Seven-day human biological rhythms: An expedition in search of their origin, synchronization, functional advantage, adaptive value and clinical relevance

Autonomic biosignals, seizure detection, and forecasting

Wearable devices have attracted significant attention in epilepsy research in recent years for their potential to enhance patient care through improved seizure monitoring and forecasting. This narrative review presents a detailed overview of the current clinical state of the art while addressing how devices that assess autonomic nervous system (ANS) function reflect seizures and central nervous system (CNS) state changes. This includes a description of the interactions between the CNS and the ANS, including physiological and epilepsy-related changes affecting their dynamics. We first discuss technical aspects of measuring autonomic biosignals and considerations for using ANS sensors in clinical practice. We then review recent seizure detection and seizure forecasting studies, highlighting their performance and capability for seizure detection and forecasting using devices measuring ANS biomarkers. Finally, we address the field's challenges and provide an outlook for future developments.

The menstrual cycle is influenced by weekly and lunar rhythms

OBJECTIVE

To study whether the menstrual cycle has a circaseptan (7 days) rhythm and whether it is associated with the lunar cycle (also defined as the synodic month, it is the cycle of the phases of the Moon as seen from Earth, averaging 29.5 days in length).

DESIGN

Cross-sectional study.

SUBJECTS

A total of 35,940 European and North American women aged 18-40 years.

EXPOSURE

Data were collected in real-life conditions.

INTERVENTION

No intervention was performed.

MAIN OUTCOME MEASURE

The onset of menstruation was assessed in prospectively measured menstrual cycles (311,064 cycles) over 3 full years (2019-2021). Associations were calculated between the onset of menstruation and the day of the week, and between the onset of menstruation and the lunar phase.

RESULTS

In this large data set, a circaseptan (7-day) rhythmicity of menstruation was observed, with a peak (acrophase) of menstrual onset on Thursdays and Fridays. This circaseptan rhythm was observed in every age group, in every phase of the lunar cycle, and in all seasons. This feature was most pronounced for cycle durations between 27 and 29 days. In winter, the circaseptan rhythm was found in cycles of 27-29 days, but not in other cycle lengths. A circalunar rhythm was also statistically significant, but not as clearly defined as the circaseptan rhythm. The peak (acrophase) of the circalunar rhythm of menstrual onset varied according to the season. In addition, there was a small but statistically significant interaction between the circaseptan rhythm and the lunar cycle.

CONCLUSION

Although relatively small in amplitude, the weekly rhythm of menstruation was statistically significant. Menstruation occurs more often on Thursdays and Fridays than on other days of the week. This is particularly true for women whose cycles last between 27 and 29 days. Circalunar rhythmicity was also statistically significant. However, it is less pronounced than the weekly rhythm.

Seizure occurrence is linked to multiday cycles in diverse physiological signals

OBJECTIVE

The factors that influence seizure timing are poorly understood, and seizure unpredictability remains a major cause of disability. Work in chronobiology has shown that cyclical physiological phenomena are ubiquitous, with daily and multiday cycles evident in immune, endocrine, metabolic, neurological, and cardiovascular function. Additionally, work with chronic brain recordings has identified that seizure risk is linked to daily and multiday cycles in brain activity. Here, we provide the first characterization of the relationships between the cyclical modulation of a diverse set of physiological signals, brain activity, and seizure timing.

METHODS

In this cohort study, 14 subjects underwent chronic ambulatory monitoring with a multimodal wrist-worn sensor (recording heart rate, accelerometry, electrodermal activity, and temperature) and an implanted responsive neurostimulation system (recording interictal epileptiform abnormalities and electrographic seizures). Wavelet and filter-Hilbert spectral analyses characterized circadian and multiday cycles in brain and wearable recordings. Circular statistics assessed electrographic seizure timing and cycles in physiology.

RESULTS

Ten subjects met inclusion criteria. The mean recording duration was 232 days. Seven subjects had reliable electroencephalographic seizure detections (mean = 76 seizures). Multiday cycles were present in all wearable device signals across all subjects. Seizure timing was phase locked to multiday cycles in five (temperature), four (heart rate, phasic electrodermal activity), and three (accelerometry, heart rate variability, tonic electrodermal activity) subjects. Notably, after regression of behavioral covariates from heart rate, six of seven subjects had seizure phase locking to the residual heart rate signal.

SIGNIFICANCE

Seizure timing is associated with daily and multiday cycles in multiple physiological processes. Chronic multimodal wearable device recordings can situate rare paroxysmal events, like seizures, within a broader chronobiology context of the individual. Wearable devices may advance the understanding of factors that influence seizure risk and enable personalized time-varying approaches to epilepsy care.

Common multi-day rhythms in smartphone behavior

The idea that abnormal human activities follow multi-day rhythms is found in ancient beliefs on the moon to modern clinical observations in epilepsy and mood disorders. To explore multi-day rhythms in healthy human behavior our analysis includes over 300 million smartphone touchscreen interactions logging up to 2 years of day-to-day activities (N401 subjects). At the level of each individual, we find a complex expression of multi-day rhythms where the rhythms occur scattered across diverse smartphone behaviors. With non-negative matrix factorization, we extract the scattered rhythms to reveal periods ranging from 7 to 52 days - cutting across age and gender. The rhythms are likely free-running - instead of being ubiquitously driven by the moon - as they did not show broad population-level synchronization even though the sampled population lived in northern Europe. We propose that multi-day rhythms are a common trait, but their consequences are uniquely experienced in day-to-day behavior.

Variability of Mortality: Additional Information on Mortality and Morbidity Curves under Normal and Pathological Conditions [Commentary on the Article by A. G. Malygin “Programmed Risks of Death in Male Patients with Diabetes” Published in Biochemistry (Moscow), vol. 86, pp. 1553-1562 (2021)]

Analysis of demographic data indicates uneven distribution of mortality within a year, month, and even week time period. This is of great practical importance for the operation of medical institutions, including intensive care units, and makes it possible to calculate economic and labor requirements of medical institutions. All the above is especially relevant during the era of the COVID-19 pandemic. Malygin showed the presence of one to two fluctuations per week in the mortality of male patients with type 2 diabetes. The height of the peaks of such fluctuations is determined, as expected, by the regular parameter indicating their position on the axis of lifespan and random parameter reflecting adverse effects of external environmental factors on the body, as well as the extent of the periodically occurring sharp decrease in the nonspecific resistance. This article discusses results of recent research in the field of small (semi-weekly, weekly, monthly, and seasonal) fluctuations of mortality. Based on a large array of accumulated data, it can be concluded that the decrease in seasonal variability of mortality accompanies an increase in the life expectancy. Studying characteristics of mortality fluctuations makes it possible to move from investigating the impact of biorhythms (Master Clock) on the development of acute and chronic phenoptotic processes directly to studying the patterns of mortality rhythms themselves (rhythms of phenoptosis).

About-Weekly Pattern in the Dynamic Complexity of a Healthy Subject's Cellular Immune Activity: A Biopsychosocial Analysis

In a previous integrative single-case study, we collected biological, psychological and social time-series data on a 25-year-old healthy woman over the course of 126 12-h intervals (63 days) and used urinary neopterin as an indicator of cellular immune activity [Schubert et al. 2012 (1)]. The present re-evaluation introduced Dynamic Complexity (DC) as an additional non-linear and non-stationary measure to further investigate the subject's biopsychosocial dynamics during the study. The new time series dealing with urinary neopterin complexity revealed a cyclic, circaseptan (about-weekly) repeating pattern (6.59 days). The only weekly reoccurring events over the course of the study that were associated with this immunological pattern were the in-depth interviews with the subject (mean distance between interviews: 6.5 days). Superposed epoch analysis (SEA) revealed a U-shaped relation between neopterin complexity and interviews, with a decrease in neopterin complexity before and during interviews and an increase after interviews. Furthermore, the complexity scores for irritation, anxiousness/depressiveness and mental activity were positively correlated with neopterin complexity. The results suggest that the interviews, which had been found to be related to the subject's need for educational and/or social accomplishment, were marked by stress (decrease in psycho-immunological flexibility and adaptability), which was then relieved after the interviews (increase in psycho-immunological flexibility and adaptability). It appears that the subject's cellular immune activity, as indicated by neopterin complexity, functionally mirrored the emotional meaning she ascribed to the in-depth interviews. This re-evaluation is in line with the view that biopsychosocial research requires multimodal analysis of single cases based on qualitative (e.g., in-depth interviews) and quantitative (e.g., time series analysis) data under conditions of "life as it is lived".

Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study

Background

Circadian and multiday rhythms are found across many biological systems, including cardiology, endocrinology, neurology, and immunology. In people with epilepsy, epileptic brain activity and seizure occurrence have been found to follow circadian, weekly, and monthly rhythms. Understanding the relationship between these cycles of brain excitability and other physiological systems can provide new insight into the causes of multiday cycles. The brain-heart link has previously been considered in epilepsy research, with potential implications for seizure forecasting, therapy, and mortality (i.e., sudden unexpected death in epilepsy).

Methods

We report the results from a non-interventional, observational cohort study, Tracking Seizure Cycles. This study sought to examine multiday cycles of heart rate and seizures in adults with diagnosed uncontrolled epilepsy (N=31) and healthy adult controls (N=15) using wearable smartwatches and mobile seizure diaries over at least four months (M=12.0, SD=5.9; control M=10.6, SD=6.4). Cycles in heart rate were detected using a continuous wavelet transform. Relationships between heart rate cycles and seizure occurrence were measured from the distributions of seizure likelihood with respect to underlying cycle phase.

Findings

Heart rate cycles were found in all 46 participants (people with epilepsy and healthy controls), with circadian (N=46), about-weekly (N=25) and about-monthly (N=13) rhythms being the most prevalent. Of the participants with epilepsy, 19 people had at least 20 reported seizures, and 10 of these had seizures significantly phase locked to their multiday heart rate cycles.

Interpretation

Heart rate cycles showed similarities to multiday epileptic rhythms and may be comodulated with seizure likelihood. The relationship between heart rate and seizures is relevant for epilepsy therapy, including seizure forecasting, and may also have implications for cardiovascular disease. More broadly, understanding the link between multiday cycles in the heart and brain can shed new light on endogenous physiological rhythms in humans.

Funding

This research received funding from the Australian Government National Health and Medical Research Council (investigator grant 1178220), the Australian Government BioMedTech Horizons program, and the Epilepsy Foundation of America's ‘My Seizure Gauge’ grant.

Twitter, time and emotions

The study of temporal trajectories of emotions shared in tweets has shown that both positive and negative emotions follow nonlinear circadian (24 h) and circaseptan (7-day) patterns. But to this point, such findings could be instrument-dependent as they rely exclusively on coding using the Linguistic Inquiry Word Count. Further, research has shown that self-referential content has higher relevance and meaning for individuals, compared with other types of content. Investigating the specificity of self-referential material in temporal patterns of emotional expression in tweets is of interest, but current research is based upon generic textual productions. The temporal variations of emotions shared in tweets through emojis have not been compared to textual analyses to date. This study hence focuses on several comparisons: (i) between Self-referencing tweets versus Other topic tweets, (ii) between coding of textual productions versus coding of emojis, and finally (iii) between coding of textual productions using different sentiment analysis tools (the Linguistic Inquiry and Word Count-LIWC; the Valence Aware Dictionary and sEntiment Reasoner-VADER and the Hu Liu sentiment lexicon-Hu Liu). In a collection of more than 7 million Self-referencing and close to 18 million Other topic content-coded tweets, we identified that (i) similarities and differences in terms of shape and amplitude can be observed in temporal trajectories of expressed emotions between Self-referring and Other topic tweets, (ii) that all tools feature significant circadian and circaseptan patterns in both datasets but not always, and there is often a correspondence in the shape of circadian and circaseptan patterns, and finally (iii) that circadian and circaseptan patterns obtained from the coding of emotional expression in emojis sometimes depart from those of the textual analysis, indicating some complementarity in the use of both modes of expression. We discuss the implications of our findings from the perspective of the literature on emotions and well-being.

Alcohol and melatonin

Investigation of the pathogenesis of alcoholism in humans using different methodological approaches has facilitated detection of important biological factors of consequent metabolic diseases, endocrine disorders, and other medical conditions, such as alcoholic cardiomyopathy, alcoholic hypertension, heart and vascular lesions, alcoholic liver disease, alcoholic pancreatitis, etc. Alcohol abuse leads to damage to the nervous system, which can result in neurological and mental disorders, including alcoholic polyneuropathy, psychosis, and alcohol dementia. The complexity and versatility of the harmful effects of regular alcohol consumption on the human body can be considered in the perspective of a chronobiological approach, because alcohol is chronotoxic to biological processes. As a rhythm regulator, melatonin exerts a wide range of different effects: circadian rhythm regulation, thermoregulation, sleep induction, antioxidant, immunomodulatory, and anti-stress ones. This review presents from a chronobiological perspective the impact of melatonin on alcohol intoxication in terms of mental disorders, sleep and inflammation, hepatic injury, and mitochondrial function. It discusses the main clinical effects of melatonin on alcohol injury and the main targets as a therapy for alcohol disorders. Chronobiological effects of ethanol are related to melatonin suppression that has been associated with, among others, cancer risk. Exogenous melatonin seems to be a promising hepato- and immune-protector due to its antioxidant and anti-inflammatory properties, which in combination with other medicines makes it useful to prevent alcoholic organ damage. The reason for the scientific interest in melatonin as a treatment for alcoholism is obvious; the number of cases of this pathology that gives rise to metabolic syndrome, and its subsequent transformation into steatohepatitis, liver fibrosis, and cirrhosis, is increasing worldwide. Melatonin not only exerts antioxidant effects but it exerts various other effects contributing to the management of liver conditions. This review discusses the interaction between normal and pathological processes caused by alcohol consumption and the relationship between alcohol and melatonin in these conditions.

Cyclic stroke mortality variations follow sunspot patterns

Background: Mapping time-structures is a burgeoning scientific field enriching the (P4) medicine models. Local evidence in Mediterranean populations is underinvestigated. Methods: The Censused stroke-related death events (D) in the largest East-Mediterranean port (Piraeus), during (1985-1989), when local population had diet (low fat/sugar, proteins and vegetables/fruits daily, and pure olive oil almost exclusively) and genetic homogeneity-later interrupted by the immigration into Greece in 1990; and Sunspot numbers were indexed by Wolf numbers (Rz) (1944-2004), and evaluated using Fast Fourier Analysis and Singular Spectrum Analysis in MATLAB. Results: D were turned with fluctuations >35% in Rz. A non-anthropogenic 6.8 days cycle was recognized. Conclusions: This study may be taken into consideration in future public health planning and chronotherapy evaluations.

Oscillatory Dynamics in Infectivity and Death Rates of COVID-19

The analysis of systematically collected data for coronavirus disease 2019 (COVID-19) infectivity and death rates has revealed, in many countries around the world, a typical oscillatory pattern with a 7-day (circaseptan) period. Additionally, in some countries, 3.5-day (hemicircaseptan) and 14-day periodicities have also been observed. Interestingly, the 7-day infectivity and death rate oscillations are almost in phase, showing local maxima on Thursdays/Fridays and local minima on Sundays/Mondays. These observations are in stark contrast to a known pattern correlating the death rate with the reduced medical staff in hospitals on the weekends. While we cannot exclude the possibility that a significant portion of the observed oscillations is associated with the reporting of the individual cases, other reasons might contribute at least partly to these data. One possible hypothesis addressing these observations is that they reflect gradually increasing stress with the progressing week, which can trigger the higher death rates on Thursdays/Fridays. Moreover, assuming the weekends provide the likely time for new infections, the maximum number of new cases might fall, again, on Thursdays/Fridays. These observations deserve further study to provide a better understanding of COVID-19 dynamics.IMPORTANCE The infectivity and death rates for COVID-19 have been observed in many countries around the world as well as in the collective data of the whole world. These oscillations show distinct circaseptan periodicity, which could be associated with numerous biological reasons as well as with improper reporting of the data collected. Since very different results are observed in different countries and even continents, such as Sweden (very significant oscillations) or India (almost no oscillations), these data provide a very important message about different conditions under which the disease is spread or is reported, which, in turn, could serve as guidance tools in future epidemics. It is necessary that follow-up studies track the observed differences and fully reliably address their origins.

Rhythmicity of health information behaviour

Purpose

This paper brings focus and attention to the aspect of time within health information behaviour. The purpose of this paper is to critically assess and present strengths and weaknesses of utilising the infodemiology approach and metrics as a novel way to examine temporal variations and patterns of online health information behaviour. The approach is shortly exemplified by presenting empirical evidence for temporal patterns of health information behaviour on different time-scales.

Design/methodology/approach

A short review of online health information behaviour is presented and methodological barriers to studying the temporal nature of this behaviour are emphasised. To exemplify how the infodemiology approach and metrics can be utilised to examine temporal patterns, and to test the hypothesis of existing rhythmicity of health information behaviour, a brief analysis of longitudinal data from a large discussion forum is analysed.

Findings

Clear evidence of robust temporal patterns and variations of online health information behaviour are shown. The paper highlights that focussing on time and the question of when people engage in health information behaviour can have significant consequences.

Practical implications

Studying temporal patterns and trends for health information behaviour can help in creating optimal interventions and health promotion campaigns at optimal times. This can be highly beneficial for positive health outcomes.

Originality/value

A new methodological approach to study online health information behaviour from a temporal perspective, a phenomenon that has previously been neglected, is presented. Providing evidence for rhythmicity can complement existing epidemiological data for a more holistic picture of health and diseases, and their behavioural aspects.

Working Time Society consensus statements: Circadian time structure impacts vulnerability to xenobiotics-relevance to industrial toxicology and nonstandard work schedules

The circadian time structure (CTS) has long been the subject of research in occupational medicine, but not to industrial toxicology, including methods of setting threshold limit values (TLVs) and employee biological monitoring. Numerous animal and human investigations document vulnerability to chemical, contagion, and other xenobiotics varies according to the circadian time of encounter. Permanent and rotating nightshift personnel are exposed to industrial contaminants in the same or higher concentration as dayshift personnel, and because of incomplete CTS adjustment to night work, contact with contaminants occurs during a different biological time than day workers. Thus, the amount of protection afforded by certain TLVs, especially for employees of high-risk settings who work night and other nonstandard shift schedules, might be inadequate. The CTS seems additionally germane to procedures of employee biological monitoring in that high-amplitude 24 h rhythms in biomarkers indicative of xenobiotic exposure may result in misjudgment of health risks when data are not gathered in sufficient frequency over time and properly interpreted. Biological reference values time-qualified for their rhythmic variation, currently of interest to laboratory medicine practice, are seemingly important to industrial medicine as circadian time and work-shift specific biological exposure indices to improve surveillance of personnel, particularly those working nonstandard shift schedules.

First In Situ Identification of Ultradian and Infradian Rhythms, and Nocturnal Locomotion Activities of Four Colonies of Red Wood Ants ( Formica rufa-Group)

In situ activity patterns of 2 Formica rufa-group species ( F. pratensis; F. polyctena) were continuously studied at 4 different red wood-ant nests for 6 months in each of the years 2010, 2011, 2012, and 2016 and related to weather factors and variations in the Earth's magnetic field. The in situ activity patterns of both species were similarly periodic and exhibited ultradian, and short- and long infradian rhythms under natural LD conditions. Crepuscular and nocturnal activities shorter than or equal to 4 h were observed in both species, especially at the new moon and first quarter after the astronomical twilight in a period of darkness in fall. We hypothesize that local variability in the Earth's magnetic field affects these long-term activity patterns, whereas humidity and temperature were more strongly associated with ultradian rhythms (less than 20 h).

Circadian and circaseptan rhythms in human epilepsy: a retrospective cohort study

BACKGROUND

Epilepsy has long been suspected to be governed by cyclic rhythms, with seizure rates rising and falling periodically over weeks, months, or even years. The very long scales of seizure patterns seem to defy natural explanation and have sometimes been attributed to hormonal cycles or environmental factors. This study aimed to quantify the strength and prevalence of seizure cycles at multiple temporal scales across a large cohort of people with epilepsy.

METHODS

This retrospective cohort study used the two most comprehensive databases of human seizures (SeizureTracker [USA] and NeuroVista [Melbourne, VIC, Australia]) and analytic techniques from circular statistics to analyse patients with epilepsy for the presence and frequency of multitemporal cycles of seizure activity. NeuroVista patients were selected on the basis of having intractable focal epilepsy; data from patients with at least 30 clinical seizures were used. SeizureTracker participants are self selected and data do not adhere to any specific criteria; we used patients with a minimum of 100 seizures. The presence of seizure cycles over multiple time scales was measured using the mean resultant length (R value). The Rayleigh test and Hodges-Ajne test were used to test for circular uniformity. Monte-Carlo simulations were used to confirm the results of the Rayleigh test for seizure phase.

FINDINGS

We used data from 12 people from the NeuroVista study (data recorded from June 10, 2010, to Aug 22, 2012) and 1118 patients from the SeizureTracker database (data recorded from Jan 1, 2007, to Oct 19, 2015). At least 891 (80%) of 1118 patients in the SeizureTracker cohort and 11 (92%) of 12 patients in the NeuroVista cohort showed circadian (24 h) modulation of their seizure rates. In the NeuroVista cohort, patient 8 had a significant cycle at precisely 1 week. Two others (patients 1 and 7) also had approximately 1-week cycles. Patients 1 and 4 had 2-week cycles. In the SeizureTracker cohort, between 77 (7%) and 233 (21%) of the 1118 patients showed strong circaseptan (weekly) rhythms, with a clear 7-day period. Between 151 (14%) and 247 (22%) patients had significant seizure cycles that were longer than 3 weeks. Seizure cycles were equally prevalent in men and women, and peak seizure rates were evenly distributed across all days of the week.

INTERPRETATION

Our results suggest that seizure cycles are robust, patient specific, and more widespread than previously understood. They align with the accepted consensus that most epilepsies have some diurnal influence. Variations in seizure rate have important clinical implications. Detection and tracking of seizure cycles on a patient-specific basis should be standard in epilepsy management practices.

FUNDING

Australian National Health and Medical Research Council.

Perspectives on the relevance of the circadian time structure to workplace threshold limit values and employee biological monitoring

The circadian time structure (CTS) and its disruption by rotating and nightshift schedules relative to work performance, accident risk, and health/wellbeing have long been areas of occupational medicine research. Yet, there has been little exploration of the relevance of the CTS to setting short-term, time-weighted, and ceiling threshold limit values (TLVs); conducting employee biological monitoring (BM); and establishing normative reference biological exposure indices (BEIs). Numerous publications during the past six decades document the CTS substantially affects the disposition - absorption, distribution, metabolism, and elimination - and effects of medications. Additionally, laboratory animal and human studies verify the tolerance to chemical, biological (contagious), and physical agents can differ extensively according to the circadian time of exposure. Because of slow and usually incomplete CTS adjustment by rotating and permanent nightshift workers, occupational chemical and other contaminant encounters occur during a different circadian stage than for dayshift workers. Thus, the intended protection of some TLVs when working the nightshift compared to dayshift might be insufficient, especially in high-risk settings. The CTS is germane to employee BM in that large-amplitude predictable-in-time 24h variation can occur in the concentration of urine, blood, and saliva of monitored chemical contaminants and their metabolites plus biomarkers indicative of adverse xenobiotic exposure. The concept of biological time-qualified (for rhythms) reference values, currently of interest to clinical laboratory pathology practice, is seemingly applicable to industrial medicine as circadian time and workshift-specific BEIs to improve surveillance of night workers, in particular. Furthermore, BM as serial assessments performed frequently both during and off work, exemplified by employee self-measurement of lung function using a small portable peak expiratory flow meter, can easily identify intolerance before induction of pathology.