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Light is a fundamental aspect of the environment, enabling animals to perceive and respond to visual stimuli as well as regulating circadian rhythms in physiology and behaviour. We have a good understanding of the rod and cone photoreceptors mediating vision, and work over the last 25 years has identified an additional retinal photoreceptor that regulates circadian rhythms and many other non-visual processes. This consists of a subset of intrinsically photosensitive retinal ganglion cells (ipRGCs) expressing the blue light sensitive protein melanopsin. To address these differences in visual and circadian responses to light, in humans, standards have been introduced to provide lighting units based upon the different photoreceptors involved. By contrast, lighting in laboratory animal facilities is still based on human vision and not the experience of the animals. Recent guidelines have, for the first time, provided the tools to measure light based upon the differing visual sensitivity of laboratory species such as mice (Mus musculus). Here, we provide an overview of why this is important, for both science and animal welfare, and how researchers and animal care staff can apply these new methods in their work. For the first time, this provides refinement opportunities to optimise lighting based on the animal’s experience of their light environment.
Although commonly accepted depressive subtypes reflect phenotypic differences, there has been minimal progress in identification of discrete pathophysiological pathways, biomarkers or differential therapeutic approaches to effectively guide clinical management.
Aims
To test the biological validity and clinical utility of a circadian subtype of depression on the basis of clinical course, differential medication response (self-reported) and genetic risk profile.
Method
Cross-sectional data were drawn from the nationwide Australian Genetics of Depression Study. Participants were classified as having a ‘circadian’ or ‘non-circadian’ subtype of depression on the basis of meeting criteria for at least three binary circadian-associated features: social jetlag, seasonality, delayed sleep midpoint, evening chronotype, morning tiredness and hypersomnia. Clinical course characteristics were compared. Associations with response to commonly prescribed antidepressants and polygenic risk scores for mental disorders and sleep, circadian, metabolic and inflammatory traits were investigated using logistic regression models.
Results
A total of 2604 participants (23%; 80% female; mean age 37.87 ± 13.62 years) had a circadian subtype. They reported an earlier age at onset (P < 0.001), more severe clinical features including (hypo)manic-like and psychotic-like experiences, suicidality, psychological distress and somatic complaints (all P < 0.001), weight gain during depressive episodes (P < 0.001), poorer response to selective serotonin reuptake inhibitors (odds ratio 0.88 [95% CI 0.82, 0.94]) and serotonin–noradrenaline reuptake inhibitors (odds ratio 0.89 [95% CI 0.83, 0.97]), and more side-effects compared with those with a non-circadian subtype. Having a circadian subtype was associated with higher polygenic risk scores for attention-deficit hyperactivity disorder (odds ratio 1.11 [95% CI 1.06, 1.17]), major depression (odds ratio 1.11 [95% CI 1.06, 1.16]), anxiety (odds ratio 1.10 [95% CI 1.04, 1.15]), bipolar disorder (odds ratio 1.09 [95% CI 1.04, 1.14]), body mass index (odds ratio 1.09 [95% CI 1.05, 1.14]), triglycerides (odds ratio 1.10 [95% CI 1.06, 1.16]), interleukin-6 (odds ratio 1.08 [95% CI 1.03, 1.13]), higher insulin resistance (odds ratio 1.08 [95% CI 1.04, 1.13]), later sleep midpoint (odds ratio 1.15 [95% CI 1.10, 1.21]), insomnia (odds ratio 1.08 [95% CI 1.03, 1.13]) and later chronotype (odds ratio 0.68 [95% CI 0.65, 0.71]).
Conclusions
These findings support the face validity and potential clinical utility of a circadian subtype of depression as a clinical profile. Pending independent replication, investigation of its biology and predictive utility are warranted.
This chapter explores four brain-based models of general hunger (i.e., hunger for any palatable food). The first is the energy control model (or homeostatic account), where a departure from the usual level (historically a set point) of some index of bodily fuel status (carbohydrate, fat, or protein) causes a compensatory response, namely an increase or decrease in hunger. The second is the biological agent account, where release of an agent centrally or peripherally (e.g., ghrelin) causes hunger. The third is the excitation-inhibition account, where hunger arises from tipping the balance towards excitation, with these processes instantiated in the neuroanatomy and neurochemistry of the brain. The fourth model, which could be included in the third, is the circadian account, namely that one cause of hunger arises from the brain’s time-keeping mechanisms. The strengths, and often the fundamental weaknesses of each accounts, are presented. This discussion provides the basis for why a psychological model involving learning and memory is necessary for a causal explanation of hunger, and how this can be successfully integrated with brain-based models.
The quality and quantity of nutrition are well-established factors influencing health. However, research on circadian rhythms has revealed that the timing of nutrition is also crucial, as highlighted by the concept of time-restricted feeding (TRF). In laboratory animals, TRF involves limiting daily energy intake to a consistent window of 8–12 h. This approach has been shown to mitigate, and in some cases reverse, the negative metabolic impacts of an obesogenic diet. Specifically, under such diets, TRF has been found to reduce body weight and adiposity; enhance liver, heart and gut health; improve glucose tolerance and blood pressure; decrease the severity of neurodegenerative diseases; and preserve muscle mass and function. When animals are fed a balanced diet, TRF does not lead to significant weight loss but modestly extends lifespan. Moreover, when combined with calorie restriction, TRF can significantly increase median lifespan. Thus, TRF can work synergistically with optimal nutrition quality and quantity to enhance health. The underlying mechanisms of TRF are being uncovered through studies in mice and fruit flies. These studies systematically examine mRNA, proteins and metabolites during the fed and fasted states of TRF, shedding light on the genes and pathways modulated by TRF in major metabolic organs, including the liver, heart, muscle, adipose tissue and gut. The aim of this review is to present the experiments that established TRF as a time-based nutritional intervention for health improvement and to summarise key molecular, physiological and metabolic findings from animal studies.
Host–parasite coevolution resulted in parasites optimizing their life cycle to obtain the most benefit from the host’s behaviour. In passerines, for instance, some parasite groups have found means to match their egg shedding rhythms with the hours of the day when hosts are most active. In other bird groups, such as shorebirds, whose active times are not determined by day–night cycles but by other external factors such as tidal or lunar cycles, it is not yet known whether their endoparasites exhibit any predictable pattern in their egg shedding rhythms. Here we used a simple wild-caught (captive) system, to provide a first approximation of the parasite egg shedding patterns in wintering Rufous-chested dotterels (Zonibyx modestus). We collected faeces every 2 hours over 10 days until completing a 24-hour cycle, which was coupled with continuous video recordings to determine their feeding and drinking habits. Contrary to our expectation, we showed that parasite egg shedding followed a cyclic pattern, characterized by 2 peaks: one at midnight and another in the afternoon. Importantly, this shedding pattern was not related to the birds’ feeding or drinking habits. We discuss possible environmental and physiological cues that parasites might use to trigger egg production, including the potential influence of tidal cycles on our results.
Increasing daylight exposure might be a simple way to improve mental health. However, little is known about daylight-symptom associations in depressive disorders.
Methods
In a subset of the Australian Genetics of Depression Study (N = 13,480; 75% female), we explored associations between self-reported number of hours spent in daylight on a typical workday and free day and seven symptom dimensions: depressive (overall, somatic, psychological); hypo-manic-like; psychotic-like; insomnia; and daytime sleepiness. Polygenic scores for major depressive disorder (MDD); bipolar disorder (BD); and schizophrenia (SCZ) were calculated. Models were adjusted for age, sex, shift work status, employment status, season, and educational attainment. Exploratory analyses examined age-stratified associations (18–24 years; 25–34 years; 35–64 years; 65 and older). Bonferroni-corrected associations (p < 0.004) are discussed.
Results
Adults with depression reported spending a median of one hour in daylight on workdays and three hours on free days. More daylight exposure on workdays and free days was associated with lower depressive (overall, psychological, somatic) and insomnia symptoms (p’s<0.001), but higher hypo-manic-like symptoms (p’s<0.002). Genetic loading for MDD and SCZ were associated with less daylight exposure in unadjusted correlational analyses (effect sizes were not meaningful). Exploratory analyses revealed age-related heterogeneity. Among 18–24-year-olds, no symptom dimensions were associated with daylight. By contrast, for the older age groups, there was a pattern of more daylight exposure and lower insomnia symptoms (p < 0.003) (except for 25–34-year-olds on free days, p = 0.019); and lower depressive symptoms with more daylight on free days, and to some extent workdays (depending on the age-group).
Conclusions
Exploration of the causal status of daylight in depression is warranted.
Hickie et al. (2023) pose the question “Are sleep and circadian rhythm disturbances (SCRD) the cause or simply the consequence of depression or other mood disorder sub-types?” and suggest strategies to better understand the role of SCRD in depression. Here, we contribute to the discussion by highlighting state-of-the-art computational omics methods (and the data sets needed to use these methods) which have potential for improving our understanding of the role of circadian biology in mood disorders.
This editorial summarises the clinical relevance of ‘chronopsychiatry’, defined as the interface between circadian science and mental health science. Chronopsychiatry represents a move towards time-variable perspectives on neurobiology and symptoms, with a greater emphasis on chronotherapeutic interventions.
The objective was to examine associations between social jetlag and diet quality among young adults in the US using nationally representative data from the 2017–2018 NHANES survey, and evaluate effect modification by gender and race/ethnicity. Social jetlag was considered ≥2-hour difference in sleep midpoint (median of bedtime and wake time) between weekends and weekdays. Diet quality was assessed with the Healthy Eating Index (HEI)-2015 and its 13 dietary components. Ordinal logistic models were run with diet scores binned into tertiles as the outcome. Models accounted for potential confounders and survey weights. Effect modification by gender and race/ethnicity was examined. The study sample included 1,356 adults aged 20–39 years. 31% of young adults had social jetlag. Overall, there were no associations between social jetlag and diet quality. However, interaction analysis revealed several associations were race-specific (P, interaction<0.05). Among Black adults, social jetlag was associated with lower overall diet quality (OR = 0.4, 95% CI 0.2, 0.8; i.e. less likely to be in higher diet quality tertiles) and more unfavourable scores on Total Vegetables (OR = 0.6, 95% CI 0.3, 1.0) and Added Sugar (i.e. OR = 0.6, 95% CI 0.4, 0.9). For Hispanic adults, social jetlag was associated with worse scores for Sodium (OR = 0.6, 95% CI 0.4, 0.9) However, White adults with social jetlag had better scores of Greens and Beans (OR = 1.9, 95% CI 1.1, 3.2). Within a nationally representative sample of US young adults, social jetlag was related to certain indicators of lower diet quality among Black and Hispanic Americans.
Circadian dysfunction is a core feature of bipolar disorder and may be due, at least in part, to abnormalities of non-visual photoreception. We critically review the evidence for light hypersensitivity in bipolar disorder and discuss how this may shape future research and clinical innovation, with a focus on a possible novel mechanism of action for lithium.
Artificial light at night (ALAN) puts major pressure on the natural environment. There are five main ways of mitigating its biological impacts: avoidance of using ALAN, minimizing ALAN use, restoring or rehabilitating areas from ALAN, and offsetting the use of ALAN. Their potential effectiveness can be better understood through careful consideration of how organisms respond to light. Here we focus particularly on responses to altering recurring natural periods of light and darkness that affect the internal clock of organisms. All clocks are light sensitive and, depending on the photoreceptors of the organism, they show maximal responsiveness to different wavelengths, from UV to near infrared. Moreover, they show a high light-sensitivity, with a threshold at about intensities occurring during full moon or even less. This suggests that minimizing the use of ALAN through dimming of emissions and reducing the daily periods for which those lamps are in use may provide valuable benefits. However, if the biological effects of ALAN are to be widely reduced additional measures will need to be taken, including strengthening protection of the remaining dark spaces, reducing numbers of existing lights and restoring darkness in previously lit areas, and extensive shielding of those lights that are retained.
Energy intake, utilization, and storage are critical to an animal’s health and fitness. The circadian clock organizes a variety of behavioral, physiological, and molecular processes to anticipate and optimize metabolic function. From behaviors such as the timing of feeding, to molecular interactions with the Clock gene, humans and other animals have evolved to coordinate metabolic processes to a 24-hour day. Thus, when circadian rhythms are disrupted or misaligned, an animal’s ability to anticipate and optimize metabolic processes is compromised. As discussed in this chapter, disruptions to circadian rhythmicity can result in adverse effects on body mass regulation and glucose homeostasis. Because these effects often present in parallel, this chapter organizes its discussion into two sections highlighting work from both clinical and preclinical animal studies. This approach allows one to appreciate the importance of circadian rhythmicity to metabolic wellbeing while introducing mechanistic explanations for how circadian disruption impacts body mass and glucose regulation.
Environmental light-dark cycles play an important role in behavioural and physiological processes. It is essential that laboratory vivaria be designed to properly control the light conditions in which laboratory mice are housed; however, this is not universally the case. Some laboratory vivarium doors are designed with windows, which allow light from the hallways to leak into the housing space during the rodents’ dark phase. Personnel entering and exiting the housing space during the dark phase can also create excessive light leak from brightly illuminated hallways. In this study, we investigated the hypothesis that exposure to dim light at night, as commonly experienced in many laboratory rodent housing spaces, alters mouse (Mus musculus) behaviour. We specifically analysed patterns of locomotor activity, anxiety- and depressive-like responses. Exposure to dim (5 lux) light at night altered home-cage locomotor activity and increased anxiety and some depressive responses among laboratory mice. These results suggest that light conditions can alter mouse behaviour and potentially influence experimental outcomes. Increased care should be taken to properly control light-dark conditions for laboratory animals.
Parasites display a wide range of behaviours that are frequently overlooked in favour of host responses. Understanding these behaviours can improve parasite control through a more precise application or development of new behaviour-based strategies. In aquaculture fish lice are an ongoing problem, infections reduce fishery production and control options are limited. Fish lice are distinct in their ability to survive and swim off hosts, allowing the transmission to multiple fish hosts across their lifespan. Here we assessed the off-host behaviour of Argulus foliaceus (a freshwater fish louse) and observed a diurnal rhythmical pattern in their behaviour. This pattern was lost when lice were exposed to constant darkness, indicating that the behaviour is not endogenously driven. Males were consistently active in light with reduced activity in darkness. In contrast, females were active during light and dark phases with peak activity at the start of dark periods. A. foliaceus was also strongly attracted to a light stimulus, preferring white- and blue-coloured lights over green- or red-coloured lights. Light is a strong driver of fish louse activity and could be used to trap parasites. Aquaculture light regimes could also be altered to reduce parasite attraction and activity.
Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. Around 25-50% of these children suffered from some kind of sleep disorder especially with chronic form of insomnia. Nowadays, we know that there is a noticeable relationship between ADHD and sleep disorders and by improving these children's sleep, not only the daily functions of them improve, but also the symptoms of ADHD maybe become better. This research evaluates the effects of melatonin on improvement of Sleep quality in children with ADHD whom received Ritalin
Method
Participants included 22 children suffered ADHD and concomitant sleep problems patients who underwent melatonin prescription and placebo at night in two sequencial periods. The effects of the melatonin were compared with placebo on the sleep problem improvements in each one.
Results
Although sleep onset, total sleep time and sleep quality advanced with melatonin, wake up time and the time to go to bed had not significant difference between the melatonin and placebo group. In addition, there were significant effects on attention, hyper activity index and impulsivity of the patients in the melatonin group.
Conclusion
Melatonin advanced circadian rhythms of sleep-wake and not only enhanced total time asleep in children with ADHD and chronic sleep onset insomnia, but also can improve the quality of life of these patients.
Obesity and excess bodyweight are highly prevalent in individuals with bipolar disorders (BD) and are associated with adverse consequences. Multiple factors may explain increased bodyweight in BD including side effects of psychotropic medications, and reduced physical activity. Research in the general population demonstrates that sleep disturbances may also contribute to metabolic burden. We present a cross-sectional study of the associations between body mass index (BMI) and sleep parameters in patients with BD as compared with healthy controls (HC).
Methods:
Twenty-six French outpatients with remitted BD and 29 HC with a similar BMI completed a 21-day study of sleep parameters using objective (actigraphy) and subjective (PSQI: Pittsburgh Sleep Quality Index) assessments.
Results:
In BD cases, but not in HC, higher BMI was significantly correlated with lower sleep efficiency (P = 0.009) and with several other sleep parameters: shorter total sleep time (P = 0.01), longer sleep onset latency (P = 0.05), higher fragmentation index (P = 0.008), higher inter-day variability (P = 0.05) and higher PSQI total score (P = 0.004).
Conclusions:
The findings suggest a link between a high BMI and several sleep disturbances in BD, including lower sleep efficiency. Physiological mechanisms in BD cases may include an exaggeration of phenomena observed in non-clinical populations. However, larger scale studies are required to clarify the links between metabolic and sleep-wake cycle disturbances in BD.
This study evaluated the potential of circadian measures as early markers of mood disorders subtypes. Patients with bipolar disorders had significantly lower levels and later onset of melatonin secretion than those with unipolar depression. Furthermore, abnormal phase angles between sleep, melatonin and temperature were found in several patients.
Sleep and mood are known to be linked and this is particularly evident in people with a diagnosis of bipolar disorder (BD). It has been proposed that psychological interventions improving sleep can be a pathway for improving mood. In order for a psychological sleep intervention to be appropriate, the common cognitive processes maintaining the range of sleep disturbances need to be investigated.
Aim:
This study aimed to explore and identify expert consensus on positive and negative sleep appraisals in the context of low and high mood states, using the Integrative Cognitive Model as a theoretical guide.
Method:
A Delphi approach was utilized to allow clinical and research professionals, with experience in the field of BD, to be anonymously consulted about their views on sleep appraisals. These experts were invited to participate in up to three rounds of producing and rating statements that represented positive and negative sleep appraisals.
Results:
A total of 38 statements were developed and rated, resulting in a final list of 19 statements that were rated as ‘essential’ or ‘important’ by >80% of the participants. These statements represent the full range of extreme sleep appraisals this study had set out to explore, confirming the importance of better understanding and identifying positive and negative sleep cognitions in the context of high and low mood.
Conclusion:
The statements reviewed in this study will be used to inform the development of a sleep cognition measure that may be useful in cognitive therapy addressing sleep disturbances experienced along the bipolar spectrum.
For over a decade a transdiagnostic clinical staging framework for youth with anxiety, mood and psychotic disorders (linked with measurement of multidimensional outcomes), has been utilised in over 8,000 young people presenting to the enhanced primary (headspace) and secondary care clinics of the Brain and Mind Centre of the University of Sydney. This framework has been evaluated alongside a broad range of other clinical, neurobiological, neuropsychological, brain imaging, circadian, metabolic, longitudinal cohort and controlled intervention studies. This has led to specific tests of its concurrent, discriminant and predictive validity. These extensive data provide strong preliminary evidence that: i) varying stages of illness are associated with predicted differences in a range of independent and objectively measured neuropsychological and other biomarkers (both cross-sectionally and longitudinally); and, ii) that earlier stages of illness progress at variable rates to later and more severe or persistent disorders. Importantly, approximately 15-20% of those young people classed as stage 1b or ‘attenuated’ syndromes at presentation progress to more severe or persistent disorders. Consequently, this cohort should be the focus of active secondary prevention trials. In clinical practice, we are moving to combine the staging framework with likely pathophysiological paths (e.g. neurodevelopmental-psychotic, anxiety-depression, circadian-bipolar) to underpin enhanced treatment selection.
For over a decade a transdiagnostic clinical staging framework for youth with anxiety, mood and psychotic disorders (linked with measurement of multidimensional outcomes), has been utilised in over 8,000 young people presenting to the enhanced primary (headspace) and secondary care clinics of the Brain and Mind Centre of the University of Sydney. This framework has been evaluated alongside a broad range of other clinical, neurobiological, neuropsychological, brain imaging, circadian, metabolic, longitudinal cohort and controlled intervention studies. This has led to specific tests of its concurrent, discriminant and predictive validity. These extensive data provide strong preliminary evidence that: i) varying stages of illness are associated with predicted differences in a range of independent and objectively measured neuropsychological and other biomarkers (both cross-sectionally and longitudinally); and, ii) that earlier stages of illness progress at variable rates to later and more severe or persistent disorders. Importantly, approximately 15-20% of those young people classed as stage 1b or ‘attenuated’ syndromes at presentation progress to more severe or persistent disorders. Consequently, this cohort should be the focus of active secondary prevention trials. In clinical practice, we are moving to combine the staging framework with likely pathophysiological paths (e.g. neurodevelopmental-psychotic, anxiety-depression, circadian-bipolar) to underpin enhanced treatment selection.