Circadian dimension and severity of depression

Structural white matter connectivity differences independent of gray matter loss in mild cognitive impairment with neuropsychiatric symptoms: Early indicators of Alzheimer's disease using network-based statistics

BACKGROUND

Depression and circadian rhythm disruptions are non-cognitive neuropsychiatric symptoms (NPS) that can appear at any stage of the Alzheimer's disease (AD) continuum. Evidence suggests that NPS are linked to AD pathophysiology and hippocampal dysfunction.

OBJECTIVE

To examine structural white matter (WM) connectivity and its association with gray matter (GM) atrophy and to identify specific AD-related neural networks linked to NPS in individuals with mild cognitive impairment (MCI).

METHODS

Ninety-six older adults participants were divided into three groups based on the Global Depression Scale, Neuropsychiatric Inventory, Clinical Dementia Rating, and Mini-Mental Status Examination. Twelve individuals with MCI and NPS (MCI+) and 49 without NPS (MCI-) were classified, along with 35 age and gender-matched healthy individuals. Voxel-based morphometry and tract-based spatial statistics were employed to identify structural and microstructural alterations. Network-based statistics analyzed structural WM connectivity differences between MCI groups and healthy controls.

RESULTS

Significant structural WM connectivity and GM loss were exclusively observed in MCI+ individuals compared to controls. The hippocampus, amygdala, and sensory cortex showed GM atrophy (p < 0.05), while the thalamus, pallidum, putamen, caudate, hippocampus, and sensory and frontal cortices exhibited structural WM connectivity loss (p < 0.01). These data indicate early limbic system involvement even without GM atrophy.

CONCLUSIONS

Structural WM connectivity loss within the Papez circuit may precede and potentially predict GM atrophy in the temporal lobe of individuals with MCI+. These findings highlight the importance of investigating structural WM alterations in the prodromal phase of AD, which may inform diagnostic and therapeutic strategies in early AD.

Insights into the Effect of Light Pollution on Mental Health: Focus on Affective Disorders-A Narrative Review

The presence of artificial light at night has emerged as an anthropogenic stressor in recent years. Various sources of light pollution have been shown to affect circadian physiology with serious consequences for metabolic pathways, possibly disrupting pineal melatonin production with multiple adverse health effects. The suppression of melatonin at night may also affect human mental health and contribute to the development or exacerbation of psychiatric disorders in vulnerable individuals. Due to the high burden of circadian disruption in affective disorders, it has been hypothesized that light pollution impacts mental health, mainly affecting mood regulation. Hence, the aim of this review was to critically summarize the evidence on the effects of light pollution on mood symptoms, with a particular focus on the role of circadian rhythms in mediating this relationship. We conducted a narrative review of the literature in the PubMed, Scopus, and Web of Science datasets. After the screening process, eighteen papers were eligible for inclusion. The results clearly indicate a link between light pollution and the development of affective symptoms, with a central role of sleep disturbances in the emergence of mood alterations. Risk perception also represents a crucial topic, possibly modulating the development of affective symptoms in response to light pollution. The results of this review should encourage a multidisciplinary approach to the design of healthier environments, including lighting conditions among the key determinants of human mental health.

Risk for Seasonal Affective Disorder (SAD) Linked to Circadian Clock Gene Variants

Molecular pathways affecting mood are associated with circadian clock gene variants and are influenced, in part, by the circadian clock, but the molecular mechanisms underlying this link are poorly understood. We use machine learning and statistical analyses to determine the circadian gene variants and clinical features most highly associated with symptoms of seasonality and seasonal affective disorder (SAD) in a deeply phenotyped population sample. We report sex-specific clock gene effects on seasonality and SAD symptoms; genotypic combinations of CLOCK3111/ZBTB20 and PER2/PER3B were significant genetic risk factors for males, and CRY2/PER3C and CRY2/PER3-VNTR were significant risk factors for females. Anxiety, eveningness, and increasing age were significant clinical risk factors for seasonality and SAD for females. Protective factors for SAD symptoms (in females only) included single gene variants: CRY1-GG and PER3-VNTR-4,5. Clock gene effects were partially or fully mediated by diurnal preference or chronotype, suggesting multiple indirect effects of clock genes on seasonality symptoms. Interestingly, protective effects of CRY1-GG, PER3-VNTR-4,5, and ZBTB20 genotypes on seasonality and depression were not mediated by chronotype, suggesting some clock variants have direct effects on depressive symptoms related to SAD. Our results support previous links between CRY2, PER2, and ZBTB20 genes and identify novel links for CLOCK and PER3 with symptoms of seasonality and SAD. Our findings reinforce the sex-specific nature of circadian clock influences on seasonality and SAD and underscore the multiple pathways by which clock variants affect downstream mood pathways via direct and indirect mechanisms.

Role and mechanism of PVN-sympathetic-adipose circuit in depression and insulin resistance induced by chronic stress

Chronic stress induces depression and insulin resistance, between which there is a bidirectional relationship. However, the mechanisms underlying this comorbidity remain unclear. White adipose tissue (WAT), innervated by sympathetic nerves, serves as a central node in the interorgan crosstalk through adipokines. Abnormal secretion of adipokines is involved in mood disorders and metabolic morbidities. We describe here a brain-sympathetic nerve-adipose circuit originating in the hypothalamic paraventricular nucleus (PVN) with a role in depression and insulin resistance induced by chronic stress. PVN neurons are labelled after inoculation of pseudorabies virus (PRV) into WAT and are activated under restraint stress. Chemogenetic manipulations suggest a role for the PVN in depression and insulin resistance. Chronic stress increases the sympathetic innervation of WAT and downregulates several antidepressant and insulin-sensitizing adipokines, including leptin, adiponectin, Angptl4 and Sfrp5. Chronic activation of the PVN has similar effects. β-adrenergic receptors translate sympathetic tone into an adipose response, inducing downregulation of those adipokines and depressive-like behaviours and insulin resistance. We finally show that AP-1 has a role in the regulation of adipokine expression under chronic stress.

Association between depression and risk of type 2 diabetes and its sociodemographic factors modifications: A prospective cohort study in southwest China

BACKGROUND

Depression may be associated with the risk of developing type 2 diabetes. The goal of this study was to explore the association of severe of depression with the risk of type 2 diabetes in adults in Guizhou, China.

METHODS

A 10-year prospective cohort study of 7158 nondiabetes adults aged 18 years or older was conducted in Guizhou, southwest China from 2010 to 2020. The Patient Health Questionnaire-9 (PHQ-9) was used to measure the prevalence of depression. Cox proportional hazard models were used to estimated hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression and incident type 2 diabetes. A quantile regression (QR) analytical approach were applied to evaluate the associations of PHQ-9 score with plasma glucose values.

RESULTS

A total of 739 type 2 diabetes cases were identified during a median follow-up of 6.59 years. The HR (95% CI) per 1-SD increase for baseline PHQ-9 score was 1.051 (1.021, 1.082) after multivariable adjustment. Compared with participants without depression, those with mild or more advanced depression had a higher risk of incident type 2 diabetes (HR:1.440 [95% CI, 1.095, 1.894]). Associations between depression with type 2 diabetes were suggested to be even stronger among women or participants aged ≥45 years (p < .05). There are significant positive associations of PHQ-9 score with 2-h oral glucose tolerance test blood glucose levels.

CONCLUSION

Depression significantly increased the risk of incident type 2 diabetes, especially in women, participants aged ≥45 years, Han ethnicity, and urban residents. These findings highlighted the importance and urgency of depression health care.

Increased Aperiodic Neural Activity During Sleep in Major Depressive Disorder

Background

In major depressive disorder (MDD), patients often express subjective sleep complaints, while polysomnographic studies report only subtle alterations of the electroencephalographic signal. We hypothesize that differentiating the signal into its oscillatory and aperiodic components may bring new insights into our understanding of sleep abnormalities in MDD. Specifically, we investigated aperiodic neural activity during sleep and its relationships with sleep architecture, depression severity, and responsivity to antidepressant treatment.

Methods

Polysomnography was recorded in 38 patients with MDD (in unmedicated and 7-day-medicated states) and 38 age-matched healthy control subjects (N= 76). The aperiodic power component was calculated using irregularly resampled auto-spectral analysis. Depression severity was assessed with the Hamilton Depression Rating Scale. We replicated the analysis using 2 independently collected datasets of medicated patients and control subjects (N = 60 and N = 80, respectively).

Results

Unmedicated patients showed flatter aperiodic slopes compared with control subjects during non-rapid eye movement (non-REM) stage 2 sleep (p = .009). Medicated patients showed flatter aperiodic slopes compared with their earlier unmedicated state (p values < .001) and control subjects during all sleep stages (p values < .03). In medicated patients, flatter aperiodic slopes during non-REM sleep were linked to the higher proportion of N1, lower proportion of REM, delayed onset of N3 and REM, and shorter total sleep time.

Conclusions

Flatter slopes of aperiodic electroencephalographic power may reflect noisier neural activity due to increased excitation-to-inhibition balance, representing a new disease-relevant feature of sleep in MDD.

Working Around the Clock: The Association between Shift Work, Sleep Health, and Depressive Symptoms among Midlife Adults

Shift work is an integral part of living in a 24-hour society. However, shift work can disrupt circadian rhythms, negatively impacting health. Guided by the Stress Process Model (SPM), this study examines the association between shift work and depressive symptoms and investigates whether sleep health (duration, quality, and latency) mediates this relationship among midlife adults. Utilizing data from the National Longitudinal Survey of Youth 1979 cohort (N = 6,372), findings show that working evening, night, and irregular shifts is associated with increased depressive symptoms. The results also show that part of the association between shift work and depressive symptoms among night and irregular shift workers, is indirect, operating through short sleep during the week and on the weekend. Although shift work can negatively affect mental health, getting more restorative sleep may mitigate part of the harmful mental health consequences of non-standard work schedules.

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank

BACKGROUND

Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes.

METHODS

Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC).

RESULTS

For MD vs. controls (n_(MD) = 24,229; n_(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67-0.69. Discrimination was reasonable for atypical vs. typical symptoms (n_(atypical) = 958; n_(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71-0.77) but poor for remaining models (AUCs 0.59-0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes.

LIMITATIONS

Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary.

DISCUSSION

Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features.

Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more

INTRODUCTION

Fatigue is the most common and debilitating symptom experienced by cancer patients undergoing chemotherapy (CTX). Prediction of symptom severity can assist clinicians to identify high-risk patients and provide education to decrease symptom severity. The purpose of this study was to predict the severity of morning fatigue in the week following the administration of CTX.

METHODS

Outpatients (n = 1217) completed questionnaires 1 week prior to and 1 week following administration of CTX. Morning fatigue was measured using the Lee Fatigue Scale (LFS). Separate prediction models for morning fatigue severity were created using 157 demographic, clinical, symptom, and psychosocial adjustment characteristics and either morning fatigue scores or individual fatigue item scores. Prediction models were created using two regression and five machine learning approaches.

RESULTS

Elastic net models provided the best fit across all models. For the EN model using individual LFS item scores, two of the 13 individual LFS items (i.e., "worn out," "exhausted") were the strongest predictors.

CONCLUSIONS

This study is the first to use machine learning techniques to accurately predict the severity of morning fatigue from prior to through the week following the administration of CTX using total and individual item scores from the Lee Fatigue Scale (LFS). Our findings suggest that the language used to assess clinical fatigue in oncology patients is important and that two simple questions may be used to predict morning fatigue severity.

Circadian rhythms-related disorders in diurnal fat sand rats under modern lifestyle conditions: A review

Modern lifestyle reduces environmental rhythmicity and may lead to circadian desynchrony. We are exposed to poor day-time lighting indoors and excessive night-time artificial light. We use air-conditioning to reduce ambient temperature cycle, and food is regularly available at all times. These disruptions of daily rhythms may lead to type 2 diabetes mellitus (T2DM), obesity, cardiometabolic diseases (CMD), depression and anxiety, all of which impose major public health and economic burden on societies. Therefore, we need appropriate animal models to gain a better understanding of their etiologic mechanisms, prevention, and management.We argue that the fat sand rat (Psammomys obesus), a diurnal animal model, is most suitable for studying the effects of modern-life conditions. Numerous attributes make it an excellent model to study human health disorders including T2DM, CMD, depression and anxiety. Here we review a comprehensive series of studies we and others conducted, utilizing the fat sand rat to study the underlying interactions between biological rhythms and health. Understanding these interactions will help deciphering the biological basis of these diseases, which often occur concurrently. We found that when kept in the laboratory (compared with natural and semi-wild outdoors conditions where they are diurnal), fat sand rats show low amplitude, nocturnal or arrhythmic activity patterns, dampened daily glucose rhythm, glucose intolerance, obesity and decreased survival rates. Short photoperiod acclimation exacerbates these pathologies and further dampens behavioral and molecular daily rhythms, resulting in CMD, T2DM, obesity, adipocyte dysfunction, cataracts, depression and anxiety. Increasing environmental rhythmicity by morning bright light exposure or by access to running wheels strengthens daily rhythms, and results in higher peak-to-trough difference in activity, better rhythmicity in clock genes expression, lower blood glucose and insulin levels, improved glucose tolerance, lower body and heart weight, and lower anxiety and depression. In summary, we have demonstrated that fat sand rats living under the correspondent of “human modern lifestyle” conditions exhibit dampened behavioral and biological rhythms and develop circadian desynchrony, which leads to what we have named “The Circadian Syndrome”. Environmental manipulations that increase rhythmicity result in improvement or prevention of these pathologies. Similar interventions in human subjects could have the same positive results and further research on this should be undertaken.

Melatonergic Receptors (Mt1/Mt2) as a Potential Additional Target of Novel Drugs for Depression

A complex pathogenesis involving several physiological systems is theorized to underline the development of depressive disorders. Depression is accompanied by circadian regulation disruption and interaction with the functioning of both central and peripheral oscillators. Many aspects of melatonin function unite these systems. The use of drugs for circadian rhythm disorders could inspire a potential treatment strategy for depression. Melatonin plays an essential role in the regulation of circadian rhythms. It exerts effect by activating two types of melatonin receptors, type 1A (MT1) and 1B (MT2). These are G-protein-coupled receptors, predominantly located in the central nervous system. MT1/MT2 agonists could be a useful treatment approach according to all three prevalent theories of the pathogenesis of depression involving either monoamines, synaptic remodeling, or immune/inflammatory events. MT1/MT2 receptors can be a potential target for novel antidepressants with impact on concentrations of neurotrophins or neurotransmitters, and reducing levels of pro-inflammatory cytokines. There is an interesting cross-talk mediated via the physical association of melatonin and serotonin receptors into functional heteromers. The antidepressive and neurogenetic effects of MT1/MT2 agonists can also be caused by the inhibition of the acid sphingomyelinase, leading to reduced ceramide, or increasing monoamine oxidase A levels in the hippocampus. Compounds targeting MT1 and MT2 receptors could have potential for new anti-depressants that may improve the quality of therapeutic interventions in treating depression and relieving symptoms. In particular, a combined effect on MT1 and/or MT2 receptors and neurotransmitter systems may be useful, since the normalization of the circadian rhythm through the melatonergic system will probably contribute to improved treatment. In this review, we discuss melatonergic receptors as a potential additional target for novel drugs for depression.

Biomarkers for Deep Brain Stimulation in Animal Models of Depression

OBJECTIVES

Despite recent advances in depression treatment, many patients still do not respond to serial conventional therapies and are considered "treatment resistant." Deep brain stimulation (DBS) has therapeutic potential in this context. This comprehensive review of recent studies of DBS for depression in animal models identifies potential biomarkers for improving therapeutic efficacy and predictability of conventional DBS to aid future development of closed-loop control of DBS systems.

MATERIALS AND METHODS

A systematic search was performed in Pubmed, EMBASE, and Cochrane Review using relevant keywords. Overall, 56 animal studies satisfied the inclusion criteria.

RESULTS

Outcomes were divided into biochemical/physiological, electrophysiological, and behavioral categories. Promising biomarkers include biochemical assays (in particular, microdialysis and electrochemical measurements), which provide real-time results in awake animals. Electrophysiological tests, showing changes at both the target site and downstream structures, also revealed characteristic changes at several anatomic targets (such as the medial prefrontal cortex and locus coeruleus). However, the substantial range of models and DBS targets limits the ability to draw generalizable conclusions in animal behavioral models.

CONCLUSIONS

Overall, DBS is a promising therapeutic modality for treatment-resistant depression. Different outcomes have been used to assess its efficacy in animal studies. From the review, electrophysiological and biochemical markers appear to offer the greatest potential as biomarkers for depression. However, to develop closed-loop DBS for depression, additional preclinical and clinical studies with a focus on identifying reliable, safe, and effective biomarkers are warranted.

Diurnal mood variation symptoms in major depressive disorder associated with evening chronotype: Evidence from a neuroimaging study

BACKGROUND

Major depressive disorder (MDD) is often accompanied with classic diurnal mood variation (DMV) symptoms. Patients with DMV symptoms feel a mood improvement and prefer activities at dusk or in the evening, which is consistent with the evening chronotype. Their neural alterations are unclear. In this study, we aimed to explore the neuropathological mechanisms underlying the circadian rhythm of mood and the association with chronotype in MDD.

METHODS

A total of 126 depressed patients, including 48 with DMV, 78 without, and 67 age/gender-matched healthy controls (HC) were recruited and underwent a resting-state functional magnetic resonance imaging. Spontaneous neural activity was investigated using amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-based functional connectivity (FC) analyses were conducted. The Morningness-Eveningness Questionnaire (MEQ) was utilized to evaluate participant chronotypes and Pearson correlations were calculated between altered ALFF/FC values and MEQ scores in patients with MDD.

RESULTS

Compared with NMV, DMV group exhibited lower MEQ scores, and increased ALFF values in the right orbital superior frontal gyrus (oSFG). We observed that increased FC between the left suprachiasmatic nucleus (SCN) and supramarginal gyrus (SMG). ALFF in the oSFG and FC of rSCN-SMG were negatively correlated with MEQ scores.

LIMITATION

Some people's chronotypes information is missing.

CONCLUSION

Patients with DMV tended to be evening type and exhibited abnormal brain functions in frontal lobes. The synergistic changes between frontotemporal lobe, SCN-SMG maybe the characteristic of patients with DMV symptoms.

Usability of a Mobile App for Real-Time Assessment of Fatigue and Related Symptoms in Patients With Multiple Sclerosis: Observational Study

Background

Although fatigue is one of the most debilitating symptoms in patients with multiple sclerosis (MS), its pathogenesis is not well understood. Neurogenic, inflammatory, endocrine, and metabolic mechanisms have been proposed. Taking into account the temporal dynamics and comorbid mood symptoms of fatigue may help differentiate fatigue phenotypes. These phenotypes may reflect different pathogeneses and may respond to different mechanism-specific treatments. Although several tools have been developed to assess various symptoms (including fatigue), monitor clinical status, or improve the perceived level of fatigue in patients with MS, options for a detailed, real-time assessment of MS-related fatigue and relevant comorbidities are still limited.

Objective

This study aims to present a novel mobile app specifically designed to differentiate fatigue phenotypes using circadian symptom monitoring and state-of-the-art characterization of MS-related fatigue and its related symptoms. We also aim to report the first findings regarding patient compliance and the relationship between compliance and patient characteristics, including MS disease severity.

Methods

After developing the app, we used it in a prospective study designed to investigate the brain magnetic resonance imaging correlates of MS-related fatigue. In total, 64 patients with MS were recruited into this study and asked to use the app over a 2-week period. The app features the following modules: Visual Analogue Scales (VASs) to assess circadian changes in fatigue, depression, anxiety, and pain; daily sleep diaries (SLDs) to assess sleep habits and quality; and 10 one-time questionnaires to assess fatigue, depression, anxiety, sleepiness, physical activity, and motivation, as well as several other one-time questionnaires that were created to assess those relevant aspects of fatigue that were not captured by existing fatigue questionnaires. The app prompts subjects to assess their symptoms multiple times a day and enables real-time symptom monitoring through a web-accessible portal.

Results

Of 64 patients, 56 (88%) used the app, of which 51 (91%) completed all one-time questionnaires and 47 (84%) completed all one-time questionnaires, VASs, and SLDs. Patients reported no issues with the usage of the app, and there were no technical issues with our web-based data collection system. The relapsing-remitting MS to secondary-progressive MS ratio was significantly higher in patients who completed all one-time questionnaires, VASs, and SLDs than in those who completed all one-time questionnaires but not all VASs and SLDs (P=.01). No other significant differences in demographics, fatigue, or disease severity were observed between the degrees of compliance.

Conclusions

The app can be used with reasonable compliance across patients with relapsing-remitting and secondary-progressive MS irrespective of demographics, fatigue, or disease severity.

The effects of COVID-19 stay-at-home order on sleep, health, and working patterns: a survey study of US health care workers

STUDY OBJECTIVES

By March 2020, COVID-19 forced much of the world to stay at home to reduce the spread of the disease. Whereas some health care workers transitioned to working from home, many continued to report to work in person as essential employees. We sought to explore changes in sleep, health, work, and mood in health care workers during the stay-at-home orders.

METHODS

We developed a cross-sectional online survey administered to health care workers. The survey assessed changes in sleep, work, screen time, media exposure, diet, exercise, substance use, and mood. The survey data were collected between March 28, 2020, and April 29, 2020.

RESULTS

A total of 834 of 936 individuals completed the entire survey. Respondents were from 41 US states. Mood after the stay-at-home orders worsened, and screen time and substance use increased. Total sleep time shortened in those continuing to work in person (P < .001), whereas it was unchanged in those working from home (P = .73). Those working from home went to bed later, woke up later, and worked fewer hours. Reduced total sleep time and increased screen time before bed were associated with worse mood and screen time. Longer sleep time was associated with better mood.

CONCLUSIONS

Health care workers' mood worsened regardless of whether work was in person or remote, although total sleep time was shorter for those working in person. Those working from home may have shifted their sleep time to be more in line with their endogenous circadian phase. Peer or other support services may be indicated to address sleep, mood, and health behaviors among health care workers during these unprecedented times.

Analysis of Differentially Expressed Genes in the Dentate Gyrus and Anterior Cingulate Cortex in a Mouse Model of Depression

Major depressive disorder (MDD) is a prevalent, chronic, and relapse-prone psychiatric disease. However, the intermediate molecules resulting from stress and neurological impairment in different brain regions are still unclear. To clarify the pathological changes in the dentate gyrus (DG) and anterior cingulate cortex (ACC) regions of the MDD brain, which are the most closely related to the disease, we investigated the published microarray profile dataset GSE84183 to identify unpredictable chronic mild stress- (UCMS-) induced differentially expressed genes (DEGs) in the DG and ACC regions. Based on the DEG data, functional annotation, protein-protein interaction, and transcription factor (TF) analyses were performed. In this study, 1071 DEGs (679 upregulated and 392 downregulated) and 410 DEGs (222 upregulated and 188 downregulated) were identified in DG and ACC, respectively. The pathways and GO terms enriched by the DEGs in the DG, such as cell adhesion, proteolysis, ion transport, transmembrane transport, chemical synaptic transmission, immune system processes, response to lipopolysaccharide, and nervous system development, may reveal the molecular mechanism of MDD. However, the DEGs in the ACC involved metabolic processes, proteolysis, visual learning, DNA methylation, innate immune responses, cell migration, and circadian rhythm. Sixteen hub genes in the DG (Fn1, Col1a1, Anxa1, Penk, Ptgs2, Cdh1, Timp1, Vim, Rpl30, Rps21, Dntt, Ptk2b, Jun, Avp, Slit1, and Sema5a) were identified. Eight hub genes in the ACC (Prkcg, Grin1, Syngap1, Rrp9, Grwd1, Pik3r1, Hnrnpc, and Prpf40a) were identified. In addition, eleven TFs (Chd2, Zmiz1, Myb, Etv4, Rela, Tcf4, Tcf12, Chd1, Mef2a, Ubtf, and Mxi1) were predicted to regulate more than two of these hub genes. The expression levels of ten randomly selected hub genes that were specifically differentially expressed in the MDD-like animal model were verified in the corresponding regions in the human brain. These hub genes and TFs may be regarded as potential targets for future MDD treatment strategies, thus aiding in the development of new therapeutic approaches to MDD.

Depression alters the circadian pattern of online activity

Human sleep/wake cycles follow a stable circadian rhythm associated with hormonal, emotional, and cognitive changes. Changes of this cycle are implicated in many mental health concerns. In fact, the bidirectional relation between major depressive disorder and sleep has been well-documented. Despite a clear link between sleep disturbances and subsequent disturbances in mood, it is difficult to determine from self-reported data which specific changes of the sleep/wake cycle play the most important role in this association. Here we observe marked changes of activity cycles in millions of twitter posts of 688 subjects who explicitly stated in unequivocal terms that they had received a (clinical) diagnosis of depression as compared to the activity cycles of a large control group (n = 8791). Rather than a phase-shift, as reported in other work, we find significant changes of activity levels in the evening and before dawn. Compared to the control group, depressed subjects were significantly more active from 7 PM to midnight and less active from 3 to 6 AM. Content analysis of tweets revealed a steady rise in rumination and emotional content from midnight to dawn among depressed individuals. These results suggest that diagnosis and treatment of depression may focus on modifying the timing of activity, reducing rumination, and decreasing social media use at specific hours of the day.

Sleep Quality, Sleep Structure, and PER3 Genotype Mediate Chronotype Effects on Depressive Symptoms in Young Adults

Depression and its related mood disorders are a major global health issue that disproportionately affects young adults. A number of factors that influence depressive symptoms are particularly relevant to the young adult developmental stage, including sleep loss, poor sleep quality, and the tendency toward eveningness in circadian preferences. However, relatively few studies have examined the relationship between sleep and circadian phenotypes, and their respective influences on mood, or considered potential molecular mechanisms driving these associations. Here, we use a multi-year, cross-sectional study of 806 primarily undergraduates to examine the relationships between sleep-wake chronotype, sleep disturbance, depression and genotypes associated with the PER3 variable number of tandom repeats (VNTR) polymorphism-circadian gene variants associated with both chronotype and sleep homeostatic drive. In addition, we use objective, Fitbit-generated sleep structure data on a subset of these participants (n = 67) to examine the relationships between chronotype, depression scores, actual measures of sleep duration, social jetlag, and the percent of deep and rapid eye movement (REM) sleep per night. In this population, chronotype is weakly associated with depressive symptoms and moderately correlated with self-reported sleep disturbance. Sleep disturbance is significantly associated with depression scores, but objective sleep parameters are not directly correlated with Beck Depression Inventory (BDI-II) scores, with the exceptions of a moderate correlation between social jetlag and depression scores in females and a marginal correlation between sleep duration and depression scores. Multiple regression and path analyses reveal that chronotype effects on depressive symptoms in this population are mediated largely by sleep disturbance. The PER3 VNTR genotype significantly predicts depressive symptoms in a model with objective sleep parameters, but it does not significantly predict depressive symptoms in a model with chronotype or subjective sleep disturbance. Interestingly, PER35,5 genotypes, in males only, are independently related to chronotype and depression scores. Our results support hypotheses linking subjective sleep quality and chronotype and provide a first step in understanding how objective sleep structure may be linked to chronotype and depressive symptoms. Our results also suggest that circadian gene variants may show sex-specific effects linking sleep duration and sleep structure to depression.

A Systematic Review and Delphi Study to Ascertain Common Risk Factors for Type 2 Diabetes Mellitus and Dementia and Brain-Related Complications of Diabetes in Adults

OBJECTIVES

Both type 2 diabetes (T2DM) and dementia have multifactorial etiologies. Both are associated with aging and have well-recognized lifestyle, cardiovascular and psychosocial risk factors. However, uncertainty exists in the literature with regard to: 1) the potentially modifiable risk factors common to both dementia and T2DM, and 2) the risk of brain-related complications in those with established diabetes. In this study, we address this uncertainty and inform design of a survey questionnaire to assess knowledge about diabetes and brain health among at-risk groups.

METHODS

This investigation consisted of a mixed-methods approach, including a Delphi consensus study preceded by a systematic literature review. The review was conducted using MEDLINE, EMBASE and Cochrane Library databases. A 2-round online Delphi study, informed by the review, invited international experts to rate their agreement with proposed risk factors and complications.

RESULTS

Of 7,337 abstracts retrieved, 13 were included in the final review. Among 46 international experts invited to take part in the Delphi study, 14 (32%) responded. In the Delphi study, hypertension, obesity, physical inactivity and heavy alcohol consumption reached consensus as risk factors common to both T2DM and dementia. Proposed brain-related diabetes complications, depression and dementia were also identified.

CONCLUSIONS

Results revealed expert consensus and literature review agreement on a number of common modifiable risk factors for T2DM and dementia, as well as agreement on brain-related complications of diabetes. A number of other proposed shared risk factors did not reach consensus agreement, suggesting a need for more high-quality studies to add to the evidence base.

In vivo molecular chronotyping, circadian misalignment, and high rates of depression in young adults

BACKGROUND

Young adults are disproportionately affected by depression and related mental disorders. Circadian misalignment (a phase advance or delay in the body's internal clock timing) is thought to exert adverse effects on downstream physiological processes regulating mood. Circadian disruption may represent an additional, under-appreciated risk factor affecting young adults. Here, we test the hypothesis that depression in young adults is associated with circadian misalignment-the lack of concordance between an individual's endogenous rhythm and their external social and academic environment.

METHODS

We screened 528 individuals for morningness-eveningness diurnal preference and sleep-wake chronotype. We selected individuals with extreme scores (n = 130) for estimation of circadian phase by measuring clock gene mRNA oscillations in hair follicles (a peripheral clock). Using an independent, data-driven cluster analysis, we define the circadian misalignment of both advanced- and delayed-phase individuals from clock gene mRNA expression levels. We compare depression (BDI-II), anxiety (STAI), social jetlag, sleep duration, and sleep disturbance (PROMIS) scores between misaligned individuals and control individuals of intermediate chronotype (n = 173).

RESULTS

We demonstrate that depression scores in young adults are significantly higher in individuals with circadian phase delays and in individuals with a mismatch between circadian behavioral phenotypes and circadian molecular phase. Evening-type individuals with circadian phase delays are 20 times more likely and mismatched individuals are 5-8 times more likely to be depressed than control individuals. Sleep disturbance shows a similar relationship with circadian phenotypes, but the mood effects described in this study are independent of sleep duration, social jetlag and gender.

LIMITATIONS

Our study examined peripheral clock genes that represents a circadian rhythm potentially influenced by both intrinsic and external, environmental factors. Our study population spanned a limited age-group and our results cannot distinguish between cause and effect of circadian, sleep and mood variables.

CONCLUSIONS

Our study validates previous theoretical predictions of circadian effects on mood disorders and highlights a critical, hidden risk factor affecting mood in young adults-circadian disruption.

Molecular basis for the association between depression and circadian rhythm

Depression is a life-threatening psychiatric disorder and a major public health concern worldwide with an incidence of 5% and a lifetime prevalence of 15%-20%. It is related with the social disability, decreased quality of life, and a high incidence of suicide. Along with increased depressive cases, health care cost in treating patients suffering from depression has also surged. Previous evidence have reported that depressed patients often exhibit altered circadian rhythms. Circadian rhythm involves physical, mental, and behavioral changes in a daily cycle, and is controlled by the suprachiasmatic nucleus of the hypothalamus in responding to light and darkness in an environment. Circadian rhythm disturbance in depressive patients causes early morning waking, sleep disturbances, diurnal mood variation, changes of the mean core temperature, endocrine release, and metabolic functions. Many medical interventions have been used to treat depression; however, several adverse effects are noted. This article reviews the types, causes of depression, mechanism of circadian rhythm, and the relationship between circadian rhythm disturbance with depression. Pharmaceutical and alternative interventions used to treat depressed patients are also discussed.

Mood rhythmicity is associated with depressive symptoms and caffeinated drinks consumption in South American young adults

Among the factors that contribute to the onset and maintenance of depressive disorders, rhythmicity of symptoms and consumption of caffeine have recently gained attention. The current study aimed to examine the differential rhythmicity of relevant variables in a sample of young participants, considering the presence of depressive symptomatology and the frequency of caffeinated drinks consumption. A significant 24-hour differential rhythmicity of mood, cognitive and physiological variables was found indicating an evening peak pattern in the participants with depressive symptoms. Interestingly, caffeinated drinks consumption was differentially associated with self-perceived peaks, according to the presence of depressive symptomatology. Our findings are among the first reports about the potential association of the 24-hours rhythmicity of relevant mood-related variables, depressive symptoms, and caffeine intake. These results support the view that the identification of risk factors for depression, and the application of novel measurements and analysis methods in the development of new preventive strategies should be a public health priority.

Modeling Strengthens Molecular Link between Circadian Polymorphisms and Major Mood Disorders

Anxiety and other mood disorders, such as major depressive disorder (MDD) and seasonal affective disorder (SAD), affect nearly one-fifth of the global population and disproportionately affect young adults. Individuals affected by mood disorders are frequently plagued by sleep and circadian problems, and recent genetic studies provide ample support for the association of circadian and sleep syndromes with depression and anxiety. Mathematical modeling has been crucial in understanding some of the essential features of the mammalian circadian clock and is now a vital tool for dissecting how circadian genes regulate the molecular mechanisms that influence mood. Here, we model the effect of five clock gene polymorphisms, previously linked to mood disorders, on circadian gene expression and, ultimately, on the period length and amplitude of the clock, two parameters that dictate the phase, or alignment, of the clock relative to the environment. We then test whether these gene variants are associated with circadian phenotypes (Horne-Ostberg Morningness-Eveningness scores) and well-established measures of depression (Beck Depression Inventory) and anxiety (State-Trait Anxiety Inventory) in a population of undergraduates ( n = 546). In this population, we find significant allelic and/or genotypic associations between CRY2 and two PER3 variants and diurnal preference. The PER3 length polymorphism (rs57875989) was significantly associated with depression in this sample, and individuals homozygous for the PER3 single nucleotide polymorphism (SNP) (rs228697) reported significantly higher anxiety. Our simple model satisfies available experimental knockdown conditions as well as existing data on clock polymorphisms associated with mood. In addition, our model enables us to predict circadian phenotypes (e.g., altered period length, amplitude) associated with mood disorders in order to identify critical effects of clock gene mutations on CRY/BMAL binding and to predict that the intronic SNPs studied represent gain-of-function mutations, causing increased transcription rate. Given the user-friendly structure of our model, we anticipate that it will be useful for further study of the relationships among clock polymorphisms, circadian misalignment, and mood disorders.

Dendritic cell nuclear protein-1 regulates melatonin biosynthesis by binding to BMAL1 and inhibiting the transcription of N-acetyltransferase in C6 cells

Dendritic cell nuclear protein-1 (DCNP1) is a protein associated with major depression. In the brains of depression patients, DCNP1 is up-regulated. However, how DCNP1 participates in the pathogenesis of major depression remains unknown. In this study, we first transfected HEK293 cells with EGFP-DCNP1 and demonstrated that the full-length DCNP1 protein was localized in the nucleus, and RRK (the residues 117-119) composed its nuclear localization signal (NLS). An RRK-deletion form of DCNP1 (DCNP1ΔRRK) and truncated form (DCNP11-116), each lacking the RRK residues, did not show the specific nuclear localization like full-length DCNP1 in the cells. A rat glioma cell line C6 can synthesize melatonin, a hormone that plays important roles in both sleep and depression. We then revealed that transfection of C6 cells with full-length DCNP1 but not DCNP1ΔRRK or DCNP11-116 significantly decreased the levels of melatonin. Furthermore, overexpression of full-length DCNP1, but not DCNP1ΔRRK or DCNP11-116, in C6 cells significantly decreased both the mRNA and protein levels of N-acetyltransferase (NAT), a key enzyme in melatonin synthesis. Full-length DCNP1 but not DCNP1ΔRRK or DCNP11-116 was detected to interact with the Nat promoter and inhibited its activity through its E-box motif. Furthermore, full-length DCNP1 but not the mutants interacted with and repressed the transcriptional activity of BMAL1, a transcription factor that transactivates Nat through the E-box motif. In conclusion, we have shown that RRK (the residues 117-119) are the NLS responsible for DCNP1 nuclear localization. Nuclear DCNP1 represses NAT expression and melatonin biosynthesis by interacting with BMAL1 and repressing its transcriptional activity. Our study reveals a connection between the major depression candidate protein DCNP1, circadian system and melatonin biosynthesis, which may contribute to the pathogenesis of depression.

Clock-Enhancing Small Molecules and Potential Applications in Chronic Diseases and Aging

Normal physiological functions require a robust biological timer called the circadian clock. When clocks are dysregulated, misaligned, or dampened, pathological consequences ensue, leading to chronic diseases and accelerated aging. An emerging research area is the development of clock-targeting compounds that may serve as drug candidates to correct dysregulated rhythms and hence mitigate disease symptoms and age-related decline. In this review, we first present a concise view of the circadian oscillator, physiological networks, and regulatory mechanisms of circadian amplitude. Given a close association of circadian amplitude dampening and disease progression, clock-enhancing small molecules (CEMs) are of particular interest as candidate chronotherapeutics. A recent proof-of-principle study illustrated that the natural polymethoxylated flavonoid nobiletin directly targets the circadian oscillator and elicits robust metabolic improvements in mice. We describe mood disorders and aging as potential therapeutic targets of CEMs. Future studies of CEMs will shed important insight into the regulation and disease relevance of circadian clocks.

A simple attention test in the acute phase of a major depressive episode is predictive of later functional remission

BACKGROUND

Functional recovery after a major depressive episode (MDE) requires both clinical remission and preservation of cognitive skills. As attentional deficit may persist after remission, leading to functional impairment, its role as a prognosis marker needs to be considered.

METHODS

Five hundred eight depressed outpatients (DSM-IV) were assessed at baseline for clinical symptoms (QIDS-SR), social functioning (Sheehan Disability Scale, SDS) and attention through the d2 test of attention and the trail making test, simple tests, respectively, requiring to quote or to interconnect relevant items. All patients were treated by agomelatine, and examined 6 to 8 weeks after baseline to assess clinical remission (QIDS-SR ≤ 5) and/or functional remission (SDS ≤ 6).

RESULTS

At follow up, 154 patients (31%) were in clinical and functional remission. Shorter cumulative duration of prior depression, shorter present MDE, and two parameters of the d2 test of attention were predictive of such positive outcome, the number of omission mistakes (F1) being the only one still significantly predictive (P < .05) with a multivariate approach. F1 was unchanged after remission, patients with less than 11 mistakes had a 2.27 times increased chance to reach full remission, and a dose-response relationship was observed, with a regular increase of positive outcome for less mistakes.

CONCLUSIONS

The number of omission mistakes (F1) of the d2 test of attention was a stable marker, being predictive of, and with a dose-effect for, clinical plus functional remission. It may constitute a specific marker of attentional deficit, involved in the resilience process that enables individuals to develop more adequate strategies to cope with everyday functional activities.

A rest-activity biomarker to predict response to SSRIs in major depressive disorder

Most adults with Major Depressive Disorder (MDD) will not experience a remission with the first antidepressant trial. No practical biomarkers presently exist to predict responsiveness to antidepressants. Herein we report pilot data for a rest-activity biomarker of antidepressant response. Fifty-eight medication-free adults with MDD underwent a week-long collection of actigraphic data before beginning a 9 week open label trial of fluoxetine, coupled with blinded randomized assignment to eszopiclone/placebo. Depression severity was repeatedly measured with the Hamilton Rating Scale for Depression (HRSD). Baseline actigraphic data was analyzed with functional data analysis to create smoothed 24-h curves of activity. The time of the lowest point of activity (the bathyphase) was calculated for each patient, as well the mean difference between bedtime and the bathyphase (BBD). At the end of treatment, patients were characterized as treatment responders (50% reduction in HRSD) or non-responders, and receiver operating curves were calculated to find the optimal cut point of the BBD for prediction of treatment response. The best cut point for BBD was at 260.2 min, resulting in an effect size of 1.45, and with a positive predictive value of 0.75 and a negative predictive value of 0.88. We conclude that actigraphically-determined measures of rest-activity patterns show promise as potential biomarker predictors of antidepressant response. However, this conclusion is based upon a small number of patients who received only one choice of antidepressant, for a single trial. Replication with a larger sample is needed.

Disruption of running activity rhythm following restricted feeding in female mice: Preventive effects of antidepressants

Biological rhythms are critical in the etiology of mood disorders; therefore, effective mood disorder treatments should address rhythm disturbances. Among the variables synchronized with the light-dark cycle, spontaneous activity in rodents is useful for investigating circadian rhythms. However, previous studies have focused only on the increase of wheel-running activity under restricted feeding conditions, while little information is available on circadian rhythm of running activity. In this study, chronometrical analysis was used to assess whether circadian rhythms during wheel-running are altered by restricted feeding and affected by antidepressant drugs. Wheel revolutions were automatically recorded and analyzed using cosinor-rhythmometry in 8-week old ICR albino mice. When feeding was restricted to 1 h per day (21:00-22:00), wheel-running rhythms were reliably disrupted. Female mice exhibited marked alterations in the pattern and extent of wheel-running beginning on day 1. Subchronic treatment with imipramine or paroxetine, as well as tandospirone and (-)-DOI, prevented wheel-running rhythm disruption. Thus, altering the circadian activity rhythms of female mice on a 1-h feeding schedule may be useful for investigating disturbances in biological rhythms.

CRY1 Variations Impacts on the Depressive Relapse Rate in a Sample of Bipolar Patients

OBJECTIVE

A relevant part of the social and personal burden caused by Bipolar Disorder (BD) is related to depressive phases. Authors investigated the genetic impact of a set of variations located in CRY1, a gene involved in the control of the circadian rhythms, towards depressive episodes in a sample of bipolar patients from the STEP-BD sample. As a secondary analysis, CYR1 variations were analyzed as predictors of sleep disruption.

METHODS

654 bipolar patients were included in the analysis. Data were available genome-wide. The part of the genome coding for the CRY1 was imputed and pruned according to standards in the field. 7 SNPs were available for the analysis. A correction for multitesting was applied and we had sufficient power (0.80) to detect a small-medium effect size (0.22) between two allelic frequencies each one represented by at least 300 subjects.

RESULTS

Intronic rs10861688 was associated with the number of depressive events corrected for the times patients were assessed during the period of observation. In particular, AA subjects (n=21) had 4.46±3.15 events, AG (n=141) had 3.08±3.17 and GG (n=342) 2.65±2.97 (p=0.0048, beta=-0.22). No other significant associations were reported.

CONCLUSION

We bring further evidence that genes involved in the regulation of circadian rhythms may be relevant to depressive bipolar phases. Independent confirmation analyses are mandatory.

Circadian rhythms in cognitive functioning among patients with schizophrenia: impact on signal detection in clinical trials of potential pro-cognitive therapies

OBJECTIVE

Cognition is affected by circadian rhythms over the course of a day. Circadian rhythms in cognitive functioning are driven by a variety of both endogenous and exogenous factors. Patients with schizophrenia are known to have disturbed circadian rhythms that can affect their cognitive functioning. We examined the impact of time of day on cognitive test scores from subjects participating in clinical trials of potential pro-cognitive therapies for schizophrenia and then explored how this diurnal variation affected signal detection.

METHOD

Baseline data from 8 separate schizophrenia clinical trials using the MATRICS Consensus Cognitive Battery (MCCB) were aggregated (Total N=2032). The MCCB assessments were divided into five 2-hour time intervals based on the start-time of the assessments (varying from 8:00 am to 5:59 pm) and then analyzed for differences by time interval. Next, data from two Phase 2 schizophrenia clinical trials of potential pro-cognitive therapies were analyzed to explore the impact of this diurnal variation on placebo separation.

RESULTS

Time of day exerted a significant effect on baseline composite MCCB scores (p=.002). Follow-up comparisons revealed significant differences among multiple temporal epochs. In both Phase 2 clinical trials, subjects whose cognitive functioning was assessed at consistent times of day between their baseline and endpoint visits showed a more robust treatment response as compared to subjects assessed at inconsistent times of day.

CONCLUSION

Cognitive functioning ebbs and flows over the course of the day. Maintaining consistency in the time of day of cognitive test administrations between visits can help to reduce the noise introduced by circadian rhythms, thereby enhancing signal detection in clinical trials of potential pro-cognitive therapies.

NIDDK international conference report on diabetes and depression: current understanding and future directions

Comorbid diabetes and depression are a major clinical challenge as the outcomes of each condition are worsened by the other. This article is based on the presentations and discussions during an international meeting on diabetes and depression convened by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) in collaboration with the National Institute of Mental Health and the Dialogue on Diabetes and Depression. While the psychological burden of diabetes may contribute to depression in some cases, this explanation does not sufficiently explain the relationship between these two conditions. Shared biological and behavioral mechanisms, such as hypothalamic-pituitary-adrenal axis activation, inflammation, autonomic dysfunction, sleep disturbance, inactive lifestyle, poor dietary habits, and environmental and cultural risk factors, are important to consider in understanding the link between depression and diabetes. Both individual psychological and pharmacological depression treatments are effective in people with diabetes, but the current range of treatment options is limited and has shown mixed effects on glycemic outcomes. More research is needed to understand what factors contribute to individual differences in vulnerability, treatment response, and resilience to depression and metabolic disorders across the life course and how best to provide care for people with comorbid diabetes and depression in different health care settings. Training programs are needed to create a cross-disciplinary workforce that can work in different models of care for comorbid conditions.

Diabetes and depression

Diabetes and depression occur together approximately twice as frequently as would be predicted by chance alone. Comorbid diabetes and depression are a major clinical challenge as the outcomes of both conditions are worsened by the other. Although the psychological burden of diabetes may contribute to depression, this explanation does not fully explain the relationship between these 2 conditions. Both conditions may be driven by shared underlying biological and behavioral mechanisms, such as hypothalamic-pituitary-adrenal axis activation, inflammation, sleep disturbance, inactive lifestyle, poor dietary habits, and environmental and cultural risk factors. Depression is frequently missed in people with diabetes despite effective screening tools being available. Both psychological interventions and antidepressants are effective in treating depressive symptoms in people with diabetes but have mixed effects on glycemic control. Clear care pathways involving a multidisciplinary team are needed to obtain optimal medical and psychiatric outcomes for people with comorbid diabetes and depression.

PPP3CC gene: a putative modulator of antidepressant response through the B-cell receptor signaling pathway

Antidepressant pharmacogenetics represents a stimulating, but often discouraging field. The present study proposes a combination of several methodologies across three independent samples. Genes belonging to monoamine, neuroplasticity, circadian rhythm and transcription factor pathways were investigated in two samples (n=369 and 88) with diagnosis of major depression who were treated with antidepressants. Phenotypes were response, remission and treatment-resistant depression. Logistic regression including appropriate covariates was performed. Genes associated with outcomes were investigated in the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) genome-wide study (n=1861). Top genes were further studied through a pathway analysis. In both original samples, markers associated with outcomes were concentrated in the PPP3CC gene. Other interesting findings were particularly in the HTR2A gene in one original sample and the STAR*D. The B-cell receptor signaling pathway proved to be the putative mediator of PPP3CC's effect on antidepressant response (P=0.03). Among innovative candidates, PPP3CC, involved in the regulation of immune system and synaptic plasticity, seems promising for further investigation.

Clinical Implications of Impaired Sleep

Despite its pervasiveness in primary care, deficient sleep often is underappreciated as a cue to other health risks. Accordingly, this review discusses contemporary evidence-based perspectives on impaired sleep and its associations with other lifestyle medicine concerns, including obesity, cardiovascular conditions, psychological problems, and health-compromising habits. The potential clinical benefits of promoting sleep health also will be considered.

Efficacy and tolerability of agomelatine in the treatment of depression

Depression is a severe and usually recurrent mental disorder which often leads to a significant impairment of everyday functioning, a reduced quality of life, and also great suffering of the patients. The treatment of a depressive disorder is not only limited to acute treatment; it also requires prolonged management. Patient compliance is of utmost importance. Unpleasant adverse effects and their impact on everyday living often lead to a premature discontinuation of antidepressant treatment and result in an unfavorable treatment outcome. The new antidepressant agomelatine, a melatonergic MT1/MT2 agonist and 5-HT2C receptor antagonist, has exhibited good antidepressant efficacy in acute, short-term, and long-term treatment. The adverse effect profile of agomelatine has been proven to be favorable and comparable to placebo, which is very important for good treatment compliance and adherence.

The melatonergic system in mood and anxiety disorders and the role of agomelatine: implications for clinical practice

Melatonin exerts its actions through membrane MT1/MT2 melatonin receptors, which belong to the super family of G-protein-coupled receptors consisting of the typical seven transmembrane domains. MT1 and MT2 receptors are expressed in various tissues of the body either as single ones or together. A growing literature suggests that the melatonergic system may be involved in the pathophysiology of mood and anxiety disorders. In fact, some core symptoms of depression show disturbance of the circadian rhythm in their clinical expression, such as diurnal mood and other symptomatic variation, or are closely linked to circadian system functioning, such as sleep-wake cycle alterations. In addition, alterations have been described in the circadian rhythms of several biological markers in depressed patients. Therefore, there is interest in developing antidepressants that have a chronobiotic effect (i.e., treatment of circadian rhythm disorders). As melatonin produces chronobiotic effects, efforts have been aimed at developing agomelatine, an antidepressant with melatonin agonist activity. The present paper reviews the role of the melatonergic system in the pathophysiology of mood and anxiety disorders and the clinical characteristics of agomelatine. Implications of agomelatine in "real world" clinical practice will be also discussed.