Discover mental health最新文献

Lactic acid is produced mainly in astrocytes in the brain and serves as a substance that supplies energy to neurons. In recent years, numerous studies identified the potential effects of lactic acid on the central nervous system and demonstrated its role in regulating brain function as an energy metabolism substrate or cellular signaling molecule. Both deficiency and accumulation of lactic acid cause neurological dysfunction, which further lead to the development of neuropsychiatric disorders, such as Major depressive disorder, Schizophrenia, Alzheimer's disease, and Multiple sclerosis. Although an association between lactic acid and neuropsychiatric disorders was reported in previous research, the underlying pathogenic mechanisms remain unclear. Therefore, an in-depth understanding of the molecular mechanisms by which lactic acid regulates brain function is of significance for the early diagnosis and prevention of neuropsychiatric disorders. In this review, we summarize evidence that is focused on the potential mechanisms of lactic acid as a signaling molecule involved in the pathogenesis of neuropsychiatric disorders and propose a new mechanism by which lactic acid regulates brain function and disease through the microbiota-gut-brain axis to offer new insight into the prevention and treatment of neuropsychiatric diseases.

Loss-of-function variants in the dystrophin gene, a well-known cause of muscular dystrophies, have emerged as a mutational risk mechanism for autism spectrum disorder (ASD), which in turn is a highly prevalent (~ 1%) genetically heterogeneous neurodevelopmental disorder. Although the association of intellectual disability with the dystrophinopathies Duchenne (DMD) and Becker muscular dystrophy (BMD) has been long established, their association with ASD is more recent, and the dystrophin genotype-ASD phenotype correlation is unclear. We therefore present a review of the literature focused on the ASD prevalence among dystrophinopathies, the relevance of the dystrophin isoforms, and most particularly the relevance of the genetic background to the etiology of ASD in these patients. Four families with ASD-DMD/BMD patients are also reported here for the first time. These include a single ASD individual, ASD-discordant and ASD-concordant monozygotic twins, and non-identical ASD triplets. Notably, two unrelated individuals, which were first ascertained because of the ASD phenotype at ages 15 and 5 years respectively, present rare dystrophin variants still poorly characterized, suggesting that some dystrophin variants may compromise the brain more prominently. Whole exome sequencing in these ASD-DMD/BMD individuals together with the literature suggest, although based on preliminary data, a complex and heterogeneous genetic architecture underlying ASD in dystrophinopathies, that include rare variants of large and medium effect. The need for the establishment of a consortia for genomic investigation of ASD-DMD/BMD patients, which may shed light on the genetic architecture of ASD, is discussed.

Evidence suggests that shared pathophysiological mechanisms in neuropsychiatric disorders (NPDs) may contribute to risk and resilience. We used single-gene and network-level transcriptomic approaches to investigate shared and disorder-specific processes underlying posttraumatic stress disorder (PTSD), Parkinson's disease (PD) and schizophrenia in a South African sample. RNA-seq was performed on blood obtained from cases and controls from each cohort. Gene expression and weighted gene correlation network analyses (WGCNA) were performed using DESeq2 and CEMiTool, respectively. Significant differences in gene expression were limited to the PTSD cohort. However, WGCNA implicated, amongst others, ribosomal expression, inflammation and ubiquitination as key players in the NPDs under investigation. Differential expression in ribosomal-related pathways was observed in the PTSD and PD cohorts, and focal adhesion and extracellular matrix pathways were implicated in PD and schizophrenia. We propose that, despite different phenotypic presentations, core transdiagnostic mechanisms may play important roles in the molecular aetiology of NPDs.

Two randomized controlled trials (RCTs) in Brazil and Peru demonstrated the effectiveness of CONEMO, a digital intervention supported by trained nurses or nurse assistants (NAs), to reduce depressive symptoms in people with diabetes and/or hypertension. This paper extends the RCTs findings by reflecting on the conditions needed for its wider implementation in routine care services. A qualitative study using semi-structured interviews and content analysis was conducted with nurses/NAs, clinicians, healthcare administrators, and policymakers. Informants reported that CONEMO would be feasible to implement in their health services, but some conditions could be improved before its scale-up: reducing workloads of healthcare workers; raising mental health awareness among clinicians and administrators; being able to inform, deliver and accompany the intervention; assuring appropriate training and supervision of nurses/NAs; and supporting the use of technology in public health services and by patients, especially older ones. We discuss some suggestions on how to overcome these challenges.

Considerable evidence suggests that psychosocial variables can shape the course of bipolar disorder. Here, though, we focus on the more specific idea that the social environment can predict the course of mania. We systematically review evidence from longitudinal studies concerning how social support, family interactions, traumatic life events, and recent life events relate to the age of onset, the frequency of episode recurrence, and the severity of manic symptoms. Although we find some evidence that the course of mania can be worsened by social environmental factors, the links are specific. Among social variables, some studies indicate that conflict and hostility are predictive, but more general social relationship qualities have not been found to predict mania. Some research indicates that childhood trauma, and recent life events involving goal attainment or sleep disruption can predict mania. Taken together, the profile of variables involving recent exposure that are most predictive include those that are activating, reward-related, or sleep-disrupting, which fits with general psychological hypotheses of behavioral activation and sleep disruption as important for mania. We discuss gaps in the literature, and we note future directions for research, including the need for more integrative, longitudinal research on a fuller range of social and biological risk variables.

One hundred and thirty years after lymphoid and myeloid cells were discovered, in 2008, the researchers presented to the scientific community the population of innate lymphoid cells (ILCs) identified in humans and mice. Human ILC subsets were first identified in secondary lymphoid tissues and subsequently reported in the intestine, lung, liver, skin, and meninges. ILCs (ILC1, ILC2, ILC3, and ILCreg) subgroups present plastic properties concerning cytokines, chemokines, and other mediators present in the microenvironment. ILC1s were characterized by their ability to produce interferon (IFN)-γ. ILC2s have a function in innate and adaptive type 2 inflammation by producing effector cytokines such as interleukin (IL)-5 and IL-13. Meningeal ILC2s were activated in an IL-33-dependent mechanism releasing type-2 cytokines and demonstrating that ILC2s proliferate in reaction to IL-33 activation. ILC3s have been discovered as a significant contribution to the homeostasis of the gut barrier and as a source of IL-22. IL-22 presents a pleiotropic activity reinforcing the gut barrier immunity by stimulating anti-microbial peptide synthesis and promoting microbial regulation. Additionally, ILCs can have a pathogenic or protective effect on many disorders, and further research is needed to determine what elements influence the nature of their actions in diverse situations. The narrative review summarizes the role of the ILCs in mental health.

Suicides are preventable tragedies, if risk factors are tracked and mitigated. We had previously developed a new quantitative suicidality risk assessment instrument (Convergent Functional Information for Suicidality, CFI-S), which is in essence a simple polyphenic risk score, and deployed it in a busy urban hospital Emergency Department, in a naturalistic cohort of consecutive patients. We report a four years follow-up of that population (n = 482). Overall, the single administration of the CFI-S was significantly predictive of suicidality over the ensuing 4 years (occurrence- ROC AUC 80%, severity- Pearson correlation 0.44, imminence-Cox regression Hazard Ratio 1.33). The best predictive single phenes (phenotypic items) were feeling useless (not needed), a past history of suicidality, and social isolation. We next used machine learning approaches to enhance the predictive ability of CFI-S. We divided the population into a discovery cohort (n = 255) and testing cohort (n = 227), and developed a deep neural network algorithm that showed increased accuracy for predicting risk of future suicidality (increasing the ROC AUC from 80 to 90%), as well as a similarity network classifier for visualizing patient's risk. We propose that the widespread use of CFI-S for screening purposes, with or without machine learning enhancements, can boost suicidality prevention efforts. This study also identified as top risk factors for suicidality addressable social determinants.

Supplementary information: The online version contains supplementary material available at 10.1007/s44192-022-00016-z.

Background: COVID-19 has affected millions of people worldwide. Clinical manifestations range from severe cases with lethal outcome to mild or asymptomatic cases. Although the proportion of infected individuals does not differ between sexes, men are more susceptible to severe COVID-19, with a higher risk of death than women. Also, men are pointed out as more lax regarding protective measures, mask wearing and vaccination. Thus, we questioned whether sex-bias may be explained by biological pathways and/or behavioral aspects or both.

Methods: Between July 2020 and July 2021, we performed an epidemiological survey including 1744 unvaccinated adult Brazilian couples, with there was at least one infected symptomatic member, who were living together during the COVID-19 infection without protective measures. Presence or absence of infection was confirmed by RT-PCR and/or serology results. Couples were divided into two groups: (1) both partners were infected (concordant couples) and (2) one partner was infected and the spouse remained asymptomatic despite the close contact with the COVID-19 symptomatic partner (discordant couples). Statistical analysis of the collected data was performed aiming to verify a differential transmission potential between genders in couples keeping contact without protective measures.

Results: The combination of our collected data showed that the man is the first (or the only) affected member in most cases when compared to women and that this difference may be explained by biological and behavioral factors.

Conclusions: The present study confirmed the existence of gender differences not only for susceptibility to infection and resistance to COVID-19 but also in its transmission rate.