Development and validation of a risk calculator for major mood disorders among the offspring of bipolar parents using information collected in routine clinical practice.

Family history is a significant risk factor for bipolar disorders (BD), but the magnitude of risk varies considerably between individuals within and across families. Accurate risk estimation may increase motivation to reduce modifiable risk exposures and identify individuals appropriate for monitoring over the peak risk period. Our objective was to develop and independently replicate an individual risk calculator for bipolar spectrum disorders among the offspring of BD parents using data collected in routine clinical practice. Data from the longitudinal Canadian High-Risk Offspring cohort study collected from 1996 to 2020 informed the development of a 5 and 10-year risk calculator using parametric time-to-event models with a cure fraction and a generalized gamma distribution. The calculator was then externally validated using data from the Lausanne-Geneva High-Risk Offspring cohort study collected from 1996 to 2020. A time-varying C-index by age in years was used to estimate the probability that the model correctly classified risk. Bias corrected estimates and 95% confidence limits were derived using a jackknife resampling approach. The primary outcome was age of onset of a major mood disorder. The risk calculator was most accurate at classifying risk in mid to late adolescence in the Canadian cohort (n = 285), and a similar pattern was replicated in the Swiss cohort (n = 128). Specifically, the time-varying C-index indicated that there was approximately a 70% chance that the model would correctly predict which of two 15-year-olds would be more likely to develop the outcome in the future. External validation within a smaller Swiss cohort showed mixed results. Findings suggest that this model may be a useful clinical tool in routine practice for improved individualized risk estimation of bipolar spectrum disorders among the adolescent offspring of a BD parent; however, risk estimation in younger high-risk offspring is less accurate, perhaps reflecting the evolving nature of psychopathology in early childhood. Based on external validation with a Swiss cohort, the risk calculator may not be as predictive in more heterogenous high-risk populations. The Canadian High-Risk Study has been funded by consecutive operating grants from the Canadian Institutes for Health Research, currently CIHR PJT Grant 152796 he Lausanne-Geneva high-risk study was and is supported by five grants from the Swiss National Foundation (#3200-040,677, #32003B-105,969, #32003B-118,326, #3200-049,746 and #3200-061,974), three grants from the Swiss National Foundation for the National Centres of Competence in Research project "The Synaptic Bases of Mental Diseases" (#125,759, #158,776, and #51NF40 - 185,897), and a grant from GlaxoSmithKline Clinical Genetics

The emergent course of bipolar disorder: observations over two decades from the Canadian high-risk offspring cohort

Objective: The authors sought to describe the emergent course of bipolar disorder in offspring of affected parents subgrouped by parental response to lithium prophylaxis.Methods: Parent bipolar disorder was confirmed by the best-estimate procedure and lithium response by research protocol. High-risk offspring (N=279) and control subjects (N=87) were blindly assessed, annually on average, with the Kiddie Schedule for Affective Disorders and Schizophrenia– Present and Lifetime version or the Schedule for Affective Disorders and Schizophrenia–Lifetime version. DSM-IV diagnoses were confirmed using the best-estimate procedure in blind consensus reviews. Cumulative incidence and median age at onset were determined for lifetime syndrome- and symptom-level data. Mixed models assessed the association between parent and offspring course. A multistate model was used to estimate the clinical trajectory into bipolar disorder.Results: The cumulative incidence of bipolar disorder was 24.5%, and the median age at onset was 20.7 years (range, 12.4 to 30.3). The clinical course of the affected parent was associated with that of the affected child. Depressive episodes predominated during the early bipolar course, especially among offspring of lithium responders. Childhood sleep and anxiety disorders significantly predicted 1.6-fold and 1.8-fold increases in risk of mood disorder, respectively, and depressive and manic symptoms predicted 2.7- fold and 2.3-fold increases in risk, respectively. The best-fit model of emerging bipolar disorder was a progressive sequence from nonspecific childhood antecedents to adolescent depression to index manic or hypomanic episode. Subthreshold sleep symptoms were significantly associated with transition from well to non-mood disorder, and psychotic symptoms in mood episodes were significantly associated with transition from unipolar to bipolar disorder.Conclusions: Bipolar disorder in individuals at familial risk typically unfolds in a progressive clinical sequence. Childhood sleep and anxiety disorders are important predictors, as are clinically significant mood symptoms and psychotic symptoms in depressive episodes

The emergent course of bipolar disorder: observations over two decades from the Canadian high-risk offspring cohort

Objective: The authors sought to describe the emergent course of bipolar disorder in offspring of affected parents subgrouped by parental response to lithium prophylaxis.Methods: Parent bipolar disorder was confirmed by the best-estimate procedure and lithium response by research protocol. High-risk offspring (N=279) and control subjects (N=87) were blindly assessed, annually on average, with the Kiddie Schedule for Affective Disorders and Schizophrenia– Present and Lifetime version or the Schedule for Affective Disorders and Schizophrenia–Lifetime version. DSM-IV diagnoses were confirmed using the best-estimate procedure in blind consensus reviews. Cumulative incidence and median age at onset were determined for lifetime syndrome- and symptom-level data. Mixed models assessed the association between parent and offspring course. A multistate model was used to estimate the clinical trajectory into bipolar disorder.Results: The cumulative incidence of bipolar disorder was 24.5%, and the median age at onset was 20.7 years (range, 12.4 to 30.3). The clinical course of the affected parent was associated with that of the affected child. Depressive episodes predominated during the early bipolar course, especially among offspring of lithium responders. Childhood sleep and anxiety disorders significantly predicted 1.6-fold and 1.8-fold increases in risk of mood disorder, respectively, and depressive and manic symptoms predicted 2.7- fold and 2.3-fold increases in risk, respectively. The best-fit model of emerging bipolar disorder was a progressive sequence from nonspecific childhood antecedents to adolescent depression to index manic or hypomanic episode. Subthreshold sleep symptoms were significantly associated with transition from well to non-mood disorder, and psychotic symptoms in mood episodes were significantly associated with transition from unipolar to bipolar disorder.Conclusions: Bipolar disorder in individuals at familial risk typically unfolds in a progressive clinical sequence. Childhood sleep and anxiety disorders are important predictors, as are clinically significant mood symptoms and psychotic symptoms in depressive episodes

Epigenetic markers in inflammation-related genes associated with mood disorder: a cross-sectional and longitudinal study in high-risk offspring of bipolar parents

Bipolar disorder is highly heritable and typically onsets in late adolescence or early adulthood. Evidence suggests that immune activation may be a mediating pathway between genetic predisposition and onset of mood disorders. Building on a prior study of mRNA and protein levels in high-risk offspring published in this Journal, we conducted a preliminary examination of methylation profiles in candidate immune genes from a subsample of well-characterized emergent adult (mean 20 years) offspring of bipolar parents from the Canadian Flourish high-risk cohort. Models were adjusted for variable age at DNA collection, sex and antidepressant and mood stabilizer use. On cross-sectional analysis, there was evidence of higher methylation rates for BDNF-1 in high-risk offspring affected (n = 27) and unaffected (n = 23) for mood disorder compared to controls (n = 24) and higher methylation rates in affected high-risk offspring for NR3C1 compared to controls. Longitudinal analyses (25 to 34 months) provided evidence of steeper decline in methylation rates in controls (n = 24) for NR3C1 compared to affected (n = 15) and unaffected (n = 11) high-risk offspring and for BDNF-2 compared to affected high-risk. There was insufficient evidence that changes in any of the candidate gene methylation rates were associated with illness recurrence in high-risk offspring. While preliminary, findings suggest that longitudinal investigation of epigenetic markers in well-characterized high-risk individuals over the peak period of risk may be informative to understand the emergence of bipolar disorder

Daily and weekly mood ratings using a remote capture method in high-risk offspring of bipolar parents: Compliance and symptom monitoring

Objectives To determine the compliance and clinical utility of weekly and daily mood symptom monitoring in adolescents and young adults at risk for mood disorder. Methods Fifty emerging adult offspring of bipolar parents were recruited from the Flourish Canadian high‐risk cohort study along with 108 university student controls. Participants were assessed by KSADS/SADS‐L semi‐structured interviews and used a remote capture method to complete weekly and daily mood symptom ratings using validated scales for 90 consecutive days. Hazard models and generalized estimating equations were used to determine differences in summary scores and regularity of ratings. Results 78% and 77% of high‐risk offspring and 97% and 93% of controls completed the first 30 days of weekly and daily ratings, respectively. There were no differences in drop‐out rates between groups over 90 days (high‐risk p=0.2149; controls p=0.9792). There were no differences in mean summary scores or regularity of weekly anxiety, depressive or hypomanic symptom ratings between high‐risk and control groups. However, high‐risk offspring compared to controls had daily ratings indicating lower positive affect and higher negative affect (p=0.0317). High‐risk offspring with remitted mood disorder compared to those without had more irregularity in weekly anxiety and depressive symptom ratings and daily ratings of lower positive affect, higher negative affect, and higher shame and self‐doubt (p=0.0365). Conclusions Findings support that high‐resolution symptom tracking may be a feasible and clinically useful approach to monitoring emerging psychopathology in young people at high‐risk of mood disorder onset or recurrence

Daily and weekly mood ratings using a remote capture method in high-risk offspring of bipolar parents: Compliance and symptom monitoring

Objectives To determine the compliance and clinical utility of weekly and daily mood symptom monitoring in adolescents and young adults at risk for mood disorder. Methods Fifty emerging adult offspring of bipolar parents were recruited from the Flourish Canadian high‐risk cohort study along with 108 university student controls. Participants were assessed by KSADS/SADS‐L semi‐structured interviews and used a remote capture method to complete weekly and daily mood symptom ratings using validated scales for 90 consecutive days. Hazard models and generalized estimating equations were used to determine differences in summary scores and regularity of ratings. Results 78% and 77% of high‐risk offspring and 97% and 93% of controls completed the first 30 days of weekly and daily ratings, respectively. There were no differences in drop‐out rates between groups over 90 days (high‐risk p=0.2149; controls p=0.9792). There were no differences in mean summary scores or regularity of weekly anxiety, depressive or hypomanic symptom ratings between high‐risk and control groups. However, high‐risk offspring compared to controls had daily ratings indicating lower positive affect and higher negative affect (p=0.0317). High‐risk offspring with remitted mood disorder compared to those without had more irregularity in weekly anxiety and depressive symptom ratings and daily ratings of lower positive affect, higher negative affect, and higher shame and self‐doubt (p=0.0365). Conclusions Findings support that high‐resolution symptom tracking may be a feasible and clinically useful approach to monitoring emerging psychopathology in young people at high‐risk of mood disorder onset or recurrence

The association between screen time and cardiometabolic risk in young children

Abstract Objectives While studies exist on the association between screen time and cardiometabolic risk among adolescents, research examining the effect of screen time on cardiometabolic risk in young children is lacking. The primary objective of this study was to examine the association between daily screen time and cardiometabolic risk (CMR) [sum of age- and sex-standardized z-scores of systolic blood pressure (SBP), glucose, log-triglycerides, waist circumference (WC), and negative high-density lipoprotein (HDL) cholesterol divided by the square root of five] in young children. Secondary objectives included examining individual CMR risk factors, including waist-to-height ratio and non high-density lipoprotein (non-HDL) cholesterol, as well as the individual cut-offs of these risk factors. Additional analyses include examining the association between screen time and CMR by handheld/non-handheld devices. Methods A study was conducted among young children 3 to 6 years from the TARGet Kids! practice-based research network in Toronto and Montreal, Canada. Children with one or more measures of screen time and CMR were included in this study. Generalized estimating equation (GEE) multivariable linear regressions and multivariable logistic regressions, using published cut-offs, were conducted to evaluate these associations. Results Data from 1317 children [mean age 52 months (SD = 13.36), 44.34% female] were included for analyses. There was no evidence of associations between screen time and total CMR score or individual risk factors (p > 0.05) after adjusting for confounders. A statistically significant, but small association between daily screen time and non-HDL cholesterol was found (B = 0.046; CI = [0.017 to 0.075]; p = 0.002. Conclusions Though no relationship was reported between daily screen time and the majority of CMR factors in early childhood, there was an association between daily screen time and non-HDL cholesterol. As the relationship between daily screen time and CMR factors may not be apparent in early childhood, studies to evaluate longer-term cardiometabolic effects of screen time are needed. Although there is an evidence-based rationale to reduce screen time in early childhood, prevention of cardiometabolic risk may not be the primary driver

Mental health need of students at entry to university: baseline findings from the U-Flourish Student Well-Being and Academic Success Study

Aim Transition to university is associated with unique stressors and coincides with the peak period of risk for onset of mental illness. Our objective in this analysis was to estimate the mental health need of students at entry to a major Canadian university. Methods After a student-led engagement campaign, all first year students were sent a mental health survey, which included validated symptom rating scales for common mental disorders. Rates of self-reported lifetime mental illness, current clinically significant symptoms and treatment stratified by gender are reported. The likelihood of not receiving treatment among those symptomatic and/or with lifetime disorders was estimated. Results Fifty-eight percent of all first-year students (n= 3,029) completed the baseline survey, of which 28% reported a lifetime mental disorder. Moreover, 30% of students screened positive for anxiety symptoms, 28%, for depressive symptoms, and 18% for sleep problems with high rates (≅45%) of associated impairment. Only 8.5% of students indicated currently receiving any form of treatment. Females were more likely to report a lifetime diagnosis, anxiety and depressive symptoms, as well as current treatment. Over 25% of students reported lifetime suicidal thoughts and 6% suicide attempt(s). Current weekly binge drinking (25%) and cannabis use (11%) were common, especially in males. Conclusions There is limited systematically collected data describing the mental health needs of young people at entry to university. Findings of this study underscore the importance of timely identification of significant mental health problems as part of a proactive system of effective student mental health care.</p

Predictors of mental health and academic outcomes in first-year university students: Identifying prevention and early-intervention targets

Background Although there is growing interest in mental health problems in university students there is limited understanding of the scope of need and determinants to inform intervention efforts. Aims To longitudinally examine the extent and persistence of mental health symptoms and the importance of psychosocial and lifestyle factors for student mental health and academic outcomes. Method Undergraduates at a Canadian university were invited to complete electronic surveys at entry and completion of their first year. The baseline survey measured important distal and proximal risk factors and the follow-up assessed mental health and well-being. Surveys were linked to academic grades. Multivariable models of risk factors and mental health and academic outcomes were fit and adjusted for confounders. Results In 1530 students surveyed at entry to university 28% and 33% screened positive for clinically significant depressive and anxiety symptoms respectively, which increased to 36% and 39% at the completion of first year. Over the academic year, 14% of students reported suicidal thoughts and 1.6% suicide attempts. Moreover, there was persistence and overlap in these mental health outcomes. Modifiable psychosocial and lifestyle factors at entry were associated with positive screens for mental health outcomes at completion of first year, while anxiety and depressive symptoms were associated with lower grades and university well-being. Conclusions Clinically significant mental health symptoms are common and persistent among first-year university students and have a negative impact on academic performance and well-being. A comprehensive mental health strategy that includes a whole university approach to prevention and targeted early-intervention measures and associated research is justified