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.

[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.

Sleep and circadian rhythms as possible trait markers of suicide attempt in bipolar disorders: An actigraphy study.

BACKGROUND: The poor prognostic of Bipolar disorders (BD) is closely linked to deaths by suicide. Sleep and circadian abnormalities are observed during all phases of BD and are also associated with suicide attempt (SA). In this context, this study sought to identify specific sleep and circadian rhythms markers associated with suicidal attempt in euthymic patients with BD. METHODS: The sample (N = 236) comprised 3 groups: 147 patients with BD including 57 with a history of SA and 90 without (NoSA), and 89 healthy controls (HC). All participants were recorded during 21 days with actigraphy. RESULTS: SA was associated with women gender (p = 0.03), familial history of SA (p = 0.03), mixed episodes (p = 0.001), and benzodiazepines (p = 0.019). SA, compared to noSA, had a morning phase preference (p = 0.04), and were more vigorous on the circadian type inventory (p = 0.04), and tended to suffer more from insomnia (45% versus 25% respectively, p = 0.10). SA was also associated with an earlier onset of daily activity assessed with actigraphy (M10 onset: p = 0.01). Backward stepwise linear regression indicated that a combination of four variables (Gender, vigour, insomnia, M10onset) significantly differentiated patients with SA from NoSA (p = 0.03). LIMITATIONS: Cross-sectional design, and no examination of suicidal behaviors' subgroups such as first attempters or repeaters, or violent suicide attempt. CONCLUSIONS: Woman gender, vigorous circadian type, insomnia and an earlier daily activity appeared independently associated with SA in BD. If these biomarkers are confirmed in prospective studies, they should be screened and used to prevent suicide, with the development of personal and targeted chronobiological treatments.

Does childhood experience of attention-deficit hyperactivity disorder symptoms increase sleep/wake cycle disturbances as measured with actigraphy in adult patients with bipolar disorder?

Childhood attention-deficit hyperactivity disorder (ADHD) is a common precursor of adult bipolar disorders (BD). Furthermore, actigraphy studies demonstrate that each disorder may be associated with abnormalities in sleep and activity patterns. This study investigates whether the presence or absence of self-reported childhood experiences of ADHD symptoms is associated with different sleep and activity patterns in adults with BD. A sample of 115 euthymic adult patients with BD was assessed for childhood ADHD symptoms using the Wender Utah Rating Scale (WURS) and then completed 21 days of actigraphy monitoring. Actigraphic measures of sleep quantity and variability and daytime activity were compared between BD groups classified as ADHD+ (n = 24) or ADHD- (n = 91), defined according to established cutoff scores for the WURS; then we examined any associations between sleep-wake cycle parameters and ADHD dimensions (using the continuous score on the WURS). Neither approach revealed any statistically significant associations between actigraphy parameters and childhood ADHD categories or dimensions. We conclude that the sleep and activity patterns of adult patients with BD do not differ according to their self-reported history of ADHD symptoms. We discuss the implications of these findings and suggest how future studies might confirm or refute our findings.

Technologies for implementation of quality assurance in the clinical laboratory.

To face the rapid evolution of the clinical laboratory activity from sample analysis towards an in-vitro diagnostic network, a Total Quality Management system must be implemented by laboratory professionals. Technological advances make it possible to introduce new tools and techniques for many issues surrounding the analytical process, as has happened for analysis automation and laboratory management. Preanalytical steps should benefit from extended traceability, using new identification devices such as electronic labels. This may promote the improvement of sample handling in this phase, such as during transportation or centrifugation. Another field is the expansion of metrology. Many factors can now easily be controlled in the clinical laboratory. New reliable automated systems are available to evaluate the performance of pipetting devices. Autonomous miniaturized recorders and probes connected to monitoring softwares allow traceable temperature monitoring. In this paper, some examples are presented to illustrate how technical solutions can support the implementation of Quality Assurance in the clinical laboratory.

New tools for laboratory design and management.

The clinical laboratory is changing from a place of activity based on sample analysis to an in vitro diagnostic network. To convince our team, partners, and administrators, we need new comprehensive tools to define a strategy with limited risk of failure or conflicts. Specific quality goals should be established before choosing automated tools for sample handling, analytical systems, laboratory information systems, communication systems, or advanced technologies. A system approach maps and simplifies the process, based more on a functional study than on classical disciplines. A customer-supplier approach establishes the requirements between partners either inside or outside the laboratory. The quality system must be a management tool, linking samples, tasks, information, and documents. Quantitative simulation modeling explores different automation alternatives and their impact on laboratory workflow. Finally, integration of results in interactive semirealistic simulation tools for laboratory design or reengineering can be used as communications tools to involve laboratory professionals in the change of their practice.