRID) PRR1-10.2196/24697

In this study, we consecutively recruited treatment-seeking young autistic adults without intellectual impairment aged 16–30 years who presented to a mental health service and evaluated general health (distress, quality of life, and disability), functioning (work loss days and social functioning), and mood symptoms (depression, anxiety, and stress) in those diagnosed with autism spectrum disorder ( n = 96). This group was compared to young adults presenting to the same service with primary mental health disorders (depression, n = 343; bipolar, n = 132; psychosis, n = 166; and anxiety, n = 303). This study also investigated the influence of mood symptoms on general health and functioning in the autism spectrum disorder group. Young autistic adults reported significant general health and functioning impairments that were of similar degree to those presenting with primary mental health disorders. Interestingly, the autistic group also reported similarly high levels of mood symptoms to those with primary depressive and anxiety disorders. In the autistic group, depressive symptoms were strongly associated with distress, quality of life, and work loss days, while stress symptoms were strongly associated with disability. This study highlights further research, and mental health services are required specifically targeting young autistic adults to address their significant unmet needs.

Neuroticism, a ‘Big Five’ personality trait, has been associated with sub-clinical traits of both autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). The objective of the current study was to examine whether causal overlap between ASD and ADHD traits can be accounted for by genetic and environmental risk factors that are shared with neuroticism. We performed twin-based structural equation modeling using self-report data from 12 items of the Neo Five-Factor Inventory Neuroticism domain, 11 Social Responsiveness Scale items, and 12 Adult ADHD Self-Report Scale items obtained from 3,170 young adult Australian individual twins (1,081 complete pairs). Univariate analysis for neuroticism, ASD, and ADHD traits suggested that the most parsimonious models were those with additive genetic and unique environmental components, without sex limitation effects. Heritability of neuroticism, ASD, and ADHD traits, as measured by these methods, was moderate (between 40% and 45% for each respective trait). In a trivariate model, we observed moderate phenotypic (between 0.45 and 0.62), genetic (between 0.56 and 0.71), and unique environmental correlations (between 0.37and 0.55) among neuroticism, ASD, and ADHD traits, with the highest value for the shared genetic influence between neuroticism and self-reported ASD traits (rg = 0.71). Together, our results suggest that in young adults, genetic, and unique environmental risk factors indexed by neuroticism overlap with those that are shared by ASD and ADHD.

Background Executive function (EF) difficulties characterise a number of psychiatric conditions and EF impairment may be a predisposing factor and/or consequence of anxiety and stress. The aim of the study was to examine EF factors in a mixed clinical cohort (Autism Spectrum Disorder and Social Anxiety Disorder) characterised by social impairment and investigate the influence of trait anxiety and state-based depression, anxiety and stress. Methods In Study 1, a factor analysis identified EF and non-EF latent factor structures (N=205). In Study 2, (N=137) multiple regression analyses investigated the association between trait anxiety and state based depression, anxiety and stress, on EF and non-EF cognitive domains and on the two composite indices of the Behavioural Rating Inventory of Executive Function (BRIEF). Results Trait anxiety was associated with better performance on neuropsychological measures of EF while state-based stress was associated with lower EF performance. A dissociation was observed between trait anxiety and state stress on the two behavioural indices of the BRIEF. Depression, anxiety and stress did not predict performance on non-EF cognitive domains. Limitations The cross-sectional design precludes cause-effect conclusions, further only self-report measures of affect were utilised and our performance measures of EF did not include a working memory test. Conclusions The results demonstrate that trait anxiety and state-based stress influence EF processes across disorders with social impairment. The transdiagnostic efficacy of this finding can facilitate remediation strategies, it may also contribute to individuals with Autism Spectrum Disorder gaining better access to mental health services.

The purpose of the study was to examine the internal consistency and validity of the 21-item Depression Anxiety Stress Scale (DASS-21) in individuals with Autism Spectrum Disorder (ASD) and without intellectual disability (IQ >= 70). Participants (NN = 123) were consecutively recruited from the Brain and Mind Centre in New South Wales, Australia. Internal consistency was determined using Cronbach's alpha. Item-total correlations were evaluated by Pearson's product-moment correlation coefficient. The convergent validity of the DASS-21 was examined by measuring its associations with quality of life and other measures of depression and anxiety. Factorial validity was assessed using confirmatory factor analysis. The DASS-21 demonstrated good internal consistency, adequate convergent validity, and all items exhibited satisfactory item-total correlations. Considering fit indices and factor loadings, the confirmatory factor analysis results provided support for the original 3-factor oblique model consisting of depression, anxiety, and stress factors. The model fit could be further improved with some modifications. Overall, the results indicate that the DASS-21 is a viable self-report screening measure for depression, anxiety, and stress in individuals with ASD and without intellectual disability.

Aim This study aimed to: (a) examine whether treatment-seeking young adults with social anxiety disorder (SAD) demonstrate similar degrees of distress, quality of life (QoL) and disability to those with other mental disorders; and (b) investigate the impact of comorbidity, specific comorbid conditions and antidepressants use on distress, QoL and disability in treatment-seeking young adults with SAD. Methods A cohort of treatment-seeking young adults (aged 16-45) diagnosed with SAD (N = 298) or other mental health disorders (N = 842; including depression, N = 349; bipolar, N = 141; psychosis, N = 173) completed self-report assessments of distress, QoL and disability. Results Young adults with SAD showed distress and disability of similar degree to those with most other mental disorders. Specifically, young adults with SAD reported significantly lower QoL than those with major depressive disorder or obsessive-compulsive disorder. Furthermore, young adults with SAD had the most difficulties in getting along with others and the second highest level of distress in comparison to other psychiatric groups. In comparison to antidepressants use, the presence of comorbidity showed a substantial negative influence on these health outcomes, particularly when presenting with comorbid depression or obsessive-compulsive disorder. Conclusions Findings highlight significant impairments in young adults seeking treatment for SAD and the important moderating influence of comorbidity. This emphasizes the urgent need for effective management and treatment for its presentation and comorbidities in mental health services targeting young adults.

In this article, we conduct a comprehensive review of existing evidence for the safety and therapeutic potential of intranasal oxytocin in pediatric populations. Unique considerations for dosing and delivery of oxytocin to the nasal passageway in pediatric populations and methods to promote adherence are reviewed. Intranasal oxytocin has been administered to 261 children in three open-label studies and eight randomized controlled trials. To date, the only published results in pediatric populations have focused on autism spectrum disorder (ASD) and Prader-Willi syndrome (PWS). Results regarding efficacy for improving social impairment in ASD are equivocal, partially due to mixed methodological designs, dosing regimens, and outcome measures. At present, there is no randomized controlled evidence that oxytocin provides benefit to individuals with PWS. There is no clear evidence of a link between oxytocin administration and any specific adverse event. Adverse events have been assessed using medical interviews, open reports, checklists, and physiological assessments. Adverse events reports have been largely classified as mild (n = 93), with few moderate (n = 9) or severe (n = 3) events reported. There were 35 additional adverse events reported, without severity ratings. Severe events, hyperactivity and irritability, occurred at first administration in both placebo and oxytocin groups, and subsided subsequent to discontinuation. We note that adverse event monitoring is inconsistent and often lacking, and reporting of its relationship to the study drug is poor. Only one study reported adherence data to suggest high adherence. Recommendations are then provided for the delivery of nasal sprays to the nasal passageway, monitoring, and reporting of efficacy, safety, and adherence for oxytocin nasal spray trials in pediatric populations.

Professor Jellinger first identified that striatal Aβ deposition at postmortem seemed to differentiate cases of dementia with Lewy bodies (DLB) from those with Parkinson's disease dementia (PDD), a finding subsequently questioned. Our replication study in 34 prospectively studied cases assessed the ability of striatal Aβ deposition to differentiate DLB from PDD, and also assessed the relationship between striatal and cortical Aβ deposition and α-synuclein-immunoreactive pathologies, using previously published protocols. Cases with DLB had significantly shorter durations and greater dementia severities compared with cases with PDD. Striatal Aβ-immunoreactive plaques were only consistently found in cases with DLB and correlated with both the severity (positive correlation) and duration (negative correlation) of dementia. Striatal Aβ-immunoreactive plaques also positively correlated with the severity of α-synuclein-immunoreactive pathologies as well as cortical Aβ-positive plaques. Striatal Aβ deposition positively predicted dementia in Lewy body cases with high specificity and had the greatest sensitivity to differentiate DLB from PDD with 100% negative predictive value. These data suggest that striatal Aβ deposition in Lewy body diseases contributes to early dementia and in these cases may impact on the efficacy of treatments targeting the striatum.

Mutations in parkin are a common cause of early-onset autosomal recessive Parkinson's disease. Parkin Co-Regulated Gene (PACRG) is a novel gene that was discovered because of its close genetic proximity to parkin and the two genes were subsequently demonstrated to be regulated by a bi-directional promoter. However the role of PACRG has not been well characterized and the distribution of the protein in both normal and diseased brain is not known. Here, we report that like parkin, PACRG is regulated by the ubiquitin-proteasomal system. Immunohistochemistry identified PACRG in astrocytes throughout the brain and in pigmented noradrenergic neurons of the locus coeruleus. PACRG was also detected in Lewy bodies and glial cytoplasmic inclusions in patients with Parkinson's disease and Multiple System Atrophy, respectively. Together, these results demonstrate that PACRG is regulated by the ubiquitin-proteasomal system and may play a role in the pathogenesis of Parkinson's disease.

Depression involves impairments in a range of cognitive and emotional capacities. It is unknown whether these functions can inform medication choice when considered as a composite predictive biomarker. We tested whether behavioral tests, grounded in the neurobiology of cognitive and emotional functions, predict outcome with common antidepressants. Medication-free outpatients with nonpsychotic major depressive disorder (N=1008; 665 completers) were assessed before treatment using 13 computerized tests of psychomotor, executive, memory–attention, processing speed, inhibitory, and emotional functions. Matched healthy controls (N=336) provided a normative reference sample for test performance. Depressed participants were then randomized to escitalopram, sertraline, or venlafaxine–extended release, and were assessed using the 16-item Quick Inventory of Depressive Symptomatology (QIDS-SR16) and the 17-item Hamilton Rating Scale for Depression. Given the heterogeneity of depression, analyses were furthermore stratified by pretreatment performance. We then used pattern classification with cross-validation to determine individual patient-level composite predictive biomarkers of antidepressant outcome based on test performance. A subgroup of depressed participants (approximately one-quarter of patients) were found to be impaired across most cognitive tests relative to the healthy norm, from which they could be discriminated with 91% accuracy. These patients with generally impaired cognitive task performance had poorer treatment outcomes. For this impaired subgroup, task performance furthermore predicted remission on the QIDS-SR16 at 72% accuracy specifically following treatment with escitalopram but not the other medications. Therefore, tests of cognitive and emotional functions can form a clinically meaningful composite biomarker that may help drive general treatment outcome prediction for optimal treatment selection in depression, particularly for escitalopram.

Background The brainstem is the main region that innervates neurotransmitter release to the Hypothalamic-Pituitary Adrenal (HPA) axis and fronto-limbic circuits, two key brain circuits found to be dysfunctional in Major Depressive Disorder (MDD). However, the brainstem’s role in MDD has only been evaluated in limited reports. Using Diffusion Tensor Imaging (DTI), we investigated whether major brainstem white matter tracts that relate to these two circuits differ in MDD patients compared to healthy controls. Methods MDD patients (n = 95) and age- and gender-matched controls (n = 34) were assessed using probabilistic tractography of DTI to delineate three distinct brainstem tracts: the nigrostriatal tract (connecting brainstem to striatum), solitary tract (connecting brainstem to amygdala) and corticospinal tract (connecting brainstem to precentral cortex). Fractional anisotropy (FA) was used to measure the white matter integrity of these tracts, and measures were compared between MDD and control participants. Results MDD participants were characterized by a significant and specific decrease in white matter integrity of the right solitary tract (p

The reactive changes in different types of astrocytes were analyzed in parkinsonian syndromes in order to identify common reactions and their relationship to disease severity. Immunohistochemistry was used on formalin-fixed, paraffin-embedded sections from the putamen, pons, and substantia nigra from 13 Parkinson disease (PD), 29 multiple-system atrophy (MSA), 34 progressive supranuclear palsy (PSP), 10 corticobasal degeneration(CBD), and 13 control cases. Classic reactive astrocytes were observed in MSA, PSP, and CBD, but not PD cases; the extent of reactivity correlated with indices of neurodegeneration and disease stage. Approximately 40% to 45% of subcortical astrocytes in PD and PSP accumulated alpha-synuclein and phospho-tau, respectively; subcortical astrocytes in MSA and CBD cases did not accumulate these proteins. Protoplasmic astrocytes were identified from fibrous astrocytes by their expression of parkin coregulated gene and apolipoprotein D, and accumulated abnormal proteins in PD, PSP, and CBD, but not MSA. The increased reactivity of parkin coregulated gene-immunoreactive protoplasmic astrocytes correlated with parkin expression in PSP and CBD. Nonreactive protoplasmic astrocytes were observed in PD and MSA cases; in PD, they accumulated alpha-synuclein, suggesting that the attenuated response might be due to an increase in the level of alpha-synuclein. These heterogeneous astroglial responses in PD, MSA, PSP, and CBD indicate distinct underlying pathogenic mechanisms in each disorder.

Udgivelsesdato: 2007-Oct p25alpha is an oligodendroglial protein that can induce aggregation of alpha-synuclein and accumulates in oligodendroglial cell bodies containing fibrillized alpha-synuclein in the neurodegenerative disease multiple system atrophy (MSA). We demonstrate biochemically that p25alpha is a constituent of myelin and a high-affinity ligand for myelin basic protein (MBP), and in situ immunohistochemistry revealed that MBP and p25alpha colocalize in myelin in normal human brains. Analysis of MSA cases reveals dramatic changes in p25alpha and MBP throughout the course of the disease. In situ immunohistochemistry revealed a cellular redistribution of p25alpha immunoreactivity from the myelin to the oligodendroglial cell soma, with no overall change in p25alpha protein concentration using immunoblotting. Concomitantly, an approximately 80% reduction in the concentration of full-length MBP protein was revealed by immunoblotting along with the presence of immunoreactivity for MBP degradation products in oligodendroglia. The oligodendroglial cell bodies in MSA displayed an enlargement along with the relocalization of p25alpha, and this was enhanced after the deposition of alpha-synuclein in the glial cytoplasmic inclusions. Overall, the data indicate that changes in the cellular interactions between MBP and p25alpha occur early in MSA and contribute to abnormalities in myelin and subsequent alpha-synuclein aggregation and the ensuing neuronal degeneration that characterizes this disease.

Presenilin-1 (PS-1) mutations can cause Pick's disease without evidence of Alzheimer's disease (AD). We describe a family with a PS-1 M146L mutation and both Pick bodies and AD. Sarkosyl-insoluble hyperphosphorylated tau showed three bands consistent with AD, although dephosphorylation showed primarily three-repeat isoforms. M146L mutant PS-1 may predispose to both Pick's disease and AD by affecting multiple intracellular pathways involving tau phosphorylation and amyloid metabolism.