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Importance: Predicting the onset of bipolar disorder (BD) could facilitate preventive treatments. Among risk measures, bipolar at-risk (BAR) criteria have shown promise in predicting onset of bipolar disorder in the first year in clinical cohorts; however, it is not known whether BAR criteria are associated with the onset of BD in the longer term., Objective: To assess the association of BAR criteria with onset of BD over 10 to 13 years follow-up., Design, Setting, and Participants: This prospective cohort study, completed between May 1, 2020, and November 7, 2022, included consenting people seeking help for nonpsychotic major mental health difficulties, including mood, personality, and substance use disorders, who were originally recruited at ages 15 to 25 years from a tertiary youth mental health setting in metropolitan Melbourne, Victoria, Australia, from May 1, 2008, to September 30, 2010., Exposure: Meeting BAR criteria at baseline. Criteria included subthreshold mania, cyclothymic features, subthreshold depression, and family history of BD. A matched clinical comparison group was recruited from the same help-seeking population., Main Outcomes and Measures: The primary outcome was expert consensus diagnosis of BD I or II based on the Mini International Neuropsychiatric Interview, self-reported information collected through online assessments, and linked data on mental health service utilization in Victoria over 10 to 13 years of follow-up., Results: Among 69 eligible participants, follow-up data were available for 60 (88.2%). The mean (SD) age at the end of follow-up was 32.9 (2.8) years, and 49 (81.7%) were women. A total of 28 participants met BAR criteria, and 32 were in the comparison group. In the BAR group, 8 patients (28.6%) developed BD over a mean (SD) of 11.1 (0.7) years of follow-up, and no patients in the comparison group developed BD. The risk of developing BD was higher in the BAR group than in the non-BAR group (χ21 = 70.0; P < .001). The proportions of transitions to BD were equal in the first and second halves of the follow-up period., Conclusions and Relevance: In this cohort study of participants seeking care for mental health difficulties, patients meeting the BAR criteria were significantly more likely to transition to BD over a decade after ascertainment compared with patients not meeting the BAR criteria. The findings suggest that those meeting BAR criteria may benefit from longer-term monitoring and support. Evaluation of predictive properties in longer-term studies using a risk measure will help with implementation of BAR criteria in clinical settings.

Mood disturbances seen in first-episode mania (FEM) are linked to disturbed functional connectivity of the striatum. Lithium and quetiapine are effective treatments for mania but their neurobiological effects remain largely unknown. We conducted a single-blinded randomized controlled maintenance trial in 61 FEM patients and 30 healthy controls. Patients were stabilized for a minimum of 2 weeks on lithium plus quetiapine then randomly assigned to either lithium (serum level 0.6 mmol/L) or quetiapine (dosed up to 800 mg/day) treatment for 12 months. Resting-state fMRI was acquired at baseline, 3 months (patient only) and 12 months. The effects of treatment group, time and their interaction, on striatal functional connectivity were assessed using voxel-wise general linear modelling. At baseline, FEM patients showed reduced connectivity in the dorsal (p = 0.05) and caudal (p = 0.008) cortico-striatal systems when compared to healthy controls at baseline. FEM patients also showed increased connectivity in a circuit linking the ventral striatum with the medial orbitofrontal cortex, cerebellum and thalamus (p = 0.02). Longitudinally, we found a significant interaction between time and treatment group, such that lithium was more rapid, compared to quetiapine, in normalizing abnormally increased functional connectivity, as assessed at 3-month and 12-month follow-ups. The results suggest that FEM is associated with reduced connectivity in dorsal and caudal corticostriatal systems, as well as increased functional connectivity of ventral striatal systems. Lithium appears to act more rapidly than quetiapine in normalizing hyperconnectivity of the ventral striatum with the cerebellum. The study was registered on the Australian and New Zealand Clinical Trials Registry (ACTRN12607000639426). http://www.anzctr.org.au.

Lithium and quetiapine are effective treatments for bipolar disorder, but their potential neuroprotective effects in humans remain unclear. A single blinded equivalence randomized controlled maintenance trial was conducted in a prospective cohort of first-episode mania (FEM) patients (n=26) to longitudinally compare the putative protective effects of lithium and quetapine on grey and white matter volume. A healthy control sample was also collected (n=20). Using structural MRI scans, voxel-wise grey and white matter volumes at baseline and changes over time in response to treatment were investigated. Patients were assessed at three time points (baseline, 3 and 12-month follow-up), whereas healthy controls were assessed at two time points (baseline and 12-month follow-up). Patients were randomized to lithium (serum level 0.6 mmol l -1 , n=20) or quetiapine (flexibly dosed up to 800 mg per day, n=19) monotherapy. At baseline, compared with healthy control subjects, patients with FEM showed reduced grey matter in the orbitofrontal cortex, anterior cingulate, inferior frontal gyrus and cerebellum. In addition, patients had reduced internal capsule white matter volume bilaterally (t 1,66 >3.20, P<0.01). Longitudinally, there was a significant treatment × time effect only in the white matter of the left internal capsule (F 2,112 =8.54, P<0.01). Post hoc testing showed that, compared with baseline, lithium was more effective than quetiapine in slowing the progression of white matter volume reduction after 12 months (t 1,24 =3.76, P<0.01). Our data support the role of lithium but not quetiapine therapy in limiting white matter reduction early in the illness course after FEM.

Current criteria identifying patients with ultra-high risk of psychosis (UHR) have low specificity, and less than one-third of UHR cases experience transition to psychosis within 3 years of initial assessment. We explored whether a Bayesian probabilistic multimodal model, combining baseline historical and clinical risk factors with biomarkers (oxidative stress, cell membrane fatty acids, resting quantitative electroencephalography (qEEG)), could improve this specificity. We analyzed data of a UHR cohort (n=40) with a 1-year transition rate of 28%. Positive and negative likelihood ratios were calculated for predictor variables with statistically significant receiver operating characteristic curves (ROCs), which excluded oxidative stress markers and qEEG parameters as significant predictors of transition. We clustered significant variables into historical (history of drug use), clinical (Positive and Negative Symptoms Scale positive, negative and general scores and Global Assessment of Function) and biomarker (total omega-3, nervonic acid) groups, and calculated the post-test probability of transition for each group and for group combinations using the odds ratio form of Bayes' rule. Combination of the three variable groups vastly improved the specificity of prediction (area under ROC=0.919, sensitivity=72.73%, specificity=96.43%). In this sample, our model identified over 70% of UHR patients who transitioned within 1 year, compared with 28% identified by standard UHR criteria. The model classified 77% of cases as very high or low risk (P>0.9, <0.1) based on history and clinical assessment, suggesting that a staged approach could be most efficient, reserving fatty-acid markers for 23% of cases remaining at intermediate probability following bedside interview.