Incidence and predictors of metabolic syndrome onset in individuals with bipolar disorders: A longitudinal study from the FACE-BD cohort.

INTRODUCTION: Metabolic syndrome (MetS) is a cluster of components including abdominal obesity, hyperglycemia, hypertension, and dyslipidemia. MetS is highly prevalent in individuals with bipolar disorders (BD) with an estimated global rate of 32.6%. Longitudinal data on incident MetS in BD are scarce and based on small sample size. The objectives of this study were to estimate the incidence of MetS in a large longitudinal cohort of 1521 individuals with BD and to identify clinical and biological predictors of incident MetS. METHODS: Participants were recruited from the FondaMental Advanced Center of Expertise for Bipolar Disorder (FACE-BD) cohort and followed-up for 3 years. MetS was defined according to the International Diabetes Federation criteria. Individuals without MetS at baseline but with MetS during follow-up were considered as having incident MetS. A logistic regression model was performed to estimate the adjusted odds ratio and its corresponding 95% confidence interval (CI) for an association between each factor and incident MetS during follow-up. We applied inverse probability-of-censoring weighting method to minimize selection bias due to loss during follow-up. RESULTS: Among individuals without MetS at baseline (n = 1521), 19.3% developed MetS during follow-up. Multivariable analyses showed that incident MetS during follow-up was significantly associated with male sex (OR = 2.2, 95% CI = 1.7-3.0, p < 0.0001), older age (OR = 2.14, 95% CI = 1.40-3.25, p = 0.0004), presence of a mood recurrence during follow-up (OR = 1.91, 95% CI = 1.22-3.00, p = 0.0049), prolonged exposure to second-generation antipsychotics (OR = 1.56, 95% CI = 0.99, 2.45, p = 0.0534), smoking status at baseline (OR = 1.30, 95% CI = 1.00-1.68), lifetime alcohol use disorders (OR = 1.33, 95% CI = 0.98-1.79), and baseline sleep disturbances (OR = 1.04, 95% CI = 1.00-1.08), independently of the associations observed for baseline MetS components. CONCLUSION: We observed a high incidence of MetS during a 3 years follow-up (19.3%) in individuals with BD. Identification of predictive factors should help the development of early interventions to prevent or treat early MetS.

Functioning and neurocognition in very early and early-life onset bipolar disorders: the moderating role of bipolar disorder type.

Defining homogeneous subgroups of bipolar disorder (BD) is a major goal in personalized psychiatry and research. According to the neurodevelopmental theory, age at onset may be a key variable. As potential trait markers of neurodevelopment, cognitive and functional impairment should be greater in the early form of the disease, particularly type 1 BD (BD I). The age at onset was assessed in a multicenter, observational sample of 4190 outpatients with BD. We used a battery of neuropsychological tests to assess six domains of cognition. Functioning was measured using the Functioning Assessment Short Test (FAST). We studied the potential moderation of the type of BD on the associations between the age at onset and cognitive and functioning in a subsample of 2072 euthymic participants, controlling for potential clinical and socio-demographic covariates. Multivariable analyses showed cognition to not be impaired in individuals with early (21-30 years) and very early-life (before 14 years) onset of BD. Functioning was equivalent between individuals with early and midlife-onset of BD II and NOS but better for individuals with early onset of BD I. In contrast, functioning was not worse in individuals with very early-onset BD I but worse in those with very early-onset BD II and NOS. Early-life onset BDs were not characterized by poorer cognition and functioning. Our results do not support the neurodevelopmental view that a worse cognitive prognosis characterizes early-life onset BD. This study suggests that functional remediation may be prioritized for individuals with midlife-onset BD I and very early life onset BD 2 and NOS.

Can network analysis shed light on predictors of lithium response in bipolar I disorder?

OBJECTIVE: To undertake a large-scale clinical study of predictors of lithium (Li) response in bipolar I disorder (BD-I) and apply contemporary multivariate approaches to account for inter-relationships between putative predictors. METHODS: We used network analysis to estimate the number and strength of connections between potential predictors of good Li response (measured by a new scoring algorithm for the Retrospective Assessment of Response to Lithium Scale) in 900 individuals with BD-I recruited to the Consortium of Lithium Genetics. RESULTS: After accounting for co-associations between potential predictors, the most important factors associated with the good Li response phenotype were panic disorder, manic predominant polarity, manic first episode, age at onset between 15-32 years and family history of BD. Factors most strongly linked to poor outcome were comorbid obsessive-compulsive disorder, alcohol and/or substance misuse, and/or psychosis (symptoms or syndromes). CONCLUSIONS: Network analysis can offer important additional insights to prospective studies of predictors of Li treatment outcomes. It appears to especially help in further clarifying the role of family history of BD (i.e. its direct and indirect associations) and highlighting the positive and negative associations of different subtypes of anxiety disorders with Li response, particularly the little-known negative association between Li response and obsessive-compulsive disorder.

[Health professionals facing the coronavirus disease 2019 (COVID-19) pandemic: What are the mental health risks?] / Les professionnels de santé face à la pandémie de la maladie à coronavirus (COVID-19) : quels risques pour leur santé mentale ?

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has caused major sanitary crisis worldwide. Half of the world has been placed in quarantine. In France, this large-scale health crisis urgently triggered the restructuring and reorganization of health service delivery to support emergency services, medical intensive care units and continuing care units. Health professionals mobilized all their resources to provide emergency aid in a general climate of uncertainty. Concerns about the mental health, psychological adjustment, and recovery of health care workers treating and caring for patients with COVID-19 are now arising. The goal of the present article is to provide up-to-date information on potential mental health risks associated with exposure of health professionals to the COVID-19 pandemic. METHODS: Authors performed a narrative review identifying relevant results in the scientific and medical literature considering previous epidemics of 2003 (SARS-CoV-1) and 2009 (H1N1) with the more recent data about the COVID-19 pandemic. We highlighted most relevant data concerning the disease characteristics, the organizational factors and personal factors that may contribute to developing psychological distress and other mental health symptoms. RESULTS: The disease characteristics of the current COVID-19 pandemic provoked a generalized climate of wariness and uncertainty, particularly among health professionals, due to a range of causes such as the rapid spread of COVID-19, the severity of symptoms it can cause in a segment of infected individuals, the lack of knowledge of the disease, and deaths among health professionals. Stress may also be caused by organizational factors, such as depletion of personal protection equipment, concerns about not being able to provide competent care if deployed to new area, concerns about rapidly changing information, lack of access to up-to-date information and communication, lack of specific drugs, the shortage of ventilators and intensive care unit beds necessary to care for the surge of critically ill patients, and significant change in their daily social and family life. Further risk factors have been identified, including feelings of being inadequately supported, concerns about health of self, fear of taking home infection to family members or others, and not having rapid access to testing through occupational health if needed, being isolated, feelings of uncertainty and social stigmatization, overwhelming workload, or insecure attachment. Additionally, we discussed positive social and organizational factors that contribute to enhance resilience in the face of the pandemic. There is a consensus in all the relevant literature that health care professionals are at an increased risk of high levels of stress, anxiety, depression, burnout, addiction and post-traumatic stress disorder, which could have long-term psychological implications. CONCLUSIONS: In the long run, this tragic health crisis should significantly enhance our understanding of the mental health risk factors among the health care professionals facing the COVID-19 pandemic. Reporting information such as this is essential to plan future prevention strategies. Protecting health care professionals is indeed an important component of public health measures to address large-scale health crisis. Thus, interventions to promote mental well-being in health care professionals exposed to COVID-19 need to be immediately implemented, and to strengthen prevention and response strategies by training health care professionals on mental help and crisis management.

Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression.

The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.

Which actigraphic variables optimally characterize the sleep-wake cycle of individuals with bipolar disorders?

OBJECTIVE: To examine which combination of objectively measured actigraphy parameters best characterizes the sleep-wake cycle of euthymic individuals with bipolar disorder (BD) compared with healthy controls (HC). METHODS: Sixty-one BD cases and 61 matched HC undertook 21 consecutive days of actigraphy. Groups were compared using discriminant function analyses (DFA) that explored dimensions derived from mean values of sleep parameters (Model 1); variability of sleep parameters (2); daytime activity (3); and combined sleep and activity parameters (4). Exploratory within-group analyses examined characteristics associated with misclassification. RESULTS: After controlling for depressive symptoms, the combined model (4) correctly classified 75% cases, while the sleep models (1 and 2) correctly classified 87% controls. The area under the curve favored the combined model (0.86). Age was significantly associated with misclassification among HC, while a diagnosis of BD-II was associated with an increased risk of misclassifications of cases. CONCLUSION: Including sleep variability and activity parameters alongside measures of sleep quantity improves the characterization of cases of euthymic BD and helps distinguish them from HC. If replicated, the findings indicate that traditional approaches to actigraphy (examining mean values for the standard set of sleep parameters) may represent a suboptimal approach to understanding sleep-wake cycles in BD.

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.

HLA genetics in bipolar disorder.

OBJECTIVE: Bipolar Disorder (BD) is characterized by deregulated adaptive immune processes. Recent genome-wide association studies (GWAS) implicate the major histocompatibility complex (MHC) region in BD. The present study investigates the potential influence of variations in human leukocyte antigen (HLA) on BD risk and/or clinical presentations. This may have relevance to the dysregulated inflammatory processes commonly found in BD. METHOD: DNAs from 475 BD patients and 195 healthy controls (HC) were genotyped for classical HLA class I and II loci. RESULTS: We found that: (i) the HLA-A*02~B*44~DRB1*07 sub-haplotype is less prevalent in BD, vs. HC (pc = 2.4 × 10-2 ); (ii) the 57.1 and the 8.1-derived ancestral haplotypes i.e. HLA-A*02~B*57~Cw*06~DRB1*07~DQB1*09 and HLA-A*02~B*08~Cw*07 are associated with rapid cycling (pc = 1.9 × 10-3 and 1.05 × 10-2 , respectively); (iii) the 8.1AH-derived HLA class II-DRB*03~HLA-DQB1*02 sub-haplotype is more frequent in BD patients with a history of suicidal behaviors (pc = 2.1 × 10-2 ); and (iv) disease onset by an hypomanic episode or by psychotic symptoms are, respectively, more frequent in BD patients bearing the 7.1 AH-derived A*03~B*07~DRB1*15 sub-haplotype (pc = 8.5 × 10-3 ) and the HLA-A*02~B*07~DRB1*15 sub-haplotype (pc = 4.0 × 10-2 ). CONCLUSION: Corroborating the established link between these HLA haplotypes/sub haplotypes and common immune disorders, our findings suggest possible HLA-mediated proinflammatory processes operating in BD.

Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach.

OBJECTIVE: Remitted bipolar disorder (BD) patients frequently present with chronic mood instability and emotional hyper-reactivity, associated with poor psychosocial functioning and low-grade inflammation. We investigated emotional hyper-reactivity as a dimension for characterization of remitted BD patients, and clinical and biological factors for identifying those with and without emotional hyper-reactivity. METHOD: A total of 635 adult remitted BD patients, evaluated in the French Network of Bipolar Expert Centers from 2010-2015, were assessed for emotional reactivity using the Multidimensional Assessment of Thymic States. Machine learning algorithms were used on clinical and biological variables to enhance characterization of patients. RESULTS: After adjustment, patients with emotional hyper-reactivity (n = 306) had significantly higher levels of systolic and diastolic blood pressure (P < 1.0 × 10-8 ), high-sensitivity C-reactive protein (P < 1.0 × 10-8 ), fasting glucose (P < 2.23 × 10-6 ), glycated hemoglobin (P = 0.0008) and suicide attempts (P = 1.4 × 10-8 ). Using models of combined clinical and biological factors for distinguishing BD patients with and without emotional hyper-reactivity, the strongest predictors were: systolic and diastolic blood pressure, fasting glucose, C-reactive protein and number of suicide attempts. This predictive model identified patients with emotional hyper-reactivity with 84.9% accuracy. CONCLUSION: The assessment of emotional hyper-reactivity in remitted BD patients is clinically relevant, particularly for identifying those at higher risk of cardiometabolic dysfunction, chronic inflammation, and suicide.

Affective lability mediates the association between childhood trauma and suicide attempts, mixed episodes and co-morbid anxiety disorders in bipolar disorders.

BACKGROUND: Many studies have shown associations between a history of childhood trauma and more severe or complex clinical features of bipolar disorders (BD), including suicide attempts and earlier illness onset. However, the psychopathological mechanisms underlying these associations are still unknown. Here, we investigated whether affective lability mediates the relationship between childhood trauma and the severe clinical features of BD. METHOD: A total of 342 participants with BD were recruited from France and Norway. Diagnosis and clinical characteristics were assessed using the Diagnostic Interview for Genetic Studies (DIGS) or the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I). Affective lability was measured using the short form of the Affective Lability Scale (ALS-SF). A history of childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Mediation analyses were performed using the SPSS process macro. RESULTS: Using the mediation model and covariation for the lifetime number of major mood episodes, affective lability was found to statistically mediate the relationship between childhood trauma experiences and several clinical variables, including suicide attempts, mixed episodes and anxiety disorders. No significant mediation effects were found for rapid cycling or age at onset. CONCLUSIONS: Our data suggest that affective lability may represent a psychological dimension that mediates the association between childhood traumatic experiences and the risk of a more severe or complex clinical expression of BD.

A re-examination of antidepressant treatment-emergent mania in bipolar disorders: evidence of gender differences.

OBJECTIVE: To explore the prevalence and clinical profile of males and females who develop antidepressant treatment-emergent mania (ATEM). METHOD: From an original sample of 754 patients with BD, we identified ATEM+ cases (n = 75) and ATEM- controls (n = 135) that met stringent criteria. We specifically examined the combinations of clinical factors that best classified males and females as ATEM+ cases. RESULTS: Seventy-five individuals were classified as ATEM+; 87% of ATEM events occurred during antidepressant monotherapy. Regression analyses demonstrated that the presence of an alcohol and/or substance use disorder [Odds Ratio (OR) 6.37], a history of one or more suicide attempts (OR 4.19) and higher number of depressive episodes per year of illness (OR 1.71) correctly classified 73% of males. In contrast, 84% of females were correctly classified on the basis of a positive history of thyroid disorder (OR 3.23), a positive family history of BD I (OR 2.68) and depressive onset polarity (OR 2.01). CONCLUSION: Using stringent definitions of ATEM status to reduce the probability of inclusion of false-positive cases and false-negative controls, we identified for the first time that the risk profiles for the development of an ATEM differ significantly according to gender.

Childhood trauma and mixed episodes are associated with poor response to lithium in bipolar disorders.

OBJECTIVES: Reliable predictors of response to lithium are still lacking in bipolar disorders (BDs). However, childhood trauma has been hypothesized to be associated with poor response to lithium. METHODS: We included 148 patients with BD, euthymic when retrospectively and clinically assessed for response to lithium and childhood trauma using reliable scales. RESULTS: According to the 'Alda scale', the sample consisted in 20.3% of excellent responders, 49.3% of partial responders and 30.4% of non-responders to lithium. A higher level of physical abuse significantly correlated with a lower level of response to lithium (P = 0.009). As compared to patients not exposed to any abuse, patients with at least two trauma abuses (emotional, physical or sexual) were more at risk of belonging to the non-responders group (OR = 4.91 95% CI (1.01-27.02)). Among investigated clinical variables, lifetime presence of mixed episodes and alcohol misuse were associated with non-response to lithium. Multivariate analyses demonstrated that physical abuse and mixed episodes were independently associated with poor response to lithium (P = 0.005 and P = 0.013 respectively). CONCLUSIONS: Childhood physical abuse might be involved in a poor future response to lithium prophylaxis, this effect being independent of the association between clinical expression of BD and poor response to lithium.

Affect lability predicts occurrence of suicidal ideation in bipolar patients: a two-year prospective study.

OBJECTIVE: The aim of our study was to investigate, in bipolar patients, whether affect lability was associated with suicidal ideation incidence during 2-year follow-up, and which subtype of affect lability was associated with suicidal ideation. METHOD: A total of 319 euthymic or mildly depressed bipolar outpatients recruited in the French FondaMental Advanced Centres of Expertise for Bipolar Disorder were divided into two subgroups according to the occurrence of suicidal ideation during a 2-year follow-up. Affect lability was assessed by the French version of the Affect Lability Scale. RESULTS: Bipolar patients with high affect lability were more likely to report suicidal ideation during follow-up, even after adjustment for age, study level, rapid cycling, current depression level, anxiety disorder, and lifetime history SA (OR = 2.47; 95% CI [1.15-5.30], P = 0.01). The risk of suicidal ideation increased with the level of affect lability. More specifically, the propensity to switch from neutral to elation affect, from anxious to depressive affect (or inversely), and from neutral to anger affect predicted suicidal ideation. CONCLUSION: Reducing affective lability could become a new therapeutic target of suicidal prevention in bipolar disorder.

Solar insolation in springtime influences age of onset of bipolar I disorder.

OBJECTIVE: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. METHOD: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. RESULTS: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). CONCLUSION: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.

[Antibiomania: Think of the manic syndrome secondary to antibiotic therapy]. / Antibiomania : penser au syndrome maniaque secondaire à une antibiothérapie.

INTRODUCTION: Antibiomania is characterized by the emergence of a manic episode in reaction to antibiotics. Although relatively uncommon, this kind of side effect is observed in a growing number of cases and mostly occurs in patients who do not have a history of bipolar disorder. Several dozen cases have been reported showing the onset of manic symptoms after taking antibiotics. The antibiotic most frequently involved is clarithromycin. CLINICAL CASE: We report the case of a 61-year-old patient who presented a manic episode after taking an antibiotic combination to treat Helicobacter pylori. Five days after the start of highly active antiretroviral therapy (HAART), behavioral problems appeared (aggressiveness, irritability, talkativeness, insomnia). At the time of hospitalization, she had an acute delusional symptomatology, with a theme of persecution, associated with intuitive, interpretive and imaginative mechanisms. Manic symptoms were obvious: psychomotor excitement, aggressiveness and irritability, flight of ideas, verbal disinhibition and a denial of problems. There was no toxic cause. Brain magnetic resonance imaging (MRI) was normal. Her condition improved very quickly and delusions disappeared in four days. Mrs. H. could critic her delirium and recovered a euthymic state. During hospitalization, treatment divalproate sodium was introduced (250mg, 3 times a day), was maintained following hospital discharge for 2 years for prevention, and then decreased to the stop. There are currently no further behavioral problems or sleep disorders two years after this episode. DISCUSSION: Facing this clinical case, several questions arise: Which drug therapy is the most suitable for this type of mental disorder? Are there predictors of antibiomania? Is there a risk of recurrence of mood episodes following an antibiomania that occurs spontaneously? What are the pathophysiological mechanisms that could explain this reaction? In all cases identified, stopping the antibiotics was decisive. However, the introduction of a psychotropic and the duration of this treatment remain unclear. First, longitudinal follow-up would assess this variable. Second, it is unclear whether the presence of personal psychiatric history is a predictor of antibiomania. Finally, there are several hypotheses to explain antibiomania: the competitive effect of GABAergic inhibitory receptors, seizure-like phenomena that mimic psychiatric symptoms, and disruption of the intestinal microbiota by antibiotics leading to a modification of the functioning of the central nervous system. The explanatory model of antibiomania is not yet known and requires further research.

[How to characterize and treat sleep complaints in bipolar disorders?] / Comment caractériser et traiter les plaintes de sommeil dans les troubles bipolaires ?

OBJECTIVES: Sleep complaints are very common in bipolar disorders (BD) both during acute phases (manic and depressive episodes) and remission (about 80 % of patients with remitted BD have poor sleep quality). Sleep complaints during remission are of particular importance since they are associated with more mood relapses and worse outcomes. In this context, this review discusses the characterization and treatment of sleep complaints in BD. METHODS: We examined the international scientific literature in June 2016 and performed a literature search with PubMed electronic database using the following headings: "bipolar disorder" and ("sleep" or "insomnia" or "hypersomnia" or "circadian" or "apnoea" or "apnea" or "restless legs"). RESULTS: Patients with BD suffer from sleep and circadian rhythm abnormalities during major depressive episodes (insomnia or hypersomnia, nightmares, nocturnal and/or early awakenings, non-restorative sleep) and manic episodes (insomnia, decreased need for sleep without fatigue), but also some of these abnormalities may persist during remission. These remission phases are characterized by a reduced quality and quantity of sleep, with a longer sleep duration, increased sleep latency, a lengthening of the wake time after sleep onset (WASO), a decrease of sleep efficiency, and greater variability in sleep/wake rhythms. Patients also present frequent sleep comorbidities: chronic insomnia, sleepiness, sleep phase delay syndrome, obstructive sleep apnea/hypopnea syndrome (OSAHS), and restless legs syndrome (RLS). These disorders are insufficiently diagnosed and treated whereas they are associated with mood relapses, treatment resistance, affect cognitive global functioning, reduce the quality of life, and contribute to weight gain or metabolic syndrome. Sleep and circadian rhythm abnormalities have been also associated with suicidal behaviors. Therefore, a clinical exploration with characterization of these abnormalities and disorders is essential. This exploration should be helped by questionnaires and documented on sleep diaries or even actimetric objective measures. Explorations such as ventilatory polygraphy, polysomnography or a more comprehensive assessment in a sleep laboratory may be required to complete the diagnostic assessment. Treatments obviously depend on the cause identified through assessment procedures. Treatment of chronic insomnia is primarily based on non-drug techniques (by restructuring behavior and sleep patterns), on psychotherapy (cognitive behavioral therapy for insomnia [CBT-I]; relaxation; interpersonal and social rhythm therapy [IPSRT]; etc.), and if necessary with hypnotics during less than four weeks. Specific treatments are needed in phase delay syndrome, OSAHS, or other more rare sleep disorders. CONCLUSIONS: BD are defined by several sleep and circadian rhythm abnormalities during all phases of the disorder. These abnormalities and disorders, especially during remitted phases, should be characterized and diagnosed to reduce mood relapses, treatment resistance and improve BD outcomes.

Using admixture analysis to examine birth-cohort effects on age at onset of bipolar disorder.

OBJECTIVE: It is suggested that age at onset (AAO) of bipolar I disorder (BP-I) is decreasing. We tested for a birth-cohort effect on AAO using admixture analysis. METHOD: A clinical sample of 3896 BP-I cases was analysed using two approaches: (i) in a subsample with untruncated AAO × birth year distribution (n = 1865), we compared the best-fitting model for the observed AAO in patients born ≤1960 and >1960, (ii) to control for potential confounders, two separate subsamples born ≤1960 and >1960 were matched for age at interview (n = 250), and a further admixture analysis was undertaken. RESULTS: The two approaches indicated that the proportion of cases in the early AAO category was significantly greater in cases born >1960; manic onsets were also more frequent in the early onset BP-I cases born >1960. CONCLUSION: The decrease in AAO of BP-I in recent birth-cohorts appears to be associated with an increase in the proportion of cases in the early onset subgroup; not with a decrease in the mean AAO in each putative subgroup. This could indicate temporal changes in exposure to risk factors for mania.

[Metabolic syndrome and bipolar disorder: Is sleep the missing link?] / Syndrome métabolique et troubles bipolaires : le sommeil est-il le chaînon manquant ?

OBJECTIVE: To examine the pathophysiologic mechanisms that may link circadian disorder and metabolic syndrome in bipolar disorder (BP). METHOD: A systematic review of the literature was conducted from January 2013 to January 2015, using the Medline and Cochrane databases, using the keywords "metabolic syndrome", "obesity", "leptin" and "circadian disorders", "sleeping disorders" and cross-referencing them with "bipolar disorder". The following types of publications were candidates for review: (i) clinical trials; (ii) studies involving patients diagnosed with bipolar disorder; (iii) studies involving patients with sleeping disorder; or (iv) data about metabolic syndrome. RESULTS: Forty articles were selected. The prevalence of metabolic syndrome in BP was significantly higher compared to the general population (from 36 to 49% in the USA [Vancampfort, 2013]), and could be explained by several factors including reduced exercise and poor diet, genetic vulnerability, frequent depressive episodes, psychiatric comorbidity and psychotropic treatment. This high frequency of metabolic syndrome worsens the prognosis of these patients, increasing morbidity and mortality. Secondly, patients with BP experienced circadian and sleep disturbance, including modification in melatonin secretion. These perturbations are known to persist in periods of mood stabilization and are found in patients' relatives. Circadian disturbances are factors of relapse in bipolar patients, and they may also have a role in the metabolic comorbidities of these patients. Recent studies show that in populations of patients with bipolar disorder, a correlation between circadian disturbance and metabolic parameters are found. To identify the pathophysiological pathway connecting both could lead to a better comprehension of the disease and new therapeutics. In the overall population, mechanisms have been identified linking circadian and metabolic disorder involving hormones like leptin and ghrelin. These hormones are keys to regulation of energy balance in the organism, via their action on the hypothalamus, and are also regulated by sleep. We have hypothesized that these pathways could be implicated in the vulnerability of bipolar patients to metabolic syndrome. This hypothesis is supported by several studies showing dysregulation in leptin and ghrelin secretion in multiple psychiatric disorders, including bipolar disorder, as well as genetic variations of leptin and ghrelin genes in these diseases. We also assume that other mechanisms may be at stake to explain this link, such as melatonin dysregulation and inflammation. CONCLUSIONS: Circadian and sleeping disorder may have a role in the prevalence of metabolic syndrome in BP. Hormones like leptin and ghrelin could be the link between these perturbations. Prevention and treatment of circadian disorder in BP may greatly reduce the occurrence of MetS in these patients. Being aware of this statement and taking care of these troubles should be a big step forward for treatment of BP.

Allelic differences between Europeans and Chinese for CREB1 SNPs and their implications in gene expression regulation, hippocampal structure and function, and bipolar disorder susceptibility.

Bipolar disorder (BD) is a polygenic disorder that shares substantial genetic risk factors with major depressive disorder (MDD). Genetic analyses have reported numerous BD susceptibility genes, while some variants, such as single-nucleotide polymorphisms (SNPs) in CACNA1C have been successfully replicated, many others have not and subsequently their effects on the intermediate phenotypes cannot be verified. Here, we studied the MDD-related gene CREB1 in a set of independent BD sample groups of European ancestry (a total of 64,888 subjects) and identified multiple SNPs significantly associated with BD (the most significant being SNP rs6785[A], P=6.32 × 10(-5), odds ratio (OR)=1.090). Risk SNPs were then subjected to further analyses in healthy Europeans for intermediate phenotypes of BD, including hippocampal volume, hippocampal function and cognitive performance. Our results showed that the risk SNPs were significantly associated with hippocampal volume and hippocampal function, with the risk alleles showing a decreased hippocampal volume and diminished activation of the left hippocampus, adding further evidence for their involvement in BD susceptibility. We also found the risk SNPs were strongly associated with CREB1 expression in lymphoblastoid cells (P<0.005) and the prefrontal cortex (P<1.0 × 10(-6)). Remarkably, population genetic analysis indicated that CREB1 displayed striking differences in allele frequencies between continental populations, and the risk alleles were completely absent in East Asian populations. We demonstrated that the regional prevalence of the CREB1 risk alleles in Europeans is likely caused by genetic hitchhiking due to natural selection acting on a nearby gene. Our results suggest that differential population histories due to natural selection on regional populations may lead to genetic heterogeneity of susceptibility to complex diseases, such as BD, and explain inconsistencies in detecting the genetic markers of these diseases among different ethnic populations.

Common variant at 16p11.2 conferring risk of psychosis.

Epidemiological and genetic data support the notion that schizophrenia and bipolar disorder share genetic risk factors. In our previous genome-wide association study, meta-analysis and follow-up (totaling as many as 18 206 cases and 42 536 controls), we identified four loci showing genome-wide significant association with schizophrenia. Here we consider a mixed schizophrenia and bipolar disorder (psychosis) phenotype (addition of 7469 bipolar disorder cases, 1535 schizophrenia cases, 333 other psychosis cases, 808 unaffected family members and 46 160 controls). Combined analysis reveals a novel variant at 16p11.2 showing genome-wide significant association (rs4583255[T]; odds ratio=1.08; P=6.6 × 10(-11)). The new variant is located within a 593-kb region that substantially increases risk of psychosis when duplicated. In line with the association of the duplication with reduced body mass index (BMI), rs4583255[T] is also associated with lower BMI (P=0.0039 in the public GIANT consortium data set; P=0.00047 in 22 651 additional Icelanders).