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Heart rate variability: Can it serve as a marker of mental health resilience?
Journal of Affective Disorders xxx (xxxx) xxx–xxx
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Mini review
Heart rate variability: Can it serve as a marker of mental health resilience? Giampaolo Pernaa,b,c,d, , Alice Rivab, Archie Defilloe, Erika Sangiorgiob, Maria Nobilef, Daniela Caldirolaa,b ⁎
a
Department of Biomedical Sciences, Humanitas University, 20090, Pieve Emanuele, Milan, Italy Department of Clinical Neurosciences, Hermanas Hospitalarias, Villa San Benedetto Menni Hospital, 22032, Albese con Cassano Como, Italy Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200, Maastricht, The Netherlands d Department of Psychiatry and Behavioral Sciences, Leonard Miller School of Medicine, Miami University, 33136 -1015, Miami, FL, USA e Medibio Limited, United States HQ, 8696 Eagle Creek Circle, Savage, MN 55378, USA f Scientific Institute IRCCS Eugenio Medea, Bosisio Parini 23842, Lecco, Italy b c
ABSTRACT
Background: Stress resilience influences mental well-being and vulnerability to psychiatric disorders. Usually, measurement of resilience is based on subjective reports, susceptible to biases. It justifies the need for objective biological/physiological biomarkers of resilience. One promising candidate as biomarker of mental health resilience (MHR) is heart rate variability (HRV). The evidence for its use was reviewed in this study. Methods: We focused on the relationship between HRV (as measured through decomposition of RR intervals from electrocardiogram) and responses to laboratory stressors in individuals without medical and psychiatric diseases. We conducted a bibliographic search of publications in the PubMed for January 2010–September 2018. Results: Eight studies were included. High vagally mediated HRV before and/or during stressful laboratory tasks was associated with enhanced cognitive resilience to competitive/self-control challenges, appropriate emotional regulation during emotional tasks, and better modulation of cortisol, cardiovascular and inflammatory responses during psychosocial/mental tasks. Limitations: All studies were cross-sectional, restricting conclusions that can be made. Most studies included only young participants, with some samples of only males or females, and a limited array of HRV indexes. Ecological validity of stressful laboratory tasks remains unclear. Conclusions: Vagally mediated HRV may serve as a global index of an individual's flexibility and adaptability to stressors. This supports the idea of HRV as a plausible, noninvasive, and easily applicable biomarker of MHR. In future longitudinal studies, the implementation of wearable health devices, able to record HRV in naturalistic contexts of real-life, may be a valuable strategy to gain more reliable insight into this topic.
1. Main body Resilience is a dynamic process wherein an organism displays a positive and functional adaptation in the face of stressful events and adversity, while preserving its stability. Resilience is a multidimensional construct involving physiological, psychological, and genetic mechanisms with inter-individual and domain-/time- dependent intra-individual heterogeneity (Carnevali et al., 2018a). Stress resilience influences mental health. High resilience has been associated with better mental well-being and lower vulnerability to psychiatric diseases, whereas low resilience confers increased risk of poorer mental well-being and development of affective/psychotic/post-traumatic stress disorders (Carnevali et al., 2018a). Usually, resilience is measured by subjective reports, susceptible to biases. Thus, introduction of objective biological/physiological biomarker of resilience is required (Walker et al., 2017).
One promising candidate as a biomarker of mental health resilience (MHR) is heart rate variability (HRV), which is the variation in time intervals between consecutive heartbeats (as measured through decomposition of RR intervals from electrocardiogram). HRV results from bidirectional heart-brain interactions, dynamic autonomic nervous system (ANS) processes, and other physiological influences, such as thermoregulation, renin-angiotensin system, and metabolic/hormonal mechanisms (Shaffer and Ginsberg, 2017). A variety of HRV indexes with different physiological origins exists, including time-domain/frequency-domain/non-linear measurements [for comprehensive overviews, please refer to Shaffer and Ginsberg (2017) and Laborde et al. (2017)]. HRV reflects the flexibility of the cardiovascular system to cope with sudden physical/psychological challenges to homeostasis. However, overlaps exist between cortico-subcortical networks that regulate autonomic adjustments and those that modulate emotions, behaviors, and cognition; therefore, HRV can be viewed as
⁎ Corresponding author at: Department of Clinical Neurosciences, Hermanas Hospitalarias, Villa San Benedetto Menni, Hospital, via Roma 16, Albese con Cassano 22032, Como, Italy. E-mail address: [email protected] (G. Perna).
https://doi.org/10.1016/j.jad.2019.10.017 Received 20 June 2019; Received in revised form 20 September 2019; Accepted 9 October 2019 Available online 12 October 2019 0165-0327/ © 2019 Elsevier B.V. All rights reserved.
Please cite this article as: Giampaolo Perna, et al., Journal of Affective Disorders, https://doi.org/10.1016/j.jad.2019.10.017
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the index of an individual's global capability to regulate psychophysiological responses in an adaptive way when facing stressors (Thayer et al., 2012). Indeed, certain associations were found between higher HRV and context-appropriate modulation of startle reactions, behavioral/self-reported emotional responses, and efficient handling of attentional/cognitive resources in individuals undergoing different laboratory tasks (Appelhans and Luecken, 2006; Thayer et al., 2009); moreover, a meta-analysis of neuroimaging studies found significant relationships between HRV and cerebral blood flow in a number of regions (e.g. the prefrontal cortex and amygdala) involved in responses to stressors and changing environment (Thayer et al., 2012). Current psychophysiological theories share the idea that the parasympathetic vagal tone may play a crucial role in regulation of allostatic systems, and they propose associations between higher parasympathetic tone and better regulation of energy exchange and immune system, cognitive performance, emotional control, social functioning, and global health (Laborde et al., 2017; Thayer and Sternberg, 2006). Hence, the HRV indexes that reflect the cardiac vagal tone [e.g. the high frequency (HF) band, and the root mean square of successive RR interval differences (RMSSD)] are expected to be particularly promising as biomarkers of MHR. In line with this, lower vagally mediated HRV was associated with psychiatric disorders (Carnevali et al., 2018a), and HF-HRV has been proposed as a potential transdiagnostic biomarker of mental illness (Beauchaine and Thayer, 2015). Furthermore, preliminary longitudinal findings revealed the development of post-deployment posttraumatic stress disorder symptomatology in individuals with reduced resting state HF power before combat deployment (Pyne et al., 2016). Similarly, reduced resting state RMSSD seemed to be prospectively involved in the development of depressive symptoms in healthy young individuals, over a three-year period (Carnevali et al., 2018b). An informative step in validating a putative biomarker of MHR is to assess its relationship with responses to laboratory stressors in individuals without concurrent psychopathologies (Walker et al., 2017). Therefore, to provide further empirical support to the idea of HRV as marker of MHR, in this brief review we summarized results of recent studies that provided HRV indexes (obtained through validated methods of signal recordings and calculation) in healthy individuals (i.e., without medical and psychiatric diseases; not taking medications that would alter HRV), aged ≥ 18 years, who underwent stressful laboratory tasks. We conducted a bibliographic search of the PubMed database for articles published between January 2010 and September 2018 using following keywords in combination: heart rate variability, resilience, stress, vulnerability, healthy. Eight studies that fitted in inclusion criteria were extracted and are summarized in Table 1.
greater self-capacity and lower opponents’ capacities compared with females and appraised the task as a challenge, displaying more active approach, whereas females appraised the task as a threat, displaying more cautious approach. Together, these findings indicate that greater heart rate flexibility reflects better coping strategies and successful outcomes in goal-relevant situations. Using the same task, Alacreu-Crespo and colleagues (2018) revealed that individuals with better decision-making skills have more adaptive cardiac autonomic response to competition, reflecting lower stress and better adaptability, with better vagal control during and after the task, which probably facilitated winning. The involvement of prefrontal cortex (PFC) both in decision-making and inhibitory control on cardiac autonomic system via vagus nerve (Smith et al., 2017) may explain the association between higher vagal control and better attentional and decision-making skills, a pattern resulting in more adaptive responses and higher resilience for coping with stress. A similar link between HRV, as measured with the standard deviation of NN intervals (SDNN index), and the self-control component of decision-making was found in a group of males who underwent dietary challenges (Maier and Hare, 2017). Individuals with higher resting SDNN were better at regulating their cravings in the face of taste temptations, thereby exerting improved dietary self-control. Additionally, during dietary challenges, these individuals displayed higher blood oxygen level-dependent activity and attenuated taste representations in the ventromedial PFC, a region involved in regulating autonomic responses and estimating subjective values of choice options. These findings suggest that higher resting SDNN may be a marker of neurophysiological adaptability that results in more efficient selfcontrol abilities in the face of environmental challenges. The SDNN index is thought to reflect all the components that contribute to HRV; however, SDNN is highly correlated with other indexes reflecting phasic vagal control (Maier and Hare, 2017) and, in short-time resting recordings used in this study, the primary source of SDNN seems to be the parasympathetic activity (Shaffer and Ginsberg, 2017). Overall, these studies reveal a link between flexibility of the autonomic system and resilience when facing mental stressors that involve different neuropsychological functions. The data indicated that higher HRV indexes, mainly those influenced by the vagal tone, reflect greater ability of deploying neuropsychological resources to successfully overcome stressful laboratory tasks, suggesting that vagally mediated HRV may serve as a proxy for cognitive resilience to competitive stress and self-control challenges. 1.2. HRV and emotion regulation Two further studies (Nasso et al., 2019; Rombold-Bruehl et al., 2017), explored the association between HRV patterns and regulation of emotional responses involved in the adaptability to changing environmental conditions and in mental well-being. In a female cohort studied by Nasso and colleagues (2017), the use of an adaptive emotion regulation (ER) (i.e., positive reappraisal) in anticipation of a stressful situation (i.e., job interview preparation) was associated with higher vagal control during anticipation of, dealing with, and recovery from the stressful situation, when compared with maladaptive (i.e., catastrophizing) ER. This was particularly evident in females with low tendency to ruminate. These results suggest that individuals who positively reappraise are more successful at regulating their autonomic responses when dealing with a stressor, probably resulting in higher coping abilities than those who display maladaptive strategies. This favorable pattern may be interpreted as a result of reappraisal-induced proactive prefrontal activation with decreased amygdala activity and negative emotion, thus facilitating appropriate autonomic regulation in response to stress. In another cohort of females undergoing an experimental distressing film paradigm, associations were found between lower vagal HRV component at baseline (before the film) and higher burden with slower
1.1. HRV and neuropsychological function Of the eight studies, three (Abad-Tortosa et al., 2017; A. AlacreuCrespo et al., 2018; Maier and Hare, 2017) evaluated associations between HRV patterns and the ability to cope with stressful tasks that involved neuropsychological function, particularly attention/perception and decision-making. Abad-Tortosa and colleagues (2017) found that winners in a perception/attention task-competition displayed greater global autonomic reactivity (i.e. greater decrease of the R-R intervals) from baseline to task condition (i.e. values during task minus values during baseline), and greater global autonomic recovery (i.e. greater increase of the R-R intervals) post-task (i.e. values during post-task minus values during task), as compared with losers. Furthermore, winners displayed higher reactivity of the vagal HRV component (HF) from baseline to task condition than losers, with opposite trajectories depending on gender (i.e., increase in males and decrease in females); this probably reflected gender-based differences in coping strategies used to achieve successful outcomes, for which rates were equal in both genders. Males perceived 2
Main objective
Maier and Hare, 2017
AlacreuCrespo et al., 2018
To test whether greater baseline HRV would be associated with better dietary SC.
To investigate the association between HRV reactivity to a laboratory competition task and decision-making skills.
Neuropsychological function D. AbadTo analyze the patterns of Tortosa et al., autonomic reactivity 2017 associated with competition, its outcome, and situational appraisal.
Study
Table 1 Details of the selected studies.
3 N = =49 (all M, mean age: 21.2 ± 2 years) from general population, randomly assigned to either stress group (n = =27) or CG (n = =22).
N = =116 (44 F) university students were classified into GD or PD on the basis of performances on IGT. Subsequently, they underwent a stress task either in a competitive (EG) [N = =86, 43 winners (14 F, mean age: 21.92 ± 0.48 years), 43 losers (14 F, mean age: 21.61 ± 0.46 years)] or non-competitive (CG) (N = =30, 16 F, mean age: 21.45 ± 0.56 years) condition.
N = =112 (46 M, mean age: 22.37 ± 0.5 years; 66 F, mean age: 21.23 ± 0.38 years) university students. Competitive condition (EG): 37 winners, 40 losers; non-competitive condition (CG): 35 participants.
Sample
HRV measures: time domain (ms), HRVtot measured as SDNN. Recording at rest before the task.
R-R intervals recorded via POLAR RS800cx watch and HR monitor chest belt.
R-R intervals recorded via POLAR RS800cx watch and HR monitor chest belt.
HRV analyzed in 5-min periods from baseline to post-task. HRV measures: time domain (ms), mean values of RR intervals; frequency domain (ms2, n.u., hz), HF, LF, and VLF components, HRVtot (sum of all the frequency bands), HF/HRVtot.
Stress task ("The letters squares", an attention/ visual perception task). Phase 1 (baseline): 10-min resting. Phase 2 (decisionmaking): IGT. Phase 3 (stress task): participants (same-sex dyads) randomly assigned to either a face-to-face competition (information given: winners would receive an economic reward) or a control condition (task explanation without mentioning competition or rewards). Phase 4 (post-task): 10-min resting.
Dietary SC challenge (decision-making task): participants had to choose the healthier of two food items presented on a screen. Two conditions: 1) conflict condition (SC challenge): the healthier item was the least tasty, 2) no-conflict condition (no-
R-R intervals recorded via 3electrodes ECG.
Instruments
HRV analyzed in 5-min periods from baseline to post-task. HRV measures: time domain (ms), mean values of RR intervals; frequency domain (n.u.), HF component.
HRV measures
Stress task ("The letters squares", an attention/ visual perception task). Participants (same-sex dyads) were randomly divided into EG (information given: winners would receive an economic reward), or CG (task explanation without mentioning competition or rewards). After the competition, subjects in the EG group were separated into winners or losers.
Task and Procedure
fMRI, STAI-trait, Three Factor Eating Questionnaire.
5-item scale (0 − 100) to characterize the perception of the competition.
Performance, blood pressure, selfadministered scales assessing situation appraisal, including selfand opponent-capacity, perceived feelings during the task, internal/external attribution of outcome.
Other measures R-R reactivity (task minus baseline) between baseline to task: greater decrease of R-R interval in winners compared to losers and CG, especially in men. R-R recovery (post-task minus task): higher in winner men compared to losers and CG. HF-HRV reactivity between baseline to task: significant HF increase in winner men, significant HF decrease in winner women. HRVtot reactivity (task minus baseline) and LF reactivity: lower in loser GD than in loser PD; lower in competing GD (winners and losers) than in GD in the CG. HRVtot recovery (post-task minus task) and LF recovery: higher in loser GD than in loser PD; higher in competing GD (winners and losers) than in GD in the CG. HF recovery: higher in loser GD than in GD in the CG. HF/HRVtot reactivity: higher in winner GD than in PD; higher in competing GD (winners and losers) than in GD in the CG; among losers, higher in GD than PD. HF/ HRVtot recovery: lower in winners GD than in PD and in the CG. Higher resting total HRV (SDNN index) were associated with greater SC success when facing dietary challenges (i.e. to choose the healthier option even when it was the less tasty).
Main results*
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Negative correlation between HRV and STAItrait. Higher HRV correlated with a decreased representation of taste attributes in the vmPFC
GD perceived higher effort than PD during the performance of the task.
Performance: equal in both genders. Systolic blood pressure changes between baseline and pre-task: significant increase in EG, significant decrease in CG. Situational appraisal: in EG, greater internal attribution ("own capacity") men than women; lower appreciation of the opponent's capacity in winner men than winner women.
Other findings of interest*
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RomboldBruehl et al., 2017
Emotion regulation Nasso et al., 2019
Study
Table 1 (continued)
To investigate whether HF and LF/HF ratio components of HRV at rest before stress would predict consecutive intrusive memories.
To investigate 1) the influence of adaptive (reappraisal) vs. maladaptive (catastophizing) anticipatory ER on autonomic nervous system during anticipation, stress and recovery phases, and 2) the moderating role of trait rumination.
Main objective
N = =60 (all F, mean age: 22.98 ± 3.17 years) university students.
N = =56 (all F, mean age: 21.76 ± 2.05 years) undergraduates, randomly assigned to either reappraisal (N = =29) or catastrophizing (N = =27) group.
Sample
ER task: participants had to simulate a job interview and their performance would be evaluated. Phase 1 (baseline): questionnaires, reading sentences of neutral content, job interview task instructions. Phase 2 (anticipatory ER): participants were told that they would undergo a guided stress management procedure to manage stress during the job interview and they were randomly assigned to either reappraisal or catastrophizing instructions. Sentences taken from the ER instructions were displayed on the screen and participants were asked to focus on their meaning. Phase 3 (actual stressor): preparation of the job interview while questions commonly asked during job interviews were displayed on the screen. Phase 4 (recovery): the experimenter stated the impossibility to perform the interview and participants were only asked to relax. Intrusion-inducing stressor: a validated experimental distressing film of a brutal rape that induces short-lasting intrusive symptoms. After the film, participants rated their distress. During the following 4
challenge): the healthier item was also the tastier. Approximately half of the trials was SC condition. Participants were scanned with fMRI during the task.
Task and Procedure
HRV measures: frequency domain (n.u.,%), HF, LF/HF ratio. 5-min recordings during baseline resting condition, 10 min prior to the stressor.
HRV measure: frequency domain (n.u.), HF component. Continuous monitoring from baseline to recovery.
HRV measures
R-R intervals recorded via POLAR RS800cx watch and HR monitor chest belt.
R-R intervals recorded via POLAR RS800X watch and HR monitor chest belt.
Instruments
STAI-trait, N of intrusive memories (online diary), rating of distress on a 7point Likert scale.
Self-reported trait rumination (RRS), affective responses (VAS).
Other measures
Women with low baseline HRV: 1) had more intrusive memories after the distressing film, and 2) displayed a slower recovery from the stressor. Specifically, lower baseline HF-HRV was associated to a higher
Higher HFnu in the reappraisal than in the catastrophizing group over all phases after baseline.
Main results*
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In low ruminators, reappraisal was associated with higher HFnu than catastrophizing. Only low ruminators showed a beneficial effect of anticipatory reappraisal on autonomic regulation.
Other findings of interest*
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Main objective
Weber et al., 2010
To investigate whether individuals with reduced resting HRV would display impaired cardiovascular, endocrine and immune recovery after acute mental stress.
Physiological regulation Pulopulos et al., To investigate whether 2018 changes in HRV during the anticipation of a stressful task were related to the cortisol response to a laboratory-based stress task.
Study
Table 1 (continued)
N = =44 (all M; mean age: 30 ± 7 years). Participants were divided into either high (N = =20) or low (N = =23) resting HRV based on a median split on resting RMSSD.
N = =171 (75 F, mean age: 29.98 ± 11.07 years). Participants were divided into cortisol responders (N = =70), who displayed a significant cortisol increase, and nonresponders (N = =101).
Sample
Mental stress tests: 1) manometer test, a standardized computerbased information processing task performed under time pressure; 2) mental arithmetic test, an increasingly difficult series of mental calculations with feedback on the performance. Phase 1 (baseline): 5-min resting. Phase 2 (stress 1): manometer test. Phase 3 (stress 2): mental arithmetic test. Phase 4 (recovery): 5-min resting.
Stress task (modified version of the TSST): a 5min videotaped speech (defending against an alleged transgression) and a 5-min mental arithmetic task. Phase 1 (baseline): 20-min resting and instructions on the TSST procedure. Phase 2 (anticipatory phase): preparation of the TSST. Phase 3 (stress task): administration of the TSST. Phase 4 (recovery phase): 50-min resting.
days, they assessed their intrusive memories.
Task and Procedure
HRV measures: timedomain (ms), RMSSD. Continuous monitoring from baseline to recovery. For each phase, mean of HRV was computed.
HRV measures: timedomain (ms,%), RMSSD, pNN50. Continuous monitoring from baseline to the first 15 min of the recovery phase.
HRV measures
ECG and finger blood pressure curves.
3-electrodes ECG and a respiratory band to measure respiration rate.
Instruments
Serum cortisol, cytokines (TNF-α, IL-6) measured before stress, immediately after the mental stress, 20 and 60 min after mental the stress. Blood pressure, heart rate: continuous monitoring from baseline to recovery. For each phase, mean of each variable was computed.
Cortisol levels (salivary samples) at baseline, 15 min after TSST, and every 10 min after until +65 min+). Three indexes of cortisol levels: 1) AUCi with respect to the increase; 2) cortisol reactivity (change from baseline to maximum level after the TSST); 3) cortisol recovery (decrease from the maximum level after the TSST to the last cortisol sample).
Other measures
In the whole group, HRV decreased from baseline to anticipation phase, and increased from the stress task to the recovery phase. A larger decrease in HRV during anticipation was related to higher cortisol AUCi and reactivity, after controlling for all the covariates. In the subgroup of cortisol responders, this relationship remained significant for cortisol reactivity, while, for cortisol AUCi, it became marginally significant after controlling for all the covariates. In the high resting HRV group: 1) higher overall HRV levels; 2) HRV decrease under stress (from resting to manometer test) and increase with recovery (from mental arithmetic test to resting) 3) cortisol increase during stress and decrease from stress to 20 min after stress; 4) significant TNF-α decrease from stress to 60 min after stress. In the low resting HRV group: 1) lower overall HRV levels; 2) no HRV changes across the phases; 3) higher and ongoing diastolic blood pressure increase under stress, with no post-stress recovery; 4) no cortisol decrease from stress to 20 min after stress; 5) no TNF-α decrease from stress to 20 min and 60 min after stress.
N of intrusive memories on day 1 and 2; higher baseline LF/HF ratio was associated with a higher N of intrusive memories on day 1.
Main results*
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In the whole sample, cortisol increase after stress was not statistically significant, while cortisol levels in the last 2 salivary samples were below baseline levels. Both in the whole group and in the subgroup of cortisol responders, the change in HRV specifically due to the stress task (i.e. change in HRV from anticipation to the stress task) was not related to the cortisol indexes. Neither anticipation-induced nor stress-induced changes in HRV were related to cortisol recovery. In the whole sample, blood pressure, heart rate, and cortisol levels significantly increased under stress.
Other findings of interest*
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To evaluate the relationships between HRV in response to a psychosocial stressor and circulating plasma TNF-α, IL-6 and CRP.
Woody et al., 2017
Task and Procedure Psychosocial stressor (speech task): mock job interview with performance evaluation. Phase 1 (resting and task instructions): questionnaire, rest period, instructions for the speech task. Phase 2 (anticipation): mental preparation for the speech. Phase 3 (stress): speech task. Phase 4 (rumination/distraction task): the participants were randomly assigned to either a rumination or distraction task. Phase 5 (resting): additional questionnaires and 45min resting.
Sample N = =34 (all F, mean age: 20.7 ± 2.3 years) undergraduate students. HRV measures: frequency domain (ms2,%), HF using both HF-FFT and HF-AR. Larger negative change HRV values (speech task minus phase 1 resting) indicated greater HRV reduction during the stressor.
HRV measures Three-lead ECG.
Instruments TNF-α, IL-6, CRP (blood samples) measured immediately pre-stressor and 60 min after stressor. Inflammatory responses were calculated by subtracting pre-stressor values from post-stressor (+60 min+) values.
Other measures When considering several covariates, greater HF-AR reduction during stress was associated with greater TNF-α and IL-6 responses, while greater HF-FFT reduction during stress was associated with greater IL-6 response.
Main results*
Other findings of interest*
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only significant results AR = autoregressive techniques, AUC = area under the curve, CG = control group, CRP = C-reactive protein, ECG = electrocardiogram, EG = experimental group, ER = emotion regulation, F = females, FFT = Fast Fourier Transformation, fMRI=functional magnetic resonance imaging, GD = good deciders (i.e. having good decision-making skills at the Iowa Gambling Task), HF = high frequency, a measure of parasympathetic vagal tone, HPA = hypothalamus-pituitary-adrenal axis, HRV(tot) = heart rate variability (total power), hz = hertz, IGT = Iowa Gambling Task, IL-6 = interleukin, LF = low frequency, a measure of both sympathetic and parasympathetic vagal tone, and baroreflex activity, LH/HF ratio, a measure of both sympathetic and parasympathetic vagal tone, and other unspecified factors, M = males, min = minute, ms = milliseconds, n = normalized, N = number, NN = interbeat intervals from which artifacts have been removed, nu = normalized units, PD = poor deciders (i.e. having good decision-making skills at the Iowa Gambling Task), pNN50 = percentage of successive R-R intervals, a measure of parasympathetic vagal tone, RMSSD = root mean square of successive R-R interval differences, a measure of parasympathetic vagal tone, RR = time interval between consecutive R-wave peaks, a measure of autonomic nervous system activity, RSS = Ruminative Responses Style Scale, SC = self-control, SDNN = standard deviation of NeN intervals, a measure of all the components that contribute to HRV; in short-time resting recordings it reflects parasympathetic vagal tone, STAI = State-Trait Anxiety Inventory, TNF-α = tumor necrosis factor, TSST = Trier Social Stress Test, VAS = Visual Analogue Scale, VLF = very low frequency, a measure of mixed, and uncertain, factors such as heart's intrinsic rhythm, parasympathetic vagal tone, sympathetic tone during physical activity, thermoregulation, renin-angiotensin system, vmPFC = ventromedial prefrontal cortex.
Main objective
Study
Table 1 (continued)
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decrease of intrusive memories for 4 days subsequently after watching the film (Rombold-Bruehl et al., 2017). These findings suggest that lower autonomic flexibility, ultimately resulting in a relative increase of sympathetic activity, enhances an individual's vulnerability to stress and contribute to the formation of intrusive memories after trauma (Gillie and Thayer, 2014). This is in line with preliminary associations between lower vagal HRV component before combat deployment and post-deployment post-traumatic stress disorder symptomatology (Pyne et al., 2016). Overall, these studies showed that higher vagally mediated HRV reflects greater abilities in reappraisal and emotion regulation when dealing with stressful emotional tasks. This suggests that vagal components of HRV may be a proxy for emotional resilience in the face of external stressors.
activity have been found to be associated with psychiatric disorders (McEwen, 2008). Overall, these studies indicated that higher vagally mediated HRV reflects better regulation of multiple physiological systems during adaptive allostatic stress responses, resulting in blunting of unnecessary physiological activation after stressor ends. This suggests that vagal components of HRV may be a proxy of autonomic, endocrine, and immune resilience in the face of stressful conditions. 1.4. Limitations and conclusions This research presents some limitations. Although most studies focused on vagally mediated HRV, they used different indexes and applied different transformation/calculation methods; higher consistency of the HRV indexes across future studies would provide more reliable and comparable results. Future studies should explore a wider array of HRV indexes as potential markers of resilience, including non-linear measurements. Dynamic non-linear ANS processes influence the HRV, and the variability of non-linear systems provides the flexibility to cope rapidly with changing environment; therefore, non-linear HRV indexes may provide additional information beyond the time-/frequency domain measures. In line with this, preliminary data indicated reduced non-linear indexes of cardiac flexibility during a laboratory-induced psychosocial stress paradigm in adolescents who developed symptoms of increasing anxiety over the subsequent 12 months, while no relationship was found using HF-HRV (de la Torre-Luque et al., 2017). Further, most studies included only young participants, with some samples of only males or females, and an unclear ecological validity of the stressful laboratory tasks. Finally, since all studies were cross-sectional, no conclusions could be drawn regarding future mental health trajectories of individuals with better or poorer HRV-task performance patterns. Therefore, future investigations should include wider age ranges, more homogeneous gender distribution, real-life challenges and stressors, and longitudinal mental health monitoring. Nowadays, advances in wearable health devices and applications have facilitated easy monitoring of multiple physiological signals, behaviors, and patientreported outcomes describing emotions during daily life. The implementation of these tools in future clinical and research studies may be a valuable strategy to gain better and reliable insight into the relationships between HRV and MHR in real-world contexts. In conclusion, HRV may be considered a global index of an individual's flexibility and ability to adapt to stress and challenges, as it reflects the efficiency of multiple aspects of physiological, emotional, and cognitive responses to stressors. Though additional research is needed, available evidence so far suggests that vagally mediated indexes of HRV may be plausible, noninvasive, and easily applicable biomarkers of MHR.
1.3. HRV and physiological regulation Three investigations (Pulopulos et al., 2018; Weber et al., 2010; Woody et al., 2017) focused on the association between HRV patterns and the physiological mechanisms involved in stress adaptability and mental consequences of stress exposure, such as cortisol, cardiovascular, and inflammatory responses. Pulopulos and colleagues (2018) established that high HRV indexes of vagal activity (RMSSD, pNN50) during anticipation of a stressful psychosocial task were associated with low stress-induced cortisol increase when individuals underwent the task, suggesting a positive vagal regulatory role on the hypothalamus–pituitary–adrenal (HPA) axis. This autonomic pattern during anticipation may represent an adaptive response allowing individuals to activate emotional/biological changes to successfully deal with the stressor. Therefore, it would reflect the ability to limit a disproportionate and/or persistent cortisol response to stress that may have detrimental effects on mental health (McEwen, 2008; Pinto et al., 2017). Next, in a cohort of males undergoing a standardized mental stress test, individuals with high resting vagally mediated HRV (RMSSD index) displayed higher overall HRV during the entire procedure, and appropriate modulation and post-stress recovery of cardiovascular, endocrine, and immune markers. Conversely, low resting HRV was associated with no changes of vagally mediated HRV during the procedure and impaired post-stress recovery of diastolic blood pressure, cortisol, and pro-inflammatory cytokine TNF-α (Weber et al., 2010). Finally, Woody and colleagues (2017), in a cohort of females, noticed that small reductions in vagal components of HRV during a stressful psychosocial task was associated with lower inflammatory reactivity 1 h after the stressor was applied, as measured by TNF-α and IL-6 level. This pattern of inflammatory reactivity may represent a favorable factor for mental health, considering that higher pro-inflammatory response to a psychosocial stressor increased the risk of developing depression in the ensuing months, in a preliminary female population (Aschbacher et al., 2012). These findings support an inhibitory role of the vagus in the regulation of allostatic systems, such as HPA axis and inflammation, in response to internal/external perturbations. The vagal connections between PFC and amygdala and between vagal nuclei in the medulla oblongata and the hypothalamus are considered to blunt excessive sympathoexcitatory responses to stress (Smith et al., 2017; Thayer et al., 2012). Likewise, the “cholinergic anti-inflammatory pathway” is considered to suppress pro-inflammatory cytokine release (Tracey, 2002), as supported by a recent meta-analysis that showed a negative relationship between vagal component of resting HRV and markers of inflammation (Williams et al., 2019). Consequently, an autonomic imbalance with reduced vagal components of HRV could reflect impaired physiological regulation when handling internal and/or environmental challenges, resulting in exaggerated stress responses and ultimately contributing to poor mental health outcomes. Accordingly, higher inflammatory markers and cortisol levels and sympathetic over-
Financial support The authors declare no funding. Disclosure Archie Defillo is a full time, paid employee (Chief Medical Officer) for Medibio LTD. Daniela Caldirola, Giampaolo Perna, Alice Riva, and Erika Sangiorgio are scientific consultants for Medibio LTD CRediT authorship contribution statement Giampaolo Perna: Conceptualization, Methodology, Supervision, Writing - review & editing. Alice Riva: Writing - original draft. Archie Defillo: Conceptualization, Methodology, Supervision, Writing - review & editing. Erika Sangiorgio: Writing - original draft. Maria Nobile: Conceptualization, Methodology, Supervision, Writing - review & editing. Daniela Caldirola: . 7
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Acknowledgements
response to stress: the influence of anticipatory emotion regulation strategies and trait rumination. Emotion 19, 443–454. Pinto, J.V., Moulin, T.C., Amaral, O.B., 2017. On the transdiagnostic nature of peripheral biomarkers in major psychiatric disorders: a systematic review. Neurosci. Biobehav. Rev. 83, 97–108. Pulopulos, M.M., Vanderhasselt, M.A., De Raedt, R., 2018. Association between changes in heart rate variability during the anticipation of a stressful situation and the stressinduced cortisol response. Psychoneuroendocrinology 94, 63–71. Pyne, J.M., Constans, J.I., Wiederhold, M.D., Gibson, D.P., Kimbrell, T., Kramer, T.L., Pitcock, J.A., Han, X., Williams, D.K., Chartrand, D., Gevirtz, R.N., Spira, J., Wiederhold, B.K., McCraty, R., McCune, T.R., 2016. Heart rate variability: pre-deployment predictor of post-deployment PTSD symptoms. Biol. Psychol. 121, 91–98. Rombold-Bruehl, F., Otte, C., Renneberg, B., Schmied, A., Zimmermann-Viehoff, F., Wingenfeld, K., Roepke, S., 2017. Lower heart rate variability at baseline is associated with more consecutive intrusive memories in an experimental distressing film paradigm. World J. Biol. Psychiatry 12, 1–6. Shaffer, F., Ginsberg, J.P., 2017. An overview of heart rate variability metrics and norms. Front. Public Health 5, 258. Smith, R., Thayer, J.F., Khalsa, S.S., Lane, R.D., 2017. The hierarchical basis of neurovisceral integration. Neurosci. Biobehav. Rev. 75, 274–296. Thayer, J.F., Ahs, F., Fredrikson, M., Sollers 3rd, J.J., Wager, T.D., 2012. A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neurosci. Biobehav. Rev. 36, 747–756. Thayer, J.F., Hansen, A.L., Saus-Rose, E., Johnsen, B.H., 2009. Heart rate variability, prefrontal neural function, and cognitive performance: the neurovisceral integration perspective on self-regulation, adaptation, and health. Ann. Behav. Med. 37, 141–153. Thayer, J.F., Sternberg, E., 2006. Beyond heart rate variability: vagal regulation of allostatic systems. Ann. N.Y. Acad. Sci. 1088, 361–372. Tracey, K.J., 2002. The inflammatory reflex. Nature 420, 853–859. Walker, F.R., Pfingst, K., Carnevali, L., Sgoifo, A., Nalivaiko, E., 2017. In the search for integrative biomarker of resilience to psychological stress. Neurosci. Biobehav. Rev. 74, 310–320. Weber, C.S., Thayer, J.F., Rudat, M., Wirtz, P.H., Zimmermann-Viehoff, F., Thomas, A., Perschel, F.H., Arck, P.C., Deter, H.C., 2010. Low vagal tone is associated with impaired post stress recovery of cardiovascular, endocrine, and immune markers. Eur. J. Appl. Physiol. 109, 201–211. Williams, D.P., Koenig, J., Carnevali, L., Sgoifo, A., Jarczok, M.N., Sternberg, E.M., Thayer, J.F., 2019. Heart rate variability and inflammation: a meta-analysis of human studies. Brain Behav. Immun. 80, 219–226. Woody, A., Figueroa, W.S., Benencia, F., Zoccola, P.M., 2017. Stress-Induced parasympathetic control and its association with inflammatory reactivity. Psychosom. Med. 79, 306–310.
The authors would like to thank Enago (www.enago.com) for the English language review. References Abad-Tortosa, D., Alacreu-Crespo, A., Costa, R., Salvador, A., Serrano, M.A., 2017. Sex differences in autonomic response and situational appraisal of a competitive situation in young adults. Biol. Psychol. 126, 61–70. Alacreu-Crespo, A., Costa, R., Abad-Tortosa, D., Salvador, A., Serrano, M.A., 2018. Good Decision-Making is Associated with an Adaptive Cardiovascular Response to Social Competitive Stress. Stress, Amsterdam, Netherlands, pp. 1–10. Appelhans, B.M., Luecken, L., 2006. Heart rate variability as an index of regulated emotional responding. Rev. Gen. Psychol. 10, 229–240. Aschbacher, K., Epel, E., Wolkowitz, O.M., Prather, A.A., Puterman, E., Dhabhar, F.S., 2012. Maintenance of a positive outlook during acute stress protects against proinflammatory reactivity and future depressive symptoms. Brain Behav. Immun. 26, 346–352. Beauchaine, T.P., Thayer, J.F., 2015. Heart rate variability as a transdiagnostic biomarker of psychopathology. Int. J. Psychophysiol. 98, 338–350. Carnevali, L., Koenig, J., Sgoifo, A., Ottaviani, C., 2018a. Autonomic and brain morphological predictors of stress resilience. Front. Neurosci. 12, 228. Carnevali, L., Thayer, J.F., Brosschot, J.F., Ottaviani, C., 2018b. Heart rate variability mediates the link between rumination and depressive symptoms: a longitudinal study. Int. J. Psychophysiol. 131, 131–138. de la Torre-Luque, A., Fiol-Veny, A., Bornas, X., Balle, M., Llabres, J., 2017. Impaired cardiac profile in adolescents with an increasing trajectory of anxiety when confronting an acute stressor. Eur. Child Adolesc. Psychiatry 26, 1501–1510. Gillie, B.L., Thayer, J.F., 2014. Individual differences in resting heart rate variability and cognitive control in posttraumatic stress disorder. Front. Psychol. 5, 758. Laborde, S., Mosley, E., Thayer, J.F., 2017. Heart rate variability and cardiac vagal tone in psychophysiological research—Recommendations for experiment planning, data analysis, and data reporting. Front. Psychol. 8, 213. Maier, S.U., Hare, T.A., 2017. Higher heart-rate variability is associated with ventromedial prefrontal cortex activity and increased resistance to temptation in dietary self-control challenges. J. Neurosci. 37, 446–455. McEwen, B.S., 2008. Central effects of stress hormones in health and disease: understanding the protective and damaging effects of stress and stress mediators. Eur. J. Pharmacol. 583, 174–185. Nasso, S., Vanderhasselt, M.A., Demeyer, I., De Raedt, R., 2019. Autonomic regulation in
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Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad
Mini review
Heart rate variability: Can it serve as a marker of mental health resilience? Giampaolo Pernaa,b,c,d, , Alice Rivab, Archie Defilloe, Erika Sangiorgiob, Maria Nobilef, Daniela Caldirolaa,b ⁎
a
Department of Biomedical Sciences, Humanitas University, 20090, Pieve Emanuele, Milan, Italy Department of Clinical Neurosciences, Hermanas Hospitalarias, Villa San Benedetto Menni Hospital, 22032, Albese con Cassano Como, Italy Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200, Maastricht, The Netherlands d Department of Psychiatry and Behavioral Sciences, Leonard Miller School of Medicine, Miami University, 33136 -1015, Miami, FL, USA e Medibio Limited, United States HQ, 8696 Eagle Creek Circle, Savage, MN 55378, USA f Scientific Institute IRCCS Eugenio Medea, Bosisio Parini 23842, Lecco, Italy b c
ABSTRACT
Background: Stress resilience influences mental well-being and vulnerability to psychiatric disorders. Usually, measurement of resilience is based on subjective reports, susceptible to biases. It justifies the need for objective biological/physiological biomarkers of resilience. One promising candidate as biomarker of mental health resilience (MHR) is heart rate variability (HRV). The evidence for its use was reviewed in this study. Methods: We focused on the relationship between HRV (as measured through decomposition of RR intervals from electrocardiogram) and responses to laboratory stressors in individuals without medical and psychiatric diseases. We conducted a bibliographic search of publications in the PubMed for January 2010–September 2018. Results: Eight studies were included. High vagally mediated HRV before and/or during stressful laboratory tasks was associated with enhanced cognitive resilience to competitive/self-control challenges, appropriate emotional regulation during emotional tasks, and better modulation of cortisol, cardiovascular and inflammatory responses during psychosocial/mental tasks. Limitations: All studies were cross-sectional, restricting conclusions that can be made. Most studies included only young participants, with some samples of only males or females, and a limited array of HRV indexes. Ecological validity of stressful laboratory tasks remains unclear. Conclusions: Vagally mediated HRV may serve as a global index of an individual's flexibility and adaptability to stressors. This supports the idea of HRV as a plausible, noninvasive, and easily applicable biomarker of MHR. In future longitudinal studies, the implementation of wearable health devices, able to record HRV in naturalistic contexts of real-life, may be a valuable strategy to gain more reliable insight into this topic.
1. Main body Resilience is a dynamic process wherein an organism displays a positive and functional adaptation in the face of stressful events and adversity, while preserving its stability. Resilience is a multidimensional construct involving physiological, psychological, and genetic mechanisms with inter-individual and domain-/time- dependent intra-individual heterogeneity (Carnevali et al., 2018a). Stress resilience influences mental health. High resilience has been associated with better mental well-being and lower vulnerability to psychiatric diseases, whereas low resilience confers increased risk of poorer mental well-being and development of affective/psychotic/post-traumatic stress disorders (Carnevali et al., 2018a). Usually, resilience is measured by subjective reports, susceptible to biases. Thus, introduction of objective biological/physiological biomarker of resilience is required (Walker et al., 2017).
One promising candidate as a biomarker of mental health resilience (MHR) is heart rate variability (HRV), which is the variation in time intervals between consecutive heartbeats (as measured through decomposition of RR intervals from electrocardiogram). HRV results from bidirectional heart-brain interactions, dynamic autonomic nervous system (ANS) processes, and other physiological influences, such as thermoregulation, renin-angiotensin system, and metabolic/hormonal mechanisms (Shaffer and Ginsberg, 2017). A variety of HRV indexes with different physiological origins exists, including time-domain/frequency-domain/non-linear measurements [for comprehensive overviews, please refer to Shaffer and Ginsberg (2017) and Laborde et al. (2017)]. HRV reflects the flexibility of the cardiovascular system to cope with sudden physical/psychological challenges to homeostasis. However, overlaps exist between cortico-subcortical networks that regulate autonomic adjustments and those that modulate emotions, behaviors, and cognition; therefore, HRV can be viewed as
⁎ Corresponding author at: Department of Clinical Neurosciences, Hermanas Hospitalarias, Villa San Benedetto Menni, Hospital, via Roma 16, Albese con Cassano 22032, Como, Italy. E-mail address: [email protected] (G. Perna).
https://doi.org/10.1016/j.jad.2019.10.017 Received 20 June 2019; Received in revised form 20 September 2019; Accepted 9 October 2019 Available online 12 October 2019 0165-0327/ © 2019 Elsevier B.V. All rights reserved.
Please cite this article as: Giampaolo Perna, et al., Journal of Affective Disorders, https://doi.org/10.1016/j.jad.2019.10.017
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the index of an individual's global capability to regulate psychophysiological responses in an adaptive way when facing stressors (Thayer et al., 2012). Indeed, certain associations were found between higher HRV and context-appropriate modulation of startle reactions, behavioral/self-reported emotional responses, and efficient handling of attentional/cognitive resources in individuals undergoing different laboratory tasks (Appelhans and Luecken, 2006; Thayer et al., 2009); moreover, a meta-analysis of neuroimaging studies found significant relationships between HRV and cerebral blood flow in a number of regions (e.g. the prefrontal cortex and amygdala) involved in responses to stressors and changing environment (Thayer et al., 2012). Current psychophysiological theories share the idea that the parasympathetic vagal tone may play a crucial role in regulation of allostatic systems, and they propose associations between higher parasympathetic tone and better regulation of energy exchange and immune system, cognitive performance, emotional control, social functioning, and global health (Laborde et al., 2017; Thayer and Sternberg, 2006). Hence, the HRV indexes that reflect the cardiac vagal tone [e.g. the high frequency (HF) band, and the root mean square of successive RR interval differences (RMSSD)] are expected to be particularly promising as biomarkers of MHR. In line with this, lower vagally mediated HRV was associated with psychiatric disorders (Carnevali et al., 2018a), and HF-HRV has been proposed as a potential transdiagnostic biomarker of mental illness (Beauchaine and Thayer, 2015). Furthermore, preliminary longitudinal findings revealed the development of post-deployment posttraumatic stress disorder symptomatology in individuals with reduced resting state HF power before combat deployment (Pyne et al., 2016). Similarly, reduced resting state RMSSD seemed to be prospectively involved in the development of depressive symptoms in healthy young individuals, over a three-year period (Carnevali et al., 2018b). An informative step in validating a putative biomarker of MHR is to assess its relationship with responses to laboratory stressors in individuals without concurrent psychopathologies (Walker et al., 2017). Therefore, to provide further empirical support to the idea of HRV as marker of MHR, in this brief review we summarized results of recent studies that provided HRV indexes (obtained through validated methods of signal recordings and calculation) in healthy individuals (i.e., without medical and psychiatric diseases; not taking medications that would alter HRV), aged ≥ 18 years, who underwent stressful laboratory tasks. We conducted a bibliographic search of the PubMed database for articles published between January 2010 and September 2018 using following keywords in combination: heart rate variability, resilience, stress, vulnerability, healthy. Eight studies that fitted in inclusion criteria were extracted and are summarized in Table 1.
greater self-capacity and lower opponents’ capacities compared with females and appraised the task as a challenge, displaying more active approach, whereas females appraised the task as a threat, displaying more cautious approach. Together, these findings indicate that greater heart rate flexibility reflects better coping strategies and successful outcomes in goal-relevant situations. Using the same task, Alacreu-Crespo and colleagues (2018) revealed that individuals with better decision-making skills have more adaptive cardiac autonomic response to competition, reflecting lower stress and better adaptability, with better vagal control during and after the task, which probably facilitated winning. The involvement of prefrontal cortex (PFC) both in decision-making and inhibitory control on cardiac autonomic system via vagus nerve (Smith et al., 2017) may explain the association between higher vagal control and better attentional and decision-making skills, a pattern resulting in more adaptive responses and higher resilience for coping with stress. A similar link between HRV, as measured with the standard deviation of NN intervals (SDNN index), and the self-control component of decision-making was found in a group of males who underwent dietary challenges (Maier and Hare, 2017). Individuals with higher resting SDNN were better at regulating their cravings in the face of taste temptations, thereby exerting improved dietary self-control. Additionally, during dietary challenges, these individuals displayed higher blood oxygen level-dependent activity and attenuated taste representations in the ventromedial PFC, a region involved in regulating autonomic responses and estimating subjective values of choice options. These findings suggest that higher resting SDNN may be a marker of neurophysiological adaptability that results in more efficient selfcontrol abilities in the face of environmental challenges. The SDNN index is thought to reflect all the components that contribute to HRV; however, SDNN is highly correlated with other indexes reflecting phasic vagal control (Maier and Hare, 2017) and, in short-time resting recordings used in this study, the primary source of SDNN seems to be the parasympathetic activity (Shaffer and Ginsberg, 2017). Overall, these studies reveal a link between flexibility of the autonomic system and resilience when facing mental stressors that involve different neuropsychological functions. The data indicated that higher HRV indexes, mainly those influenced by the vagal tone, reflect greater ability of deploying neuropsychological resources to successfully overcome stressful laboratory tasks, suggesting that vagally mediated HRV may serve as a proxy for cognitive resilience to competitive stress and self-control challenges. 1.2. HRV and emotion regulation Two further studies (Nasso et al., 2019; Rombold-Bruehl et al., 2017), explored the association between HRV patterns and regulation of emotional responses involved in the adaptability to changing environmental conditions and in mental well-being. In a female cohort studied by Nasso and colleagues (2017), the use of an adaptive emotion regulation (ER) (i.e., positive reappraisal) in anticipation of a stressful situation (i.e., job interview preparation) was associated with higher vagal control during anticipation of, dealing with, and recovery from the stressful situation, when compared with maladaptive (i.e., catastrophizing) ER. This was particularly evident in females with low tendency to ruminate. These results suggest that individuals who positively reappraise are more successful at regulating their autonomic responses when dealing with a stressor, probably resulting in higher coping abilities than those who display maladaptive strategies. This favorable pattern may be interpreted as a result of reappraisal-induced proactive prefrontal activation with decreased amygdala activity and negative emotion, thus facilitating appropriate autonomic regulation in response to stress. In another cohort of females undergoing an experimental distressing film paradigm, associations were found between lower vagal HRV component at baseline (before the film) and higher burden with slower
1.1. HRV and neuropsychological function Of the eight studies, three (Abad-Tortosa et al., 2017; A. AlacreuCrespo et al., 2018; Maier and Hare, 2017) evaluated associations between HRV patterns and the ability to cope with stressful tasks that involved neuropsychological function, particularly attention/perception and decision-making. Abad-Tortosa and colleagues (2017) found that winners in a perception/attention task-competition displayed greater global autonomic reactivity (i.e. greater decrease of the R-R intervals) from baseline to task condition (i.e. values during task minus values during baseline), and greater global autonomic recovery (i.e. greater increase of the R-R intervals) post-task (i.e. values during post-task minus values during task), as compared with losers. Furthermore, winners displayed higher reactivity of the vagal HRV component (HF) from baseline to task condition than losers, with opposite trajectories depending on gender (i.e., increase in males and decrease in females); this probably reflected gender-based differences in coping strategies used to achieve successful outcomes, for which rates were equal in both genders. Males perceived 2
Main objective
Maier and Hare, 2017
AlacreuCrespo et al., 2018
To test whether greater baseline HRV would be associated with better dietary SC.
To investigate the association between HRV reactivity to a laboratory competition task and decision-making skills.
Neuropsychological function D. AbadTo analyze the patterns of Tortosa et al., autonomic reactivity 2017 associated with competition, its outcome, and situational appraisal.
Study
Table 1 Details of the selected studies.
3 N = =49 (all M, mean age: 21.2 ± 2 years) from general population, randomly assigned to either stress group (n = =27) or CG (n = =22).
N = =116 (44 F) university students were classified into GD or PD on the basis of performances on IGT. Subsequently, they underwent a stress task either in a competitive (EG) [N = =86, 43 winners (14 F, mean age: 21.92 ± 0.48 years), 43 losers (14 F, mean age: 21.61 ± 0.46 years)] or non-competitive (CG) (N = =30, 16 F, mean age: 21.45 ± 0.56 years) condition.
N = =112 (46 M, mean age: 22.37 ± 0.5 years; 66 F, mean age: 21.23 ± 0.38 years) university students. Competitive condition (EG): 37 winners, 40 losers; non-competitive condition (CG): 35 participants.
Sample
HRV measures: time domain (ms), HRVtot measured as SDNN. Recording at rest before the task.
R-R intervals recorded via POLAR RS800cx watch and HR monitor chest belt.
R-R intervals recorded via POLAR RS800cx watch and HR monitor chest belt.
HRV analyzed in 5-min periods from baseline to post-task. HRV measures: time domain (ms), mean values of RR intervals; frequency domain (ms2, n.u., hz), HF, LF, and VLF components, HRVtot (sum of all the frequency bands), HF/HRVtot.
Stress task ("The letters squares", an attention/ visual perception task). Phase 1 (baseline): 10-min resting. Phase 2 (decisionmaking): IGT. Phase 3 (stress task): participants (same-sex dyads) randomly assigned to either a face-to-face competition (information given: winners would receive an economic reward) or a control condition (task explanation without mentioning competition or rewards). Phase 4 (post-task): 10-min resting.
Dietary SC challenge (decision-making task): participants had to choose the healthier of two food items presented on a screen. Two conditions: 1) conflict condition (SC challenge): the healthier item was the least tasty, 2) no-conflict condition (no-
R-R intervals recorded via 3electrodes ECG.
Instruments
HRV analyzed in 5-min periods from baseline to post-task. HRV measures: time domain (ms), mean values of RR intervals; frequency domain (n.u.), HF component.
HRV measures
Stress task ("The letters squares", an attention/ visual perception task). Participants (same-sex dyads) were randomly divided into EG (information given: winners would receive an economic reward), or CG (task explanation without mentioning competition or rewards). After the competition, subjects in the EG group were separated into winners or losers.
Task and Procedure
fMRI, STAI-trait, Three Factor Eating Questionnaire.
5-item scale (0 − 100) to characterize the perception of the competition.
Performance, blood pressure, selfadministered scales assessing situation appraisal, including selfand opponent-capacity, perceived feelings during the task, internal/external attribution of outcome.
Other measures R-R reactivity (task minus baseline) between baseline to task: greater decrease of R-R interval in winners compared to losers and CG, especially in men. R-R recovery (post-task minus task): higher in winner men compared to losers and CG. HF-HRV reactivity between baseline to task: significant HF increase in winner men, significant HF decrease in winner women. HRVtot reactivity (task minus baseline) and LF reactivity: lower in loser GD than in loser PD; lower in competing GD (winners and losers) than in GD in the CG. HRVtot recovery (post-task minus task) and LF recovery: higher in loser GD than in loser PD; higher in competing GD (winners and losers) than in GD in the CG. HF recovery: higher in loser GD than in GD in the CG. HF/HRVtot reactivity: higher in winner GD than in PD; higher in competing GD (winners and losers) than in GD in the CG; among losers, higher in GD than PD. HF/ HRVtot recovery: lower in winners GD than in PD and in the CG. Higher resting total HRV (SDNN index) were associated with greater SC success when facing dietary challenges (i.e. to choose the healthier option even when it was the less tasty).
Main results*
(continued on next page)
Negative correlation between HRV and STAItrait. Higher HRV correlated with a decreased representation of taste attributes in the vmPFC
GD perceived higher effort than PD during the performance of the task.
Performance: equal in both genders. Systolic blood pressure changes between baseline and pre-task: significant increase in EG, significant decrease in CG. Situational appraisal: in EG, greater internal attribution ("own capacity") men than women; lower appreciation of the opponent's capacity in winner men than winner women.
Other findings of interest*
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RomboldBruehl et al., 2017
Emotion regulation Nasso et al., 2019
Study
Table 1 (continued)
To investigate whether HF and LF/HF ratio components of HRV at rest before stress would predict consecutive intrusive memories.
To investigate 1) the influence of adaptive (reappraisal) vs. maladaptive (catastophizing) anticipatory ER on autonomic nervous system during anticipation, stress and recovery phases, and 2) the moderating role of trait rumination.
Main objective
N = =60 (all F, mean age: 22.98 ± 3.17 years) university students.
N = =56 (all F, mean age: 21.76 ± 2.05 years) undergraduates, randomly assigned to either reappraisal (N = =29) or catastrophizing (N = =27) group.
Sample
ER task: participants had to simulate a job interview and their performance would be evaluated. Phase 1 (baseline): questionnaires, reading sentences of neutral content, job interview task instructions. Phase 2 (anticipatory ER): participants were told that they would undergo a guided stress management procedure to manage stress during the job interview and they were randomly assigned to either reappraisal or catastrophizing instructions. Sentences taken from the ER instructions were displayed on the screen and participants were asked to focus on their meaning. Phase 3 (actual stressor): preparation of the job interview while questions commonly asked during job interviews were displayed on the screen. Phase 4 (recovery): the experimenter stated the impossibility to perform the interview and participants were only asked to relax. Intrusion-inducing stressor: a validated experimental distressing film of a brutal rape that induces short-lasting intrusive symptoms. After the film, participants rated their distress. During the following 4
challenge): the healthier item was also the tastier. Approximately half of the trials was SC condition. Participants were scanned with fMRI during the task.
Task and Procedure
HRV measures: frequency domain (n.u.,%), HF, LF/HF ratio. 5-min recordings during baseline resting condition, 10 min prior to the stressor.
HRV measure: frequency domain (n.u.), HF component. Continuous monitoring from baseline to recovery.
HRV measures
R-R intervals recorded via POLAR RS800cx watch and HR monitor chest belt.
R-R intervals recorded via POLAR RS800X watch and HR monitor chest belt.
Instruments
STAI-trait, N of intrusive memories (online diary), rating of distress on a 7point Likert scale.
Self-reported trait rumination (RRS), affective responses (VAS).
Other measures
Women with low baseline HRV: 1) had more intrusive memories after the distressing film, and 2) displayed a slower recovery from the stressor. Specifically, lower baseline HF-HRV was associated to a higher
Higher HFnu in the reappraisal than in the catastrophizing group over all phases after baseline.
Main results*
(continued on next page)
In low ruminators, reappraisal was associated with higher HFnu than catastrophizing. Only low ruminators showed a beneficial effect of anticipatory reappraisal on autonomic regulation.
Other findings of interest*
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Main objective
Weber et al., 2010
To investigate whether individuals with reduced resting HRV would display impaired cardiovascular, endocrine and immune recovery after acute mental stress.
Physiological regulation Pulopulos et al., To investigate whether 2018 changes in HRV during the anticipation of a stressful task were related to the cortisol response to a laboratory-based stress task.
Study
Table 1 (continued)
N = =44 (all M; mean age: 30 ± 7 years). Participants were divided into either high (N = =20) or low (N = =23) resting HRV based on a median split on resting RMSSD.
N = =171 (75 F, mean age: 29.98 ± 11.07 years). Participants were divided into cortisol responders (N = =70), who displayed a significant cortisol increase, and nonresponders (N = =101).
Sample
Mental stress tests: 1) manometer test, a standardized computerbased information processing task performed under time pressure; 2) mental arithmetic test, an increasingly difficult series of mental calculations with feedback on the performance. Phase 1 (baseline): 5-min resting. Phase 2 (stress 1): manometer test. Phase 3 (stress 2): mental arithmetic test. Phase 4 (recovery): 5-min resting.
Stress task (modified version of the TSST): a 5min videotaped speech (defending against an alleged transgression) and a 5-min mental arithmetic task. Phase 1 (baseline): 20-min resting and instructions on the TSST procedure. Phase 2 (anticipatory phase): preparation of the TSST. Phase 3 (stress task): administration of the TSST. Phase 4 (recovery phase): 50-min resting.
days, they assessed their intrusive memories.
Task and Procedure
HRV measures: timedomain (ms), RMSSD. Continuous monitoring from baseline to recovery. For each phase, mean of HRV was computed.
HRV measures: timedomain (ms,%), RMSSD, pNN50. Continuous monitoring from baseline to the first 15 min of the recovery phase.
HRV measures
ECG and finger blood pressure curves.
3-electrodes ECG and a respiratory band to measure respiration rate.
Instruments
Serum cortisol, cytokines (TNF-α, IL-6) measured before stress, immediately after the mental stress, 20 and 60 min after mental the stress. Blood pressure, heart rate: continuous monitoring from baseline to recovery. For each phase, mean of each variable was computed.
Cortisol levels (salivary samples) at baseline, 15 min after TSST, and every 10 min after until +65 min+). Three indexes of cortisol levels: 1) AUCi with respect to the increase; 2) cortisol reactivity (change from baseline to maximum level after the TSST); 3) cortisol recovery (decrease from the maximum level after the TSST to the last cortisol sample).
Other measures
In the whole group, HRV decreased from baseline to anticipation phase, and increased from the stress task to the recovery phase. A larger decrease in HRV during anticipation was related to higher cortisol AUCi and reactivity, after controlling for all the covariates. In the subgroup of cortisol responders, this relationship remained significant for cortisol reactivity, while, for cortisol AUCi, it became marginally significant after controlling for all the covariates. In the high resting HRV group: 1) higher overall HRV levels; 2) HRV decrease under stress (from resting to manometer test) and increase with recovery (from mental arithmetic test to resting) 3) cortisol increase during stress and decrease from stress to 20 min after stress; 4) significant TNF-α decrease from stress to 60 min after stress. In the low resting HRV group: 1) lower overall HRV levels; 2) no HRV changes across the phases; 3) higher and ongoing diastolic blood pressure increase under stress, with no post-stress recovery; 4) no cortisol decrease from stress to 20 min after stress; 5) no TNF-α decrease from stress to 20 min and 60 min after stress.
N of intrusive memories on day 1 and 2; higher baseline LF/HF ratio was associated with a higher N of intrusive memories on day 1.
Main results*
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In the whole sample, cortisol increase after stress was not statistically significant, while cortisol levels in the last 2 salivary samples were below baseline levels. Both in the whole group and in the subgroup of cortisol responders, the change in HRV specifically due to the stress task (i.e. change in HRV from anticipation to the stress task) was not related to the cortisol indexes. Neither anticipation-induced nor stress-induced changes in HRV were related to cortisol recovery. In the whole sample, blood pressure, heart rate, and cortisol levels significantly increased under stress.
Other findings of interest*
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To evaluate the relationships between HRV in response to a psychosocial stressor and circulating plasma TNF-α, IL-6 and CRP.
Woody et al., 2017
Task and Procedure Psychosocial stressor (speech task): mock job interview with performance evaluation. Phase 1 (resting and task instructions): questionnaire, rest period, instructions for the speech task. Phase 2 (anticipation): mental preparation for the speech. Phase 3 (stress): speech task. Phase 4 (rumination/distraction task): the participants were randomly assigned to either a rumination or distraction task. Phase 5 (resting): additional questionnaires and 45min resting.
Sample N = =34 (all F, mean age: 20.7 ± 2.3 years) undergraduate students. HRV measures: frequency domain (ms2,%), HF using both HF-FFT and HF-AR. Larger negative change HRV values (speech task minus phase 1 resting) indicated greater HRV reduction during the stressor.
HRV measures Three-lead ECG.
Instruments TNF-α, IL-6, CRP (blood samples) measured immediately pre-stressor and 60 min after stressor. Inflammatory responses were calculated by subtracting pre-stressor values from post-stressor (+60 min+) values.
Other measures When considering several covariates, greater HF-AR reduction during stress was associated with greater TNF-α and IL-6 responses, while greater HF-FFT reduction during stress was associated with greater IL-6 response.
Main results*
Other findings of interest*
⁎
only significant results AR = autoregressive techniques, AUC = area under the curve, CG = control group, CRP = C-reactive protein, ECG = electrocardiogram, EG = experimental group, ER = emotion regulation, F = females, FFT = Fast Fourier Transformation, fMRI=functional magnetic resonance imaging, GD = good deciders (i.e. having good decision-making skills at the Iowa Gambling Task), HF = high frequency, a measure of parasympathetic vagal tone, HPA = hypothalamus-pituitary-adrenal axis, HRV(tot) = heart rate variability (total power), hz = hertz, IGT = Iowa Gambling Task, IL-6 = interleukin, LF = low frequency, a measure of both sympathetic and parasympathetic vagal tone, and baroreflex activity, LH/HF ratio, a measure of both sympathetic and parasympathetic vagal tone, and other unspecified factors, M = males, min = minute, ms = milliseconds, n = normalized, N = number, NN = interbeat intervals from which artifacts have been removed, nu = normalized units, PD = poor deciders (i.e. having good decision-making skills at the Iowa Gambling Task), pNN50 = percentage of successive R-R intervals, a measure of parasympathetic vagal tone, RMSSD = root mean square of successive R-R interval differences, a measure of parasympathetic vagal tone, RR = time interval between consecutive R-wave peaks, a measure of autonomic nervous system activity, RSS = Ruminative Responses Style Scale, SC = self-control, SDNN = standard deviation of NeN intervals, a measure of all the components that contribute to HRV; in short-time resting recordings it reflects parasympathetic vagal tone, STAI = State-Trait Anxiety Inventory, TNF-α = tumor necrosis factor, TSST = Trier Social Stress Test, VAS = Visual Analogue Scale, VLF = very low frequency, a measure of mixed, and uncertain, factors such as heart's intrinsic rhythm, parasympathetic vagal tone, sympathetic tone during physical activity, thermoregulation, renin-angiotensin system, vmPFC = ventromedial prefrontal cortex.
Main objective
Study
Table 1 (continued)
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decrease of intrusive memories for 4 days subsequently after watching the film (Rombold-Bruehl et al., 2017). These findings suggest that lower autonomic flexibility, ultimately resulting in a relative increase of sympathetic activity, enhances an individual's vulnerability to stress and contribute to the formation of intrusive memories after trauma (Gillie and Thayer, 2014). This is in line with preliminary associations between lower vagal HRV component before combat deployment and post-deployment post-traumatic stress disorder symptomatology (Pyne et al., 2016). Overall, these studies showed that higher vagally mediated HRV reflects greater abilities in reappraisal and emotion regulation when dealing with stressful emotional tasks. This suggests that vagal components of HRV may be a proxy for emotional resilience in the face of external stressors.
activity have been found to be associated with psychiatric disorders (McEwen, 2008). Overall, these studies indicated that higher vagally mediated HRV reflects better regulation of multiple physiological systems during adaptive allostatic stress responses, resulting in blunting of unnecessary physiological activation after stressor ends. This suggests that vagal components of HRV may be a proxy of autonomic, endocrine, and immune resilience in the face of stressful conditions. 1.4. Limitations and conclusions This research presents some limitations. Although most studies focused on vagally mediated HRV, they used different indexes and applied different transformation/calculation methods; higher consistency of the HRV indexes across future studies would provide more reliable and comparable results. Future studies should explore a wider array of HRV indexes as potential markers of resilience, including non-linear measurements. Dynamic non-linear ANS processes influence the HRV, and the variability of non-linear systems provides the flexibility to cope rapidly with changing environment; therefore, non-linear HRV indexes may provide additional information beyond the time-/frequency domain measures. In line with this, preliminary data indicated reduced non-linear indexes of cardiac flexibility during a laboratory-induced psychosocial stress paradigm in adolescents who developed symptoms of increasing anxiety over the subsequent 12 months, while no relationship was found using HF-HRV (de la Torre-Luque et al., 2017). Further, most studies included only young participants, with some samples of only males or females, and an unclear ecological validity of the stressful laboratory tasks. Finally, since all studies were cross-sectional, no conclusions could be drawn regarding future mental health trajectories of individuals with better or poorer HRV-task performance patterns. Therefore, future investigations should include wider age ranges, more homogeneous gender distribution, real-life challenges and stressors, and longitudinal mental health monitoring. Nowadays, advances in wearable health devices and applications have facilitated easy monitoring of multiple physiological signals, behaviors, and patientreported outcomes describing emotions during daily life. The implementation of these tools in future clinical and research studies may be a valuable strategy to gain better and reliable insight into the relationships between HRV and MHR in real-world contexts. In conclusion, HRV may be considered a global index of an individual's flexibility and ability to adapt to stress and challenges, as it reflects the efficiency of multiple aspects of physiological, emotional, and cognitive responses to stressors. Though additional research is needed, available evidence so far suggests that vagally mediated indexes of HRV may be plausible, noninvasive, and easily applicable biomarkers of MHR.
1.3. HRV and physiological regulation Three investigations (Pulopulos et al., 2018; Weber et al., 2010; Woody et al., 2017) focused on the association between HRV patterns and the physiological mechanisms involved in stress adaptability and mental consequences of stress exposure, such as cortisol, cardiovascular, and inflammatory responses. Pulopulos and colleagues (2018) established that high HRV indexes of vagal activity (RMSSD, pNN50) during anticipation of a stressful psychosocial task were associated with low stress-induced cortisol increase when individuals underwent the task, suggesting a positive vagal regulatory role on the hypothalamus–pituitary–adrenal (HPA) axis. This autonomic pattern during anticipation may represent an adaptive response allowing individuals to activate emotional/biological changes to successfully deal with the stressor. Therefore, it would reflect the ability to limit a disproportionate and/or persistent cortisol response to stress that may have detrimental effects on mental health (McEwen, 2008; Pinto et al., 2017). Next, in a cohort of males undergoing a standardized mental stress test, individuals with high resting vagally mediated HRV (RMSSD index) displayed higher overall HRV during the entire procedure, and appropriate modulation and post-stress recovery of cardiovascular, endocrine, and immune markers. Conversely, low resting HRV was associated with no changes of vagally mediated HRV during the procedure and impaired post-stress recovery of diastolic blood pressure, cortisol, and pro-inflammatory cytokine TNF-α (Weber et al., 2010). Finally, Woody and colleagues (2017), in a cohort of females, noticed that small reductions in vagal components of HRV during a stressful psychosocial task was associated with lower inflammatory reactivity 1 h after the stressor was applied, as measured by TNF-α and IL-6 level. This pattern of inflammatory reactivity may represent a favorable factor for mental health, considering that higher pro-inflammatory response to a psychosocial stressor increased the risk of developing depression in the ensuing months, in a preliminary female population (Aschbacher et al., 2012). These findings support an inhibitory role of the vagus in the regulation of allostatic systems, such as HPA axis and inflammation, in response to internal/external perturbations. The vagal connections between PFC and amygdala and between vagal nuclei in the medulla oblongata and the hypothalamus are considered to blunt excessive sympathoexcitatory responses to stress (Smith et al., 2017; Thayer et al., 2012). Likewise, the “cholinergic anti-inflammatory pathway” is considered to suppress pro-inflammatory cytokine release (Tracey, 2002), as supported by a recent meta-analysis that showed a negative relationship between vagal component of resting HRV and markers of inflammation (Williams et al., 2019). Consequently, an autonomic imbalance with reduced vagal components of HRV could reflect impaired physiological regulation when handling internal and/or environmental challenges, resulting in exaggerated stress responses and ultimately contributing to poor mental health outcomes. Accordingly, higher inflammatory markers and cortisol levels and sympathetic over-
Financial support The authors declare no funding. Disclosure Archie Defillo is a full time, paid employee (Chief Medical Officer) for Medibio LTD. Daniela Caldirola, Giampaolo Perna, Alice Riva, and Erika Sangiorgio are scientific consultants for Medibio LTD CRediT authorship contribution statement Giampaolo Perna: Conceptualization, Methodology, Supervision, Writing - review & editing. Alice Riva: Writing - original draft. Archie Defillo: Conceptualization, Methodology, Supervision, Writing - review & editing. Erika Sangiorgio: Writing - original draft. Maria Nobile: Conceptualization, Methodology, Supervision, Writing - review & editing. Daniela Caldirola: . 7
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Acknowledgements
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