Seasonal pattern in bipolar disorders and cardio-vascular risk factors: A study from the FACE-BD cohort

PM2.5 and PM10 air pollution peaks are associated with emergency department visits for psychotic and mood disorders

Particulate matters with a diameter of less than 10 µm (PM10) or less than 2.5 µm (PM2.5) are major air pollutants. Their relationship to psychiatric disorders has not yet been extensively studied. We aimed to explore the relationship between PM10 and PM2.5 air pollution peaks and the daily number of emergency visits for psychotic and mood disorders. Clinical data were collected from the Emergency Department of a Paris suburb (Créteil, France) from 2008 to 2018. Air pollution data were measured by the Paris region air quality network (Airparif) and collected from public databases. Pollution peak periods were defined as days for which the daily mean level of PM was above nationally predefined warning thresholds (20 µg/m3 for PM2.5, and 50 µg/m3 for PM10), and the 6 following days. Multivariable analyses compared the number of daily visits for psychotic and mood (unipolar and bipolar) disorders according to pollution peak, using negative binomial regression. After adjustment on meteorological variables (temperature, humidity, amount of sunshine in minutes), the daily number of emergency visits for psychotic disorders was significantly higher during PM2.5 and PM10 air pollution peak periods; while the number of visits for unipolar depressive disorders was higher only during PM10 peak periods (β = 0.059, p-value = 0.034). There were no significant differences between peak and non-peak periods for bipolar disorders. Differences in the effects of PM air pollution on psychotic and mood disorders should be analyzed in further studies.

Neurovascular alterations in bipolar disorder: A review of perfusion weighted magnetic resonance imaging studies

BACKGROUND

Bipolar Disorder (BD) is a severe chronic psychiatric disorder whose aetiology is still largely unknown. However, increasing literature reported the involvement of neurovascular factors in the pathophysiology of BD, suggesting that a measure of Cerebral Blood Flow (CBF) could be an important biomarker of the illness. Therefore, since, to date, Magnetic Resonance Perfusion Weighted Imaging (PWI) techniques, such as Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labelling (ASL), are the most common approaches that allow non-invasive in-vivo perfusion measurements,this review aims to summarize the results from all PWI studies that evaluated the CBF in BD.

METHODS

A bibliographic search in PubMed up until May 2021 was performed. 16 PWI studies that used DSC or ASL sequences met our inclusion criteria.

RESULTS

Overall, the results supported the presence of hyper-perfusion in the cingulate cortex and fronto-temporal regions, as well as the presence of hypo-perfusion in the cerebellum in BD, compared with both healthy controls and patients with unipolar depression. CBF changes after cognitive and aerobic training, as well as in relation with other physiological, clinical, and neurocognitive variables were also reported.

LIMITATIONS

The heterogeneity across the studies, in terms of experimental designs, sample selection, and methodological approach employed, limited the studies' comparison.

CONCLUSIONS

These findings showed CBF alterations in the cingulate cortex, fronto-temporal regions, and cerebellum in BD, suggesting that CBF may be an important pathophysiological marker of BD that merits further investigation to clarify the extent of neurovascular alterations.

The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.

Key findings on bipolar disorders from the longitudinal FondaMental Advanced Center of Expertise-Bipolar Disorder (FACE-BD) cohort

BACKGROUND

The FACE-BD cohort is an observational cohort of individuals with bipolar disorders (BD) who benefited from a systematic evaluation with evidence-based treatment recommendations and who were followed-up every year for 3 years in France. The objectives were to describe the lifetime course of BD, associated psychiatric and somatic comorbidities, and cognition profile. This cohort aims to identify clinical/biological signatures of outcomes, trajectories of functioning and transition between clinical stages. This article summarizes 10 years of findings of the FACE-BD cohort.

METHOD & RESULTS

We included 4422 individuals, all having a baseline assessment, among which 61.2% had at least one follow-up visit at either one, two or three years. A subsample of 1200 individuals had at least one biological sample (serum, plasma, DNA). Assessments include family history of psychiatric disorders, psychiatric diagnosis, current mood symptoms, functioning, hospitalizations, suicidal attempts, physical health, routine blood tests, treatment history, psychological dimensions, medico-economic data and a cognitive assessment. Studies from this cohort illustrate that individuals with BD display multiple coexistent psychiatric associated conditions including sleep disturbances, anxiety disorders, substance use disorders and suicide attempts as well as a high prevalence of metabolic syndrome. During follow-up, we observed a 55% reduction of the number of days of hospitalization and a significant improvement in functioning.

CONCLUSIONS

The FACE-BD cohort provides a strong research infrastructure for clinical research in BD and has a unique position among international cohorts because of its comprehensive clinical assessment and sustainable funding from the French Ministry of Health.

Prevalence and psychiatric comorbidities of night-eating behavior in obese bariatric patients: preliminary evidence for a connection between night-eating and bipolar spectrum disorders

PURPOSE

The co-occurrence of obesity, eating and mood disorders has been frequently reported in clinical and epidemiological settings. This study aimed to explore the prevalence of night-eating obese patients referred for bariatric surgery and to identify associated psychopathology and psychiatric comorbidity.

METHODS

The sample was composed of 121 obese patients consecutively enrolled between November 2010 and May 2012 during psychiatric evaluations for bariatric intervention. Clinical features and psychiatric diagnoses were collected. Night-eating was investigated through the administration of the Night-eating Questionnaires (NEQ) and was defined as the presence of self-reported evening hyperphagia and/or nocturnal ingestions. Binge-eating and purging behaviors and general psychopathology were respectively assessed using the Bulimic Investigatory Test, Edinburgh and the Symptom Checklist-90-Revised.

RESULTS

Night-eating was reported by twenty subjects (16.5%). Patients with night-eating behavior were significantly more frequently diagnosed with bipolar spectrum disorders and with comorbid eating and mood disorders in comparison with other patients. Night-eating patients showed significantly more binging/purging behaviors and greater severity of somatization, obsessive-compulsive symptoms, phobic anxiety, psychoticism and sleep disorders. Patients with bipolar disorder type 1 or 2 scored significantly higher than those without mood disorders at NEQ total score, mood/sleep and nocturnal ingestions subscales, but also scored significantly higher than other patients with mood disorders at the latter subscale.

CONCLUSION

Patients with evening hyperphagia and/or nocturnal ingestions should be carefully evaluated to detect possible bipolar spectrum disorders and other eating disorders. Prompt management of these conditions should be provided before bariatric interventions.

LEVEL OF EVIDENCE

V, cross-sectional descriptive study.

Validity and Usage of the Seasonal Pattern Assessment Questionnaire (SPAQ) in a French Population of Patients with Depression, Bipolar Disorders and Controls

The Seasonal Pattern Assessment Questionnaire (SPAQ), by Rosenthal et al. (1984), is by far the most used questionnaire to evaluate seasonal effects on mood and behavior. It includes a general seasonality score (GSS), composed of 6 items, from which cutoffs have been established to screen for seasonal affective disorder (SAD). However, it has never been validated in French and associations with circadian rhythm and symptoms of depression and bipolarity remain unclear. In this study, including 165 subjects (95 controls and 70 patients with depression or bipolar disorder), we confirmed the validity of the French version of the SPAQ, with a two-factor structure (a psychological factor: energy, mood, social activity and sleep length; and a food factor: weight and appetite) and a good fit was observed by all indicators. Mood and social activity dimensions were significantly affected by seasons in the depressed/bipolar group and a stronger global seasonality score (GSS) was associated with more severe phenotypes of depression and mania. Subjects meeting SAD and subsyndromal-SAD criteria also showed a delayed circadian rhythm compared to controls. Simple tools, such as the SPAQ, can aid the identification of significant seasonal changes and have direct implications on therapeutics including the use of bright light therapy in order to enhance personalized treatments, but also to prevent adverse seasonal effects.

Clinical characteristics of obstructive sleep apnea in bipolar disorders

BACKGROUND

Obstructive sleep apnea (OSA) is one of the leading non-psychiatric comorbidities in bipolar disorders (BD). We sought to explore associations between risk of OSA in BD, clinical characteristics alongside with both subjective sleep complaints and objective sleep abnormalities.

METHODS

Euthymic patients with BD (n = 144) were assessed over a three-week period, by actigraphy, clinical interviews and questionnaires.

RESULTS

Of the study sample, 32 (22%) individuals were at high risk of OSA (HR-OSA) and 112 (78%) had a low risk (LR-OSA), as assessed with the Berlin questionnaire. HR-OSA, compared to LR-OSA, were older (p = 0.031), had higher BMI (p < 0.0005), larger neck circumference (p = 0.002), and more residual depressive symptoms (p < 0.0005). HR-OSA was also associated with greater sleepiness (p = 0.003), poorer sleep quality (p = 0.003), insomnia complaints (p = 0.027), "languid" chronotype (p = 0.002), and higher actigraphy-derived fragmentation index (p = 0.015). Backward stepwise linear regression retained BMI and depressive symptoms (correct classification of 83% of participants). Classification increased up to 85.4% when adding sleepiness and languid-vigorous scales and up to 87.8% when adding fragmentation index. Combining ROC curve analysis and Youden Index provided best cut-offs (HR-OSA if cut-off greater than or equal to) of 29.84 for BMI (Sensibility(Se) = 0.47, Specificity(Spe) = 0.96) and 1.5 for MADRS total score (Se = 0.84, Spe = 0.58).

LIMITATIONS

No confirmation of OSA diagnosis with polysomnography.

CONCLUSIONS

Higher BMI and residual depressive symptoms are the two best independent predictors of OSA in BD. Such information contributes to improving the screening and management of OSA in BD.

TRIAL NUMBER

NCT02627404.

Metabolic syndrome and actigraphy measures of sleep and circadian rhythms in bipolar disorders during remission

OBJECTIVE

This study explored the correlations between sleep and circadian rhythm measures and the metabolic syndrome (MetS) components in remitted patients with bipolar disorder (BD).

METHOD

Euthymic patients with BD (n = 67) were recorded by 3 weeks with actigraphy. We used nonparametric correlations to study the links between the MetS parameters, atherogenic index of plasma (AIP), sleep efficacy, sleep latency, fragmentation index, and phase and amplitude of rhythms. We performed multivariable analyses to take into account potential confounding factors such as sleep apnea risk, antipsychotics use, and smoker status.

RESULTS

We found correlations between lower sleep efficiency and higher triglyceride levels (P = 0.002), lower M10 onset (beginning of the 10 most active hours during the 24-h cycle) and higher systolic blood pressure (P = 0.03), higher fragmentation index and higher systolic blood pressure (P = 0.009), lower sleep efficiency, higher fragmentation index, and higher AIP (respectively P = 0.02 and P = 0.04). These correlations mostly remained significant when adjusting for confounders, with the exception of M10 onset and systolic blood pressure.

CONCLUSION

Sleep efficiency and fragmentation index might contribute to the cardiovascular risk of patients with BD independently of major confounding factors. Although these associations did not imply causality, proposing interventions on sleep quality and circadian rhythm regularity might contribute to reduce cardiovascular risk in patients with BD.