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Cognitive impairments are well-established features of psychotic disorders and are present when individuals are at ultra-high risk for psychosis. However, few interventions target cognitive functioning in this population.
Aims
To investigate whether omega-3 polyunsaturated fatty acid (n−3 PUFA) supplementation improves cognitive functioning among individuals at ultra-high risk for psychosis.
Method
Data (N = 225) from an international, multi-site, randomised controlled trial (NEURAPRO) were analysed. Participants were given omega-3 supplementation (eicosapentaenoic acid and docosahexaenoic acid) or placebo over 6 months. Cognitive functioning was assessed with the Brief Assessment of Cognition in Schizophrenia (BACS). Mixed two-way analyses of variance were computed to compare the change in cognitive performance between omega-3 supplementation and placebo over 6 months. An additional biomarker analysis explored whether change in erythrocyte n−3 PUFA levels predicted change in cognitive performance.
Results
The placebo group showed a modest greater improvement over time than the omega-3 supplementation group for motor speed (ηp2 = 0.09) and BACS composite score (ηp2 = 0.21). After repeating the analyses without individuals who transitioned, motor speed was no longer significant (ηp2 = 0.02), but the composite score remained significant (ηp2 = 0.02). Change in erythrocyte n-3 PUFA levels did not predict change in cognitive performance over 6 months.
Conclusions
We found no evidence to support the use of omega-3 supplementation to improve cognitive functioning in ultra-high risk individuals. The biomarker analysis suggests that this finding is unlikely to be attributed to poor adherence or consumption of non-trial n−3 PUFAs.
Subthreshold/attenuated syndromes are established precursors of full-threshold mood and psychotic disorders. Less is known about the individual symptoms that may precede the development of subthreshold syndromes and associated social/functional outcomes among emerging adults.
Methods
We modeled two dynamic Bayesian networks (DBN) to investigate associations among self-rated phenomenology and personal/lifestyle factors (role impairment, low social support, and alcohol and substance use) across the 19Up and 25Up waves of the Brisbane Longitudinal Twin Study. We examined whether symptoms and personal/lifestyle factors at 19Up were associated with (a) themselves or different items at 25Up, and (b) onset of a depression-like, hypo-manic-like, or psychotic-like subthreshold syndrome (STS) at 25Up.
Results
The first DBN identified 11 items that when endorsed at 19Up were more likely to be reendorsed at 25Up (e.g., hypersomnia, impaired concentration, impaired sleep quality) and seven items that when endorsed at 19Up were associated with different items being endorsed at 25Up (e.g., earlier fatigue and later role impairment; earlier anergia and later somatic pain). In the second DBN, no arcs met our a priori threshold for inclusion. In an exploratory model with no threshold, >20 items at 19Up were associated with progression to an STS at 25Up (with lower statistical confidence); the top five arcs were: feeling threatened by others and a later psychotic-like STS; increased activity and a later hypo-manic-like STS; and anergia, impaired sleep quality, and/or hypersomnia and a later depression-like STS.
Conclusions
These probabilistic models identify symptoms and personal/lifestyle factors that might prove useful targets for indicated preventative strategies.
Regional planning may help to ensure that the specific measures implemented as part of a national suicide prevention strategy are aligned with the varying needs of local services and communities; however, there are concerns that the reliability of local programme development may be limited in practice.
Aims
The potential impacts of independent regional planning on the effectiveness of suicide prevention programmes in the Australian state of New South Wales were quantified using a system dynamics model of mental health services provision and suicidal behaviour in each of the state's ten Primary Health Network (PHN) catchments.
Method
Reductions in projected suicide mortality over the period 2021–2031 were calculated for scenarios in which combinations of four and five suicide prevention and mental health services interventions (selected from 13 possible interventions) are implemented separately in each PHN catchment. State-level impacts were estimated by summing reductions in projected suicide mortality for each intervention combination across PHN catchments.
Results
The most effective state-level combinations of four and five interventions prevent, respectively, 20.3% and 22.9% of 10 312 suicides projected under a business-as-usual scenario (i.e. no new policies or programmes, constant services capacity growth). Projected numbers of suicides under the optimal intervention scenarios for each PHN are up to 6% lower than corresponding numbers of suicides projected for the optimal state-level intervention combinations.
Conclusions
Regional suicide prevention planning may contribute to significant reductions in suicide mortality where local health authorities are provided with the necessary resources and tools to support reliable, evidence-based decision-making.
The schizophrenia polygenic risk score (SCZ-PRS) is an emerging tool in psychiatry.
Aims
We aimed to evaluate the utility of SCZ-PRS in a young, transdiagnostic, clinical cohort.
Method
SCZ-PRSs were calculated for young people who presented to early-intervention youth mental health clinics, including 158 patients of European ancestry, 113 of whom had longitudinal outcome data. We examined associations between SCZ-PRS and diagnosis, clinical stage and functioning at initial assessment, and new-onset psychotic disorder, clinical stage transition and functional course over time in contact with services.
Results
Compared with a control group, patients had elevated PRSs for schizophrenia, bipolar disorder and depression, but not for any non-psychiatric phenotype (for example cardiovascular disease). Higher SCZ-PRSs were elevated in participants with psychotic, bipolar, depressive, anxiety and other disorders. At initial assessment, overall SCZ-PRSs were associated with psychotic disorder (odds ratio (OR) per s.d. increase in SCZ-PRS was 1.68, 95% CI 1.08–2.59, P = 0.020), but not assignment as clinical stage 2+ (i.e. discrete, persistent or recurrent disorder) (OR = 0.90, 95% CI 0.64–1.26, P = 0.53) or functioning (R = 0.03, P = 0.76). Longitudinally, overall SCZ-PRSs were not significantly associated with new-onset psychotic disorder (OR = 0.84, 95% CI 0.34–2.03, P = 0.69), clinical stage transition (OR = 1.02, 95% CI 0.70–1.48, P = 0.92) or persistent functional impairment (OR = 0.84, 95% CI 0.52–1.38, P = 0.50).
Conclusions
In this preliminary study, SCZ-PRSs were associated with psychotic disorder at initial assessment in a young, transdiagnostic, clinical cohort accessing early-intervention services. Larger clinical studies are needed to further evaluate the clinical utility of SCZ-PRSs, especially among individuals with high SCZ-PRS burden.
The ‘16Up’ study conducted at the QIMR Berghofer Medical Research Institute from January 2014 to December 2018 aimed to examine the physical and mental health of young Australian twins aged 16−18 years (N = 876; 371 twin pairs and 18 triplet sets). Measurements included online questionnaires covering physical and mental health as well as information and communication technology (ICT) use, actigraphy, sleep diaries and hair samples to determine cortisol concentrations. Study participants generally rated themselves as being in good physical (79%) and mental (73%) health and reported lower rates of psychological distress and exposure to alcohol, tobacco products or other substances than previously reported for this age group in the Australian population. Daily or near-daily online activity was almost universal among study participants, with no differences noted between males and females in terms of frequency or duration of internet access. Patterns of ICT use in this sample indicated that the respondents were more likely to use online information sources for researching physical health issues than for mental health or substance use issues, and that they generally reported partial levels of satisfaction with the mental health information they found online. This suggests that internet-based mental health resources can be readily accessed by adolescent Australians, and their computer literacy augurs well for future access to online health resources. In combination with other data collected as part of the ongoing Brisbane Longitudinal Twin Study, the 16Up project provides a valuable resource for the longitudinal investigation of genetic and environmental contributions to phenotypic variation in a variety of human traits.
Predictors of new-onset bipolar disorder (BD) or psychotic disorder (PD) have been proposed on the basis of retrospective or prospective studies of ‘at-risk’ cohorts. Few studies have compared concurrently or longitudinally factors associated with the onset of BD or PDs in youth presenting to early intervention services. We aimed to identify clinical predictors of the onset of full-threshold (FT) BD or PD in this population.
Method
Multi-state Markov modelling was used to assess the relationships between baseline characteristics and the likelihood of the onset of FT BD or PD in youth (aged 12–30) presenting to mental health services.
Results
Of 2330 individuals assessed longitudinally, 4.3% (n = 100) met criteria for new-onset FT BD and 2.2% (n = 51) met criteria for a new-onset FT PD. The emergence of FT BD was associated with older age, lower social and occupational functioning, mania-like experiences (MLE), suicide attempts, reduced incidence of physical illness, childhood-onset depression, and childhood-onset anxiety. The emergence of a PD was associated with older age, male sex, psychosis-like experiences (PLE), suicide attempts, stimulant use, and childhood-onset depression.
Conclusions
Identifying risk factors for the onset of either BD or PDs in young people presenting to early intervention services is assisted not only by the increased focus on MLE and PLE, but also by recognising the predictive significance of poorer social function, childhood-onset anxiety and mood disorders, and suicide attempts prior to the time of entry to services. Secondary prevention may be enhanced by greater attention to those risk factors that are modifiable or shared by both illness trajectories.
Loneliness is related to mental and somatic health outcomes, including borderline personality disorder. Here, we analyze the sources of variation that are responsible for the relationship between borderline personality features (including four dimensions, affective instability, identity disturbance, negative relationships, self-harm and a total score) and loneliness. Using genetically informative data from two large nonclinical samples of adult twin pairs from Australia and the Netherlands (N = 11,329), we estimate the phenotypic, genetic and environmental correlations between self-reported borderline personality features and loneliness. Individual differences in borderline personality and loneliness were best explained by additive genetic factors with heritability estimates h2 = 41% for the borderline personality total score and h2 = 36% for loneliness, with the remaining variation explained by environmental influences that were not shared by twins from the same pair. Genetic and environmental factors influencing borderline personality (total score and four subscales separately) were also partial causes of loneliness. The correlation between loneliness and the borderline personality total score was rph = .51. The genetic correlation was estimated at rg = .64 and the environmental correlation at re = .40. Our study suggests common etiological factors in loneliness and borderline personality features.
Subjective cognitive difficulties are common in mental illness and have a negative impact on role functioning. Little is understood about subjective cognition and the longitudinal relationship with depression and anxiety symptoms in young people.
Aims
To examine the relationship between changes in levels of depression and anxiety and changes in subjective cognitive functioning over 3 months in help-seeking youth.
Method
This was a cohort study of 656 youth aged 12–25 years attending Australian headspace primary mental health services. Subjective changes in cognitive functioning (rated as better, same, worse) reported after 3 months of treatment was assessed using the Neuropsychological Symptom Self-Report. Multivariate multinomial logistic regression analysis was conducted to evaluate the impact of baseline levels of and changes in depression (nine-item Patient Health Questionnaire; PHQ9) and anxiety symptoms (seven-item Generalised Anxiety Disorder scale; GAD7) on changes in subjective cognitive function at follow-up while controlling for covariates.
Results
With a one-point reduction in PHQ9 at follow-up, there was an estimated 11–18% increase in ratings of better subjective cognitive functioning at follow-up, relative to stable cognitive functioning. A one-point increase in PHQ9 from baseline to follow-up was associated with 7–14% increase in ratings of worse subjective cognitive functioning over 3 months, relative to stable cognitive functioning. A similar attenuated pattern of findings was observed for the GAD7.
Conclusions
A clear association exists between subjective cognitive functioning outcomes and changes in self-reported severity of affective symptoms in young people over the first 3 months of treatment. Understanding the timing and mechanisms of these associations is needed to tailor treatment.
Nick Martin is a pioneer in recognizing the need for large sample size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick’s studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA samples. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA samples) over a time frame of a few months — analyses are currently ongoing. The mantra of sample size, sample size, sample size has guided Nick’s research over the last 30 years and continues to do so.
Neurocognitive impairments robustly predict functional outcome. However, heterogeneity in neurocognition is common within diagnostic groups, and data-driven analyses reveal homogeneous neurocognitive subgroups cutting across diagnostic boundaries.
Aims
To determine whether data-driven neurocognitive subgroups of young people with emerging mental disorders are associated with 3-year functional course.
Method
Model-based cluster analysis was applied to neurocognitive test scores across nine domains from 629 young people accessing mental health clinics. Cluster groups were compared on demographic, clinical and substance-use measures. Mixed-effects models explored associations between cluster-group membership and socio-occupational functioning (using the Social and Occupational Functioning Assessment Scale) over 3 years, adjusted for gender, premorbid IQ, level of education, depressive, positive, negative and manic symptoms, and diagnosis of a primary psychotic disorder.
Results
Cluster analysis of neurocognitive test scores derived three subgroups described as ‘normal range’ (n = 243, 38.6%), ‘intermediate impairment’ (n = 252, 40.1%), and ‘global impairment’ (n = 134, 21.3%). The major mental disorder categories (depressive, anxiety, bipolar, psychotic and other) were represented in each neurocognitive subgroup. The global impairment subgroup had lower functioning for 3 years of follow-up; however, neither the global impairment (B = 0.26, 95% CI −0.67 to 1.20; P = 0.581) or intermediate impairment (B = 0.46, 95% CI −0.26 to 1.19; P = 0.211) subgroups differed from the normal range subgroup in their rate of change in functioning over time.
Conclusions
Neurocognitive impairment may follow a continuum of severity across the major syndrome-based mental disorders, with data-driven neurocognitive subgroups predictive of functional course. Of note, the global impairment subgroup had longstanding functional impairment despite continuing engagement with clinical services.
The identification of people at high risk for future mental disorders is accompanied by the imperative to provide stage-adequate treatments that successfully prevent progression to more severe illness stages. Current evidence-based treatments include psychological and psychosocial treatments on one hand as well as pharmacotherapy. The latter is limited by inadequate efficacy and prominent side effects in many cases, making the discovery of novel biological treatment strategies necessary. Such novel treatments need to be safe, effective, characterised by a benign side effect profile and accessible to young people. In this chapter, emerging biological treatment approaches are reviewed and discussed in regard to their potential impact on early intervention and clinical staging. Substances reviewed here include long-chain omega-3 fatty acids (fish oil), n-acetylcysteine (NAC), cannabidiol and repeated transcranial magnetic stimulation (rTMS) with a particular focus on recent advancements in their application in youth with incipient mental disorders. Finally, research priorities in the field of treatment trials are discussed in this chapter.
For over a decade a transdiagnostic clinical staging framework for youth with anxiety, mood and psychotic disorders (linked with measurement of multidimensional outcomes), has been utilised in over 8,000 young people presenting to the enhanced primary (headspace) and secondary care clinics of the Brain and Mind Centre of the University of Sydney. This framework has been evaluated alongside a broad range of other clinical, neurobiological, neuropsychological, brain imaging, circadian, metabolic, longitudinal cohort and controlled intervention studies. This has led to specific tests of its concurrent, discriminant and predictive validity. These extensive data provide strong preliminary evidence that: i) varying stages of illness are associated with predicted differences in a range of independent and objectively measured neuropsychological and other biomarkers (both cross-sectionally and longitudinally); and, ii) that earlier stages of illness progress at variable rates to later and more severe or persistent disorders. Importantly, approximately 15-20% of those young people classed as stage 1b or ‘attenuated’ syndromes at presentation progress to more severe or persistent disorders. Consequently, this cohort should be the focus of active secondary prevention trials. In clinical practice, we are moving to combine the staging framework with likely pathophysiological paths (e.g. neurodevelopmental-psychotic, anxiety-depression, circadian-bipolar) to underpin enhanced treatment selection.
Over the last two decades application of the clinical staging model in mental health has been advocated to improve diagnosis, intervention, prediction of illness trajectory and, ultimately, outcomes. The model offers a substantive advance for mental health care as it goes beyond traditional fixed categories to incorporate a stepwise continuum to guide much more appropriate treatment planning and prognosis. In this chapter, an overview of this advanced type of clinical staging is provided. With its focus on the continuum of mental illness, and underlying differential trajectories of illness progression that are not well captured by current categorical diagnostic practice, staging addresses the key limitations of traditional diagnostic categorical systems. It proposes that effective, safe and timely stage-specific treatments can be implemented to inhibit and delay illness onset and progression. It also enables biomarkers to be analysed according not only to syndrome but also stage. The model is supported by a number of clinical, longitudinal and neurobiological studies. Whilst clinical staging has clear and immediate potential benefits, further research investigating risk and protective factors and treatment outcomes across different stages and the creation of tools that clinicians can routinely use will determine the ultimate utility and value of the model.
For over a decade a transdiagnostic clinical staging framework for youth with anxiety, mood and psychotic disorders (linked with measurement of multidimensional outcomes), has been utilised in over 8,000 young people presenting to the enhanced primary (headspace) and secondary care clinics of the Brain and Mind Centre of the University of Sydney. This framework has been evaluated alongside a broad range of other clinical, neurobiological, neuropsychological, brain imaging, circadian, metabolic, longitudinal cohort and controlled intervention studies. This has led to specific tests of its concurrent, discriminant and predictive validity. These extensive data provide strong preliminary evidence that: i) varying stages of illness are associated with predicted differences in a range of independent and objectively measured neuropsychological and other biomarkers (both cross-sectionally and longitudinally); and, ii) that earlier stages of illness progress at variable rates to later and more severe or persistent disorders. Importantly, approximately 15-20% of those young people classed as stage 1b or ‘attenuated’ syndromes at presentation progress to more severe or persistent disorders. Consequently, this cohort should be the focus of active secondary prevention trials. In clinical practice, we are moving to combine the staging framework with likely pathophysiological paths (e.g. neurodevelopmental-psychotic, anxiety-depression, circadian-bipolar) to underpin enhanced treatment selection.