Sleep patterns among preschool offspring of parents with and without psychopathology: Association with the development of psychopathology in childhood.

BACKGROUND: Disturbed sleep during early childhood predicts social-emotional problems. However, it is not known how various early childhood sleep phenotypes are associated with the development of childhood psychopathology, nor whether these relationships vary as a function of parental psychopathology. We identified sleep phenotypes among preschool youth; examined whether these phenotypes were associated with child and parent factors; and determined if early sleep phenotypes predicted later childhood psychopathology. METHODS: Using data from the Pittsburgh Bipolar Offspring study, parents with bipolar disorder (BD), non-BD psychopathology, and healthy controls reported about themselves and their offspring (n = 218) when their children were ages 2-5. Offspring and parents were interviewed directly approximately every 2 years from ages 6-18. Latent class analysis (LCA) identified latent sleep classes; we compared these classes on offspring demographics, parental sleep variables, and parental diagnoses. Kaplan-Meier survival models estimated hazard of developing any new-onset Axis-I disorders, as well as BD specifically, for each class. RESULTS: The optimal LCA solution featured four sleep classes, which we characterized as (1) good sleep, (2) wake after sleep onset problems, (3) bedtime problems (e.g., trouble falling asleep, resists going to bed), and (4) poor sleep generally. Good sleepers tended to have significantly less parental psychopathology than the other three classes. Risk of developing new-onset Axis-I disorders was highest among the poor sleep class and lowest among the good sleep class. CONCLUSIONS: Preschool sleep phenotypes are an important predictor of the development of psychopathology. Future work is needed to understand the biopsychosocial processes underlying these trajectories.

Early indicators of bipolar risk in preschool offspring of parents with bipolar disorder.

BACKGROUND: Offspring of parents with bipolar disorder (BD-I/II) are at increased risk to develop the disorder. Previous work indicates that bipolar spectrum disorder (BPSD) is often preceded by mood/anxiety symptoms. In school-age offspring of parents with BD, we previously built a risk calculator to predict BPSD onset, which generates person-level risk scores. Here, we test whether preschool symptoms predict school-age BPSD risk. METHODS: We assessed 113 offspring of parents with BD 1-3 times during preschool years (2-5 years old) and then approximately every 2 years for a mean of 10.6 years. We used penalized (lasso) regression with linear mixed models to assess relationships between preschool mood, anxiety, and behavioral symptoms (parent-reported) and school-age predictors of BPSD onset (i.e., risk score, subthreshold manic symptoms, and mood lability), adjusting for demographics and parental symptomatology. Finally, we conducted survival analyses to assess associations between preschool symptoms and school-age onset of BPSD and mood disorder. RESULTS: Of 113 preschool offspring, 33 developed new-onset mood disorder, including 19 with new-onset BPSD. Preschool irritability, sleep problems, and parental factors were lasso-selected predictors of school-age risk scores. After accounting for demographic and parental factors, preschool symptoms were no longer significant. Lasso regressions to predict mood lability and subthreshold manic symptoms yielded similar predictors (irritability, sleep problems, and parental affective lability), but preschool symptoms remained predictive even after adjusting for parental factors (ps < .005). Exploratory analyses indicated that preschool irritability univariately predicted new-onset BPSD (p = .02) and mood disorder (p = .02). CONCLUSIONS: These results provide initial prospective evidence that, as early as preschool, youth who will develop elevated risk scores, mood lability, and subthreshold manic symptoms are already showing symptomatology; these preschool symptoms also predict new-onset BPSD. While replication of findings in larger samples is warranted, results point to the need for earlier assessment of risk and development of early interventions.

Prospectively ascertained mania and hypomania among young adults with child- and adolescent-onset bipolar disorder.

OBJECTIVES: While adults with bipolar disorder (BD) often report symptoms starting in childhood, continuity of mania and/or hypomania (mania/hypomania) from childhood to adulthood has been questioned. Using longitudinal data from the Course and Outcome of Bipolar Youth (COBY) study, we assessed threshold mania/hypomania in young adults who manifested BD as youth. METHODS: COBY is a naturalistic, longitudinal study of 446 youth with BD (84% recruited from outpatient clinics), 7-17 years old at intake, and over 11 years of follow-up. Focusing on youth with BD-I/II (n = 297), we examined adult mania/hypomania risk (>18 years old; mean 7.9 years of follow-up) according to child (<13 years old) versus adolescent (13-17 years old) onset. We next used penalized regression to test demographic and clinical predictors of young adult mania/hypomania. RESULTS: Most participants (64%) had child-onset mania/hypomania, 57% of whom also experienced mania/hypomania in adolescence. Among those who experienced an episode in adolescence, over 40% also had mania/hypomania during adulthood; the risk did not differ according to child versus adolescent onset. In contrast, 7% with mania/hypomania in childhood, but not adolescence, experienced mania/hypomania in adulthood. Family history (of mania and suicide attempts) predicted mania/hypomania in young adulthood (p-values <0.05); age of onset was not a significant predictor. Among participants with no mania/hypomania during adulthood, 53% (105/198) still experienced subthreshold manic episodes. DISCUSSION: We find substantial continuity across developmental stage indicating that, in this carefully characterized sample, children who experience mania/hypomania-particularly those who also experience mania/hypomania in adolescence-are likely to experience mania/hypomania in young adulthood.

Longitudinal cognitive trajectories and associated clinical variables in youth with bipolar disorder.

OBJECTIVE: There is substantial interest in delineating the course of cognitive functioning in bipolar (BP) youth. However, there are no longitudinal studies aimed at defining subgroups of BP youth based on their distinctive cognitive trajectories and their associated clinical variables. METHOD: Cognitive functioning was measured in 135 participants from the Course and Outcome of BP Youth (COBY) study using several subtests of the Cambridge Neuropsychological Test Automated Battery (CANTAB). Youth were prospectively evaluated three times on average every 13.75 months over 2.5 years. Clinical and functional outcomes were assessed using the Longitudinal Interval Follow-Up Evaluation (LIFE). RESULTS: Latent class growth analysis identified three longitudinal patterns of cognitive functioning based on a general cognitive index: class 1, "persistently high" (N=21; 15.6%); class 2, "persistently moderate" (N=82; 60.74%); and class 3, "persistently low" (N=32; 23.7%). All classes showed normal cognitive functioning when compared with the CANTAB normative data. After adjustment for confounders, youth from class 3 had a significantly greater percentage of time with overall, manic, and depressive syndromal symptoms than youth in the other two classes. Also, after adjustment for confounders, youth from class 3 had significantly poorer global, academic, and social functioning than youth from class 1. CONCLUSIONS: BP youth showed normal overall cognitive functioning that remained stable during the follow-up within each class. However, 24% of BP youth showed poorer cognitive functioning than the other BP youth. This subgroup had poorer mood course and functioning, and may benefit from cognitive remediation and early management with evidence-based pharmacological treatments.

Altered amygdala-prefrontal response to facial emotion in offspring of parents with bipolar disorder.

This study aimed to identify neuroimaging measures associated with risk for, or protection against, bipolar disorder by comparing youth offspring of parents with bipolar disorder versus youth offspring of non-bipolar parents versus offspring of healthy parents in (i) the magnitude of activation within emotional face processing circuitry; and (ii) functional connectivity between this circuitry and frontal emotion regulation regions. The study was conducted at the University of Pittsburgh Medical Centre. Participants included 29 offspring of parents with bipolar disorder (mean age = 13.8 years; 14 females), 29 offspring of non-bipolar parents (mean age = 13.8 years; 12 females) and 23 healthy controls (mean age = 13.7 years; 11 females). Participants were scanned during implicit processing of emerging happy, sad, fearful and angry faces and shapes. The activation analyses revealed greater right amygdala activation to emotional faces versus shapes in offspring of parents with bipolar disorder and offspring of non-bipolar parents than healthy controls. Given that abnormally increased amygdala activation during emotion processing characterized offspring of both patient groups, and that abnormally increased amygdala activation has often been reported in individuals with already developed bipolar disorder and those with major depressive disorder, these neuroimaging findings may represent markers of increased risk for affective disorders in general. The analysis of psychophysiological interaction revealed that offspring of parents with bipolar disorder showed significantly more negative right amygdala-anterior cingulate cortex functional connectivity to emotional faces versus shapes, but significantly more positive right amygdala-left ventrolateral prefrontal cortex functional connectivity to happy faces (all P-values corrected for multiple tests) than offspring of non-bipolar parents and healthy controls. Taken together with findings of increased amygdala-ventrolateral prefrontal cortex functional connectivity, and decreased amygdala-anterior cingulate cortex functional connectivity previously shown in individuals with bipolar disorder, these connectivity patterns in offspring of parents with bipolar disorder may be risk markers for, rather than markers conferring protection against, bipolar disorder in youth. The patterns of activation and functional connectivity remained unchanged after removing medicated participants and those with current psychopathology from analyses. This is the first study to demonstrate that abnormal functional connectivity patterns within face emotion processing circuitry distinguish offspring of parents with bipolar disorder from those of non-bipolar parents and healthy controls.

Dialectical Behavior Therapy for Adolescents With Bipolar Disorder: A Randomized Clinical Trial.

Importance: Early-onset bipolar disorder conveys substantial risk for suicide. No psychosocial intervention for this population expressly targets suicidal behavior. Objective: To determine whether dialectical behavior therapy (DBT) for adolescents with bipolar spectrum disorder is more effective than standard of care (SOC) psychotherapy in decreasing suicide attempts over 1 year. Design, Settings, and Participants: Adolescents aged 12 to 18 years diagnosed with bipolar spectrum disorder were recruited from a specialty outpatient psychiatric clinic between November 2014 and September 2019. Independent evaluators conducted quarterly assessments over 1 year with participants and parents. Data were analyzed from March 2021 to November 2022. Interventions: Participants were randomly assigned to 1 year of DBT (36 sessions; n = 47) or SOC psychotherapy (schedule clinically determined; n = 53). All youth received medication management via a flexible algorithm. Main Outcomes and Measures: Primary outcomes included suicide attempts over 1 year and mood symptoms and states (depression and hypomania/mania). Secondary analyses included moderation of DBT effects by history of suicide attempt and mediation through emotion dysregulation. Results: Of 100 included participants, 85 (85%) were female, and the mean (SD) age was 16.1 (1.6) years. Participants were followed up over a mean (SD) of 47 (14) weeks. Both treatment groups demonstrated significant and similar improvement in mood symptoms and episodes over 1 year (standardized depression rating scale slope, -0.17; 95% CI, -0.31 to -0.03; standardized mania rating scale slope, -0.24; 95% CI, -0.34 to -0.14). DBT and SOC participants reported similar suicide attempt rates at intake as measured on the Adolescent Longitudinal Follow-Up Evaluation (ALIFE; mean [SD] attempts, 2.0 [4.5] vs 1.8 [3.9], respectively; P = .80). DBT participants reported slightly more suicide attempts at intake as measured on the Columbia-Suicide Severity Rating Scale Pediatric Version (C-SSRS; mean [SD] attempts, 1.4 [3.6] vs 0.6 [0.9]; P = .02). DBT participants reported significantly fewer suicide attempts over follow-up compared with SOC participants via the ALIFE (mean [SD] attempts per follow-up period, 0.2 [0.4] vs 1.1 [4.3], controlling for baseline attempts: P = .03) and the C-SSRS (mean [SD] attempts per follow-up period, 0.04 [0.2] vs 0.10 [0.3], controlling for baseline attempts; P = .03). DBT was significantly more effective than SOC psychotherapy at decreasing suicide attempts over 1 year (ALIFE: incidence rate ratio [IRR], 0.32; 95% CI, 0.11-0.96; C-SSRS: IRR, 0.13; 95% CI, 0.02-0.78). Decreased rate of suicide attempts in DBT was moderated by presence of lifetime history of suicide attempt and time (IRR, 0.23; 95% CI, 0.13-0.44) and mediated by improvement in emotion dysregulation (IRR, 0.61; 95% CI, 0.42-0.89), particularly for those with high baseline emotion dysregulation (standardized ß, -0.59; 95% CI, -0.92 to -0.26). Conclusions and Relevance: In this randomized clinical trial, DBT demonstrated efficacy in decreasing suicide attempts among the high-risk population of adolescents with bipolar spectrum disorder. Trial Registration: ClinicalTrials.gov Identifier: NCT02003690.

Validation of a youth suicide risk calculator in an adult sample with bipolar disorder.

BACKGROUND: Bipolar disorder (BD) conveys the highest risk of suicide of all mental disorders. We sought to externally validate a risk calculator (RC) of suicide attempts developed in youth with BD from the Course and Outcome of Bipolar Youth (COBY) study in an adult sample. METHODS: A prospective cohort of adults with BD from the National Institute of Mental Health Collaborative Depression Study (CDS; N = 427; mean (+/- SD) age at intake (36 +/- 13 years)) was secondarily analyzed to validate the COBY RC for one-year risk of suicide attempts/deaths. Nine of the ten predictor variables from the COBY RC were available in the CDS and used: age, age of mood disorder onset, first and second (partial) degree family history of suicide, history of psychotic symptoms, substance use disorder, prior suicide attempt, socioeconomic status, and non-suicidal self-injury (prospectively, incompletely at baseline). RESULTS: Over a mean (SD) follow-up of 19 (10) years, 29 % of the CDS sample attempted suicide. The RC predicted suicide attempts/deaths over one-year follow-up with an area under the receiver operating characteristic curve (AUC) of 0.78 (95 % CI 0.75-0.80). The RC performed slightly better in those with a younger age of mood disorder onset. LIMITATIONS: Clinical samples may limit generalizability; the RC does not assess more acute suicide risk. CONCLUSIONS: One-year risk of suicide attempts/deaths can be predicted with acceptable accuracy in youth and adults with BD, comparable to commonly used RCs to predict cardiovascular risk. This RC may help identify higher-risk individuals with BD for personalized treatment and research. https://cobysuicideattemptsrc.shinyapps.io/Shiny.

Controlled Study of Metabolic Syndrome Among Offspring of Parents With Bipolar Disorder.

Objectives: Bipolar disorder (BD) is highly heritable and associated with increased rates of metabolic syndrome (MetS). However, little is known about MetS in offspring of parents with BD. We therefore examined this topic in the Pittsburgh Bipolar Offspring Study cohort.Methods: Participants included 199 parents (n = 116 BD, diagnosed using DSM-IV; n = 83 non-BD) and 330 offspring (mean age 19.9 ± 5.3 years), including 198 high-risk offspring of parents with BD (n = 80 affected with a mood disorder) and 132 control offspring. We defined MetS and its components using International Diabetes Federation (IDF) guidelines (primary) and National Cholesterol Education Program (NCEP) guidelines (secondary). Multivariable analyses controlled for age and socioeconomic status in offspring. Sensitivity analyses controlled for psychotropic medications.Results: There was higher prevalence of MetS in parents with BD as compared to controls. NCEP-defined MetS was significantly more prevalent among affected high-risk offspring (16.3%) and controls (15.2%) vs unaffected high-risk offspring (6.0%; χ2 = 6.54, P = .04). There was greater mean number of MetS components (IDF: 1.7 ± 1.1; NCEP: 1.4 ± 1.0) among affected high-risk offspring vs unaffected high-risk offspring (IDF: 1.2 ± 1.0; NCEP: 1.0 ± 1.0) and controls (IDF: 1.3 ± 1.2; NCEP: 1.1 ± 1.1; IDF: H[2] = 10.26, P = .006; NCEP: H[2] = 9.18, P = .01). Most findings became nonsignificant in multivariable analyses. Some between-group results became nonsignificant after controlling for second-generation antipsychotics.Conclusions: This preliminary study found increased risk of MetS among affected high-risk offspring, which may be attributable to socioeconomic status. Prospective studies may determine timing of MetS onset in relation to mood disorder onset, and the role of socioeconomic status in moderating this association.

Polygenic Scores and Onset of Major Mood or Psychotic Disorders Among Offspring of Affected Parents.

OBJECTIVE: Family history is an established risk factor for mental illness. The authors sought to investigate whether polygenic scores (PGSs) can complement family history to improve identification of risk for major mood and psychotic disorders. METHODS: Eight cohorts were combined to create a sample of 1,884 participants ages 2-36 years, including 1,339 offspring of parents with mood or psychotic disorders, who were prospectively assessed with diagnostic interviews over an average of 5.1 years. PGSs were constructed for depression, bipolar disorder, anxiety, attention deficit hyperactivity disorder (ADHD), schizophrenia, neuroticism, subjective well-being, p factor, and height (as a negative control). Cox regression was used to test associations between PGSs, family history of major mental illness, and onsets of major mood and psychotic disorders. RESULTS: There were 435 onsets of major mood and psychotic disorders across follow-up. PGSs for neuroticism (hazard ratio=1.23, 95% CI=1.12-1.36), schizophrenia (hazard ratio=1.15, 95% CI=1.04-1.26), depression (hazard ratio=1.11, 95% CI=1.01-1.22), ADHD (hazard ratio=1.10, 95% CI=1.00-1.21), subjective well-being (hazard ratio=0.90, 95% CI=0.82-0.99), and p factor (hazard ratio=1.14, 95% CI=1.04-1.26) were associated with onsets. After controlling for family history, neuroticism PGS remained significantly positively associated (hazard ratio=1.19, 95% CI=1.08-1.31) and subjective well-being PGS remained significantly negatively associated (hazard ratio=0.89, 95% CI=0.81-0.98) with onsets. CONCLUSIONS: Neuroticism and subjective well-being PGSs capture risk of major mood and psychotic disorders that is independent of family history, whereas PGSs for psychiatric illness provide limited predictive power when family history is known. Neuroticism and subjective well-being PGSs may complement family history in the early identification of persons at elevated risk.

Effects of medication on neuroimaging findings in bipolar disorder: an updated review.

OBJECTIVE: Neuroimaging is an important tool for better understanding the neurobiological underpinnings of bipolar disorder (BD). However, potential study participants are often receiving psychotropic medications which can possibly confound imaging data. To better interpret the results of neuroimaging studies in BD, it is important to understand the impact of medications on structural magnetic resonance imaging (sMRI), functional MRI (fMRI), and diffusion tensor imaging (DTI). METHODS: To better understand the impact of medications on imaging data, we conducted a literature review and searched MEDLINE for papers that included the key words bipolar disorder and fMRI, sMRI, or DTI. The search was limited to papers that assessed medication effects and had not been included in a previous review by Phillips et al. (Medication effects in neuroimaging studies of bipolar disorder. Am J Psychiatry 2008; 165: 313-320). This search yielded 74 sMRI studies, 46 fMRI studies, and 15 DTI studies. RESULTS: Medication appeared to influence many sMRI studies, but had limited impact on fMRI and DTI findings. From the structural studies, the most robust finding (20/45 studies) was that lithium was associated with increased volumes in areas important for mood regulation, while antipsychotic agents and anticonvulsants were generally not. Regarding secondary analysis of the medication effects of fMRI and DTI studies, few showed significant effects of medication, although rigorous analyses were typically not possible when the majority of subjects were medicated. Medication effects were more frequently observed in longitudinal studies designed to assess the impact of particular medications on the blood oxygen level-dependent (BOLD) signal. With a few exceptions, the observed effects were normalizing, meaning that the medicated individuals with BD were more similar than their unmedicated counterparts to healthy subjects. CONCLUSIONS: The effects of psychotropic medications, when present, are predominantly normalizing and thus do not seem to provide an alternative explanation for differences in volume, white matter tracts, or BOLD signal between BD participants and healthy subjects. However, the normalizing effects of medication could obfuscate differences between BD and healthy subjects, and thus might lead to type II errors.

Confounding of indirect effects: a sensitivity analysis exploring the range of bias due to a cause common to both the mediator and the outcome.

Several investigators have demonstrated that the assessment of indirect and direct effects is biased in the presence of a cause that is common to both the mediator and the outcome if one has not controlled for this variable in the analysis. However, little work has been done to quantify the bias caused by this type of unmeasured confounding and determine whether this bias will materially affect conclusions regarding mediation. The author developed a sensitivity analysis program to address this crucial issue. Data from 2 well-known studies in the methodological literature on mediation were reanalyzed using this program. The results of mediation analyses were found not to be as vulnerable to the impact of confounding as previously described; however, these findings varied sharply between the 2 studies. Although the indirect effect observed in one study could potentially be due to a cause common to both the mediator and the outcome, such confounding could not feasibly explain the results of the other study. These disparate results demonstrate the utility of the current sensitivity analysis when assessing mediation.

Alternative assumptions for the identification of direct and indirect effects.

The assessment of mediation is important for testing the mechanisms that explain an observed relationship between exposure and disease. Several types of direct and indirect effects have been defined, broadly characterized as either controlled or natural. The identification of these effects requires a stricter set of assumptions than those necessary for the identification of the total effect of exposure on disease. The particular assumptions that are required differ depending on the type of effect. We use an approach based on response types to derive new assumptions for the identification of direct and indirect effects, both controlled and natural. These assumptions are stated in terms of response types and potential outcomes, and are compared with those already in the literature. This approach yields an alternative, and sometimes less stringent, set of assumptions for the identification of direct and indirect effects than those previously proposed.

Generalizing the Prediction of Bipolar Disorder Onset Across High-Risk Populations.

OBJECTIVE: Risk calculators (RC) to predict clinical outcomes are gaining interest. An RC to estimate risk of bipolar spectrum disorders (BPSD) could help reduce the duration of undiagnosed BPSD and improve outcomes. Our objective was to adapt an RC previously validated in the Pittsburgh Bipolar Offspring Study (BIOS) sample to achieve adequate predictive ability in both familial high-risk and clinical high-risk youths. METHOD: Participants (aged 6-12 years at baseline) from the Longitudinal Assessment of Manic Symptoms (LAMS) study (N = 473) were evaluated semi-annually. Evaluations included a Kiddie Schedule for Affective Disorders (K-SADS) interview. After testing an RC that closely approximated the original, we made modifications to improve model prediction. Models were trained in the BIOS data, which included biennial K-SADS assessments, and tested in LAMS. The final model was then trained in LAMS participants, including family history of BPSD as a predictor, and tested in the familial high-risk sample. RESULTS: Over follow-up, 65 youths newly met criteria for BPSD. The original RC identified youths who developed BPSD only moderately well (area under the curve [AUC] = 0.67). Eliminating predictors other than the K-SADS screening items for mania and depression improved accuracy (AUC = 0.73) and generalizability. The model trained in LAMS, including family history as a predictor, performed well in the BIOS sample (AUC = 0.74). CONCLUSION: The clinical circumstances under which the assessment of symptoms occurs affects RC accuracy; focusing on symptoms related to the onset of BPSD improved generalizability. Validation of the RC under clinically realistic circumstances will be an important next step.

Mindfulness-based intervention to decrease mood lability in at-risk youth: Preliminary evidence for changes in resting state functional connectivity.

BACKGROUND: In youth at familial risk for bipolar disorder (BD), mood lability is an important precursor to BD onset. Previous work in adults indicates that mindfulness-based interventions (MBI) may improve emotion regulation, in part by increasing resting-state functional connectivity (rsFC) between posterior cingulate cortex (PCC) and executive control network (ECN). In this pilot study, we assessed effects of an MBI on PCC-ECN rsFC and mood lability in at-risk youth. METHODS: We recruited 35 youth (10-14 years old) with a first-degree family history of BD and mood lability, and 21 age-matched healthy controls. Eligible at-risk youth were scanned pre/post an 8-week MBI and assessed three months later. Healthy controls were scanned at matched timepoints but did not participate in the MBI. The MBI used age-appropriate strategies to promote non-judgmental, present-moment awareness. We assessed pre/post changes in PCC-ECN rsFC and how rsFC changes were related to mood outcomes. RESULTS: Twenty at-risk youth were scanned pre/post MBI; 16 had high-quality rsFC data. Following MBI, at-risk youth showed increased rsFC between PCC and left dorsolateral prefrontal cortex (DLPFC) (BA 9; k = 28; corrected p=.006); healthy controls did not show this increase. Following MBI, at-risk youth reported more mindfulness (F = 7.15, p=.003), less mood lability (F = 7.2, p=.002), and less suppression of negative emotions (F = 5.05, p=.01). PCC-DLPFC rsFC increases predicted less mood lability (t=-2.25, p=.04) and less emotion suppression (t=-2.75, p=.02) at follow-up. LIMITATIONS: Small sample and lack of a control intervention. CONCLUSIONS: PCC-DLPFC rsFC may be a clinically meaningful neural target of an MBI in at-risk youth, related to improvements in mood lability.

Lithium Versus Other Mood-Stabilizing Medications in a Longitudinal Study of Youth Diagnosed With Bipolar Disorder.

OBJECTIVE: Lithium is the mainstay for bipolar disorder (BD) treatment in adults, but evidence in youths is limited. We used data from the Course and Outcome of Bipolar Youth (COBY) study to assess whether lithium vs other mood-stabilizing medication (OMS) was associated with improved outcomes, including mood symptoms and suicidality. METHOD: COBY is a naturalistic, longitudinal study of 413 youths, 7 to 17.11 years old at intake, with BD. At each visit, medication exposure, psychiatric symptoms, and psychosocial function over the preceding follow-up period were assessed using the Adolescent Longitudinal Interval Follow-Up Evaluation. Using mixed models, we determined whether participants taking lithium vs OMS (but not lithium) differed regarding mood symptoms, suicidality, psychosocial function, hospitalization, aggression, and substance use. RESULTS: A total of 340 participants contributed 2,638 six-month follow-up periods (886 lithium, 1,752 OMS), over a mean follow-up of 10 years. During lithium (vs OMS) follow-up periods, participants were older, less likely to have lifetime anxiety, and less likely to be on antidepressants (p values<.005). After covariate adjustment, the lithium group (vs OMS) had half as many suicide attempts (p = .03), fewer depressive symptoms (p = .004), less psychosocial impairment (p = .003), and less aggression (p = .0004). Similar findings were observed in the subgroup of follow-up periods in which participants were <18 years old. CONCLUSION: Findings are consistent with adult studies, showing that lithium is associated with decreased suicidality, less depression, and better psychosocial functioning. Given the paucity of evidence regarding lithium in children and adolescents, these findings have important clinical implications for the pharmacological management of youths with BD.

"Proportion explained": a causal interpretation for standard measures of indirect effect?

The assessment of indirect effects is an important tool for epidemiologists interested in exploring the mechanisms of exposure-disease relations. A standard way of expressing an indirect effect is in terms of the "proportion explained"; this is the proportion of the total effect that is explained by a particular mediator (or set of mediators). There are several ways to calculate the proportion explained, based on both additive and multiplicative models. However, these standard methods (particularly those based on multiplicative models) have been criticized for lacking a causal interpretation. To address this issue, the author uses a framework of potential outcomes to define the indirect effects of interest (natural effects) and assess the correspondence between the natural effects and standard measures. The author finds that standard additive measures represent an unbiased weighted average of the effects of interest; standard multiplicative measures, on the other hand, yield a biased weighted average of these effects. If the investigator is primarily interested in whether or not an indirect effect exists, standard measures for mediation will often yield the correct answer. In contrast, if valid quantification of the indirect effect is desired, counterfactual-based methods should be used.

A Longitudinal Study of Family Functioning in Offspring of Parents Diagnosed With Bipolar Disorder.

OBJECTIVE: To compare the longitudinal course of family functioning in offspring of parents with bipolar disorder (BD), offspring of parents with non-BD psychopathology, and offspring of healthy control (HC) parents. METHOD: Offspring of parents with BD (256 parents and 481 offspring), parents without BD (82 parents and 162 offspring), and HC parents (88 parents and 175 offspring) 7 to 18 years of age at intake, from the Bipolar Offspring Study (BIOS), were followed for an average of 4.3 years. Family functioning was evaluated using the child- and parent-reported Family Adaptability and Cohesion Scale-II and the Conflict Behavior Questionnaire. The data were analyzed using multivariate multilevel regression, generalized linear estimating equation models, and path analysis. RESULTS: Families of parents with BD and parents with non-BD psychopathology showed lower cohesion and adaptability and higher conflict compared with HC families. There were no significant differences in cohesion and adaptability between families of parents with psychopathology. The effect of parental psychopathology on family functioning was mediated by parental psychosocial functioning and, to a lesser extent, offspring disorders. In all 3 groups, parent-reported family conflict was significantly higher than child-reported conflict. Across groups, family cohesion decreased over follow-up, whereas conflict increased. CONCLUSION: Any parental psychopathology predicted family impairment. These results were influenced by the offspring's age and were mediated by parental psychosocial functioning and, to a lesser degree, by offspring psychopathology. These findings emphasize the need to routinely assess family functioning in addition to psychopathology and provide appropriate interventions to parents and offspring.

Intrinsic functional connectivity correlates of person-level risk for bipolar disorder in offspring of affected parents.

Offspring of parents with bipolar disorder (OBP) are at increased risk to develop bipolar disorder (BD). Alterations in resting-state functional connectivity (rsFC) have been identified in OBP; however, replication has been limited and correlation with person-level risk is unknown. A recent study found reduced rsFC between left inferior frontal gyrus (IFG) and clusters in the left insula (LINS), lentiform nucleus (LENT), and midcingulate cortex (MCING) in OBP (Roberts et al. 2017); here, we aim to extend these findings to at-risk youth. We scanned a subset of the Pittsburgh Bipolar Offspring Study, a longitudinal study of OBP and community controls. Twenty-four OBP, 20 offspring of control parents with non-bipolar psychopathology (OCP), and 27 healthy controls (HC) had acceptable rsFC data. After preprocessing steps, we assessed group differences in seed-based rsFC between the IFG and target clusters (LINS, LENT, MCING) using multivariate regression. Next, we tested whether rsFC correlated with person-level risk score and with other dimensional measures. We did not find group differences in rsFC between IFG and target regions. Within OBP, risk score negatively correlated with IFG-LINS rsFC (p = 0.002). Across groups, mood lability correlated negatively with rsFC between IFG and target regions (p = 0.0002), due to negative correlation with IFG-LINS (p = 0.0003) and IFG-MCING (p = 0.001) rsFC. While group-level differences were not replicated, IFG-LINS rsFC was negatively correlated with a person-level risk score in OBP and with mood lability (a predictor of BD) across the sample. Thus, IFG-LINS rsFC might constitute a risk marker, within OBP, for the development of BD.