Oral administration of Lactococcus lactis WHH2078 alleviates depressive and anxiety symptoms in mice with induced chronic stress

Depression is a mood disorder with a high prevalence rate globally, which is associated with abnormalities in 5-hydroxytryptamine (5-HT) metabolism. Emerging evidence suggests that certain probiotics that modulate 5-HT metabolism...

Digital Phenotype of Mood Disorders: a conceptual and critical review (Preprint)

BACKGROUND Mood disorder is commonly diagnosed and staged using clinical features that rely merely on subjective data. The concept of digital phenotyping is based on the idea that collecting real-time markers of human behavior allow one to determine the "digital signature of a pathology". This strategy assumes that behaviors are "quantifiable" from data extracted and analyzed through digital sensors, wearable devices or smartphones. That concept could bring a shift for the diagnosis of mood disorder, introducing for the first time paraclinical testing on psychiatric routine care. OBJECTIVE The main objective of this review was to propose a conceptual and critical review of the literature regarding the theoretical and technical principles of digital phenotypes applied to mood disorders. METHODS We conducted a selective review of the literature by updating a previous article and querying the PubMed database between February 2017 and November 2021 on titles with the relevant keywords regarding digital phenotyping, mood disorders and artificial intelligence. RESULTS 858 articles were included for evaluation, 43 articles were taken into account and classified by data source (multimodal, actigraphy, ECG, smartphone use, voice analysis, body temperature). For depressive episodes, the main finding is the decrease in terms of functional and biological parameters (decrease in activities and walking, decrease in the number of calls and SMS, decrease in temperature and HRV) while the manic phase produces the reverse phenomenon (increase in activities, number of calls and HRV). CONCLUSIONS The various studies presented support the potential interest in digital phenotyping to computerize the clinical characteristics of mood disorders

Apathy in Parkinson’s Disease: A Retrospective Study of Its Prevalence and Relationship With Mood, Anxiety, and Cognitive Function

Apathy is thought to be an important clinical feature of Parkinson’s disease (PD). However, its prevalence ranges greatly across studies because of differing definitions, assessment tools, and patient inclusion criteria. Furthermore, it remains unclear how the presentation of apathy in PD is related to mood disorder and/or cognitive impairment. This study sought to examine the prevalence of a pure apathy syndrome in PD, distinct from both depression and anxiety, and reveal its associated cognitive profile. A retrospective study was performed on 177 PD patients who had completed measures of apathy [Apathy Evaluation Scale (AES)] and mood functioning [Hospital Anxiety and Depression Scale (HADS)] and had undergone extensive neuropsychological assessment, using measures of intellectual functioning, memory, executive function, attention, language, visual processing, and cognitive speed; 14.7% of the sample indicated clinically significant levels of apathy, but this nearly always co-presented with depression and/or anxiety, with cases of “pure” apathy very rare (2.8%). On extensive cognitive assessment, patients with mood disorder performed worse on a measure of non-verbal intellectual functioning, but patients with additional apathy or apathy only demonstrated no further losses. The syndrome of apathy in PD greatly overlaps with that of depression and anxiety, suggesting that apathy in PD may be in large an epiphenomenon of mood disorder, with no specific neuropsychological features.

Lithium neurotoxicity with electroencephalogram changes

Lithium is a medication with a variety of medical usage for various diseases including bipolar mood disorder. As the therapeutic window of lithium is narrow, its usage is commonly associated with toxicity. Lithium toxicity affects multiple systems especially the central nervous system, leading to neuropsychiatric complications. Haemodialysis is an effective method for lithium removal especially in severe lithium toxicity such as neurotoxicity with electroencephalogram changes. We describe a case of lithium neurotoxicity with electroencephalographic abnormalities which was reversed following haemodialysis.

Mood Disorders

Mood disorders—depressive and bipolar disorders—are the second most common set of psychiatric disorders, behind anxiety disorders. The lifetime prevalence of any mood disorder in US adults is approximately 20%, and the 12-month prevalence is approximately 10%. Although depressive disorders and bipolar disorder have been split into 2 chapters in the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition), the criteria have stayed the same as in its Fourth Edition, Text Revision while the terminology has changed slightly.

Contextual and mental health service factors in mental disorder-based disability pensioning in Finland – a regional comparison

Background We investigated the regional differences in all mental disorder disability pensions (DP) between 2010 and 2015 in Finland, and separately in mood disorders and non-affective psychotic disorder DP. We also studied the contribution of several district-level contextual and mental health service factors to mental disorder DP. Methods Subjects were all those granted mental disorder DP for the first time between 2010 and 2015 in Finland (N = 36,879). Associations between the district-level contextual and mental health service factors and regional DP risks collected from the year 2015 were studied with negative binomial regression analysis in the Finnish hospital districts. The population number on the age (18 to 65 years), gender, occupational status and residential hospital district of the Finnish population from 2015 was used as exposure in the model. Results Significant differences in the regional mental disorder DP risks between and within hospital districts did not appear to follow the traditional Finnish health differences. A lower risk of DP was associated with contextual indicators of higher regional socioeconomic level. Furthermore, population density as a proxy for access to mental health services indicated a higher regional DP risk for lower density in all mental (IRR 1.10; 95% CI 1.06–1.14) and mood disorder (IRR 1.12; 95% CI 1.08–1.16) DP. Both the highest and the lowest regional numbers of all mental health outpatient visits were associated with a higher DP risk in all mental and mood disorder DP, whereas particularly low regional numbers of inpatient treatment periods and of patients were associated with a lower risk of DP. Conclusions In this comprehensive population-level study, we found evidence of significant regional variation in mental disorder DP and related district-level factors. This variation may at least partly relate to differences in regional mental health service systems and treatment practices. Adapting to the needs of the local population appears to be indicated for both regional mental health service systems and treatment practices to achieve optimal performance.