Dynamical state transitions into addictive behaviour and their early-warning signals

Application of early warning signs to physiological contexts: a comparison of multivariate indices in patients on long-term hemodialysis

Early warnings signs (EWSs) can anticipate abrupt changes in system state, known as "critical transitions," by detecting dynamic variations, including increases in variance, autocorrelation (AC), and cross-correlation. Numerous EWSs have been proposed; yet no consensus on which perform best exists. Here, we compared 15 multivariate EWSs in time series of 763 hemodialyzed patients, previously shown to present relevant critical transition dynamics. We calculated five EWSs based on AC, six on variance, one on cross-correlation, and three on AC and variance. We assessed their pairwise correlations, trends before death, and mortality predictive power, alone and in combination. Variance-based EWSs showed stronger correlations (r = 0.663 ± 0.222 vs. 0.170 ± 0.205 for AC-based indices) and a steeper increase before death. Two variance-based EWSs yielded HR95 > 9 (HR95 standing for a scale-invariant metric of hazard ratio), but combining them did not improve the area under the receiver-operating curve (AUC) much compared to using them alone (AUC = 0.798 vs. 0.796 and 0.791). Nevertheless, the AUC reached 0.825 when combining 13 indices. While some indicators did not perform overly well alone, their addition to the best performing EWSs increased the predictive power, suggesting that indices combination captures a broader range of dynamic changes occurring within the system. It is unclear whether this added benefit reflects measurement error of a unified phenomenon or heterogeneity in the nature of signals preceding critical transitions. Finally, the modest predictive performance and weak correlations among some indices call into question their validity, at least in this context.

Emodiversity evaluation of remote workers through health monitoring based on intra-day emotion sampling

Introduction

In recent years, the widespread shift from on-site to remote work has led to a decline in employees' mental health. Consequently, this transition to remote work poses several challenges for both employees and employers. To address these challenges, there is an urgent need for techniques to detect declining mental health in employees' daily lives. Emotion-based health assessment, which examines emotional diversity (emodiversity) experienced in daily life, is a possible solution. However, the feasibility of emodiversity remains unclear, especially from the perspectives of its applicability to remote workers and countries other than Europe and the United States. This study investigated the association between subjective mental health decline and emotional factors, such as emodiversity, as well as physical conditions, in remote workers in Japan.

Method

To explore this association, we conducted a consecutive 14-day prospective observational experiment on 18 Japanese remote workers. This experiment comprised pre-and post-questionnaire surveys, physiological sensing, daytime emotion self-reports, and subjective health reports at end-of-day. In daytime emotion self-reports, we introduced smartphone-based experience sampling (also known as ecological momentary assessment), which is suitable for collecting context-dependent self-reports precisely in a recall bias-less manner. For 17 eligible participants (mean ± SD, 39.1 ± 9.1 years), we evaluated whether and how the psycho-physical characteristics, including emodiversity, changed on subjective mental health-declined experimental days after analyzing descriptive statistics.

Results

Approximately half of the experimental days (46.3 ± 18.9%) were conducted under remote work conditions. Our analysis showed that physical and emotional indices significantly decreased on mental health-declined days. Especially on high anxiety and depressive days, we found that emodiversity indicators significantly decreased (global emodiversity on anxiety conditions, 0.409 ± 0.173 vs. 0.366 ± 0.143, p = 0.041), and positive emotional experiences were significantly suppressed (61.5 ± 7.7 vs. 55.5 ± 6.4, p < 0.001).

Discussion

Our results indicated that the concept of emodiversity can be applicable even to Japanese remote workers, whose cultural background differs from that of individuals in Europe and the United States. Emodiversity showed significant associations with emotion dysregulation-related mental health deterioration, suggesting the potential of emodiversity as useful indicators in managing such mental health deterioration among remote workers.

Sex- and age-specific effects on the development of addiction and compulsive-like drinking in rats

BACKGROUND

Biological factors are known to influence disease trajectories and treatment effectiveness in alcohol addiction and preclinical and clinical evidence suggests that sex is an important factor influencing disease dynamics in alcohol dependence. Another critical factor is age at first intoxicating drink, which has been identified as a risk factor for later alcohol binging. Preclinical research allows prospective monitoring of rodents throughout the lifespan, providing very detailed information that cannot be acquired in humans. Lifetime monitoring in rodents can be conducted under highly controlled conditions, during which one can systematically introduce multiple biological and environmental factors that impact behaviors of interest.

METHODS

Here, we used the alcohol deprivation effect (ADE) rat model of alcohol addiction in a computerized drinkometer system, acquiring high-resolution data to study changes over the course of addictive behavior as well as compulsive-like drinking in cohorts of adolescent vs. adult as well as male vs. female rats.

RESULTS

Female rats drank more alcohol than male rats during the whole experiment, drinking much more weak alcohol (5%) and similar amounts of stronger alcohol solutions (10%, 20%); female rats also consumed more alcohol than male rats during quinine taste adulteration. Increased consumption in females compared to males was driven by larger access sizes of alcohol. Differences in circadian patterns of movement were observed between groups. Early age of onset of drinking (postnatal day 40) in male rats had surprisingly little impact on the development of drinking behavior and compulsivity (quinine taste adulteration) when compared to rats that started drinking during early adulthood (postnatal day 72).

CONCLUSIONS

Our results suggest that there are sex-specific drinking patterns, not only in terms of total amount consumed, but specifically in terms of solution preference and access size. These findings provide a better understanding of sex and age factors involved in the development of drinking behavior, and can inform the preclinical development of models of addiction, drug development and exploration of options for new treatments.

Early warnings for multi-stage transitions in dynamics on networks

Successfully anticipating sudden major changes in complex systems is a practical concern. Such complex systems often form a heterogeneous network, which may show multi-stage transitions in which some nodes experience a regime shift earlier than others as an environment gradually changes. Here we investigate early warning signals for networked systems undergoing a multi-stage transition. We found that knowledge of both the ongoing multi-stage transition and network structure enables us to calculate effective early warning signals for multi-stage transitions. Furthermore, we found that small subsets of nodes could anticipate transitions as well as or even better than using all the nodes. Even if we fix the network and dynamical system, no single best subset of nodes provides good early warning signals, and a good choice of sentinel nodes depends on the tipping direction and the current stage of the dynamics within a multi-stage transition, which we systematically characterize.

Alcohol solution strength preference predicts compulsive-like drinking behavior in rats

BACKGROUND

Understanding compulsive drinking behavior is key to improving outcomes in the treatment of addiction. In the present study, we investigated compulsive-like drinking in alcohol-addicted rats using the alcohol deprivation effect (ADE) model of relapse behavior, which involves repeated deprivation and reintroduction phases; the latter approximate relapse.

METHODS

High-resolution longitudinal drinking and locomotor data were measured while rats (n = 30) underwent a four-bottle (water, 5%, 10%, 20% alcohol v/v) free-choice ADE paradigm. Alcohol bottles were adulterated with the bitter compound quinine during a reintroduction phase to test for compulsive behavior. We characterized how drinking and locomotor behavior during ADE + quinine differed from a regular ADE and how, at the individual level, behavioral parameters extracted from the regular ADE related to compulsive-like drinking. Associations of drinking with locomotor activity were also examined.

RESULTS

In the ADE with quinine, we observed reduced consumption of alcohol and a shift to preference for stronger alcohol. Quinine acted by decreasing both the access size and frequency of drinking of 5% alcohol while increasing the frequency of consumption of 20% alcohol. Preference for higher alcohol concentrations prior to the quinine challenge was associated with greater compulsive-like drinking behavior; higher baseline consumption of 20% alcohol correlated with more drinking of quinine-adulterated solutions while high frequency and amount of 5% alcohol consumption at baseline were correlated with being more strongly affected by quinine. Associations between locomotor activity and drinking behavior were observed at the hourly level. These associations reflected changing preferences across experimental phases.

CONCLUSION

Drinking patterns, and specifically solution preference, may offer insights into the presentation of compulsive-like drinking. The findings provide a preclinical basis for observations from epidemiological studies that link higher risk and burden of alcohol-related disease to stronger alcohol concentrations and encourage further translational studies to better understand the underlying mechanisms.

Predictive Modeling of Mental Illness Onset Using Wearable Devices and Medical Examination Data: Machine Learning Approach

The prevention and treatment of mental illness is a serious social issue. Prediction and intervention, however, have been difficult because of lack of objective biomarkers for mental illness. The objective of this study was to use biometric data acquired from wearable devices as well as medical examination data to build a predictive model that can contribute to the prevention of the onset of mental illness. This was an observational study of 4,612 subjects from the health database of society-managed health insurance in Japan provided by JMDC Inc. The inputs to the predictive model were 3-months of continuous wearable data and medical examinations within and near that period; the output was the presence or absence of mental illness over the following month, as defined by insurance claims data. The features relating to the wearable data were sleep, activity, and resting heart rate, measured by a consumer-grade wearable device (specifically, Fitbit). The predictive model was built using the XGBoost algorithm and presented an area-under-the-receiver-operating-characteristic curve of 0.712 (SD = 0.02, a repeated stratified group 10-fold cross validation). The top-ranking feature importance measure was wearable data, and its importance was higher than the blood-test values from medical examinations. Detailed verification of the model showed that predictions were made based on disrupted sleep rhythms, mild physical activity duration, alcohol use, and medical examination data on disrupted eating habits as risk factors. In summary, the predictive model showed useful accuracy for grouping the risk of mental illness onset, suggesting the potential of predictive detection, and preventive intervention using wearable devices. Sleep abnormalities in particular were detected as wearable data 3 months prior to mental illness onset, and the possibility of early intervention targeting the stabilization of sleep as an effective measure for mental illness onset was shown.

Female mice are more prone to develop an addictive-like phenotype for sugar consumption

The concept of “sugar addiction” is gaining increasing attention in both the lay media and scientific literature. However, the concept of sugar addiction is controversial and only a few studies to date have attempted to determine the “addictive” properties of sugar using rigorous scientific criteria. Here we set out to systematically test the addictive properties of sugar in male and female mice using established paradigms and models from the drug addiction field. Male and female C57BL/6N (8–10 weeks old) were evaluated in 4 experimental procedures to study the addictive properties of sugar: (i) a drinking in the dark (DID) procedure to model sugar binging; (ii) a long-term free choice home cage drinking procedure measuring the sugar deprivation effect (SDE) following an abstinence phase; (iii) a long-term operant sugar self-administration with persistence, motivation and compulsivity measures and (iv) intracranial self-stimulation (ICSS). Female mice were more vulnerable to the addictive properties of sugar than male mice, showing higher binge and long-term, excessive drinking, a more pronounced relapse-like drinking following deprivation, and higher persistence and motivation for sugar. No sex differences were seen in a compulsivity test or reward sensitivity measured using ICSS following extended sugar consumption. This study demonstrates the occurrence of an addictive-like phenotype for sugar in male and female mice, similar to drugs of abuse, and suggests sex-dependent differences in the development of sugar addiction.

Translational approach to understanding momentary factors associated with alcohol consumption

Multiple interindividual and intra-individual factors underlie variability in drinking motives, challenging clinical translatability of animal research and limiting treatment success of substance use-related problems. Intra-individual variability refers to time-dependent continuous and discrete changes within the individual and in substance use research is studied as momentary variation in the internal states (craving, stressed, anxious, impulsive and tired) and response to external triggers (stressors, drug-associated environmental cues and social encounters). These momentary stimuli have a direct impact on behavioural decisions and may be triggers and predictors of substance consumption. They also present potential targets for real-time behavioural and pharmacological interventions. In this review, we provide an overview of the studies demonstrating different momentary risk factors associated with increased probability of alcohol drinking in humans and changes in alcohol seeking and consumption in animals. The review also provides an overview of pharmacological interventions related to every individual risk factor.

Flickering of cardiac state before the onset and termination of atrial fibrillation

Complex dynamical systems can shift abruptly from a stable state to an alternative stable state at a tipping point. Before the critical transition, the system either slows down in its recovery rate or flickers between the basins of attraction of the alternative stable states. Whether the heart critically slows down or flickers before it transitions into and out of paroxysmal atrial fibrillation (PAF) is still an open question. To address this issue, we propose a novel definition of cardiac states based on beat-to-beat (RR) interval fluctuations derived from electrocardiogram data. Our results show the cardiac state flickers before PAF onset and termination. Prior to onset, flickering is due to a "tug-of-war" between the sinus node (the natural pacemaker) and atrial ectopic focus/foci (abnormal pacemakers), or the pacing by the latter interspersed among the pacing by the former. It may also be due to an abnormal autonomic modulation of the sinus node. This abnormal modulation may be the sole cause of flickering prior to termination since atrial ectopic beats are absent. Flickering of the cardiac state could potentially be used as part of an early warning or screening system for PAF and guide the development of new methods to prevent or terminate PAF. The method we have developed to define system states and use them to detect flickering can be adapted to study critical transition in other complex systems.

Addiction Research Consortium: Losing and regaining control over drug intake (ReCoDe)-From trajectories to mechanisms and interventions

One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.

Drinking Levels and Profiles of Alcohol Addicted Rats Predict Response to Nalmefene

Background: Pharmacotherapeutic options supporting the treatment of alcohol dependence are recommended and available but underutilized, partly due to questions about efficacy. Nalmefene, a μ-opioid receptor antagonist and partial kappa receptor agonist, is recommended for reduction of alcohol consumption, but evidence about its effectiveness has been equivocal; identifying factors which predict response will help optimize treatment.

Methods: The alcohol deprivation effect paradigm is a tightly controlled procedure comprising repeated deprivation and reintroduction phases, leading to increased preference for alcohol; reintroduction approximates relapse. Using a digital drinkometer system measuring high-resolution drinking behavior, we examined the effects of nalmefene on relapse drinking behavior in alcohol addicted rats. We also tested whether drinking behavior in the relapse phase prior to nalmefene administration predicted treatment response. We further examined whether longitudinal drinking behavior and locomotor activity predicted treatment response.

Results: Our results showed that nalmefene (0.3 mg/kg) reduced relapse-like consumption significantly (∼20%) compared to vehicle on the first 2 days of alcohol reintroduction. Examining the first 6 h of a preceded treatment-free relapse episode revealed drinking patterns clustering the rats into responders (reduction of >40%, n = 17) and non-responders (reduction of <40%, n = 7) to subsequent nalmefene treatment. During the first 6 h of the preceding relapse phase, responders consumed more alcohol than non-responders; the amount of alcohol consumed during each drinking approach was larger but frequency of drinking did not differ. Longitudinal drinking behavior and locomotor activity did not significantly predict response.

Conclusion: Our results suggest that nalmefene reduces alcohol intake during a relapse-like situation but effectiveness can differ greatly at the individual level. However, who responds may be informed by examining drinking profiles and rats that show high drinking levels prior to treatment are more likely to respond to nalmefene.

Dynamical state transitions into addictive behaviour and their early-warning signals

The theory of critical transitions in complex systems (ecosystems, climate, etc.), and especially its ability to predict abrupt changes by early-warning signals based on analysis of fluctuations close to tipping points, is seen as a promising avenue to study disease dynamics. However, the biomedical field still lacks a clear demonstration of this concept. Here, we used a well-established animal model in which initial alcohol exposure followed by deprivation and subsequent reintroduction of alcohol induces excessive alcohol drinking as an example of disease onset. Intensive longitudinal data (ILD) of rat drinking behaviour and locomotor activity were acquired by a fully automated drinkometer device over 14 weeks. Dynamical characteristics of ILD were extracted using a multi-scale computational approach. Our analysis shows a transition into addictive behaviour preceded by early-warning signals such as instability of drinking patterns and locomotor circadian rhythms, and a resultant increase in low frequency, ultradian rhythms during the first week of deprivation. We find evidence that during prolonged deprivation, a critical transition takes place pushing the system to excessive alcohol consumption. This study provides an adaptable framework for processing ILD from clinical studies and for examining disease dynamics and early-warning signals in the biomedical field.