Chronotype and subjective sleep quality predict white matter integrity in young people with emerging mental disorders.

Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity in emerging mental disorders. Young people (N = 364) accessing early-intervention clinics underwent assessments for chronotype, subjective sleep quality, and diffusion tensor imaging. Using machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity: fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD). We prioritised tracts that showed a univariate association with sleep quality or chronotype and considered predictors identified by ≥80% of machine learning (ML) models as 'important'. The most important predictors of WM integrity were demographics (age, sex and education) and diagnosis (depressive and bipolar disorders). Subjective sleep quality only predicted FA in the perihippocampal cingulum tract, whereas chronotype had limited predictive importance for WM integrity. To further examine links with mood disorders, we conducted a subgroup analysis. In youth with depressive and bipolar disorders, chronotype emerged as an important (often top-ranking) feature, predicting FA in the cingulum (cingulate gyrus), AD in the anterior corona radiata and genu of the corpus callosum, and RD in the corona radiata, anterior corona radiata, and genu of corpus callosum. Subjective quality was not important in this subgroup analysis. In summary, chronotype predicted altered WM integrity in the corona radiata and corpus callosum, whereas subjective sleep quality had a less significant role, suggesting that circadian factors may play a more prominent role in WM integrity in emerging mood disorders.

Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder?

OBJECTIVES: Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder. METHODS: We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high-/low-activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors? RESULTS: Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high- or low-activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high-/low-activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised. CONCLUSION: Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states and deserves prioritisation in research in bipolar disorders.

Clinical staging and the differential risks for clinical and functional outcomes in young people presenting for youth mental health care.

BACKGROUND: Clinical staging proposes that youth-onset mental disorders develop progressively, and that active treatment of earlier stages should prevent progression to more severe disorders. This retrospective cohort study examined the longitudinal relationships between clinical stages and multiple clinical and functional outcomes within the first 12 months of care. METHODS: Demographic and clinical information of 2901 young people who accessed mental health care at age 12-25 years was collected at predetermined timepoints (baseline, 3 months, 6 months, 12 months). Initial clinical stage was used to define three fixed groups for analyses (stage 1a: 'non-specific anxious or depressive symptoms', 1b: 'attenuated mood or psychotic syndromes', 2+: 'full-threshold mood or psychotic syndromes'). Logistic regression models, which controlled for age and follow-up time, were used to compare clinical and functional outcomes (role and social function, suicidal ideation, alcohol and substance misuse, physical health comorbidity, circadian disturbances) between staging groups within the initial 12 months of care. RESULTS: Of the entire cohort, 2093 young people aged 12-25 years were followed up at least once over the first 12 months of care, with 60.4% female and a baseline mean age of 18.16 years. Longitudinally, young people at stage 2+ were more likely to develop circadian disturbances (odds ratio [OR]=2.58; CI 1.60-4.17), compared with individuals at stage 1b. Additionally, stage 1b individuals were more likely to become disengaged from education/employment (OR=2.11, CI 1.36-3.28), develop suicidal ideations (OR=1.92; CI 1.30-2.84) and circadian disturbances (OR=1.94, CI 1.31-2.86), compared to stage 1a. By contrast, we found no relationship between clinical stage and the emergence of alcohol or substance misuse and physical comorbidity. CONCLUSIONS: The differential rates of emergence of poor clinical and functional outcomes between early versus late clinical stages support the clinical staging model's assumptions about illness trajectories for mood and psychotic syndromes. The greater risk of progression to poor outcomes in those who present with more severe syndromes may be used to guide specific intervention packages.

Predicting the emergence of full-threshold bipolar I, bipolar II and psychotic disorders in young people presenting to early intervention mental health services.

BACKGROUND: 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.

Social and occupational outcomes for young people who attend early intervention mental health services: a longitudinal study.

OBJECTIVE: To identify trajectories of social and occupational functioning in young people during the two years after presenting for early intervention mental health care; to identify demographic and clinical factors that influence these trajectories. DESIGN: Longitudinal, observational study of young people presenting for mental health care. SETTING: Two primary care-based early intervention mental health services at the Brain and Mind Centre (University of Sydney), 1 June 2008 - 31 July 2018. PARTICIPANTS: 1510 people aged 12-25 years who had presented with anxiety, mood, or psychotic disorders, for whom two years' follow-up data were available for analysis. MAIN OUTCOME MEASURES: Latent class trajectories of social and occupational functioning based on growth mixture modelling of Social and Occupational Assessment Scale (SOFAS) scores. RESULTS: We identified four trajectories of functioning during the first two years of care: deteriorating and volatile (733 participants, 49%); persistent impairment (237, 16%); stable good functioning (291, 19%); and improving, but late recurrence (249, 16%). The less favourable trajectories (deteriorating and volatile; persistent impairment) were associated with physical comorbidity, not being in education, employment, or training, having substance-related disorders, having been hospitalised, and having a childhood onset mental disorder, psychosis-like experiences, or a history of self-harm or suicidality. CONCLUSIONS: Two in three young people with emerging mental disorders did not experience meaningful improvement in social and occupational functioning during two years of early intervention care. Most functional trajectories were also quite volatile, indicating the need for dynamic service models that emphasise multidisciplinary interventions and measurement-based care.

Metabolic and clinical profiles of young people with mood or psychotic disorders who are prescribed metformin in an inpatient setting.

OBJECTIVE: Youth with early-onset mood or psychotic disorders are occasionally prescribed metformin to manage cardiometabolic risk. This retrospective study explores the demographic, clinical and metabolic factors associated with metformin prescription youth with mood or psychotic disorders. METHOD: Participants included 72 youth with mood or psychotic disorders from a young adult mental health inpatient unit, of which 18 (33%) were newly prescribed metformin, and 54 (66%) were not prescribed metformin. Demographic and clinical information were extracted from the patients' medical files along with body mass index (BMI), fasting serum bloods and calculated updated homeostatic model of insulin resistance assessment (HOMA2-IR) scores to compare profiles between groups. RESULTS: Of those prescribed metformin, 83% were overweight or obese and 72% had elevated HOMA2-IR scores. Of those not receiving metformin treatment, 41% were overweight or obese and 22% had elevated HOMA2-IR scores. Youth prescribed metformin had significantly higher BMI, and elevated markers of insulin resistance, but did not differ to those not prescribed metformin on other demographic, clinical or metabolic factors. CONCLUSIONS: While metformin is prescribed to some youth with mood or psychotic disorders displaying markers of cardiometabolic disturbance, there is a need to develop clearer treatment guidelines for metformin in these youth.

Increased spindle density correlates with sleep continuity improvements following an eight-week course of a melatonin agonist in people with depression: A proof-of-concept study with agomelatine.

Sleep fragmentation and reductions in sleep spindles have been observed in individuals with depression. Sleep spindles are known to play a protective role for sleep, and there are indications that melatonin agents can enhance spindles in healthy people. Whether agomelatine, a melatonin agonist indicated for the treatment of depression, may increase spindle density sufficiently to impact sleep continuity in people with depression remains unknown. This proof-of-concept study investigated changes in spindles following agomelatine intake in young adults with depression and assessed how they may relate to potential changes in sleep continuity and depressive symptoms. This study was based on an open-label design. Fifteen participants between 17 and 28 years of age (mean = 22.2; standard deviation [SD] = 3.4) with a diagnosis of a depressive disorder underwent polysomnography before and after an intervention including a 1 hr psychoeducation session centered on sleep and circadian rhythms, and an 8-week course of agomelatine (25-50 mg) with a guided sleep phase advance. Fast spindle density significantly increased from pre- to post-intervention. This increase in spindle density significantly correlated with a reduction in wake after sleep onset, and a similar trend was found with increased sleep efficiency. There was no significant correlation between spindle parameters and depressive symptoms. These findings suggest that agomelatine may contribute to enhanced sleep consolidation, possibly in part through the modulation of spindle production. This should be confirmed by larger randomized control trials.

Can network analysis of self-reported psychopathology shed light on the core phenomenology of bipolar disorders in adolescents and young adults?

OBJECTIVES: Network analysis is increasingly applied to psychopathology research. We used it to examine the core phenomenology of emerging bipolar disorder (BD I and II) and 'at risk' presentations (major depression with a family history of BD). METHODOLOGY: The study sample comprised a community cohort of 1867 twin and nontwin siblings (57% female; mean age ~26) who had completed self-report ratings of (i) depression-like, hypomanic-like and psychotic-like experiences; (ii) family history of BD; and (iii) were assessed for mood and psychotic syndromes using the Composite International Diagnostic Interview (CIDI). Symptom networks were compared for recent onset BD versus other cohort members and then for individuals at risk of BD (depression with/without a family history of BD). RESULTS: The four key symptoms that differentiated recent onset BD from other cohort members were: anergia, psychomotor speed, hypersomnia and (less) loss of confidence. The four key symptoms that differentiated individuals at high risk of BD from unipolar depression were anergia, psychomotor speed, impaired concentration and hopelessness. However, the latter network was less stable and more error prone. CONCLUSIONS: We are encouraged by the overlaps between our findings and those from two recent publications reporting network analyses of BD psychopathology, especially as the studies recruited from different populations and employed different network models. However, the advantages of applying network analysis to youth mental health cohorts (which include many individuals with multimorbidity) must be weighed against the disadvantages including basic issues such as judgements regarding the selection of items for inclusion in network models.

16Up: Outline of a Study Investigating Wellbeing and Information and Communication Technology Use in Adolescent Twins.

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.

Right care, first time: a highly personalised and measurement-based care model to manage youth mental health.

Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change. Consequently, the effects of adolescent-onset mood and psychotic syndromes can have long term consequences. A key clinical challenge for youth mental health is to develop and test new systems that align with current evidence for comorbid presentations and underlying neurobiology, and are useful for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. Our highly personalised and measurement-based care model includes three core concepts: ▶ A multidimensional assessment and outcomes framework that includes: social and occupational function; self-harm, suicidal thoughts and behaviour; alcohol or other substance misuse; physical health; and illness trajectory. ▶ Clinical stage. ▶ Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on proposed pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). The model explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within this highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care as well as utilisation of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality, mental health care for young people. CHAPTER 1: MULTIDIMENSIONAL OUTCOMES IN YOUTH MENTAL HEALTH CARE: WHAT MATTERS AND WHY?: Mood and psychotic syndromes present one of the most serious public health challenges that we face in the 21st century. Factors including prevalence, age of onset, and chronicity contribute to substantial burden and secondary risks such as alcohol or other substance misuse. Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change; thus, effects can have long term consequences. We propose five key domains which make up a multidimensional outcomes framework that aims to address the specific needs of young people presenting to health services with emerging mental illness. These include social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Impairment and concurrent morbidity are well established in young people by the time they present for mental health care. Despite this, services and health professionals tend to focus on only one aspect of the presentation - illness type, stage and trajectory - and are often at odds with the preferences of young people and their families. There is a need to address the disconnect between mental health, physical health and social services and interventions, to ensure that youth mental health care focuses on the outcomes that matter to young people. CHAPTER 2: COMBINING CLINICAL STAGE AND PATHOPHYSIOLOGICAL MECHANISMS TO UNDERSTAND ILLNESS TRAJECTORIES IN YOUNG PEOPLE WITH EMERGING MOOD AND PSYCHOTIC SYNDROMES: Traditional diagnostic classification systems for mental disorders map poorly onto the early stages of illness experienced by young people, and purport categorical distinctions that are not readily supported by research into genetic, environmental and neurobiological risk factors. Consequently, a key clinical challenge in youth mental health is to develop and test new classification systems that align with current evidence on comorbid presentations, are consistent with current understanding of underlying neurobiology, and provide utility for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. This chapter outlines a transdiagnostic framework for classifying common adolescent-onset mood and psychotic syndromes, combining two independent but complementary dimensions: clinical staging, and three proposed pathophysiological mechanisms. Clinical staging reflects the progression of mental disorders and is in line with the concept used in general medicine, where more advanced stages are associated with a poorer prognosis and a need for more intensive interventions with a higher risk-to-benefit ratio. The three proposed pathophysiological mechanisms are neurodevelopmental abnormalities, hyperarousal and circadian dysfunction, which, over time, have illness trajectories (or pathways) to psychosis, anxious depression and bipolar spectrum disorders, respectively. The transdiagnostic framework has been evaluated in young people presenting to youth mental health clinics of the University of Sydney's Brain and Mind Centre, alongside a range of clinical and objective measures. Our research to date provides support for this framework, and we are now exploring its application to the development of more personalised models of care. CHAPTER 3: A COMPREHENSIVE ASSESSMENT FRAMEWORK FOR YOUTH MENTAL HEALTH: GUIDING HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE USING MULTIDIMENSIONAL AND OBJECTIVE MEASURES: There is an urgent need for improved care for young people with mental health problems, in particular those with subthreshold mental disorders that are not sufficiently severe to meet traditional diagnostic criteria. New comprehensive assessment frameworks are needed to capture the biopsychosocial profile of a young person to drive highly personalised and measurement-based mental health care. We present a range of multidimensional measures involving five key domains: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Objective measures include: neuropsychological function; sleep-wake behaviours and circadian rhythms; metabolic and immune markers; and brain structure and function. The recommended multidimensional measures facilitate the development of a comprehensive clinical picture. The objective measures help to further develop informative and novel insights into underlying pathophysiological mechanisms and illness trajectories to guide personalised care plans. A panel of specific multidimensional and objective measures are recommended as standard clinical practice, while others are recommended secondarily to provide deeper insights with the aim of revealing alternative clinical paths for targeted interventions and treatments matched to the clinical stage and proposed pathophysiological mechanisms of the young person. CHAPTER 4: PERSONALISING CARE OPTIONS IN YOUTH MENTAL HEALTH: USING MULTIDIMENSIONAL ASSESSMENT, CLINICAL STAGE, PATHOPHYSIOLOGICAL MECHANISMS, AND INDIVIDUAL ILLNESS TRAJECTORIES TO GUIDE TREATMENT SELECTION: New models of mental health care for young people require that interventions be matched to illness type, clinical stage, underlying pathophysiological mechanisms and individual illness trajectories. Narrow syndrome-focused classifications often direct clinical attention away from other key factors such as functional impairment, self-harm and suicidality, alcohol or other substance misuse, and poor physical health. By contrast, we outline a treatment selection guide for early intervention for adolescent-onset mood and psychotic syndromes (ie, active treatments and indicated and more specific secondary prevention strategies). This guide is based on experiences with the Brain and Mind Centre's highly personalised and measurement-based care model to manage youth mental health. The model incorporates three complementary core concepts: ▶A multidimensional assessment and outcomes framework including: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness trajectory. ▶Clinical stage. ▶Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on three underlying pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). These core concepts are not mutually exclusive and together may facilitate improved outcomes through a clinical stage-appropriate and transdiagnostic framework that helps guide decisions regarding the provision of appropriate and effective care options. Given its emphasis on adolescent-onset mood and psychotic syndromes, the Brain and Mind Centre's model of care also respects a fundamental developmental perspective - categorising childhood problems (eg, anxiety and neurodevelopmental difficulties) as risk factors and respecting the fact that young people are in a period of major biological and social transition. Based on these factors, a range of social, psychological and pharmacological interventions are recommended, with an emphasis on balancing the personal benefit-to-cost ratio. CHAPTER 5: A SERVICE DELIVERY MODEL TO SUPPORT HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE IN YOUTH MENTAL HEALTH: Over the past decade, we have seen a growing focus on creating mental health service delivery models that better meet the unique needs of young Australians. Recent policy directives from the Australian Government recommend the adoption of stepped-care services to improve the appropriateness of care, determined by severity of need. Here, we propose that a highly personalised approach enhances stepped-care models by incorporating clinical staging and a young person's current and multidimensional needs. It explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within a highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care and use of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality of, mental health care for young people.

Sleep-wake cycle phenotypes in young people with familial and non-familial mood disorders.

OBJECTIVES: Converging evidence identifies that the offspring of parents with bipolar disorder (BD), individuals at clinical high risk of BD, and young people with recent onset BD may differ from other clinical cases or healthy controls in terms of sleep-wake profiles. However, it is possible that these differences may reflect current mental state, subtype of mood disorder, or familial traits. This study aimed to determine objective and subjective sleep-wake profiles in individuals aged 15-25 years with a current major depressive episode, in relation to familial traits. METHODS: Frequency matching was employed to ensure that each individual with a confirmed family history of BD (FH+) could be compared to four controls who did not have a familial mood disorder (FH-). Pre-selected objective actigraphy and subjective Pittsburgh Sleep Quality Index (PSQI) ratings were compared using one-way analysis of variance (ANOVA) and applying the Benjamini-Hochberg (BH) correction for false discoveries. RESULTS: The sample comprised 60 individuals with a mean age of 19 years. The FH+ (n=12) and FH- groups (n=48) differed on three key sleep parameters: mean sleep duration on week nights (P=.049), variability in waking after sleep onset (P=.038), and daily disturbances (PSQI dimension of sleep disturbance and daytime dysfunction; P=.01). CONCLUSIONS: The sleep profiles we identified in this study, especially the daily disturbances phenotype, provide support for research into endophenotypes for BD. Also, the findings may offer the opportunity for more tailored, personalized interventions that target specific components of the sleep-wake cycle in individuals with a family history of BD.

Sleep-wake profiles predict longitudinal changes in manic symptoms and memory in young people with mood disorders.

Mood disorders are characterized by disabling symptoms and cognitive difficulties which may vary in intensity throughout the course of the illness. Sleep-wake cycles and circadian rhythms influence emotional regulation and cognitive functions. However, the relationships between the sleep-wake disturbances experienced commonly by people with mood disorders and the longitudinal changes in their clinical and cognitive profile are not well characterized. This study investigated associations between initial sleep-wake patterns and longitudinal changes in mood symptoms and cognitive functions in 50 young people (aged 13-33 years) with depression or bipolar disorder. Data were based on actigraphy monitoring conducted over approximately 2 weeks and clinical and neuropsychological assessment. As part of a longitudinal cohort study, these assessments were repeated after a mean follow-up interval of 18.9 months. No significant differences in longitudinal clinical changes were found between the participants with depression and those with bipolar disorder. Lower sleep efficiency was predictive of longitudinal worsening in manic symptoms (P = 0.007). Shorter total sleep time (P = 0.043) and poorer circadian rhythmicity (P = 0.045) were predictive of worsening in verbal memory. These findings suggest that some sleep-wake and circadian disturbances in young people with mood disorders may be associated with less favourable longitudinal outcomes, notably for subsequent manic symptoms and memory difficulties.

Quantifying the effect of body mass index, age, and depression severity on 24-h activity patterns in persons with a lifetime history of affective disorders.

BACKGROUND: Patients with affective disorders of different ages have been found to present weight changes and different circadian activity patterns. This study assessed the effects of age, Body Mass Index (BMI) and depression severity on the activity-rest cycle in persons with affective disorders using a novel multifactorial 24-h analysis method. METHODS: Two hundred and thirty-six participants aged between 14 and 85 years underwent 5 to 22 days of actigraphy monitoring (mean duration = 14 days). BMI was also recorded and symptom severity was assessed with the Hamilton Depression Rating Scale (HDRS). Participants were divided into two groups: healthy controls (n = 68) and participants with a lifetime diagnosis of affective disorders (n = 168). First, the multiple regression method was employed to formulate the circadian activity pattern in term of the factors age, BMI and HDRS. For each group, the functional linear analysis method was applied to assess the relative effects of the factors. Finally, Wald-tests were used to assess the contribution of each factor on the circadian activity pattern. RESULTS: In the affective disorders group, higher BMI was associated with higher activity levels from 3 am until 5.30 am and with lower activity levels from 10 am until 10.30 pm. Older age was associated with less activity across the day, evening, and night - from 11 am until 5.30 am. Higher HDRS scores were associated with higher activity around 1:30 am. In healthy controls, the effects of BMI and age on activity patterns were less pronounced and affected a narrower portion of the 24-h period. CONCLUSION: These findings suggest that older age and higher BMI are linked to lower daytime activity levels. Higher BMI and worse symptom severity were also associated with nocturnal activity patterns suggestive of sleep disturbances. The influence of age and BMI on 24-h activity profiles appear to be especially pronounced in people with affective disorders.

Changes in sleep patterns in people with a history of depression during the COVID-19 pandemic: a natural experiment.

BACKGROUND: The COVID-19 pandemic, while a major stressor, increased flexibility in sleep-wake schedules. OBJECTIVES: To investigate the impact of the pandemic on sleep patterns in people with a history of depression and identify sociodemographic, clinical or genetic predictors of those impacts. METHODS: 6453 adults from the Australian Genetics of Depression Study (45±15 years; 75% women) completed surveys before (2016-2018) and during the pandemic (2020-2021). Participants were assigned to 'short sleep' (<6 hours), 'optimal sleep' (6-8 hours) or 'long sleep' (>8 hours). We focused on those having prepandemic 'optimal sleep'. FINDINGS: Pre pandemic, the majority (70%, n=4514) reported optimal sleep, decreasing to 49% (n=3189) during the pandemic. Of these, 57% maintained optimal sleep, while 16% (n=725) shifted to 'short sleep' and 27% (n=1225) to 'long sleep'. In group comparisons 'optimal-to-short sleep' group had worse prepandemic mental health and increased insomnia (p's<0.001), along with an elevated depression genetic score (p=0.002). The 'optimal-to-long sleep' group were slightly younger and had higher distress (p's<0.05), a greater propensity to being evening types (p<0.001) and an elevated depression genetic score (p=0.04). Multivariate predictors for 'optimal-to-short sleep' included reported stressful life events, psychological or somatic distress and insomnia severity (false discovery rate-corrected p values<0.004), while no significant predictors were identified for 'optimal-to-long sleep'. CONCLUSION AND IMPLICATIONS: The COVID-19 pandemic, a natural experiment, elicited significant shifts in sleep patterns among people with a history of depression, revealing associations with diverse prepandemic demographic and clinical characteristics. Understanding these dynamics may inform the selection of interventions for people with depression facing major challenges.

Cross-sectional and longitudinal associations between cardiometabolic measures and clinical stage in young people accessing early intervention mental health services.

AIM: This retrospective cohort study aimed to identify the cardiometabolic characteristics, cross-sectionally and longitudinally, associated with clinical stage in youth accessing early intervention mental health services. METHODS: Cardiometabolic data we collected in 511 young people (aged 12-25 years at entry) receiving mental health care at the early intervention services in Sydney, Australia. RESULTS: The majority of young people (N = 448, 87.67%) were classified in stage 1a or 1b at entry. At entry to care, there was no cross-sectional relationship between clinical stage and age, gender, fasting insulin, fasting glucose, updated homeostatic model assessment for insulin resistance (HOMA2-IR) score, BMI or waist circumference. Of the 111 (21.7%) young people initially classified at stage 1a ('non-specific symptoms') and the 337 (65.9%) classified in stage 1b ('attenuated syndromes'), 40 individuals transitioned to stage 2+ (7.8%) ("full-threshold disorders") longitudinally. No cardiometabolic factors predicted clinical stage transitions. However, those with an increase in BMI over the course of care (n = 54) were 1.46 (OR; 95% CI: 1.02-2.17) times more likely to progress to stage 2+ at follow up. CONCLUSIONS: Whilst no relationships were found between demographic or cardiometabolic variables and clinical stage at entry to care, an increased BMI over time was associated with clinical stage transition longitudinally. Further longitudinal research is needed to understand the demographic, clinical, illness progression or treatment factors associated with changes in cardiometabolic status.

The temporal dependencies between social, emotional and physical health factors in young people receiving mental healthcare: a dynamic Bayesian network analysis.

AIMS: The needs of young people attending mental healthcare can be complex and often span multiple domains (e.g., social, emotional and physical health factors). These factors often complicate treatment approaches and contribute to poorer outcomes in youth mental health. We aimed to identify how these factors interact over time by modelling the temporal dependencies between these transdiagnostic social, emotional and physical health factors among young people presenting for youth mental healthcare. METHODS: Dynamic Bayesian networks were used to examine the relationship between mental health factors across multiple domains (social and occupational function, self-harm and suicidality, alcohol and substance use, physical health and psychiatric syndromes) in a longitudinal cohort of 2663 young people accessing youth mental health services. Two networks were developed: (1) 'initial network', that shows the conditional dependencies between factors at first presentation, and a (2) 'transition network', how factors are dependent longitudinally. RESULTS: The 'initial network' identified that childhood disorders tend to precede adolescent depression which itself was associated with three distinct pathways or illness trajectories; (1) anxiety disorder; (2) bipolar disorder, manic-like experiences, circadian disturbances and psychosis-like experiences; (3) self-harm and suicidality to alcohol and substance use or functioning. The 'transition network' identified that over time social and occupational function had the largest effect on self-harm and suicidality, with direct effects on ideation (relative risk [RR], 1.79; CI, 1.59-1.99) and self-harm (RR, 1.32; CI, 1.22-1.41), and an indirect effect on attempts (RR, 2.10; CI, 1.69-2.50). Suicide ideation had a direct effect on future suicide attempts (RR, 4.37; CI, 3.28-5.43) and self-harm (RR, 2.78; CI, 2.55-3.01). Alcohol and substance use, physical health and psychiatric syndromes (e.g., depression and anxiety, at-risk mental states) were independent domains whereby all direct effects remained within each domain over time. CONCLUSIONS: This study identified probable temporal dependencies between domains, which has causal interpretations, and therefore can provide insight into their differential role over the course of illness. This work identified social, emotional and physical health factors that may be important early intervention and prevention targets. Improving social and occupational function may be a critical target due to its impacts longitudinally on self-harm and suicidality. The conditional independence of alcohol and substance use supports the need for specific interventions to target these comorbidities.

Double-blind, randomised placebo-controlled clinical trial of metformin as an adjunct to a sleep-wake, activity and metabolically focused behavioural intervention to improve cardiometabolic outcomes and mood symptoms in youth with major mood syndromes: study protocol.

INTRODUCTION: Metformin is a medication likely to improve measures of cardiometabolic disturbance in young people with mental illness. Evidence also suggests metformin may improve depressive symptoms. This 52-week double-blind randomised control trial (RCT) aims to investigate the efficacy of metformin pharmacotherapy as an adjunct to a healthy lifestyle behavioural intervention in improving cardiometabolic outcomes, and depressive, anxiety and psychotic symptoms in youth with clinically diagnosed major mood syndromes. METHODS AND ANALYSIS: At least 266 young people aged 16-25 presenting for mental healthcare for major mood syndromes who are also at risk for poor cardiometabolic outcomes will be invited to participate in this study. All participants will engage in a 12-week sleep-wake, activity and metabolically focused behavioural intervention programme. As an adjunctive intervention, participants will receive either metformin (500-1000 mg) or placebo pharmacotherapy for 52 weeks.Participants will undergo a series of assessments including: (1) self-report and clinician-administered assessments; (2) blood tests; (3) anthropometric assessments (height, weight, waist circumference and blood pressure); and (4) actigraphy. Univariate and multivariate tests (generalised mixed-effects models) will be used to examine changes in primary and secondary outcomes (and associations with predetermined predictor variables). ETHICS AND DISSEMINATION: This study has been approved by the Sydney Local Health District Research Ethics and Governance Office (X22-0017). The results of this double-blind RCT will be disseminated into the scientific and broader community through peer-reviewed journals, conference presentations, social media and university websites. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ANZCTR) Number: ACTRN12619001559101p, 12 November 2019.

Dynamic modelling of chronotype and hypo/manic and depressive symptoms in young people with emerging mental disorders.

There is significant interest in the possible influence of chronotype on clinical states in young people with emerging mental disorders. We apply a dynamic approach (bivariate latent change score modelling) to examine the possible prospective influence of chronotype on depressive and hypo/manic symptoms in a youth cohort with predominantly depressive, bipolar, and psychotic disorders (N = 118; 14-30-years), who completed a baseline and follow-up assessment of these constructs (mean interval = 1.8-years). Our primary hypotheses were that greater baseline eveningness would predict increases in depressive but not hypo/manic symptoms. We found moderate to strong autoregressive effects for chronotype (ß = -0.447 to -0.448, p < 0.001), depressive (ß = -0.650, p < 0.001) and hypo/manic symptoms (ß = -0.819, p < 0.001). Against our predictions, baseline chronotypes did not predict change in depressive (ß = -0.016, p = 0.810) or hypo/manic symptoms (ß = 0.077, p = 0.104). Similarly, the change in chronotype did not correlate with the change in depressive symptoms (ß = -0.096, p = 0.295) nor did the change in chronotype and the change in hypo/manic symptoms (ß = -0.166, p = 0.070). These data suggest that chronotypes may have low utility for predicting future hypo/manic and depressive symptoms in the short term, or that more frequent assessments over longer periods are needed to observe these associations. Future studies should test whether other circadian phenotypes (e.g. sleep-wake variability) are better indicators of illness course.

A systematic review and meta-analysis of sleep and circadian rhythms disturbances in individuals at high-risk of developing or with early onset of bipolar disorders.

Sleep and circadian rhythms disturbances (SCRD) in young people at high risk or with early onset of bipolar disorders (BD) are poorly understood. We systematically searched for studies of self, observer or objective estimates of SCRD in asymptomatic or symptomatic offspring of parents with BD (OSBD), individuals with presentations meeting recognised BD-at-risk criteria (BAR) and youth with recent onset of full-threshold BD (FT-BD). Of 76 studies eligible for systematic review, 35 (46%) were included in random effects meta-analyses. Pooled analyses of self-ratings related to circadian rhythms demonstrated greater preference for eveningness and more dysregulation of social rhythms in BAR and FT-BD groups; analyses of actigraphy provided some support for these findings. Meta-analysis of prospective studies showed that pre-existing SCRD were associated with a 40% increased risk of onset of BD, but heterogeneity in assessments was a significant concern. Overall, we identified longer total sleep time (Hedges g: 0.34; 95% confidence intervals:.1, .57), especially in OSBD and FT-BD and meta-regression analysis indicated the effect sizes was moderated by the proportion of any sample manifesting psychopathology or receiving psychotropic medications. This evolving field of research would benefit from greater attention to circadian rhythm as well as sleep quality measures.

Effects of adjunctive brexpiprazole on sleep-wake and circadian parameters in youth with depressive disorders: study protocol for a clinical trial.

INTRODUCTION: Sleep-wake and circadian disturbance is a key feature of mood disorders with a potential causal role and particular relevance to young people. Brexpiprazole is a second-generation antipsychotic medication with demonstrated efficacy as an adjunct to antidepressant treatment for major depressive disorder (MDD) in adults, with preliminary evidence suggesting greater effectiveness in subgroups of depressed patients with sleep disturbances. This clinical trial aims to evaluate the relationships between changes in sleep-wake and circadian parameters and changes in depressive symptoms following adjunctive brexpiprazole treatment in young adults with MDD and sleep-wake disturbance. METHODS AND ANALYSIS: This study is designed as a 16 week (8 weeks active treatment, 8 weeks follow-up) mechanistic, open-label, single-arm, phase IV clinical trial and aims to recruit 50 young people aged 18-30 with MDD and sleep-wake cycle disturbance through an early intervention youth mental health clinic in Sydney, Australia. At baseline, participants will undergo multidimensional outcome assessment and subsequently receive 8 weeks of open-label treatment with brexpiprazole as adjunctive to their stable psychotropic medication. Following 4 weeks of treatment, clinical and self-report measures will be repeated. Ambulatory sleep-wake monitoring will be conducted continuously for the duration of treatment. After 8 weeks of treatment, all multidimensional outcome assessments will be repeated. Follow-up visits will be conducted 4 and 8 weeks after trial completion (including sleep-wake, clinical and self-report assessments). Circadian rhythm biomarkers including salivary melatonin, cortisol and core body temperature will be collected during an in-lab assessment. Additionally, metabolic, inflammatory and genetic risk markers will be collected at baseline and after 8 weeks of treatment. ETHICS AND DISSEMINATION: This trial protocol has been approved by the Human Research Ethics Committee of the Sydney Local Health District (X19-0417 and 2019/ETH12986, Protocol Version 1-3, dated 25 February 2021). The results of this study, in deidentified form, will be disseminated through publication in peer-reviewed journals, scholarly book chapters, presentation at conferences and publication in conference proceedings. TRIAL REGISTRATION NUMBER: ACTRN12619001456145.