Seasonality of brain function: role in psychiatric disorders

Identifying clinical and proteomic markers for early diagnosis and prognosis prediction of major psychiatric disorders

BACKGROUND

To clarify if blood proteins can predict disease progression among individuals at clinical high-risk of severe mental illness (CHR-SMI), we developed a statistical model incorporating clinical and blood protein markers to distinguish the transition group (who developed severe mental illness) (CHR-SMI-T) and from non-transition group (CHR-SMI-NT) at baseline.

METHODS

Ninety individuals (74 at CHR-SMI: 16 patients) were monitored for ≤4 years and were the focus of predictive models. Three predictive models (1 [100 clinical variables], 2 [158 peptides], and 3 [100 clinical variables +158 peptides]) were evaluated using area under the receiver operating characteristic (AUROC) values. Clinical and protein feature patterns were evaluated by linear mixed-effect analysis within the model at 12 and 24 months among patients who did (CHR-SMI-T) and did not transition (CHR-SMI-NT) and the entire group.

RESULT

Eighteen CHR-SMI individuals with major psychiatric disorders (first episode psychosis: 2; bipolar II disorder: 13; major depressive disorder; 3) developed disorders over an average of 17.7 months. The combined model showed the highest discriminatory performance (AUROC = 0.73). Cytosolic malate dehydrogenase and transgelin-2 levels were lower in the CHR-SMI-T than the CHR-SMI-NT group. Complement component C9, inter-alpha-trypsin inhibitor heavy chain H4, von Willebrand factor, and C-reactive protein were lower in the patient than the CHR-SMI-NT group. These differences were non-significant after FDR adjustment.

LIMITATIONS

Small sample, no control for medication use.

CONCLUSION

This exploratory study identified clinical and proteomic markers that might predict severe mental illness early onset, which could aid in early detection and intervention. Future studies with larger samples and controlled variables are needed to validate these findings.

The neurobiological mechanisms of photoperiod impact on brain functions: a comprehensive review

Variations in day length, or photoperiodism, whether natural or artificial light, significantly impact biological, physiological, and behavioral processes within the brain. Both natural and artificial light sources are environmental factors that significantly influence brain functions and mental well-being. Photoperiodism is a phenomenon, occurring either over a 24 h cycle or seasonally and denotes all biological responses of humans and animals to these fluctuations in day and night length. Conversely, artificial light occurrence refers to the presence of light during nighttime hours and/or its absence during the daytime (unnaturally long and short days, respectively). Light at night, which is a form of light pollution, is prevalent in many societies, especially common in certain emergency occupations. Moreover, individuals with certain mental disorders, such as depression, often exhibit a preference for darkness over daytime light. Nevertheless, disturbances in light patterns can have negative consequences, impacting brain performance through similar mechanisms albeit with varying degrees of severity. Furthermore, changes in day length lead to alterations in the activity of receptors, proteins, ion channels, and molecular signaling pathways, all of which can impact brain health. This review aims to summarize the mechanisms by which day length influences brain functions through neural circuits, hormonal systems, neurochemical processes, cellular activity, and even molecular signaling pathways.

Human PERIOD3 variants lead to winter depression-like behaviours via glucocorticoid signalling

Our brain adapts to seasonal changes. Mis-adaptations may lead to seasonal patterns in several psychiatric disorders, but we know little regarding the underlying mechanisms. Our previous work identified two variants in the human circadian clock gene PERIOD3 (PER3), that is, P415A and H417R, which are associated with winter depression, but whether and how these variants lead to the disorder remain to be characterized. Here we find that male mice carrying human P415A and H417R display winter depression-like behaviours that are caused by the actions of P415A and H417R in the adrenal gland. Systemic corticosterone level is downregulated in adaptation to shortening of day length, while P415A and H417R eliminate this downregulation by increasing corticosterone synthesis. Enhanced glucocorticoid signalling represses the transcription of Tph2, which encodes the rate-limiting enzyme of serotonin synthesis, leading to increased depression-like behaviours. Taken together, our findings unveil a mechanism according to which human variants contribute to seasonal mood traits.

Changes in Rest-Activity Rhythms in Adolescents as They Age: Associations With Brain and Behavioral Changes in the ABCD Study

OBJECTIVE

Adolescents with disrupted rest-activity rhythms (RARs), including shorter sleep duration, later sleep timing, and low physical activity levels, are at greater risk for mental health and behavioral problems. It remains unclear whether the same associations can be observed for within-subject changes in RARs.

METHOD

This longitudinal investigation on RARs used Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study at the 2-year follow-up (FL2) (ages 10-13 years) and 4-year follow-up (FL4) (ages 13-16 years). Good-quality Fitbit data were available for 963 youths at both time points. Changes in RARs from FL2 to FL4, their environmental and demographic contributors, and brain and behavioral correlates were examined.

RESULTS

From FL2 to FL4, adolescents showed decreases in sleep duration and physical activity as well as delayed sleep timing (Cohen d = 0.44-0.75). Contributions of environmental and demographic factors to RAR changes were greatest for sleep timing (explained 10% variance) and least for sleep duration (explained 1% variance). Delays in sleep timing had stronger correlations with behavioral problems including impulsivity and poor academic performance than reductions in sleep duration or physical activity. Additionally, the various brain measures differed in their sensitivity to RAR changes. Reductions in sleep duration were associated with decreased functional connectivity between subcortical regions and sensorimotor and cingulo-opercular networks and with enhanced functional connectivity between sensorimotor, visual, and auditory networks. Delays in sleep timing were mainly associated with gray matter changes in subcortical regions.

CONCLUSION

The current findings corroborate the importance of sleep and physical activity in brain neurodevelopment and behavioral problems in adolescents. RARs might serve as biomarkers for monitoring behavioral problems and be potential therapeutic targets for mental disorders in adolescents.

How does the macroenvironment influence brain and behaviour-a review of current status and future perspectives

The environment influences brain and mental health, both detrimentally and beneficially. Existing research has emphasised the individual psychosocial 'microenvironment'. Less attention has been paid to 'macroenvironmental' challenges, including climate change, pollution, urbanicity, and socioeconomic disparity. Notably, the implications of climate and pollution on brain and mental health have only recently gained prominence. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

REM sleep and mental disorders on the 70th anniversary of the discovery of REM sleep

The discovery of rapid eye movement sleep in 1953 led to numerous studies investigating the relationship between rapid eye movement sleep abnormalities and psychiatric disorders. The most salient findings were the association of rapid eye movement sleep alterations-reduced rapid eye movement sleep latency, increased rapid eye movement sleep volume of total sleep, and increased rapid eye movement density-with major depression. This paper briefly reviews the history of rapid eye movement sleep research in psychiatry with a focus on the work related to major depressive disorder and some of the various theories that have been proposed to explain the associated rapid eye movement sleep abnormalities. Given the increasing evidence that rapid eye movement sleep is important for emotional processing, memory and cognition, a better understanding of the underlying mechanisms for the relationship between rapid eye movement sleep and mood disorders could lead to improved treatments for these common and disabling illnesses.

Risk of neuropsychiatric adverse events associated with montelukast use in children and adolescents: a population-based case-crossover study

PURPOSE

Montelukast is used extensively in children and adolescents for allergic rhinitis and asthma. However, concerns have been raised regarding the increased risk of neuropsychiatric adverse events (NPAEs) associated with montelukast use. Therefore, our case-crossover study was conducted to observe whether there is an increased risk of NPAEs associated with montelukast use in children and adolescents.

MATERIALS AND METHODS

A population-based case-crossover study using the customised Health Insurance Review and Assessment (HIRA) dataset was conducted. Paediatric patients aged between 0 and 19 years diagnosed with allergic rhinitis and/or asthma with a history of at least one montelukast prescription between 1 January 2018 and 31 December 2021 were included. Exposure to montelukast was assessed during 3-, 7-, 14-, 28- and 56-day hazard periods prior to each patient's NPAE. Stratified analyses according to age group, gender and season for the risk of NPAEs associated with montelukast use in the previous 7 days and 14 days were performed, respectively. Conditional logistic regression analysis was used to calculate adjusted ORs (aORs) with their corresponding 95% CIs, adjusting for concomitant medications.

RESULTS

A total of 161 386 paediatric patients was identified. An increased risk of NPAEs associated with montelukast was found in all time window periods, including 3-day (aOR 1.28, 95% CI 1.24 to 1.32), 7-day (aOR 1.29, 95% CI 1.26 to 1.33), 14-day (aOR 1.34, 95% CI 1.31 to 1.37), 28-day (aOR 1.38, 95% CI 1.36 to 1.41) and 56-day (aOR 1.21, 95% CI 1.19 to 1.22) preceding hazard periods compared with use in the four control periods.

CONCLUSION

Children and adolescents with allergic rhinitis and/or asthma should be prescribed montelukast with caution considering clinical benefits.

Seasonal variation in D2/3 dopamine receptor availability in the human brain

PURPOSE

Brain functional and physiological plasticity is essential to combat dynamic environmental challenges. The rhythmic dopamine signaling pathway, which regulates emotion, reward and learning, shows seasonal patterns with higher capacity of dopamine synthesis and lower number of dopamine transporters during dark seasons. However, seasonal variation of the dopamine receptor signaling remains to be characterized.

METHODS

Based on a historical database of healthy human brain [11C]raclopride PET scans (n = 291, 224 males and 67 females), we investigated the seasonal patterns of D2/3 dopamine receptor signaling. Daylength at the time of scanning was used as a predictor for brain regional non-displaceable binding of the radiotracer, while controlling for age and sex.

RESULTS

Daylength was negatively correlated with availability of D2/3 dopamine receptors in the striatum. The largest effect was found in the left caudate, and based on the primary sample, every 4.26 h (i.e., one standard deviation) increase of daylength was associated with a mean 2.8% drop (95% CI -0.042 to -0.014) of the receptor availability.

CONCLUSIONS

Seasonally varying D2/3 receptor signaling may also underlie the seasonality of mood, feeding, and motivational processes. Our finding suggests that in future studies of brain dopamine signaling, especially in high-latitude regions, the effect of seasonality should be considered.

Transitional photoperiod induces a mania-like behavior in male mice

This study aimed to investigate the behavioral responses and circadian rhythms of mice to both rapid and gradual increases in photoperiod, mimicking the transition from winter to summer, which is associated with a heightened prevalence of hospitalizations for mania and suicidal behavior. Behavioral tests were performed in C57BL/6 male mice exposed to a transitional photoperiod, from short to long durations. To determine if circadian rhythms are affected, we measured spontaneous locomotor activity and body temperature. Mice exhibited heightened exploratory and risk-taking behaviors compared with equatorial and static long (16:8 h of light-dark cycle for several days) groups. These behaviors were prevented by lithium. Spontaneous locomotor activity and body temperature rhythms persisted and were effectively synchronized; however, the relative amplitude of activity and interdaily stability were diminished. Additionally, the animals displayed increased activity during the light phase. Photoperiodic transition modulates behavior and circadian rhythms, mirroring certain features observed in bipolar disorder patients. This study introduces an animal model for investigating mania-like behavior induced by photoperiodic changes, offering potential insights for suicide prevention strategies and the management of mood disorders.

Circadian Interventions in Preclinical Models of Huntington's Disease: A Narrative Review

Huntington's Disease (HD) is a neurodegenerative disorder caused by an autosomal-dominant mutation in the huntingtin gene, which manifests with a triad of motor, cognitive and psychiatric declines. Individuals with HD often present with disturbed sleep/wake cycles, but it is still debated whether altered circadian rhythms are intrinsic to its aetiopathology or a consequence. Conversely, it is well established that sleep/wake disturbances, perhaps acting in concert with other pathophysiological mechanisms, worsen the impact of the disease on cognitive and motor functions and are a burden to the patients and their caretakers. Currently, there is no cure to stop the progression of HD, however, preclinical research is providing cementing evidence that restoring the fluctuation of the circadian rhythms can assist in delaying the onset and slowing progression of HD. Here we highlight the application of circadian-based interventions in preclinical models and provide insights into their potential translation in clinical practice. Interventions aimed at improving sleep/wake cycles' synchronization have shown to improve motor and cognitive deficits in HD models. Therefore, a strong support for their suitability to ameliorate HD symptoms in humans emerges from the literature, albeit with gaps in our knowledge on the underlying mechanisms and possible risks associated with their implementation.

Adaptation to photoperiod via dynamic neurotransmitter segregation

Changes in the amount of daylight (photoperiod) alter physiology and behaviour1,2. Adaptive responses to seasonal photoperiods are vital to all organisms-dysregulation associates with disease, including affective disorders3 and metabolic syndromes4. The circadian rhythm circuitry is implicated in such responses5,6, yet little is known about the precise cellular substrates that underlie phase synchronization to photoperiod change. Here we identify a brain circuit and system of axon branch-specific and reversible neurotransmitter deployment that are critical for behavioural and sleep adaptation to photoperiod. A type of neuron called mrEn1-Pet17 in the mouse brainstem median raphe nucleus segregates serotonin from VGLUT3 (also known as SLC17A8, a proxy for glutamate) to different axonal branches that innervate specific brain regions involved in circadian rhythm and sleep-wake timing8,9. This branch-specific neurotransmitter deployment did not distinguish between daylight and dark phase; however, it reorganized with change in photoperiod. Axonal boutons, but not cell soma, changed neurochemical phenotype upon a shift away from equinox light/dark conditions, and these changes were reversed upon return to equinox conditions. When we genetically disabled Vglut3 in mrEn1-Pet1 neurons, sleep-wake periods, voluntary activity and clock gene expression did not synchronize to the new photoperiod or were delayed. Combining intersectional rabies virus tracing and projection-specific neuronal silencing, we delineated a preoptic area-to-mrEn1Pet1 connection that was responsible for decoding the photoperiodic inputs, driving the neurotransmitter reorganization and promoting behavioural synchronization. Our results reveal a brain circuit and periodic, branch-specific neurotransmitter deployment that regulates organismal adaptation to photoperiod change.

Seasonal variations in psychiatry outpatient service utilization in a tertiary health care center in subtropical arid regions of northwestern India

Background

Research on climatic parameters contributing to psychiatric disorder seasonality is limited, particularly in subtropical, arid climates like Rajasthan, necessitating investigation into seasonal variations in psychiatric disorder incidence in the region. This study investigates seasonal variations in psychiatric disorder prevalence over 2 years at a Rajasthan tertiary healthcare center, aiming to uncover links with climatic factors.

Aims

To investigate seasonal variations in the utilization of outpatient psychiatry services and elucidate potential determinants contributing to these temporal variations.

Settings and Design

This is a hospital-based study. A retrospective chart review of all new patients who utilized psychiatry outpatient services from July 2021 to July 2023 was conducted.

Methods and Material

Data were gathered from psychiatric outpatient records of adults (July 2021 to July 2023), diagnosed using ICD-10. Seasons were categorized: winter (November-January), spring (February-April), summer (May-July), and rainy (August-October). Meteorological data, temperature, and day length were obtained. Statistical analyses, including Pearson correlation and Chi-square fitness, assessed seasonal associations with psychiatric disorders.

Results

A total of 29,164 patient records were observed. Depression correlated with temperature and photoperiod. Mania peaked in August, linked to day length. Schizophrenia showed seasonal variation without environmental correlation. Anxiety peaked in March with no statistical significance. Obsessive compulsive disorder cases spiked in June, moderately correlated with temperature and photoperiod. Alcohol-related disorders peaked in December, while opioid dependence remained steady. Cannabis-induced psychosis peaked in summer, strongly correlated with temperature and day length. Headaches surged in August, positively correlated with temperature and day length.

Conclusions

This study reveals complex relationships between seasonality, environmental factors, and psychiatric disorders, emphasizing their importance in mental health research and practice.

Personality Moderates Intra-Individual Variability in EEG Microstates and Spontaneous Thoughts

Variability in brain activity that persists after accounting for overt behavioral and physiological states is often considered noise and controlled as a covariate in research. However, studying intra-individual variability in brain function can provide valuable insights into the dynamic nature of the brain. To explore this, we conducted a study on 43 participants analyzing the EEG microstate dynamics and self-reported spontaneous mental activity during five-minute resting-state recordings on two separate days with a twenty days average delay between recordings. Our results showed that the associations between EEG microstates and spontaneous cognition significantly changed from one day to another. Moreover, microstate changes were associated with changes in spontaneous cognition. Specifically, inter-day changes in Verbal thoughts about Others and future Planning were positively related to bottom-up sensory network-related microstate changes and negatively associated with top-down, attention, and salience network-related microstates. In addition, we find that personality traits are related to inter-day changes in microstates and spontaneous thoughts. Specifically, extraversion, neuroticism, agreeableness, and openness to experience moderated the relationship between inter-day changes in EEG microstates and spontaneous thoughts. Our study provides valuable information on the dynamic changes in the EEG microstate-spontaneous cognition organization, which could be essential for developing interventions and treatments for neuropsychiatric disorders.

Shared genetic mechanisms underlying association between sleep disturbances and depressive symptoms

OBJECTIVES

Polygenic scores (PGS) for sleep disturbances and depressive symptoms in an epidemiological cohort were contrasted. The overlap between genes assigned to variants that compose the PGS predictions was tested to explore the shared genetic bases of sleep problems and depressive symptoms.

METHODS

PGS analysis was performed on the São Paulo Epidemiologic Sleep Study (EPISONO, N = 1042), an adult epidemiological sample. A genome wide association study (GWAS) for depression grounded the PGS calculations for Beck Depression Index (BDI), while insomnia GWAS based the PGS for Insomnia Severity Index (ISI) and Pittsburg Sleep Quality Index (PSQI). Pearson's correlation was applied to contrast PGS and clinical scores. Fisher's Exact and Benjamin-Hochberg tests were used to verify the overlaps between PGS-associated genes and the pathways enriched among their intersections.

RESULTS

All PGS models were significant when individuals were divided as cases or controls according to BDI (R2 = 1.2%, p = 0.00026), PSQI (R2 = 3.3%, p = 0.007) and ISI (R2 = 3.4%, p = 0.021) scales. When clinical scales were used as continuous variables, the PGS models for BDI (R2 = 1.5%, p = 0.0004) and PSQI scores (R2 = 3.3%, p = 0.0057) reached statistical significance. PSQI and BDI scores were correlated, and the same observation was applied to their PGS. Genes assigned to variants that compose the best-fit PGS predictions for sleep quality and depressive symptoms were significantly overlapped. Pathways enriched among the intersect genes are related to synapse function.

CONCLUSIONS

The genetic bases of sleep quality and depressive symptoms are correlated; their implicated genes are significantly overlapped and converge on neural pathways. This data suggests that sleep complaints accompanying depressive symptoms are not secondary issues, but part of the core mental illness.

Seasonality in regional brain glucose metabolism

BACKGROUND

Daylength and the rates of changes in daylength have been associated with seasonal fluctuations in psychiatric symptoms and in cognition and mood in healthy adults. However, variations in human brain glucose metabolism in concordance with seasonal changes remain under explored.

METHODS

In this cross-sectional study, we examined seasonal effects on brain glucose metabolism, which we measured using 18F-fluorodeoxyglucose-PET in 97 healthy participants. To maximize the sensitivity of regional effects, we computed relative metabolic measures by normalizing the regional measures to white matter metabolism. Additionally, we explored the role of rest-activity rhythms/sleep-wake activity measured with actigraphy in the seasonal variations of regional brain metabolic activity.

RESULTS

We found that seasonal variations of cerebral glucose metabolism differed across brain regions. Glucose metabolism in prefrontal regions increased with longer daylength and with greater day-to-day increases in daylength. The cuneus and olfactory bulb had the maximum and minimum metabolic values around the summer and winter solstice respectively (positively associated with daylength), whereas the temporal lobe, brainstem, and postcentral cortex showed maximum and minimum metabolic values around the spring and autumn equinoxes, respectively (positively associated with faster daylength gain). Longer daylength was associated with greater amplitude and robustness of diurnal activity rhythms suggesting circadian involvement.

CONCLUSIONS

The current findings advance our knowledge of seasonal patterns in a key indicator of brain function relevant for mood and cognition. These data could inform treatment interventions for psychiatric symptoms that peak at specific times of the year.

Impact of Serotonin Deficiency on Circadian Dopaminergic Rhythms

Physiology and behavior are structured temporally to anticipate daily cycles of light and dark, ensuring fitness and survival. Neuromodulatory systems in the brain-including those involving serotonin and dopamine-exhibit daily oscillations in neural activity and help shape circadian rhythms. Disrupted neuromodulation can cause circadian abnormalities that are thought to underlie several neuropsychiatric disorders, including bipolar mania and schizophrenia, for which a mechanistic understanding is still lacking. Here, we show that genetically depleting serotonin in Tph2 knockout mice promotes manic-like behaviors and disrupts daily oscillations of the dopamine biosynthetic enzyme tyrosine hydroxylase (TH) in midbrain dopaminergic nuclei. Specifically, while TH mRNA and protein levels in the Substantia Nigra (SN) and Ventral Tegmental Area (VTA) of wild-type mice doubled between the light and dark phase, TH levels were high throughout the day in Tph2 knockout mice, suggesting a hyperdopaminergic state. Analysis of TH expression in striatal terminal fields also showed blunted rhythms. Additionally, we found low abundance and blunted rhythmicity of the neuropeptide cholecystokinin (Cck) in the VTA of knockout mice, a neuropeptide whose downregulation has been implicated in manic-like states in both rodents and humans. Altogether, our results point to a previously unappreciated serotonergic control of circadian dopamine signaling and propose serotonergic dysfunction as an upstream mechanism underlying dopaminergic deregulation and ultimately maladaptive behaviors.

The missing hallmark of health: psychosocial adaptation

The eight biological hallmarks of health that we initially postulated (Cell. 2021 Jan 7;184(1):33-63) include features of spatial compartmentalization (integrity of barriers, containment of local perturbations), maintenance of homeostasis over time (recycling & turnover, integration of circuitries, rhythmic oscillations) and an array of adequate responses to stress (homeostatic resilience, hormetic regulation, repair & regeneration). These hallmarks affect all eight somatic strata of the human body (molecules, organelles, cells, supracellular units, organs, organ systems, systemic circuitries and meta-organism). Here we postulate that mental and socioeconomic factors must be added to this 8×8 matrix as an additional hallmark of health ("psychosocial adaptation") and as an additional stratum ("psychosocial interactions"), hence building a 9×9 matrix. Potentially, perturbation of each of the somatic hallmarks and strata affects psychosocial factors and vice versa. Finally, we discuss the (patho)physiological bases of these interactions and their implications for mental health improvement.

Exploring seasonality in catatonia diagnosis: Evidence from a large-scale population study

Catatonia is a severe psychomotor syndrome mainly associated with psychiatric disorders, such as mood disorders and schizophrenia. Seasonal patterns have been described for these psychiatric disorders, and a previous study conducted in South London showed for the first time a seasonal pattern in the onset of catatonia. In this study, we aim to extend those findings to a larger national sample of patients admitted to French metropolitan hospitals, between 2015 and 2022, and to perform subgroup analyses by the main associated psychiatric disorder. A total of 6225 patients diagnosed with catatonia were included. A seasonal pattern for catatonia diagnosis was described, using cosinor models. Two peaks of diagnoses for catatonic cases were described in March and around September-October. Depending on the associated psychiatric disorder, the seasonality of catatonia diagnosis differed. In patients suffering with mood disorders, peaks of catatonia diagnosis were found in March and July. For patients suffering with schizophrenia, no seasonal pattern was found.

Vasculature of the Suprachiasmatic Nucleus: Pathways for Diffusible Output Signals

Transplant studies demonstrate unequivocally that the suprachiasmatic nucleus (SCN) produces diffusible signals that can sustain circadian locomotor rhythms. There is a vascular portal pathway between the SCN and the organum vasculosum of the lamina terminalis in mouse brain. Portal pathways enable low concentrations of neurosecretions to reach specialized local targets without dilution in the systemic circulation. To explore the SCN vasculature and the capillary vessels whereby SCN neurosecretions might reach portal vessels, we investigated the blood vessels (BVs) of the core and shell SCN. The arterial supply of the SCN differs among animals, and in some animals, there are differences between the 2 sides. The rostral SCN is supplied by branches from either the superior hypophyseal artery (SHpA) or the anterior cerebral artery or the anterior communicating artery. The caudal SCN is consistently supplied by the SHpA. The rostral SCN is drained by the preoptic vein, while the caudal is drained by the basal vein, with variations in laterality of draining vessels. In addition, several key features of the core and shell SCN regions differ: Median BV diameter is significantly smaller in the shell than the core based on confocal image measurements, and a similar trend occurs in iDISCO-cleared tissue. In the cleared tissue, whole BV length density and surface area density are significantly greater in the shell than the core. Finally, capillary length density is also greater in the shell than the core. The results suggest three hypotheses: First, the distinct arterial and venous systems of the rostral and caudal SCN may contribute to the in vivo variations of metabolic and neural activities observed in SCN networks. Second, the dense capillaries of the SCN shell are well positioned to transport blood-borne signals. Finally, variations in SCN vascular supply and drainage may contribute to inter-animal differences.

A seasonal switch hypothesis for the neuroendocrine control of aggression

Aggression is a well-studied social behavior that is universally exhibited by animals across a wide range of contexts. Prevailing knowledge suggests gonadal steroids primarily mediate aggression; however, this is based mainly on studies of male-male aggression in laboratory rodents. When males and females of other species, including humans, are examined, a positive relationship between gonadal steroids and aggression is less substantiated. For instance, hamsters housed in short 'winter-like' days show increased aggression compared with long-day housed hamsters, despite relatively low circulating gonadal steroids. These results suggest alternative, non-gonadal mechanisms controlling aggression. Here, we propose the seasonal switch hypothesis, which employs a multidisciplinary approach to describe how seasonal variation in extra-gonadal steroids, orchestrated by melatonin, drives context-specific changes in aggression.

Association between glyphosate exposure and cognitive function, depression, and neurological diseases in a representative sample of US adults: NHANES 2013-2014 analysis

Glyphosate, the most widely used herbicide globally, has been linked to neurological impairments in some occupational studies. However, the potential neurotoxic effects of glyphosate exposure in the general population are still not fully understood. We conducted analyses on existing data collected from 1532 adults of the 2013-2014 National Health and Nutrition Examination Survey (NHANES) to explore the possible relationship between glyphosate exposure and cognitive function, depressive symptoms, disability, and neurological medical conditions. Our results showed a significant negative association between urinary glyphosate levels and the Consortium to Establish a Registry for Alzheimer's Disease Word List Memory Test (CERAD-WLT) trial 3 recall and delayed recall scores in both models, with ß coefficients of -0.288 (S.E. = 0.111, P = 0.021) and -0.426 (S.E. = 0.148, P = 0.011), respectively. Furthermore, the odds ratio did not show a significant increase with the severity of depressive symptoms with a one-unit increase in ln-glyphosate levels. However, the odds ratio for severe depressive symptoms was significantly higher than for no symptoms (odds ratio = 4.148 (95% CI = 1.009-17.133), P = 0.049). Notably, the odds ratio showed a significant increase for individuals with serious hearing difficulty (odds ratio = 1.354 (95% CI = 1.018-1.800), P = 0.039) with a one-unit increase in ln-glyphosate levels, but not for other neurological medical conditions. In conclusion, our findings provide the first evidence that glyphosate exposure may be associated with neurological health outcomes in the US adult population. Additional investigation is necessary to understand the potential mechanisms and clinical significance of these correlations.

Seasonal patterns of sickness absence due to diagnosed mental disorders: a nationwide 12-year register linkage study

AIMS

Although seasonality has been documented for mental disorders, it is unknown whether similar patterns can be observed in employee sickness absence from work due to a wide range of mental disorders with different severity level, and to what extent the rate of change in light exposure plays a role. To address these limitations, we used daily based sickness absence records to examine seasonal patterns in employee sickness absence due to mental disorders.

METHODS

We used nationwide diagnosis-specific psychiatric sickness absence claims data from 2006 to 2017 for adult individuals aged 16-67 (n = 636,543 sickness absence episodes) in Finland, a high-latitude country with a profound variation in daylength. The smoothed time-series of the ratio of observed and expected (O/E) daily counts of episodes were estimated, adjusted for variation in all-cause sickness absence rates during the year.

RESULTS

Unipolar depressive disorders peaked in October-November and dipped in July, with similar associations in all forms of depression. Also, anxiety and non-organic sleep disorders peaked in October-November. Anxiety disorders dipped in January-February and in July-August, while non-organic sleep disorders dipped in April-August. Manic episodes reached a peak from March to July and dipped in September-November and in January-February. Seasonality was not dependent on the severity of the depressive disorder.

CONCLUSIONS

These results suggest a seasonal variation in sickness absence due to common mental disorders and bipolar disorder, with high peaks in depressive, anxiety and sleep disorders towards the end of the year and a peak in manic episodes starting in spring. Rapid changes in light exposure may contribute to sickness absence due to bipolar disorder. The findings can help clinicians and workplaces prepare for seasonal variations in healthcare needs.

How does the macroenvironment influence brain and behaviour - a review of current status and future perspectives

The environment influences mental health, both detrimentally and beneficially. Current research has emphasized the individual psychosocial 'microenvironment'. Less attention has been paid to 'macro-environmental' challenges including climate change, pollution, urbanicity and socioeconomic disparity. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

A brain circuit and neuronal mechanism for decoding and adapting to change in daylength

Changes in daylight amount (photoperiod) drive pronounced alterations in physiology and behaviour1,2. Adaptive responses to seasonal photoperiods are vital to all organisms - dysregulation is associated with disease, from affective disorders3 to metabolic syndromes4. Circadian rhythm circuitry has been implicated5,6 yet little is known about the precise neural and cellular substrates that underlie phase synchronization to photoperiod change. Here we present a previously unknown brain circuit and novel system of axon branch-specific and reversible neurotransmitter deployment that together prove critical for behavioural and sleep adaptation to photoperiod change. We found that the recently defined neuron type called mrEn1-Pet17 located in the mouse brainstem Median Raphe Nucleus (MRN) segregates serotonin versus VGLUT3 (here proxy for the neurotransmitter glutamate) to different axonal branches innervating specific brain regions involved in circadian rhythm and sleep/wake timing8,9. We found that whether measured during the light or dark phase of the day this branch-specific neurotransmitter deployment in mrEn1-Pet1 neurons was indistinguishable; however, it strikingly reorganizes on photoperiod change. Specifically, axonal boutons but not cell soma show a shift in neurochemical phenotype upon change away from equinox light/dark conditions that reverses upon return to equinox. When we genetically disabled the deployment of VGLUT3 in mrEn1-Pet1 neurons, we found that sleep/wake periods and voluntary activity failed to synchronize to the new photoperiod or was significantly delayed. Combining intersectional rabies virus tracing and projection-specific neuronal silencing in vivo, we delineated a Preoptic Area-to-mrEn1Pet1 connection responsible for decoding the photoperiodic inputs, driving the neurochemical shift and promoting behavioural synchronization. Our results reveal a previously unrecognized brain circuit along with a novel form of periodic, branch-specific neurotransmitter deployment that together regulate organismal adaptation to photoperiod changes.

Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts

Introduction

Despite a recent global decrease in suicide rates, death by suicide has increased in the United States. It is therefore imperative to identify the risk factors associated with suicide attempts to combat this growing epidemic. In this study, we aim to identify potential risk factors of suicide attempt using geospatial features in an Artificial intelligence framework.

Methods

We use iterative Random Forest, an explainable artificial intelligence method, to predict suicide attempts using data from the Million Veteran Program. This cohort incorporated 405,540 patients with 391,409 controls and 14,131 attempts. Our predictive model incorporates multiple climatic features at ZIP-code-level geospatial resolution. We additionally consider demographic features from the American Community Survey as well as the number of firearms and alcohol vendors per 10,000 people to assess the contributions of proximal environment, access to means, and restraint decrease to suicide attempts. In total 1,784 features were included in the predictive model.

Results

Our results show that geographic areas with higher concentrations of married males living with spouses are predictive of lower rates of suicide attempts, whereas geographic areas where males are more likely to live alone and to rent housing are predictive of higher rates of suicide attempts. We also identified climatic features that were associated with suicide attempt risk by age group. Additionally, we observed that firearms and alcohol vendors were associated with increased risk for suicide attempts irrespective of the age group examined, but that their effects were small in comparison to the top features.

Discussion

Taken together, our findings highlight the importance of social determinants and environmental factors in understanding suicide risk among veterans.

Seasonal effect-an overlooked factor in neuroimaging research

In neuroimaging research, seasonal effects are often neglected or controlled as confounding factors. However, seasonal fluctuations in mood and behavior have been observed in both psychiatric disorders and healthy participants. There are vast opportunities for neuroimaging studies to understand seasonal variations in brain function. In this study, we used two longitudinal single-subject datasets with weekly measures over more than a year to investigate seasonal effects on intrinsic brain networks. We found that the sensorimotor network displayed a strong seasonal pattern. The sensorimotor network is not only relevant for integrating sensory inputs and coordinating movement, but it also affects emotion regulation and executive function. Therefore, the observed seasonality effects in the sensorimotor network could contribute to seasonal variations in mood and behavior. Genetic analyses revealed seasonal modulation of biological processes and pathways relevant to immune function, RNA metabolism, centrosome separation, and mitochondrial translation that have a significant impact on human physiology and pathology. In addition, we revealed critical factors such as head motion, caffeine use, and scan time that could interfere with seasonal effects and need to be considered in future studies.

Emotionally clocked out: cell-type specific regulation of mood and anxiety by the circadian clock system in the brain

Circadian rhythms are self-sustained oscillations of biological systems that allow an organism to anticipate periodic changes in the environment and optimally align feeding, sleep, wakefulness, and the physiological and biochemical processes that support them within the 24 h cycle. These rhythms are generated at a cellular level by a set of genes, known as clock genes, which code for proteins that inhibit their own transcription in a negative feedback loop and can be perturbed by stress, a risk factor for the development of mood and anxiety disorders. A role for circadian clocks in mood and anxiety has been suggested for decades on the basis of clinical observations, and the dysregulation of circadian rhythms is a prominent clinical feature of stress-related disorders. Despite our understanding of central clock structure and function, the effect of circadian dysregulation in different neuronal subtypes in the suprachiasmatic nucleus (SCN), the master pacemaker region, as well as other brain systems regulating mood, including mesolimbic and limbic circuits, is just beginning to be elucidated. In the brain, circadian clocks regulate neuronal physiological functions, including neuronal activity, synaptic plasticity, protein expression, and neurotransmitter release which in turn affect mood-related behaviors via cell-type specific mechanisms. Both animal and human studies have revealed an association between circadian misalignment and mood disorders and suggest that internal temporal desynchrony might be part of the etiology of psychiatric disorders. To date, little work has been conducted associating mood-related phenotypes to cell-specific effects of the circadian clock disruptions. In this review, we discuss existing literature on how clock-driven changes in specific neuronal cell types might disrupt phase relationships among cellular communication, leading to neuronal circuit dysfunction and changes in mood-related behavior. In addition, we examine cell-type specific circuitry underlying mood dysfunction and discuss how this circuitry could affect circadian clock. We provide a focus for future research in this area and a perspective on chronotherapies for mood and anxiety disorders.