The relationship between mental and physical health: Insights from the study of heart rate variability

    The Relationship Between Mental and Physical Health: Insights from the Study of Heart Rate Variability Andrew H. Kemp, Daniel S. Quintana PII: DOI: Reference:

S0167-8760(13)00189-X doi: 10.1016/j.ijpsycho.2013.06.018 INTPSY 10686

To appear in:

International Journal of Psychophysiology

Received date: Revised date: Accepted date:

29 January 2013 6 June 2013 13 June 2013

Please cite this article as: Kemp, Andrew H., Quintana, Daniel S., The Relationship Between Mental and Physical Health: Insights from the Study of Heart Rate Variability, International Journal of Psychophysiology (2013), doi: 10.1016/j.ijpsycho.2013.06.018

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ACCEPTED MANUSCRIPT The Relationship Between Mental and Physical Health: Insights from the Study of Heart

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Andrew H. Kemp1,2,3*

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Rate Variability

Daniel S. Quintana1,4

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SCAN Research & Teaching Unit, School of Psychology, University of Sydney 2

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Discipline of Psychiatry, University of Sydney

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Hospital Universitário, University of São Paulo, São Paulo, Brazil 4

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Brain and Mind Research Institute, University of Sydney

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Corresponding author: Andrew Kemp, [email protected]

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Abstract Here we review our recent body of work on the impact of the mood and comorbid anxiety disorders, alcohol dependence, and their treatments on heart rate variability (HRV), a

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psychophysiological marker of mental and physical wellbeing. We have shown that otherwise healthy, unmedicated patients with these disorders display reduced resting-state

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HRV, and that pharmacological treatments do not ameliorate these reductions. Other studies highlight that tricyclic medications and the serotonin and noradrenaline reuptake inhibitors in particular may have adverse cardiovascular consequences. Reduced HRV has important functional significance for motivation to engage social situations, social

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approach behaviours, self-regulation and psychological flexibility in the face of stressors. Over the longer-term, reduced HRV leads to immune dysfunction and inflammation,

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cardiovascular disease and mortality, attributable to the downstream effects of a poorly functioning cholinergic anti-inflammatory reflex. We place our research in the context of the broader literature base and propose a working model for the effects of the mood

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disorders, comorbid conditions, and their treatments to help guide future research activities. Further research is urgently needed on the long-term effects of autonomic dysregulation in

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otherwise healthy psychiatric patients, and appropriate interventions to halt the

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progression of a host of conditions associated with morbidity and mortality.

Keywords: heart rate variability, cardiovascular disease, mortality, depression, anxiety,

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alcohol dependence, psychological treatment, pharmacological treatment, cardiovascular risk reduction

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Introduction “A sad soul can kill you quicker, far quicker than a germ” (John Steinbeck, Travels with Charley: In Search of America, 1962)

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Unipolar depressive disorders and cardiovascular disease (CVD) (including heart disease and stroke) are already leading burdens of disease and this burden is projected to worsen

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up to 2030 (Mathers and Loncar, 2006). The global cost of mental health is estimated to cost US$6 trillion by 2030, increasing from US$2.5 trillion in 2010, while CVD is estimated to cost US$1.04 trillion by 2030 (rising from US$863 billion in 2010) (Bloom et al., 2011). Critically, there is increasing recognition that these disorders are related: depression is

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independently associated with morbidity and mortality, and is common among patients with CVD (Carney and Freedland, 2009; Lichtman et al., 2008). Increasing recognition of

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the relationship between depression and CVD led the American Heart Association to recommend routine screening of depression in patients with coronary heart disease (CHD) (Lichtman et al., 2008), a leading cause of CVD mortality. While depression increases risk

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for the development of CVD approximately 1.5-fold, patients with CVD and depression have a two- to three-fold increased risk of future cardiac events compared to cardiac

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patients without depression (Rudisch and Nemeroff, 2003). More recent research is consistent with this earlier data, and clinically diagnosed major depressive disorder is the

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most important risk factor (Van Der Kooy et al., 2007). A meta-analysis (Pan et al., 2011) on more than 300,000 participants followed-up over a

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period ranging from 2 to 29 years reported a pooled adjusted hazard ratio of 1.45 for depression and stroke. The authors estimated that 3.9% (n=273,000) of stroke cases in the United States could be attributable to depression. Another recent study (Russ et al., 2012) reported a dose-response association between psychological distress across the full range of severity and an increased risk of mortality from a number of causes including CVD, cancer and external causes over 8 years. This study was conducted on more than 65,000 people from the general population free of CVD and cancer at study baseline. The researchers measured psychological distress using the General Health Questionnaire (GHQ-12), a valid screening tool for anxiety and depression as diagnosed by the Diagnostic and Statistical Manual of Mental Disorders (Schmitz et al., 1999). Age and sex adjusted hazard ratios were 1.20 for subclinically symptomatic, 1.43 for symptomatic and 1.94 for highly symptomatic participants. It is worth noting that comorbid anxiety disorders are present in more than 60% of cases of MDD (Kessler et al., 2005), highlighting a need 3

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to distinguish between the impact of depression versus anxiety on future adverse events. Interestingly, evidence indicates that patients with such comorbidity display an almost threefold increase in the prevalence of CVD, while no such associations were observed for depressive disorders without comorbidity (Vogelzangs et al., 2010). A study on 4,256

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participants (Phillips et al., 2009) revealed that the comorbidity of MDD and GAD is strongly associated with all-cause mortality (hazard ratio = 2.29) and CVD (hazard ratio =

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2.68) even after accounting for a host of confounding variables. Another body of evidence indicates that alcohol dependence – a disorder associated with a variety of psychological problems including depression and anxiety – also leads to CVD and mortality (Rehm et al.,

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2009). In fact, age- and gender-adjusted risk of death has been estimated at 2.3 to 2.6-fold among patients with depressive, anxiety or alcohol use disorders (Markkula et al., 2012). When controlling for psychiatric comorbidity, these associations decreased (HR=1.56-

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2.34) although these remained significant for depressive (HR=1.97) and alcohol use disorders (including misuse and dependence) (HR=1.72).

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The mood and anxiety disorders are associated with a variety of behavioural issues including smoking (Jane-Llopis and Matytsina, 2006), problems with alcohol (Jane-Llopis

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and Matytsina, 2006) and physical inactivity (Goodwin, 2003), and these all increase risk for CVD and mortality. However, these behavioural aspects do not fully account for the

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strong relationship between mental and physical illness. While a variety of biological factors – including the hypothalamic-pituitary-adrenal (HPA) axis and inflammatory processes – contribute to this relationship, one specific mechanism thought to underlie a

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substantial part of risk for increased mortality is autonomic dysregulation (Nemeroff and Goldschmidt-Clermont, 2012; Thayer et al., 2010b), indexed by reductions in heart rate variability (HRV). Here we review the link between depression, cardiovascular disease and mortality, discuss the relationship between HRV, mental, and physical wellbeing, highlight recent studies from our laboratory on physically healthy, psychiatric patients and treatments for these disorders, and propose a model to guide future research activities. Several points regarding our review should be noted. First, for brevity, we focus on the mood disorders and common comorbid conditions. It is important to note that reduced heart rate variability has been reported in a variety of psychiatric disorders including schizophrenia (Berger et al., 2010), bipolar disorder disorder (Henry et al., 2010; Lee et al., 2012), attention deficit hyperactivity disorder (Buchhorn et al., 2012) and conduct disorder (Beauchaine et al., 2007). This data highlight the adverse effects of a wide range of disorders on the autonomic nervous system, a finding that may be related to emotion 4

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dysregulation, a core feature of all of these conditions. Second, while studies have generally reported reduced HRV in many psychiatric disorders, contradictory findings have also been published. These contradictory findings highlight the importance of taking into consideration potential confounding variables including the effects of medication and a

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history of CVD. With respects to our own work, contradictory findings in the literature led us to conduct meta-analyses on major depressive disorder (Kemp et al., 2010) and alcohol

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dependence (Quintana et al., 2013b), the results of which are discussed below. Third, our review draws heavily on models (Pavlov and Tracey, 2012; Thayer and Brosschot, 2005; Thayer and Lane, 2007; Thayer et al., 2010b; Tracey, 2002b, 2007) that propose a link

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between HRV and longer-term changes in health and wellbeing. These models also highlight that changes in HRV may be a particularly sensitive early marker for CVD. However, we note that these models are not without controversy (Kluttig et al., 2010;

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Thayer et al., 2010a), indicating a need for large longitudinal, epidemiological studies to further explore the proposed importance of HRV changes in the context of more established risk markers including age, smoking, cholesterol, hypertension, diabetes and

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obesity. Fourth, we focus specifically on the relationship between decreased HRV, psychiatric illness, adverse downstream effects and CVD. Chronic decreases in HRV will

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lead to immune dysfunction and inflammation, and subsequently, a wide variety of conditions and diseases including diabetes, obesity, osteoporosis, arthritis, Alzheimer’s

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disease, periodontal disease, cancer, frailty and disability (Katon et al., 2011; Kissane et al., 2011; Thayer et al., 2010b).

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Heart rate variability (HRV): A psychophysiological phenomenon with broad implications

HRV is a measure of beat-to-beat temporal changes in heart rate and these changes, rather than being random noise, reflect the output of the central autonomic network. This inhibitory cortico-subcortical neural circuit – comprising the prefrontal cortex, cingulate cortex, insula, amygdala, and brainstem regions – is responsible for the control of visceral response to stimuli (Thayer et al., 2009; Thayer and Lane, 2000; Thayer and Lane, 2009). HRV is mediated through preganglionic sympathetic and parasympathetic neurons innervating the heart via the stellate ganglia and the vagus nerve, respectively (Thayer et al., 2009). The parasympathetic nervous system (PNS) is mediated by acetylcholine, which inhibits cardiac muscle and slows heart rate, while the sympathetic nervous system (SNS) is medicated by norepinephrine, which excites cardiac muscle and speeds heart rate. HRV is dominated by parasympathetic (vagal) influence, which has a very short 5

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latency of response; its peak effects are observed within ½ second and returns to baseline within 1 second. By contrast, the sympathetic influence on the heart is too slow to produce beat-to-beat changes, with peak effects occurring after approximately 4 seconds and returning to baseline after 20 seconds (Appelhans and Luecken, 2006). Heart rate varies

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with respiration; it increases on inspiration and decreases on expiration, a phenomenon known as respiratory sinus arrhythmia (RSA) (Yasuma, 2004). Research now shows that

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this well-known physiological phenomenon is associated with emotion and mood, and these associations may have important implications for mental and physical wellbeing. This research will be discussed further below.

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HRV may be considered a marker of ones capacity for self-regulation, social engagement and psychological flexibility. A recent study (Geisler et al., 2013) reported that young

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adults with higher resting state HRV display more adaptive self-regulation and more social engagement than those with lower resting state HRV. More specifically, individuals with higher HRV reported using more engagement strategies when coping with distress and

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less disengagement when regulating negative emotions. They were more inclined to seek social support to deal with distress and sadness. Consistent with the idea that HRV is

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associated with self-regulation, we (Quintana et al., in press) have shown that resting-state HRV predicts alcohol cravings as measured by the obsessive compulsive drinking scale, in

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alcohol dependent outpatients, such that decreases in HRV are associated with increases in cravings. With respects to a role for HRV in social engagement, we reported (Kemp et al., 2012b) that oxytocin – a mammalian neuropeptide that plays a central regulatory role

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in human social behaviour and social cognition – increases resting state HRV. We interpreted these findings as reflecting increased participant’s capacity for social approachrelated motivation and capacity for social engagement. On the basis of this research and the work of others we have proposed a role for parasympathetic nervous system in the effects of oxytocin social behaviour (Quintana et al., 2013a). According to polyvagal theory (Porges, 1995, 1997; Porges, 2001; Porges, 2003a, b, 2007, 2009a, 2011; W Porges, 1998). HRV is associated with the experience and expression of social and emotional behaviour. This theory distinguishes between the myelinated and unmyelinated vagus nerves (hence ‘polyvagal’), such that the myelinated vagus underpins changes in HRV and approach-related behaviours including social engagement, while the phylogenetically older unmyelinated vagus – in combination with the SNS – supports the organism during dangerous or life-threatening events. This theory is a phylogenetically ordered hierarchical model that draws on the Jacksonian principle of dissolution in which higher neural circuits 6

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inhibit lower circuits, but when higher circuitry is rendered functionless, the lower rise in activity (Porges, 2009b). This process is a potential mechanism for the expression and disruption of positive social behaviours. According to the theory, social engagement can only occur when the environment is perceived as safe and the defensive circuits are

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inhibited. If these circuits are not inhibited when they should be, then the ability to detect

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and express positive social cues is compromised.

We have also demonstrated a relationship between HRV and social cognition in healthy volunteers (Quintana et al., 2012), reporting that increased resting-state HRV is associated with better subsequent emotion recognition, an important facet of social communication.

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This study suggests that emotion recognition may be impaired when HRV is low. Supporting this interpretation, an earlier study on children with autism spectrum disorders

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– associated with marked impairment in social interactions – reported reduced respiratory sinus arrhythmia (RSA) and a positive relationship between RSA and faster emotion recognition (Bal et al., 2010). Together these studies indicate that individuals with

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decreased parasympathetic nervous system function – as indicated by reduced HRV – are unable to suppress sympathetic nervous system function, leading to a mobilised

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behavioural state and negative affect which adversely impacts on social engagement. The link between HRV and social cognition is supported by recent studies that have examined

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the relationship between cerebral blood flow and HRV, summarised in a recent metaanalysis (Thayer et al., 2012), which concluded that HRV may index a central autonomic

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network that directly regulates the heart and guides flexible control over behaviour. This central autonomic network plays a major role in the inhibition of medullary cardioacceleratory circuits; controlling psychophysiological resources during emotion; goal-directed behaviour and flexibility to environmental change (Thayer et al., 2009; Thayer and Lane, 2000; Thayer and Lane, 2009). A recent study (Di Simplicio et al., 2012) measured HRV during an emotion regulation task which required participants to either passively view negative images versus down-regulating the affect elicited by the images. This study demonstrated that individuals with low neuroticism displayed higher HRV during down-regulation relative to passive viewing, while those with high neuroticism displayed decreased HRV. These findings were interpreted as signalling a distinct impairment in cognitive inhibitory responses over negative affect. These findings are consistent with those of other studies reporting that persons with high HRV display better performance on tasks involving executive function (Hansen et al., 2003), and more differentiated emotionmodulated startle effects, suggesting a more flexible response to situational demands 7

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(Ruiz-Padial et al., 2003). Increased HRV is also associated with various indices of psychological wellbeing including cheerfulness and calmness (Geisler et al., 2010), trait positive emotionality (Oveis et al., 2009), motivation for social engagement (Kemp et al., 2012b; Porges, 2011), resilience and wellbeing (Kashdan and Rottenberg, 2010). By

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contrast, reduced HRV – reflecting a hypoactive parasympathetic (vagal) system – is associated with cognitive and affective dysregulation (Kashdan and Rottenberg, 2010;

psychological risk factors for psychopathology.

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Thayer et al., 2009), and psychological inflexibility (Kashdan and Rottenberg, 2010), major

HRV may also be considered a somatic marker that contributes to emotional experience

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and initiates subsequent emotion regulation strategies. While visceral information is conveyed to the CNS through many channels, vagal afferent feedback to the nucleus of

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solitary tract (NST) (and cortex) plays an important role (Porges, 1995, 1997; Porges, 2001; Porges, 2003a, b, 2007, 2009a, 2011; W Porges, 1998). The process by which visceral afferent feedback may impact on subsequent behavioural patterns has been

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labelled ‘neuroception’ (Porges, 2009b), a risk-evaluation process involving the continuous non-conscious processing of sensory information from the environment and the viscera.

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According to Polyvagal theory (Porges, 2011), perception of threat is associated with increases in amygdala activity and vagal withdrawal (decreased HRV), triggering fight or

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flight responses and negative social interactions with the environment (social withdrawal). Information relating to the status of the viscera and internal milieu is then fed back to the nucleus of solitary tract, and the cortex, allowing for subsequent regulation of the emotion

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response. By contrast, cortical inhibition of amygdala and increases in vagal tone allow for socially engaging facial expressions to be elicited, leading to positive interactions with the environment (social engagement). Again, the nucleus of the solitary tract receives vagal afferent feedback from the viscera and internal milieu allowing for ongoing neuroception. The neurovisceral integration model (Thayer et al., 2009; Thayer and Lane, 2000; Thayer and Lane, 2009) further highlights an important inhibitory role for vagal activity (indexed by HRV) in the regulation of a variety of allostatic systems including inflammatory processes, glucose regulation and hypothalamic-pituitary-adrenal (HPA) function (Thayer and Sternberg, 2006) (see also Pavlov and Tracey, 2012; Tracey, 2002b, 2007). According to this model, reduced HRV leads to an excess of proinflammatory cytokines, impaired fasting glucose levels and HPA-axis dysregulation; all conditions associated with increased allostasis and poor health. Eventually, if not addressed, these conditions will lead to premature aging, cardiovascular disease and mortality (Thayer et al., 2010b). The 8

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long-term sequelae of impaired autonomic nervous system function – indicated by reduced HRV – will therefore contribute to contribute to cardiovascular, lipid and endocrine abnormalities and increase risk for developing important components of the metabolic syndrome (i.e., hypertension, diabetes, and obesity) (Koskinen et al., 2009; Licht et al.,

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2013; Soares-Miranda et al., 2012; Windham et al., 2012). The process by which vagal activity regulates these allostatic systems may relate to the actions of the vagus nerve

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labelled as the “inflammatory reflex” (Tracey, 2002a; Tracey, 2002b, 2007): the afferent (sensory) vagus nerve is responsible for detecting cytokines and pathogen-derived products, while the efferent (motor) vagus nerve is responsible for their regulation and

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control. The ANS is well suited to play a key regulatory role in inflammatory signalling given its precise, rapid and lightning-fast responsivity; in this way acute inflammation is contained and spread of inflammation to the bloodstream prevented. The principle

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parasympathetic neurotransmitter, acetylcholine, effectively inhibits macrophage activation and synthesis of tumor-necrosis factor (TNF) via the alpha-7 nicotinic acetylcholine receptor sub-unit expressed on monocytes, macrophages and other cytokine producing

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cells (Huston and Tracey, 2011; Wang et al., 2003). This inhibitory action of the efferent vagus nerve has been interpreted (Thayer, 2009) as an early intervention to short-circuit

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the subsequent inflammatory cascade and over the longer-term, inflammatory-mediated disease. Neural anti-inflammatory mechanisms may also inhibit release of other cytokines

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in inflammatory cascade including interleukin-1 and high mobility group B1 (Tracey, 2002b). Large longitudinal epidemiological studies are now required to further examine the

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prognostic utility of early changes in HRV. Physically healthy patients with mood and anxiety disorders, and alcohol dependence display reductions in HRV When we started investigating this issue, the majority of studies on HRV in depressed samples had been conducted on patients with a prior history of CVD (see Carney and Freedland, 2009; Taylor, 2010 for review). These studies had made significant progress in understanding the relationships between depressed mood physiology and mortality. Yet, it had remained unclear whether HRV was also decreased in physically healthy patients with depression, as factors concomitant with CVD could be contributing to decreases in variability. If HRV were to be decreased in physical healthy samples of depressed patients, then this would have important implications for our understanding and treatment of this disorder, particularly in young adults. When we examined the literature in regards to this question, the research was characterised by generally small samples and inconsistent 9

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findings leading us to conduct and publish our meta-analysis on the impact of major depressive disorder (MDD) on HRV (Kemp et al., 2010). Our findings indicated that otherwise healthy, unmedicated patients with major depressive disorder (MDD) (n=673) display reduced heart-rate variability (HRV) relative to controls (n=407) (Kemp et al., 2010),

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indicating compromised cardiovascular function even in those patients without a prior history of CVD. We also observed that these reductions in HRV were associated with

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increasing depression severity. We concluded that depression is associated with reductions in HRV and that these reductions are most apparent with nonlinear measures (Hedges’ g = -1.955). We also noted that antidepressant medications might not have HRV-

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mediated cardioprotective effects and highlighted that patients even in remission from depression may still be at risk of future ill health.

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While our meta-analysis was based on a relatively large sample size (patient n = 673), an earlier study (Licht et al., 2008) on 1075 MDD patients concluded that although depression is associated with reduced HRV, these reductions were driven by antidepressant

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medication. This proposal has led to significant debate and discussion (Kemp, 2011; Kemp, 2012; Kemp et al., 2011a; Kemp et al., 2011b; Licht et al., 2011a; Licht et al.,

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2011b). Regardless, the findings reported by Licht and colleagues (Licht et al., 2008) raised two important issues. Firstly, medication status may be a moderating variable of

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observed effects, highlighting the importance of excluding medicated patients when seeking to determine the impact of a disorder on HRV (as we did in our meta-analysis). Secondly, it highlighted the need for further study on the impact of psychotropic

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medication on HRV and major endpoints such as CVD and mortality. Recently, we extended on our meta-analytic findings (Kemp et al., 2010), confirming the finding of reduced HRV in an independent and otherwise healthy, unmedicated MDD patient sample (Kemp et al., 2012a). Our new study also indicated that MDD patients with comorbid GAD (n=24) in particular, display the greatest reductions in HRV relative to MDD patients without comorbidity as well as those with comorbid panic and posttraumatic stress disorder. We concluded that MDD patients with comorbid GAD would benefit from comprehensive cardiovascular risk reduction strategies. We have recently confirmed these findings using meta-analysis on anxiety disorders (Chalmers et al., in preparation), observing that patients with GAD display the largest reductions in HRV relative to controls. We have suggested (Kemp et al., 2012a) that GAD, a disorder characterised by worry and hypervigilance, may have difficulty disengaging from threat detection, which may lead to a chronic withdrawal of parasympathetic nervous system activity, over-activation of 10

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sympathetic nervous system activity and long-term reductions in HRV, subsequently increasing the risk for CVD and sudden cardiac death. More recently, we have reported evidence indicating that alcohol dependent patients

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(Quintana et al., 2013b) (n=177) relative to healthy, non-dependent controls (n=216) display reductions in HRV, and that these findings are not due to cardiovascular disease

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or comorbid psychiatric illness. This finding was associated with a medium effect size (Hedges’ g = -0.6), which is slightly smaller than effects we observed in patients with MDD and comorbid anxiety disorder (Cohen’s d = -0.8) (Kemp et al., 2012a). While an earlier study reported that heavy alcohol use (n=337), rather than alcohol dependence (n=208) is

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associated with dysregulation of the autonomic nervous system (Boschloo et al., 2011), inclusion of this study in our meta-analysis did not change our overall conclusions

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(Quintana et al., 2013b), although it did reduce the effect size (Hedges’ g = 0.29). In summary, we have observed robust reductions in HRV in patients with mood (Kemp et al., 2010) and anxiety (Kemp et al., 2012a) disorders, and alcohol dependence (Quintana et

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al., 2013b) who do not have CVD. It remains unclear however, to what extent these HRV reductions in patients without CVD actually predict future adverse events such as CVD

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and mortality. Future research is needed to examine this particular issue.

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Treatments for the mood and anxiety disorders, and heart rate variability If HRV is reduced in otherwise healthy patients with depression and comorbid conditions, then an important question is whether treatments for these disorders is able to ameliorate

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these decreases. Antidepressant medications have surpassed antihypertensive agents to become the most commonly prescribed medications in medical practice (Cherry et al., 2007; Middleton et al., 2007). While the adverse effects of tricyclic (TCA) antidepressants are well described, the second-generation antidepressants including the selective serotonin reuptake inhibitors (SSRIs) in particular, are generally considered to have a much safer pharmacological profile. In our meta-analysis (Kemp et al., 2010), we explored the question as to whether antidepressant medications ameliorate the reductions in HRV associated with depression. Although tricyclic medication was found to further decrease HRV – a finding associated with a large effect size – we found no evidence for the SSRIs or other antidepressant medications including mirtazapine, and nefazodone to increase (or decrease) HRV, even when patients responded to treatment. The impact of the tricyclic antidepressants on HRV has been well reported and our results highlight the robustness of this finding. Decreases in HRV predict future CVD (discussed further below), raising the 11

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question as to whether these older medications increase risk for CVD. A prospective cohort study of 14,784 adults provided such a confirmation (Hamer et al., 2010). TCA antidepressants were reported to raise the risk of developing cardiovascular disease by 35% over 8 years but not all-cause mortality risk. The SSRIs were not associated with

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CVD or all-cause mortality in this study.

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While our meta-analysis provided evidence for the benign effects of the SSRIs, a 2-year longitudinal study (Licht et al., 2010) reported that all classes of antidepressants including the TCAs, the selective serotonin and noradrenaline reuptake inhibitors and the SSRIs, were associated with adverse cardiovascular effects as indicated by reductions in heart

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rate variability (HRV). Patients in the 2-year longitudinal study who discontinued antidepressants experienced the opposite effect; HRV returned to levels observed among

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patients not on antidepressants. Although there were a number of methodological issues with this study that may have contributed to the reported findings (Licht et al., 2010) – we have commented on these previously (Kemp, 2011; Kemp et al., 2011b) – it highlighted

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the sensitivity of HRV measures to different classes of antidepressants and the need for the impact of antidepressants to be examined over much longer time scales (years) than a

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typical clinical trial (8 – 12 weeks).

In addition to the adverse HRV findings on the SSRIs, other studies highlight the need for

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an urgent re-examination of the longer-term impact of the second-generation antidepressants. For instance, the significantly lowered risk of death in patients with

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depression and coronary heart disease treated for SSRIs (Pizzi et al., 2011), is no longer observed when studies with methodological problems are removed from meta-analysis. Another study (Whang et al., 2009) on 63,469 women aged 30 to 55 years without baseline coronary heart disease (CHD) found that while depressive symptoms were associated with fatal CHD, antidepressant use (61% of participants were using an SSRI) was specifically associated with a 3.34 increased risk for sudden cardiac death even after controlling for a variety of confounds including age, smoking status, alcohol intake, physical activity, body mass index and coronary risk factors. Intriguingly, depression no longer conferred an elevated risk after these variables were accounted for. Finally, the US Food and Drug Administration recently advised that the SSRI, citalopram, should no longer be used at doses >40 mg/day, due to prolongation of the QT interval of the electrocardiogram (2011), which might be fatal. In this regard, studies have determined that prolonged QT interval might increase risk of mortality by as much as 35% to 71% (Zhang et al., 2011). 12

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It is interesting to note here that the effects of cognitive behavioural therapy (CBT) appears to have differential effects on HRV as compared to antidepressant medications. In a study of 30 depressed patients with stable CHD (Carney et al., 2000), average heart rate and daytime HRV significantly improved after 16 sessions of CBT, although this finding was

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only observed in the 12 severely depressed individuals relative to the mildly depressed and control patients. In another study of 54 patients with panic disorder (Garakani et al.,

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2009), only those administered CBT displayed decreases in heart rate and increases in HRV, while those receiving CBT with sertraline (an SSRI) did not display any change despite significant clinical improvement. These SSRI findings are consistent with those

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from our own meta-analysis on depression (Kemp et al., 2010), which indicated that antidepressant medication did not increase (or decrease) HRV in MDD patients. Other non-pharmacological interventions including electroconvulsive therapy (Nahshoni et al.,

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2004; Nahshoni et al., 2001), repetitive transcranial magnetic stimulation (Udupa et al., 2007) and biofeedback (Karavidas et al., 2007) also appear to increase HRV in MDD patients. In addition, we recently showed that slow breathing and HRV biofeedback with a

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focus on prolongation of the outbreath enhanced HRV and decreased self-reported anxiety in anxious musicians during stressful performance (Wells et al., 2012). Together,

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these studies provide intriguing evidence of the capacity to increase HRV through nonpharmacological means; this is an important consideration for clinicians treating patients

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with already compromised parasympathetic function. In their review of the literature (Thayer et al., 2010b), Thayer and colleagues describe a

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variety of modifiable CVD risk factors including hypertension, diabetes, cholesterol, psychosocial and lifestyle-related risk factors highlighting the opportunity to minimise the long-term deleterious effects of psychiatric illness. Initiatives such as 10,000 steps a day in combination with objective monitoring of physical activity with pedometers provide a pragmatic means to measure and track habitual levels of activity (Tudor-Locke et al., 2011). Interestingly, exercise increases HRV and reduces levels of TNF and other cytokines, suggesting that the beneficial effects of exercise may, in part, be attributable to the cholinergic anti-inflammatory pathway. Indeed, exercise and other cardiovascular risk reduction strategies including physical exercise, meditation, smoking cessation, dietary changes have been shown to have beneficial effects on HRV (Minami et al., 1999; Park et al., 2009; Rennie et al., 2003; Tang et al., 2009). Critically, research findings now highlight an association between positive psychological wellbeing – a psychological state associated with increased HRV – and cardiovascular health (Boehm and Kubzansky, 13

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2012; Dubois et al., 2012); attributes such as mindfulness, optimism and gratitude appear to be particularly pertinent. Future studies are needed to further examine the effects of antidepressant medications versus psychological treatments of the mood and anxiety disorders on HRV and additional endpoints including the development of CVD and

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mortality.

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Reduced HRV is associated with future adverse health outcomes

While HRV clearly has important functional significance for mental health, over the longerterm, reductions in HRV precede the presence of a variety of CVD risk factors such as hypertension. HRV is also an early marker of CVD and is predictive of mortality (see

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Thayer et al., 2010b for review). An early prospective study on 1,338 normotensive participants recruited as part of the Atherosclerosis Risk in Communities (ARIC) study

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(Liao et al., 1996), reported an inverse association between baseline HRV and risk of incident hypertension within a 3-year follow-up period. Adjusted incident odds ratios ranged from 1.00, 1.46, 1.50 and 2.44 for the highest to the lowest quartiles of HRV

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respectively. A more recent publication from the same study (Schroeder et al., 2003) reported that reduced HRV predicted greater risk of incident hypertension in 7099

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individuals without hypertension at baseline over 9 years of follow-up. Hazard ratios for the lowest compared to the highest quartile ranged between 1.24 and 1.44 providing further

of hypertension.

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support for the proposal that the autonomic nervous system is involved in the development

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Another ARIC study (Dekker et al., 2000) determined HRV from a 2-minute rhythm ECG strip in a random sample of 900 participants (aged 45 to 65) without prevalent coronary heart disease at baseline. Participants with low HRV had an adverse cardiovascular risk profile and an elevated risk of incident CHD and death. The authors reported that middleaged men and women with high heart rate and especially low HRV was associated with a two-fold increased risk of mortality in individuals without a history of CVD. A more recent study on 85 healthy and unmedicated adults with a mean age of 58 years reported that persons with a one standard deviation increase in HRV – determined from a 20-minute ECG resting-state recording – had a 52-59% reduction in their 10-year risk of developing coronary heart disease (CHD) (Yoo et al., 2011). This study also reported an inverse correlation between HRV and the Framingham risk score, a global risk assessment of CHD focusing on patient age, smoking activity, low density lipoprotein cholesterol, high

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density lipoprotein cholesterol, blood pressure and presence of diabetes, although this finding was only observed in men. An early study (Tsuji et al., 1994) on the relationship between reduced HRV and all-cause

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mortality reported that HRV were associated with mortality even after adjusting for relevant risk factors. These findings were based on an elderly cohort of 736 participants from the

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Framingham Heart Study with a mean age of 72 years. One standard deviation decrement in HRV was associated with a 1.70 times greater hazard for all-cause mortality during 4years of follow-up. Two years later, the same authors (Tsuji et al., 1996) reported findings on 2501 participants from the Framingham Heart study (mean age of 53 years) who were

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initially free of clinically apparent coronary heart disease or congestive heart failure. As with their earlier study, the authors concluded that estimation of HRV from 2-hours of

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ambulatory monitoring offered prognostic information beyond that provided by traditional CVD risk factors including age, sex, smoking, diabetes and left ventricular hypertrophy. One standard deviation decrement in HRV was associated with a hazard ratio of 1.47 for

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new cardiac events 3.5 years later.

Another body of work has examined the ability to predict mortality in patients with stable

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CHD and in those with a recent acute coronary event, with findings indicating that HRV accounts for a substantial part of the risk associated with depression in CHD (see Carney

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and Freedland, 2009 for review). In the Multicenter Post-Infarction Program (MPIP), 715 patients underwent a 24-hour continuous ECG recording 2-weeks after myocardial

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infarction and were then followed-up over a period of 4-years (Bigger et al., 1992). The authors reported that even after controlling for 5 previously established post-infarction risk predictors including age, New York Heart Association functional class, pulmonary rales in the coronary care unit phase of the infarction, left ventricular ejection fraction and frequency of ventricular arrhythmias, HRV was able to identify participants with a 2.5 year mortality risk of ~50%. In a later study published by the same authors, 331 un-medicated participants recruited in the Cardiac Arrhythmia Pilot Study underwent a 24-h electrocardiographic (ECG) recording 1-year after infarction and were then followed-up over an interval time up to 3-years after enrolment (Bigger et al., 1993). HRV demonstrated a strong association with mortality with relative risks ranging from 2.5 to 5.6, and these findings were independent of other well known post-infarction risk predictors including heart failure, left ventricular ejection fraction and ventricular arrhythmias. A more recent study (Carney et al., 2005) on 311 depressed patients with a recent acute myocardial infarction recruited for the Enhancing Recovery in Coronary Heart Disease 15

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(ENRICHD) study, reported that depressed patients remained at a higher risk for all-cause mortality over a 30-month follow-up period (hazard ratio: 2.8) after adjusting for potential confounders. The authors also reported that reduced HRV accounted for one-quarter of

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the mortality risk for depression. A working model for the adverse effects of depression, comorbid conditions and

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treatment on HRV

A model (Fig 1) for the adverse effects of the mood and anxiety disorders, alcohol dependence as well as their treatments is presented to guide future research activities. It is hypothesised that the adverse effects (i.e. cardiovascular disease and mortality) of these

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disorders and treatment with antidepressants – particularly the tricyclic antidepressants and serotonin and noradrenaline reuptake inhibitors (SNRIs) – are a consequence of

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chronic autonomic dysregulation (Thayer et al., 2010b), and impairment in the cholinergic inflammatory reflex (Pavlov and Tracey, 2012; Tracey, 2002b, 2007) as operationalized by reductions in HRV. This proposal is based on a number of lines of research: 1) HRV is

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reduced in otherwise healthy, unmedicated patients with mood (Kemp et al., 2010), anxiety disorders (Friedman, 2007; Kemp et al., 2012a), and alcohol dependence

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(Quintana et al., 2013b), 2) associations between HRV and the metabolic syndrome (Licht et al., 2013; Soares-Miranda et al., 2012), with evidence indicating that autonomic

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dysregulation predicts an increase in metabolic abnormalities over time (Licht et al., 2013), 3) reduced vagal activity (reduced HRV) leads to a variety of conditions associated with

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increased allostasis and poor health (Thayer and Sternberg, 2006), attributable to the cholinergic anti-inflammatory pathway (Pavlov and Tracey, 2012; Tracey, 2002b, 2007), 4) associations between the mood disorders and physical illness such as diabetes (Katon et al., 2011), CVD (Glassman et al., 2010) and cancer (Kissane et al., 2011), 5) longitudinal evidence (Licht et al., 2010) indicating that all classes of antidepressants decrease HRV and that HRV increases following their cessation, 6) evidence indicating that the adverse cardiovascular effects are greatest for the TCAs, followed by SNRIs and SSRIs (Licht et al., 2010; Licht et al., 2012), further supported in recent cross-sectional analysis of baseline characteristics (Kemp & colleagues, unpublished observations) of the Brazilian longitudinal study of adult health (ELSA-BRASIL) (Aquino et al., 2012). There is less consensus on the adverse effects of the SSRIs (Kemp et al., 2011b), and 8) epidemiological evidence linking psychological distress (Russ et al., 2012), the mood and anxiety disorders (Phillips et al., 2009) and their pharmacological treatments (Whang et al., 2009) to CVD and mortality. The model draws heavily on the evidence indicating that changes in HRV and chronic 16

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autonomic dysregulation may be the final common pathway for a host of conditions and diseases, including cardiovascular disease and mortality (Thayer et al., 2010b), which may be attributable to impairment in the cholinergic anti-inflammatory pathway (Pavlov and Tracey, 2012; Tracey, 2002b, 2007). It highlights that change in HRV will be observed

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prior to changes in inflammatory markers and oxidative stress; while a typical, diffusible inflammatory response may take hours to days to develop, neural signalling contributing to

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changes in HRV occur within milliseconds (Tracey, 2002b). The established link (Dantzer et al., 2008) between inflammation, sickness and depression is acknowledged, indicated by a bi-directional arrow connecting the mood disorders and comorbid conditions with

highlights

the

possibility

that

the

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downstream risk markers associated with inflammatory processes. The model also adverse

effects

of

chronically

administered

antidepressants – particularly the TCAs and the SNRIs – are associated with downstream

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increases in inflammatory markers including interleukin-6 and C-reactive protein. Indeed, there is already some evidence that this is the case (Hamer et al., 2011). It is also noted that the alleviation of disorder symptoms may, in part, ameliorate the adverse

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cardiovascular effects of antidepressants (i.e. depression severity is negatively correlated with HRV (Kemp et al., 2010)). Non-pharmacological treatments including cognitive and

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behavioural therapies and cardiovascular risk reduction strategies are associated with

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increased HRV – indicated by dashed lines and borders – and reduced disorder severity. Conclusions: Cross-disciplinary findings from clinical epidemiology, to psychophysiology, neuroimaging and molecular neuroscience support a key role for HRV in mental and

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physical wellbeing. While further research is needed on the implications of reduced HRV in otherwise healthy, psychiatric populations, the available evidence suggests that chronic reductions in HRV are closely linked to impairments in the cholinergic anti-inflammatory reflex and downstream changes in allostatic systems that increase risk for CVD and mortality. By contrast, interventions leading to increased HRV and the alleviation of psychiatric symptoms, appear to lower the risk of future morbidity and mortality. We suggest here that otherwise healthy patients with psychiatric illness should consider cardiovascular risk reduction strategies including physical exercise, meditation, smoking cessation, dietary changes– all of which are known to increase HRV – especially when treated with antidepressant medication. In conclusion, HRV provides an easily accessible and meaningful measure of future health and wellbeing.

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References

AC

CE

PT

ED

MA

NU

SC RI

PT

Appelhans, B., Luecken, L., 2006. Heart rate variability as an index of regulated emotional responding. Review of General Psychology 10, 229-240. Aquino, E.M.L., Barreto, S.M., Benseñor, I.M., Carvalho, M.S., Chor, D., Duncan, B.B., Lotufo, P.A., Mill, J.G., Molina, M.D.C., Mota, E.L.A., Azeredo Passos, V.M., Schmidt, M.I., Szklo, M., 2012. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): Objectives and Design. American journal of epidemiology 175, 315-324. Bal, E., Harden, E., Lamb, D., Van Hecke, A.V., Denver, J.W., Porges, S.W., 2010. Emotion recognition in children with autism spectrum disorders: relations to eye gaze and autonomic state. J Autism Dev Disord 40, 358-370. Beauchaine, T.P., Gatzke-Kopp, L., Mead, H.K., 2007. Polyvagal Theory and developmental psychopathology: emotion dysregulation and conduct problems from preschool to adolescence. Biol Psychol 74, 174-184. Berger, S., Boettger, M.K., Tancer, M., Guinjoan, S.M., Yeragani, V.K., Bar, K.J., 2010. Reduced cardio-respiratory coupling indicates suppression of vagal activity in healthy relatives of patients with schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 34, 406-411. Bigger, J.T., Jr., Fleiss, J.L., Rolnitzky, L.M., Steinman, R.C., 1993. Frequency domain measures of heart period variability to assess risk late after myocardial infarction. J Am Coll Cardiol 21, 729-736. Bigger, J.T., Jr., Fleiss, J.L., Steinman, R.C., Rolnitzky, L.M., Kleiger, R.E., Rottman, J.N., 1992. Frequency domain measures of heart period variability and mortality after myocardial infarction. Circulation 85, 164-171. Bloom, D.E., Cafiero, E., Jané-Llopis, E., Abrahams-Gessel, S., Bloom, L.R., Fathima, S., Feigl, A.B., Gaziano, T., Hamandi, A., Mowafi, M., 2011. The Global Economic Burden of Noncommunicable Diseases. World Economic Forum and the Harvard School of Public Health, Geneva. Boehm, J.K., Kubzansky, L.D., 2012. The heart's content: the association between positive psychological well-being and cardiovascular health. Psychol Bull 138, 655-691. Boschloo, L., Vogelzangs, N., Licht, C.M., Vreeburg, S.A., Smit, J.H., van den Brink, W., Veltman, D.J., de Geus, E.J., Beekman, A.T., Penninx, B.W., 2011. Heavy alcohol use, rather than alcohol dependence, is associated with dysregulation of the hypothalamicpituitary-adrenal axis and the autonomic nervous system. Drug Alcohol Depend 116, 170176. Buchhorn, R., Conzelmann, A., Willaschek, C., Stork, D., Taurines, R., Renner, T.J., 2012. Heart rate variability and methylphenidate in children with ADHD. Atten Defic Hyperact Disord 4, 85-91. Carney, R.M., Blumenthal, J.A., Freedland, K.E., Stein, P.K., Howells, W.B., Berkman, L.F., Watkins, L.L., Czajkowski, S.M., Hayano, J., Domitrovich, P.P., Jaffe, A.S., 2005. Low heart rate variability and the effect of depression on post-myocardial infarction mortality. Archives of internal Medicine 165, 1486-1491. Carney, R.M., Freedland, K.E., 2009. Depression and heart rate variability in patients with coronary heart disease. Cleveland Clinic Journal of Medicine 76, S13-S17. Carney, R.M., Freedland, K.E., Stein, P.K., Skala, J.A., Hoffman, P., Jaffe, A.S., 2000. Change in heart rate and heart rate variability during treatment for depression in patients with coronary heart disease. Psychosomatic Medicine 62, 639-647. Cherry, D., Woodwell, D., Rechsteiner, E., 2007. National Ambulatory Medical Care Survey: , 2005 Summary. Advance Data From Vital and Health Statistics; No. 387. National Center for Health Statistics, Hyattsville, MD.

18

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Kemp & Quintana, for review

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AC

CE

PT

ED

MA

NU

SC RI

PT

Dantzer, R., O'Connor, J.C., Freund, G.G., Johnson, R.W., Kelley, K.W., 2008. From inflammation to sickness and depression: when the immune system subjugates the brain. Nature Reviews Neuroscience 9, 46-56. Dekker, J.M., Crow, R.S., Folsom, A.R., Hannan, P.J., Liao, D., Swenne, C.A., Schouten, E.G., 2000. Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes: the ARIC Study. Atherosclerosis Risk In Communities. Circulation 102, 1239-1244. Di Simplicio, M., Costoloni, G., Western, D., Hanson, B., Taggart, P., Harmer, C.J., 2012. Decreased heart rate variability during emotion regulation in subjects at risk for psychopathology. Psychol Med 42, 1775-1783. Dubois, C.M., Beach, S.R., Kashdan, T.B., Nyer, M.B., Park, E.R., Celano, C.M., Huffman, J.C., 2012. Positive psychological attributes and cardiac outcomes: associations, mechanisms, and interventions. Psychosomatics 53, 303-318. FDA, 2011. FDA Drug Safety Communication: Abnormal heart rhythms associated with high doses of Celexa (citalopram hydrobromide), http://www.fda.gov/Drugs/DrugSafety/ucm269086.htm. Friedman, B.H., 2007. An autonomic flexibility-neurovisceral integration model of anxiety and cardiac vagal tone. Biological Psychology 74, 185-199. Garakani, A., Martinez, J.M., Aaronson, C.J., Voustianiouk, A., Kaufmann, H., Gorman, J.M., 2009. Effect of medication and psychotherapy on heart rate variability in panic disorder. Depress Anxiety 26, 251-258. Geisler, F.C., Kubiak, T., Siewert, K., Weber, H., 2013. Cardiac vagal tone is associated with social engagement and self-regulation. Biol Psychol 93, 279-286. Geisler, F.C.M., Vennewald, N., Kubiak, T., Weber, H., 2010. The impact of heart rate variability on subjective well-being is mediated by emotion regulation. Personality and Individual Differences 49, 723-728. Glassman, A., Maj, M., Sartorius, N., 2010. Depression and Heart Disease. John Wiley & Sons Ltd, Chichester, UK. Goodwin, R.D., 2003. Association between physical activity and mental disorders among adults in the United States. Preventive medicine 36, 698-703. Hamer, M., Batty, G., Marmot, M.G., Singh-Manoux, A., Kivimaki, M., 2011. Antidepressant medication use and C-reactive protein: Results from two population-based studies. Brain, behavior, and immunity 25, 168-173. Hamer, M., Batty, G.D., Seldenrijk, A., Kivimaki, M., 2010. Antidepressant medication use and future risk of cardiovascular disease: the Scottish Health Survey. European heart journal. Hansen, A.L., Johnsen, B.H., Thayer, J.F., 2003. Vagal influence on working memory and attention. Int J Psychophysiol 48, 263-274. Henry, B.L., Minassian, A., Paulus, M.P., Geyer, M.A., Perry, W., 2010. Heart rate variability in bipolar mania and schizophrenia. J Psychiatr Res 44, 168-176. Huston, J.M., Tracey, K.J., 2011. The pulse of inflammation: heart rate variability, the cholinergic anti-inflammatory pathway and implications for therapy. J Intern Med 269, 4553. Jane-Llopis, E., Matytsina, I., 2006. Mental health and alcohol, drugs and tobacco: a review of the comorbidity between mental disorders and the use of alcohol, tobacco and illicit drugs. Drug Alcohol Rev 25, 515-536. Karavidas, M.K., Lehrer, P.M., Vaschillo, E., Vaschillo, B., Marin, H., Buyske, S., Malinovsky, I., Radvanski, D., Hassett, A., 2007. Preliminary results of an open label study of heart rate variability biofeedback for the treatment of major depression. Appl Psychophysiol Biofeedback 32, 19-30. Kashdan, T.B., Rottenberg, J., 2010. Psychological flexibility as a fundamental aspect of health. Clinical Psychology Review 30, 865-878. 19

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Katon, W., Maj, M., Sartorius, N., 2011. Depression and Diabetes. John Wiley & Sons Ltd, Chichester, UK. Kemp, A., 2011. Depression, antidepressant treatment and the cardiovascular system. Acta Neuropsychiatrica 23, 82-83. Kemp, A.H., 2012. Reply to: Are Antidepressants Good for the Soul but Bad for the Matter? Using Noninvasive Brain Stimulation to Detangle Depression/Antidepressants Effects on Heart Rate Variability and Cardiovascular Risk. Biological Psychiatry. Kemp, A.H., Quintana, D.S., Felmingham, K.L., Matthews, S., Jelinek, H.F., 2012a. Depression, Comorbid Anxiety Disorders, and Heart Rate Variability in Physically Healthy, Unmedicated Patients: Implications for Cardiovascular Risk. PLoS ONE 7, e30777. Kemp, A.H., Quintana, D.S., Gray, M.A., 2011a. Is Heart Rate Variability Reduced in Depression Without Cardiovascular Disease. BPS 69, 3-4. Kemp, A.H., Quintana, D.S., Gray, M.A., Felmingham, K.L., Brown, K., Gatt, J.M., 2010. Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biol Psychiatry 67, 1067-1074. Kemp, A.H., Quintana, D.S., Kuhnert, R.-L., Griffiths, K., Hickie, I.B., Guastella, A.J., 2012b. Oxytocin Increases Heart Rate Variability in Humans at Rest: Implications for Social Approach-Related Motivation and Capacity for Social Engagement. PLoS ONE 7, e44014. Kemp, A.H., Quintana, D.S., Malhi, G.S., 2011b. Effects of serotonin reuptake inhibitors on heart rate variability: methodological issues, medical comorbidity, and clinical relevance. Biological Psychiatry 69, e25-26; author reply e27-28. Kessler, R.C., Chiu, W.T., Demler, O., Merikangas, K.R., Walters, E.E., 2005. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of general psychiatry 62, 617-627. Kissane, D., Maj, M., Sartorius, N., 2011. Depression and Cancer. John Wiley & Sons Ltd, Chichester, UK. Kluttig, A., Kuss, O., Greiser, K.H., 2010. Ignoring lack of association of heart rate variability with cardiovascular disease and risk factors: response to the manuscript "The relationship of autonomic imbalance, heart rate variability cardiovascular disease risk factors" by Julian F. Thayer, Shelby S. Yamamoto, Jos F. Brosschot. Int J Cardiol 145, 375-376. Koskinen, T., Kahonen, M., Jula, A., Mattsson, N., Laitinen, T., Keltikangas-Jarvinen, L., Viikari, J., Valimaki, I., Ronnemaa, T., Raitakari, O.T., 2009. Metabolic syndrome and short-term heart rate variability in young adults. The cardiovascular risk in young Finns study. Diabet Med 26, 354-361. Lee, J.S., Kim, B., Hong, Y., Joo, Y.H., 2012. Heart rate variability in the subsyndromal depressive phase of bipolar disorder. Psychiatry Clin Neurosci 66, 361-366. Liao, D., Cai, J., Barnes, R.W., Tyroler, H.A., Rautaharju, P., Holme, I., Heiss, G., 1996. Association of cardiac autonomic function and the development of hypertension: the ARIC study. Am J Hypertens 9, 1147-1156. Licht, C.M., de Geus, E.J., Penninx, B.W., 2013. Dysregulation of the Autonomic Nervous System Predicts the Development of the Metabolic Syndrome. J Clin Endocrinol Metab. Licht, C.M.M., de Geus, E.J.C., van Dyck, R., Penninx, B.W.J.H., 2010. Longitudinal evidence for unfavorable effects of antidepressants on heart rate variability. Biological Psychiatry 68, 861-868. Licht, C.M.M., de Geus, E.J.C., Zitman, F.G., Hoogendijk, W.J.G., van Dyck, R., Penninx, B.W.J.H., 2008. Association between major depressive disorder and heart rate variability in the Netherlands Study of Depression and Anxiety (NESDA). Archives of general psychiatry 65, 1358-1367.

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Licht, C.M.M., Penninx, B.W., de Geus, E.J.C., 2011a. To include or not to include? A response to the meta-analysis of heart rate variability and depression. Biological Psychiatry 69, e1; author reply e3-4. Licht, C.M.M., Penninx, B.W.J.H., de Geus, E.J.C., 2012. Effects of Antidepressants, but not Psychopathology, on Cardiac Sympathetic Control: A Longitudinal Study. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 1-9. Licht, C.M.M., Penninx, B.W.J.H., Geus, E.J.C.d., 2011b. Reply to: Effects of Serotonin Reuptake Inhibitors on Heart Rate Variability: Methodological Issues, Medical Comorbidity, and Clinical Relevance. BPS, 1-2. Lichtman, J.H., Bigger, J.T., Blumenthal, J.A., Frasure-Smith, N., Kaufmann, P.G., Lespérance, F., Mark, D.B., Sheps, D.S., Taylor, C.B., Froelicher, E.S., Nursing, A.H.A.P.C.o.t.C.o.C., Cardiology, A.H.A.C.o.C., Prevention, A.H.A.C.o.E.a., Research, A.H.A.I.C.o.Q.o.C.a.O., Association, A.P., 2008. Depression and coronary heart disease: recommendations for screening, referral, and treatment: a science advisory from the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing, Council on Clinical Cardiology, Council on Epidemiology and Prevention, and Interdisciplinary Council on Quality of Care and Outcomes Research: endorsed by the American Psychiatric Association. Circulation 118, 1768-1775. Markkula, N., Harkanen, T., Perala, J., Partti, K., Pena, S., Koskinen, S., Lonnqvist, J., Suvisaari, J., Saarni, S.I., 2012. Mortality in people with depressive, anxiety and alcohol use disorders in Finland. Br J Psychiatry 200, 143-149. Mathers, C.D., Loncar, D., 2006. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Medicine 3, e442. Middleton, K., Him, E., Xu, J., 2007. National Hospital Ambulatory Medical Care Survey:, 2005 Outpatient Department Summary. Advance Data From Vital and Health Statistics;

AC

CE

No. 389. National Center for Health Statistics, Hyattsville, MD. Minami, J., Ishimitsu, T., Matsuoka, H., 1999. Effects of smoking cessation on blood pressure and heart rate variability in habitual smokers. Hypertension 33, 586-590. Nahshoni, E., Aizenberg, D., Sigler, M., Strasberg, B., Zalsman, G., Imbar, S., Adler, E., Weizman, A., 2004. Heart rate variability increases in elderly depressed patients who respond to electroconvulsive therapy. Journal of psychosomatic research 56, 89-94. Nahshoni, E., Aizenberg, D., Sigler, M., Zalsman, G., Strasberg, B., Imbar, S., Weizman, A., 2001. Heart rate variability in elderly patients before and after electroconvulsive therapy. The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry 9, 255-260. Nemeroff, C.B., Goldschmidt-Clermont, P.J., 2012. Heartache and heartbreak—the link between depression and cardiovascular disease. Nature Publishing Group 9, 526-539. Oveis, C., Cohen, A.B., Gruber, J., Shiota, M.N., Haidt, J., Keltner, D., 2009. Resting respiratory sinus arrhythmia is associated with tonic positive emotionality. Emotion (Washington, DC) 9, 265-270. Pan, A., Sun, Q., Okereke, O.I., Rexrode, K.M., Hu, F.B., 2011. Depression and risk of stroke morbidity and mortality: a meta-analysis and systematic review. JAMA: The Journal of the American Medical Association 306, 1241-1249. Park, S.K., Tucker, K.L., O'Neill, M.S., Sparrow, D., Vokonas, P.S., Hu, H., Schwartz, J., 2009. Fruit, vegetable, and fish consumption and heart rate variability: the Veterans Administration Normative Aging Study. Am J Clin Nutr 89, 778-786. Pavlov, V.A., Tracey, K.J., 2012. The vagus nerve and the inflammatory reflex--linking immunity and metabolism. Nat Rev Endocrinol 8, 743-754. Phillips, A.C., Batty, G.D., Gale, C.R., Deary, I.J., Osborn, D., MacIntyre, K., Carroll, D., 2009. Generalized anxiety disorder, major depressive disorder, and their comorbidity as 21

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predictors of all-cause and cardiovascular mortality: the Vietnam experience study. Psychosom Med 71, 395-403. Pizzi, C., Rutjes, A.W.S., Costa, G.M., Fontana, F., Mezzetti, A., Manzoli, L., 2011. MetaAnalysis of Selective Serotonin Reuptake Inhibitors in Patients With Depression and Coronary Heart Disease. The American journal of cardiology 107, 972-979. Porges, S.W., 1995. Orienting in a defensive world: mammalian modifications of our evolutionary heritage. A Polyvagal Theory. Psychophysiology 32, 301-318. Porges, S.W., 1997. Emotion: an evolutionary by-product of the neural regulation of the autonomic nervous system. Ann N Y Acad Sci 807, 62-77. Porges, S.W., 2001. The polyvagal theory: phylogenetic substrates of a social nervous system. International journal of psychophysiology : official journal of the International Organization of Psychophysiology 42, 123-146. Porges, S.W., 2003a. The Polyvagal Theory: phylogenetic contributions to social behavior. Physiology & Behavior 79, 503-513. Porges, S.W., 2003b. Social engagement and attachment: a phylogenetic perspective. Annals of the New York Academy of Sciences 1008, 31-47. Porges, S.W., 2007. The polyvagal perspective. Biological Psychology 74, 116-143. Porges, S.W., 2009a. The polyvagal theory: new insights into adaptive reactions of the autonomic nervous system. Cleveland Clinic Journal of Medicine 76 Suppl 2, S86-90. Porges, S.W., 2009b. The polyvagal theory: New insights into adaptive reactions of the autonomic nervous system. Cleveland Clinic Journal of Medicine 76, S86-S90. Porges, S.W., 2011. The Polyvagal Theory: Neurophysiological Foundations of Emotions, Attachment, Communication, and Self-regulation, 1st ed. W. W. Norton & Company, New York. Quintana, D., Guastella, A., McGregor, I., Hickie, I., Kemp, A., in press. Heart rate variability predicts alcohol craving in alcohol dependent outpatients: Further evidence for HRV as a psychophysiological marker of self-regulation. Drug and Alcohol Dependence. Quintana, D.S., Guastella, A.J., Outhred, T., Hickie, I.B., Kemp, A.H., 2012. Heart rate variability is associated with emotion recognition: Direct evidence for a relationship between the autonomic nervous system and social cognition. International Journal of Psychophysiology 86, 168-172. Quintana, D.S., Kemp, A.H., Alvares, G.A., Guastella, A.J., 2013a. A role for autonomic cardiac control in the effects of oxytocin on social behavior and psychiatric illness. Front Neurosci 7, 48. Quintana, D.S., McGregor, I.S., Guastella, A.J., Malhi, G.S., Kemp, A.H., 2013b. A MetaAnalysis on the Impact of Alcohol Dependence on Short-Term Resting-State Heart Rate Variability: Implications for Cardiovascular Risk. Alcoholism: Clinical and Experimental Research 37, E23-29. Rehm, J., Mathers, C., Popova, S., Thavorncharoensap, M., Teerawattananon, Y., Patra, J., 2009. Global burden of disease and injury and economic cost attributable to alcohol use and alcohol-use disorders. Lancet 373, 2223-2233. Rennie, K.L., Hemingway, H., Kumari, M., Brunner, E., Malik, M., Marmot, M., 2003. Effects of moderate and vigorous physical activity on heart rate variability in a British study of civil servants. American journal of epidemiology 158, 135-143. Rudisch, B., Nemeroff, C.B., 2003. Epidemiology of comorbid coronary artery disease and depression. Biol Psychiatry 54, 227-240. Ruiz-Padial, E., Sollers, J.J., 3rd, Vila, J., Thayer, J.F., 2003. The rhythm of the heart in the blink of an eye: emotion-modulated startle magnitude covaries with heart rate variability. Psychophysiology 40, 306-313. Russ, T.C., Stamatakis, E., Hamer, M., Starr, J.M., Kivimaki, M., Batty, G.D., 2012. Association between psychological distress and mortality: individual participant pooled analysis of 10 prospective cohort studies. BMJ 345, e4933. 22

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Schmitz, N., Kruse, J., Heckrath, C., Alberti, L., Tress, W., 1999. Diagnosing mental disorders in primary care: the General Health Questionnaire (GHQ) and the Symptom Check List (SCL-90-R) as screening instruments. Soc Psychiatry Psychiatr Epidemiol 34, 360-366. Schroeder, E.B., Liao, D., Chambless, L.E., Prineas, R.J., Evans, G.W., Heiss, G., 2003. Hypertension, blood pressure, and heart rate variability: the Atherosclerosis Risk in Communities (ARIC) study. Hypertension 42, 1106-1111. Soares-Miranda, L., Sandercock, G., Vale, S., Santos, R., Abreu, S., Moreira, C., Mota, J., 2012. Metabolic syndrome, physical activity and cardiac autonomic function. Diabetes Metab Res Rev 28, 363-369. Tang, Y., Ma, Y., Fan, Y., Feng, H., WANG, J., Feng, S., Lu, Q., Hu, B., Lin, Y., Li, J., 2009. Central and autonomic nervous system interaction is altered by short-term meditation. Proceedings of the National Academy of Sciences 106, 8865-8870. Taylor, C.B., 2010. Depression, heart rate related variables and cardiovascular disease. International journal of psychophysiology : official journal of the International Organization of Psychophysiology 78, 80-88. Thayer, J.F., 2009. Vagal tone and the inflammatory reflex. Cleveland Clinic Journal of Medicine 76 Suppl 2, S23-26. Thayer, J.F., Ahs, F., Fredrikson, M., Sollers Iii, 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. Neuroscience and Biobehavioral Reviews 36, 747-756. Thayer, J.F., Brosschot, J.F., 2005. Psychosomatics and psychopathology: looking up and down from the brain. Psychoneuroendocrinology 30, 1050-1058. 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., Lane, R.D., 2000. A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders 61, 201-216. Thayer, J.F., Lane, R.D., 2007. The role of vagal function in the risk for cardiovascular disease and mortality. Biological Psychology 74, 224-242. Thayer, J.F., Lane, R.D., 2009. Claude Bernard and the heart-brain connection: further elaboration of a model of neurovisceral integration. Neuroscience and Biobehavioral Reviews 33, 81-88. Thayer, J.F., Sternberg, E., 2006. Beyond heart rate variability: vagal regulation of allostatic systems. Annals of the New York Academy of Sciences 1088, 361-372. Thayer, J.F., Yamamoto, S.S., Brosschot, J.F., 2010a. On the nature of risk factors: a response to Kluttig, Kuss, and Greiser. Int J Cardiol 145, 560-561. Thayer, J.F., Yamamoto, S.S., Brosschot, J.F., 2010b. The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. International Journal of Cardiology 141, 122-131. Tracey, K., 2002a. The inflammatory reflex. Nature 420, 853-859. Tracey, K.J., 2002b. The inflammatory reflex. Nature 420, 853-859. Tracey, K.J., 2007. Physiology and immunology of the cholinergic antiinflammatory pathway. J Clin Invest 117, 289-296. Tsuji, H., Larson, M., Venditti, F., Manders, E., Evans, J., Feldman, C., Levy, D., 1996. Impact of reduced heart rate variability on risk for cardiac events: the Framingham Heart Study. Circulation 94, 2850. Tsuji, H., Venditti Jr, F., Manders, E., Evans, J., Larson, M., Feldman, C., Levy, D., 1994. Reduced heart rate variability and mortality risk in an elderly cohort. The Framingham Heart Study. Circulation 90, 878. Tudor-Locke, C., Craig, C.L., Brown, W.J., Clemes, S.A., De Cocker, K., Giles-Corti, B., Hatano, Y., Inoue, S., Matsudo, S.M., Mutrie, N., Oppert, J.M., Rowe, D.A., Schmidt, M.D., 23

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Schofield, G.M., Spence, J.C., Teixeira, P.J., Tully, M.A., Blair, S.N., 2011. How many steps/day are enough? For adults. The international journal of behavioral nutrition and physical activity 8, 79. Udupa, K., Sathyaprabha, T.N., Thirthalli, J., Kishore, K.R., Raju, T.R., Gangadhar, B.N., 2007. Modulation of cardiac autonomic functions in patients with major depression treated with repetitive transcranial magnetic stimulation. Journal of Affective Disorders 104, 231236. Van Der Kooy, K., Van Hout, H., Marwijk, H., Marten, H., Stehouwer, C., Beekman, A., 2007. Depression and the risk for cardiovascular diseases: systematic review and meta analysis. International Journal of Geriatric Psychiatry 22, 613-626. Vogelzangs, N., Seldenrijk, A., Beekman, A.T.F., van Hout, H.P.J., de Jonge, P., Penninx, B.W.J.H., 2010. Cardiovascular disease in persons with depressive and anxiety disorders. Journal of Affective Disorders 125, 241-248. W Porges, S., 1998. Love: An emergent property of the mammalian autonomic nervous system. Psychoneuroendocrinology 23, 837-861. Wang, H., Yu, M., Ochani, M., Amella, C.A., Tanovic, M., Susarla, S., Li, J.H., Wang, H., Yang, H., Ulloa, L., Al-Abed, Y., Czura, C.J., Tracey, K.J., 2003. Nicotinic acetylcholine receptor alpha7 subunit is an essential regulator of inflammation. Nature 421, 384-388. Wells, R., Outhred, T., Heathers, J.A.J., Quintana, D.S., Kemp, A.H., 2012. Matter Over Mind: A Randomised-Controlled Trial of Single-Session Biofeedback Training on Performance Anxiety and Heart Rate Variability in Musicians. PLoS ONE 7, e46597. Whang, W., Kubzansky, L.D., Kawachi, I., Rexrode, K.M., Kroenke, C.H., Glynn, R.J., Garan, H., Albert, C.M., 2009. Depression and Risk of Sudden Cardiac Death and Coronary Heart Disease in Women. Journal of the American College of Cardiology 53, 950-958. Windham, B.G., Fumagalli, S., Ble, A., Sollers, J.J., Thayer, J.F., Najjar, S.S., Griswold, M.E., Ferrucci, L., 2012. The Relationship between Heart Rate Variability and Adiposity Differs for Central and Overall Adiposity. Journal of Obesity 2012, 8. Yasuma, F., 2004. Respiratory Sinus Arrhythmia: Why Does the Heartbeat Synchronize With Respiratory Rhythm? Chest 125, 683-690. Yoo, C.S., Lee, K., Yi, S.H., Kim, J.S., Kim, H.C., 2011. Association of heart rate variability with the framingham risk score in healthy adults. Korean journal of family medicine 32, 334-340. Zhang, Y., Post, W.S., Blasco-Colmenares, E., Dalal, D., Tomaselli, G.F., Guallar, E., 2011. Electrocardiographic QT interval and mortality: a meta-analysis. Epidemiology 22, 660-670.

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Model summary for the link between the mood disorders, comorbid conditions, cardiovascular disease and mortality. The mood and anxiety disorders, and alcohol dependence are associated with reduced HRV. Antidepressant medications – particularly tricyclic medications and the serotonin and noradrenaline reuptake inhibitors – are also associated with reduced HRV, while non-pharmacological therapies are associated with increased HRV. Response to treatment and cardiovascular risk reduction strategies such as physical exercise, meditation, smoking cessation and dietary changes may increase HRV partly ameliorating adverse downstream effects. Current debate in the literature has focused on whether the disorder or medications are driving the adverse effects reported in the literature highlighting the need for further study. Fewer studies have focused on the impact of non-pharmacological therapies – relative to medication – on HRV. HRV is argued to precede downstream risk markers such as tumor-necrosis factor on the basis of evidence highlighting an important regulatory role of the vagus nerve in inflammatory processes. A poorly functioning cholinergic inflammatory reflex (indexed by reduced HRV) will lead to downstream risk markers, and morbidity and mortality from a host of conditions including cardiovascular disease.

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Figure 1

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Highlights 1) Heart rate variability (HRV) reflects autonomic dysregulation 2) Autonomic dysregulation leads to morbidity and mortality

4) Antidepressant medications have adverse effects on HRV

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3) HRV is reduced in otherwise healthy patients with mood disorders

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5) Further research on physically healthy patients with mood disorders disease needed

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