Psychiatric evaluation presents a significant challenge because it conceptually integrates the input from multiple psychopathological approaches. Recent technological advances in the study of protein structure, function, and interactions have provided a breakthrough in the diagnosis and treatment of mood disorders (MD), and have identified novel biomarkers to be used as indicators of normal and disease states or response to drug treatment. The investigation of biomarkers for psychiatric disorders, such as enzymes (catechol-O-methyl transferase and monoamine oxidases) or neurotransmitters (dopamine, serotonin, norepinephrine) and their receptors, particularly their involvement in neuroendocrine activity, brain structure, and function, and response to psychotropic drugs, should facilitate the diagnosis of MD. In clinical settings, prognostic biomarkers may be revealed by analyzing serum, saliva, and/or the cerebrospinal fluid, which should promote timely diagnosis and personalized treatment. The mechanisms underlying the activity of most currently used drugs are based on the functional regulation of proteins, including receptors, enzymes, and metabolic factors. In this study, we analyzed recent advances in the identification of biomarkers for MD, which could be used for the timely diagnosis, treatment stratification, and prediction of clinical outcomes.

Volume reduction and shape abnormality of the hippocampus have been associated with mood disorders. However, the hippocampus is not a uniform structure and consists of several subfields, such as the cornu ammonis (CA) subfields CA1-4, the dentate gyrus (DG) including a granule cell layer (GCL) and a molecular layer (ML) that continuously crosses adjacent subiculum (Sub) and CA fields. It is known that cellular and molecular mechanisms associated with mood disorders may be localized to specific hippocampal subfields. Thus, it is necessary to investigate the link between the in vivo hippocampal subfield volumes and specific mood disorders, such as bipolar disorder (BD) and major depressive disorder (MDD). In the present study, we used a state-of-the-art hippocampal segmentation approach, and we found that patients with BD had reduced volumes of hippocampal subfields, specifically in the left CA4, GCL, ML and both sides of the hippocampal tail, compared with healthy subjects and patients with MDD. The volume reduction was especially severe in patients with bipolar I disorder (BD-I). We also demonstrated that hippocampal subfield volume reduction was associated with the progression of the illness. For patients with BD-I, the volumes of the right CA1, ML and Sub decreased as the illness duration increased, and the volumes of both sides of the CA2/3, CA4 and hippocampal tail had negative correlations with the number of manic episodes. These results indicated that among the mood disorders the hippocampal subfields were more affected in BD-I compared with BD-II and MDD, and manic episodes had focused progressive effect on the CA2/3 and CA4 and hippocampal tail.

Lithium remains the mainstay of treatment for patients with bipolar affective disorder; however, nearly half of patients with bipolar disorder fail to respond to lithium. Recently, there have been an increasing number of preliminary clinical reports that clozapine, an atypical antipsychotic agent, has potential efficacy in patients with mood disorders. We review the available clinical data supporting the potential use of clozapine in these psychiatric disorders and report our preliminary data from a study that used clozapine in the acute treatment of mania in treatment-refractory patients. Twenty-five patients meeting the DSM-III-R criteria for the manic phase of either bipolar or schizoaffective disorder entered a 13-week open prospective trial of clozapine. These patients either had failed to respond to or had been intolerant to treatment with lithium, an anticonvulsant, and at least two typical neuroleptics. Eighteen of 25 patients demonstrated a greater than 50% decrease in the Young Mania Rating Scale score. These preliminary data as well as the clinical reports reviewed indicate that the efficacy of clozapine in treatment-resistant patients is not limited to patients with schizophrenia.

Background: Sleep problems in childhood are an early predictor of mood disorders among individuals at high familial risk. However, the majority of the research has focused on sleep disturbances in already diagnosed individuals and has largely neglected investigating potential differences between weeknight and weekend sleep in high-risk offspring. This study examined sleep parameters in offspring of parents with major depressive disorder or bipolar disorder during both weeknights and weekends. Methods: We used actigraphy, sleep diaries, and questionnaires to measure several sleep characteristics in 73 offspring aged 4-19 years: 23 offspring of a parent with major depressive disorder, 22 offspring of a parent with bipolar disorder, and 28 control offspring. Results: Offspring of parents with major depressive disorder slept, on average, 26 min more than control offspring on weeknights (95% confidence interval, 3 to 49 min, p = 0.027). Offspring of parents with bipolar disorder slept, on average, 27 min more on weekends than on weeknights compared to controls, resulting in a significant family history × weekend interaction (95% confidence interval, 7 to 47 min, p = 0.008). Conclusions: Sleep patterns in children and adolescents were related to the psychiatric diagnosis of their parent(s). Future follow-up of these results may clarify the relations between early sleep differences and the risk of developing mood disorders in individuals at high familial risk.

Mood spectrum disorders (bipolar disorder, recurrent depressive disorder and seasonal affective disorder) are accompanied by circadian deregulations, which can occur during acute mood episodes as well as during euthymic periods, and are particularly common among bipolar patients in remission. This suggests that altered circadian rhythms may be biological markers of these disorders. Rhythm dysfunctions have been observed in mood disorder patients by using actigraphic measures and by assessing social metric rhythms, diurnal preferences and melatonin secretion. Since many of these markers are heritable and therefore driven by clock genes, these genes may represent susceptibility factors for mood spectrum disorders. Indeed, several genetic association studies have suggested that certain circadian gene variants play a role in susceptibility to these disorders. Such connections to circadian genes such as CLOCK, ARNTL1, NPAS2, PER3 and NR1D1 have been repeatedly demonstrated for bipolar disorders, and to a lesser extent for recurrent depressive disorders and seasonal affective disorders. The study of circadian phenotypes and circadian genes in mood spectrum disorders represents a major field of research that may yet reveal the pathophysiological determinants of these disorders.

The effects of acetylsalicylic acid (ASA) on mood disorders (MD) and on inflammatory parameters in preclinical and clinical studies have not yet been comprehensively evaluated. The aim of this study was to systematically summarize the available knowledge on this topic according to PRISMA guidelines. Data from preclinical and clinical studies were analyzed, considering the safety and efficacy of ASA in the treatment of MD and the correlation of inflammatory parameters with the effect of ASA treatment. Twenty-one studies were included. Both preclinical and clinical studies found evidence indicating the safety and efficacy of low-dose ASA in the treatment of all types of affective episodes in MD. Observational studies have indicated a reduced risk of all types of affective episodes in chronic low-dose ASA users (HR 0.92, 95% CI: 0.88, 0.95, p < 0.0001). An association between ASA response and inflammatory parameters was found in preclinical studies, but this was not confirmed in clinical trials. Further long-term clinical trials evaluating the safety and efficacy of ASA in recurrent MD, as well as assessing the linkage of ASA treatment with inflammatory phenotype and cytokines, are required. There is also a need for preclinical studies to understand the exact mechanism of action of ASA in MD.

Identification of biomarkers could facilitate earlier diagnosis and better treatment, say Runsen Chen and colleagues

Magnesium (Mg2+) has received considerable attention with regards to its potential role in the pathophysiology of the mood disorders, but the available evidence seems inconclusive.AimsTo review and quantitatively summarise the human literature on Mg2+ intake and Mg2+ blood levels in the mood disorders and the effects of Mg2+ supplements on mood.

The current cross-sectional study investigates the prevalence of the food addiction (FA) phenotype and its association with psychiatric disorders in bariatric surgery candidates. It also investigates the eating behavior characteristics associated with FA and the association between FA and loss of control over specific foods high in sugar, salt and/or fat. We included 128 bariatric surgery candidates and we assessed FA (YFAS 2.0), mood and anxiety disorders, suicidality, eating disorders (current bulimia nervosa and current anorexia nervosa), alcohol and tobacco use disorders (MINI 5.0.0, beck depression inventory, AUDIT, Fagerström Test for Nicotine Dependence) and eating behavior (DEBQ). Prevalence of FA in our sample was 25%. FA was significantly associated with higher prevalence of current mood and anxiety disorders and past mood disorders, higher current suicidality but not with eating disorders and alcohol use disorder. FA was significantly associated with higher emotional eating, and with loss of control over consumption of foods high in fat, sugar and/or salt, but not of fruits, vegetables or grain products. Our results provide arguments for considering psychiatric disorders and suicidality in FA and for considering FA as an addictive disorder in obese patients, with many risk factors in common with other addictions.

Mood disorders, i.e. major depressive disorder (MDD) and bipolar disorders, are leading sources of disability worldwide. Currently available treatments do not yield remission in approximately a third of patients with a mood disorder. This is in part because these treatments do not target a specific core pathology underlying these heterogeneous disorders. In recent years, abnormal inflammatory processes have been identified as putative pathophysiological mechanisms and treatment targets in mood disorders, particularly among individuals with treatment-resistant conditions.

Affective computing (also referred to as artificial emotion intelligence or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate emotion or other affective phenomena. With the rapid growth in the aging population around the world, affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. For late-life depression, affective computing ranging from vocal biomarkers to facial expressions to social media behavioral analysis can be used to address inadequacies of current screening and diagnostic approaches, mitigate loneliness and isolation, provide more personalized treatment approaches, and detect risk of suicide. Similarly, for Alzheimer's disease, eye movement analysis, vocal biomarkers, and driving and behavior can provide objective biomarkers for early identification and monitoring, allow more comprehensive understanding of daily life and disease fluctuations, and facilitate an understanding of behavioral and psychological symptoms such as agitation. To optimize the utility of affective computing while mitigating potential risks and ensure responsible development, ethical development of affective computing applications for late-life mood and cognitive disorders is needed.

Mood disorders affect a significant portion of the general population. Cycling mood disorders are characterized by intermittent episodes (or events) of the disease.

The genetic background of mood disorders is gradually emerging through the use of large multicenter samples but a detailed phenotyping is complementary in elucidating the role of modulating variants.

The chromosome 1p36 region was previously indicated as a locus for susceptibility to recurrent major depressive disorder based on a linkage study in a sample of 497 sib pairs. We investigated the gamma-aminobutyric acid A (GABA(A)) delta receptor subunit gene, GABRD, as a susceptibility gene to childhood-onset mood disorders (COMD) because of substantial evidence implicating GABAergic dysfunction in mood disorders and the position of this gene near the 1p36 linkage region. Using a sample consisting of 645 Hungarian families with a child/adolescent proband diagnosed with a mood disorder with the onset of the first episode before age 15, we found some evidence for the association of two polymorphisms located within the gene, rs2376805 and rs2376803, as well as significant evidence for biased transmission of the haplotypes of these two markers (global chi(2) test for haplotypes = 12.746, 3 df, P = 0.0052). Furthermore, significant evidence of association was only observed in male subjects (n = 438) when the results were analyzed by sex (chi(2) = 9.000 1 df, P = 0.003 for rs2376805). This was in contrast with the previous linkage findings, as LOD scores exceeding 3 were only in female-female pairs in that study. These findings point to the GABRD gene as a susceptibility gene for COMD; however, this gene may not explain the previous linkage finding.

Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior-avoiding social situations for fear of embarrassment, for instance-is a core feature of such anxiety. However, as for many other psychiatric symptoms the biological mechanisms underlying avoidance remain unclear.

Staging of psychiatric disorders is gaining momentum and the purpose of this review is to examine whether major mood disorders can be defined according to stages.

Anxiety is characterized by altered responses under uncertain conditions, but the precise mechanism by which uncertainty changes the behaviour of anxious individuals is unclear. Here we probe the computational basis of learning under uncertainty in healthy individuals and individuals suffering from a mix of mood and anxiety disorders. Participants were asked to choose between four competing slot machines with fluctuating reward and punishment outcomes during safety and stress. We predicted that anxious individuals under stress would learn faster about punishments and exhibit choices that were more affected by those punishments, thus formalizing our predictions as parameters in reinforcement learning accounts of behaviour. Overall, the data suggest that anxious individuals are quicker to update their behaviour in response to negative outcomes (increased punishment learning rates). When treating anxiety, it may therefore be more fruitful to encourage anxious individuals to integrate information over longer horizons when bad things happen, rather than try to blunt their responses to negative outcomes.

Family, twin and epidemiologic studies all point to an important genetic contribution to the risk to develop mood and anxiety disorders. While some progress has been made in identifying relevant pathomechanisms for these disorders, candidate based strategies have often yielded controversial findings. Hopes were thus high when genome-wide genetic association studies became available and affordable and allowed a hypothesis-free approach to study genetic risk factors for these disorders. In an unprecendented scientific collaborative effort, large international consortia formed to allow the analysis of these genome-wide association datasets across thousands of cases and controls ([1] and see also http://www.broadinstitute.org/mpg/ricopili/). Now that large meta-analyses of genome-wide association studies (GWAS) have been published for bipolar disorder and major depression it has become clear that main effects of common variants are difficult to identify in these disorders, suggesting that additional approaches maybe needed to understand the genetic basis of these disorders [2,3].

Worldwide, depression and bipolar disorder affect a large and growing number of people. However, current pharmacotherapy options remain limited. Despite adequate treatment, many patients continue to have subsyndromal symptoms, which predict relapse in bipolar illness and often result in functional impairments. Aspirin, a common nonsteroidal anti-inflammatory drug (NSAID), has purported beneficial effects on mood symptoms, showing protective effects against depression in early cohort studies. This systematic review thus aimed to investigate the role of aspirin in mood disorders. Using the keywords (aspirin or acetylsalicy* or asa) and (mood or depress* or bipolar or mania or suicid*), a comprehensive search of PubMed, EMBASE, Medline, PsycINFO, Clinical Trials Register of the Cochrane Collaboration Depression, Anxiety and Neurosis Group (CCDANTR), Clinicaltrials.gov and Google Scholar databases found 13,952 papers published in English between 1 January 1988 and 1 May 2019. A total of six clinical studies were reviewed. There were two randomized, placebo-controlled, double-blind trials and populations drawn from two main cohort studies (i.e., the Geelong Osteoporosis Study and the Osteoarthritis Initiative study). Using a random-effects model, the pooled hazard ratio of the three cohort studies was 0.624 (95% confidence interval: 0.0503 to 1.198, p = 0.033), supporting a reduced risk of depression with aspirin exposure. Overall, the dropout rates were low, and aspirin appears to be well-tolerated with minimal risk of affective switch. In terms of methodological quality, most studies had a generally low risk of bias. Low-dose aspirin (80 to 100 mg/day) is safe, well-tolerated and potentially efficacious for improving depressive symptoms in both unipolar and bipolar depression. Due to its ability to modulate neuroinflammation and central nervous system processes, aspirin may also have valuable neuroprotective and pro-cognitive effects that deserve further exploration. Further randomized, controlled trials involving the adjunctive use of aspirin should be encouraged to confirm its therapeutic benefits.

A dimensional approach in psychiatry aims to identify core mechanisms of mental disorders across nosological boundaries.