Mind and heart: Heart rate variability in major depressive disorder and coronary heart disease

Abstract

Objective:

There is a reciprocal association between major depressive disorder (MDD) and coronary heart disease (CHD). These conditions are linked by a causal network of mechanisms. This causal network should be quantitatively studied and it is hypothesised that the investigation of vagal function represents a promising starting point. Heart rate variability (HRV) has been used to investigate cardiac vagal control in the context of MDD and CHD. This review aims to examine the relationship of HRV to both MDD and CHD in the context of vagal function and to make recommendations for clinical practice and research.

Methods:

The search terms ‘heart rate variability’, ‘depression’ and ‘heart disease’ were entered into an electronic multiple database search engine. Abstracts were screened for their relevance and articles were individually selected and collated.

Results:

Decreased HRV is found in both MDD and CHD. Both diseases are theorised to disrupt autonomic control feedback loops on the heart and are linked to vagal function. Existing theories link vagal function to both mood and emotion as well as cardiac function. However, several factors can potentially confound HRV measures and would thus impact on a complete understanding of vagal mechanisms in the link between MDD and CHD.

Conclusions:

The quantitative investigation of vagal function using HRV represents a reasonable starting point in the study of the relationship between MDD and CHD. Many psychotropic and cardiac medications have effects on HRV, which may have clinical importance. Future studies of HRV in MDD and CHD should consider antidepressant medication, as well as anxiety, as potential confounders.

Keywords

Coronary heart disease heart rate variability major depressive disorder

Introduction

Both major depressive disorder (MDD) and coronary heart disease (CHD) are significant diseases on a worldwide scale. MDD is a major contributor to the global burden of disease (Vos and Mathers, 2000), as is CHD (World Health Organization, 2008). MDD is currently ranked third in terms of global burden of disease worldwide and CHD is ranked fourth globally, although in middle- and high-income countries MDD is ranked first and CHD second (World Health Organization, 2008). Importantly, there is a reciprocal relationship between MDD and CHD. People suffering MDD have an increased risk of adverse ischaemic cardiac events (Carney et al., 1988; Rugulies, 2002; Wulsin and Singal, 2003). Conversely, there is a greater prevalence of major depression in CHD patients (Rozanski et al., 1999; Thombs et al., 2006). MDD and CHD are linked by several mechanisms, including behavioural mechanisms, genetic mechanisms, immune mechanisms, polyunsaturated omega-3 fatty acid deficiency, mechanisms involving coagulopathy and endothelial dysfunction, and autonomic mechanisms. Several reviews have discussed one or more of these causal mechanisms (e.g. Barth et al., 2004; Goldston and Baillie, 2008; Musselman et al., 1998). These mechanisms may form the nodes in a causal network which gives rise to a reciprocal association between the diseases (De Jonge et al., 2010; Stapelberg et al., 2011). To understand this causal network, a quantitative methodology is required to investigate each mechanism or node in the network and quantify the contribution that each makes to the entire network.

Objective

The present review aims to explore the use of heart rate variability (HRV) measures to investigate vagal function in both MDD and CHD, with the view to making recommendations for clinical practice and research. A recent review in this journal (Stapelberg et al., 2011) has already provided a detailed discussion of the various mechanisms linking CHD and MDD, including sympathetic and parasympathetic mechanisms. The justification to examine vagal function, as a means of investigating the quantitative study of the relationship between CHD and MDD, relies on two premises: the central role of vagal function in both diseases and the existence of HRV as a quantitative index of vagal function.

First, vagal function is significantly linked with other autonomic mechanisms, as well as inflammatory mechanisms, in the causal network linking MDD and CHD (see Stapelberg et al., 2011). Furthermore, vagal activity is a controlling mechanism, as shown by its interaction with sympathetic autonomic mechanisms and in the vagal control of immune function. Cardiac vagal control (CVC) is considered to be the result of a dynamic equilibrium between sympathetic and parasympathetic activity (Rottenberg, 2007), although this equilibrium may be driven primarily by vagal influence. Furthermore, the vagal control of immune function is described by Tracey (2002) in the context of the theory of the neuro-inflammatory reflex, where it is postulated that normal vagal function is a key inhibitor of cytokine release. Vagal dysfunction has been linked to increased levels of inflammatory cytokines, which in turn has been linked to CHD.

Second, it has been argued that measures of CVC, such as HRV, reflect vagal activity (Brown et al., 2009; Levy, 1990; Thayer and Lane, 2000). Heart rate varies continuously, reflecting the dynamic equilibrium which exists between the various control mechanisms acting on the heart. These complex beat-to-beat variations are termed ‘heart rate variability’ (Carney et al., 2001). HRV measures have been discussed as direct measures of CVC (Rottenberg, 2007). As a consequence, the application of linear and non-linear measures of HRV can be used to quantitatively assess vagal function in MDD and CHD.

Methods

A literature search was conducted with the purpose of cross-referencing HRV methods with both MDD and CHD. The terms ‘heart rate variability’ AND ‘depression’ AND ‘heart disease’ were entered to search the following databases: MEDLINE 1950 to present (Ovid), BioMed Central, BMJ Clinical Evidence, BMJ Journals Online, Cambridge Journals Online, Highwire Press, IngentaConnect, LANGE Educational Library, Lippincott, Williams & Wilkins e-journals (Ovid), LOCATORplus, Medi-Lexicon, MEDLINE (EBSCOhost), MEDLINE (via PubMed), MEDLINE – OLDMEDLINE 1951–1965 (Ovid), MEDLINE In-Process (Ovid), Oxford Journals Online, PLoS: Public Library of Science, ProQuest (multiple databases), ProQuest Dissertations and Theses – Full Text, PsycINFO (Ovid), PubMed, ScienceDirect, ScienceDirect: Medicine and Dentistry, SCIRUS (Elsevier), SpringerLink, STAT!Ref: Nursing and Allied Health Collection, SUMSearch, SwetsWise, Taylor and Francis ebook collection, Web of Knowledge (ISI), Web of Science (ISI) and Wiley InterScience. There were no constraints applied to the search.

The abstracts of each article arising from the search were screened for their relevance to the topic and scope of the review. During this process, the articles were divided up into empirical studies and literature reviews. Articles were individually selected and collated. In addition, the reference lists of relevant articles were screened for further articles of relevance. The contents of the resulting articles were critically synthesised by identifying articles that directly investigated or reviewed vagal function and/or HRV in the context of MDD and CHD. The major themes that resulted from this review are reported below.

Results

Theories of vagal function in the relationship between major depression and CHD

The literature search revealed two major theories of a vagally mediated link between MDD and CHD: polyvagal theory and the theory of neurovisceral integration. Both theories implicate the vagal system in emotion and social communication and shed light on the role of autonomic dysfunction in relation to MDD and CHD. The theories differ in that while the polyvagal theory utilises functional anatomical and evolutionary paradigms, the theory of neurovisceral integration expands on these concepts using a dynamical systems perspective.

Polyvagal theory

Polyvagal theory established a link between the autonomic nervous system and various aspects of social communication, particularly the communication of emotion (Porges, 1995, 1997, 1998, 2001, 2003). The primary hypothesis of the polyvagal theory is that the range of affective and social behaviours in mammals is dependent on the ability to regulate visceral homeostasis, including cardiac control, mediated by vagal signalling (Rottenberg et al., 2007). Vagal dysfunction therefore has an impact on emotion and social communication, which can manifest as MDD. The polyvagal theory is supported by functional anatomical evidence and evolutionary phylogenetic evidence.

Functional anatomical evidence

The vagus nerve has two branches termed the ventrally located nucleus ambiguus (nA) (Nabi et al., 2010) and the dorsal motor nucleus (DMN) (Porges, 1995). Porges (1995) suggested that the efferent pathway that emerges from the nA in the brain stem evolved a role in emotion and communication of emotion. This branch of the vagus innervates a number of visceral organs such as the heart, soft palate, pharynx, larynx, oesophagus, bronchi, and facial muscles. These in turn are involved in communication (vocalizations) and emotional responses. If the vagus nerve, or a branch thereof, is implicated in facilitating communication and in modulating emotional states, vagal dysfunction may be linked to emotional changes, particularly psychopathology such as depression (Rottenberg, 2007).

Because dysfunction in non-verbal communication and social behaviour are central to mood disorders, the polyvagal theory thus provides a link between depressed states and vagal dysfunction. Depression has been associated with reduced social engagement and social isolation (Rottenberg and Gotlib, 2004), as well as relationship problems such as marital difficulties or conflicted relationships with family and friends (Segrin and Abramson, 1994). Non-verbal communication is also affected. People with depression exhibit a flattening of affect, showing a reduced range of facial expressions (Greden et al., 1986) and reduced gaze behaviour (Ellgring, 1989). Depression is also linked to inflexibility in responding to environmental demands and changing set when a situation demands it (Rottenberg, 2005). For example, depressed patients show a decrease in magnitude of startle response compared to normal subjects (Allen et al., 1999).

Evolutionary phylogenetic evidence

The polyvagal theory maintains that the functionally distinct vagal systems in mammals are characterized in terms of their evolution (Porges, 1995, 2003). The DMN is proposed to be a phylogenetically more primitive vagal system than the nA. It is postulated to exist as the sole vagal system in animals such as reptiles and innervates visceral organs such as the gastrointestinal tract (Porges, 2003). Mammals have the two vagal systems described above, with the nA having evolved to innervate the heart and lungs, but also to gradually have a function in communication and social behaviour. However, Grossman and Taylor (2007) have argued that the polyvagal theory does not accurately depict evolution of vagal control of HRV and that the theory does not account for the evolution of a functional role for vagal control of the heart, including respiratory sinus arrhythmia (RSA). It has been suggested that the evolution of the vagal system as proposed by Porges implies that precise vagal control of the heart first evolved in mammals, which is controversial (Grossman and Taylor, 2007).

RSA as a measure of the nA vagal branch

A key tenet of the polyvagal theory is that RSA is a principal measure of nA-generated vagal efferent discharge. One of the criticisms of the polyvagal theory is that RSA does not accurately reflect the activity of the nA vagal branch. It has been argued that if RSA is the key measure used to evaluate the premises of the polyvagal theory, inaccuracies in the measure could undermine the theory (Grossman and Taylor, 2007). Interpretation of vagal tone may be subject to many specific confounders, including respiratory parameters, differences in how RSA is related to cardiac vagal tone in individual people, and levels of physical activity at the time of measurement (Grossman and Taylor, 2007). In addition, beta-adrenergic tone can confound RSA. There is also evidence that RSA is not a pure measure of vagal tone as it can be affected by sympathetic tone (Grossman and Taylor, 2007). Despite some aspects of the theory remaining controversial, however, there has been widespread interest in the polyvagal theory as shown by the original paper by Porges (1995) having had 486 citations to date.

The theory of neurovisceral integration

The theory of neurovisceral integration, described by Thayer and Lane (2000), arises from the application of dynamical systems theory to the concepts of emotion and behaviour. It also builds on the ideas of polyvagal theory. In this context, emotion is described as facilitating the rapid initiation of an appropriate behavioural sequence in response to environmental stimuli (Thayer and Lane, 2000). An emotional response to a given environmental situation thus allows the selection of specific goal-directed behaviours – and the inhibition of other less appropriate behaviours – from the organism’s total behavioural repertoire.

The evidence for the neurovisceral theory arises from studies which demonstrate cortical control of cardiac activity, the inhibition of right cortical input in circumstances of stress and vagal control of emotional, physiological and cognitive regulation (Thayer and Lane, 2009). Goal-directed behaviour is linked to autonomic function via systems such as the central autonomic network (CAN) (Benarroch, 1993) which links several brain structures with vagal output. These include the anterior cingulate, insular, and ventromedial prefrontal cortices, the central nucleus of the amygdala, the paraventricular and related nuclei of the hypothalamus, the periaquaductal grey matter, the parabrachial nucleus, the nucleus of the solitary tract, the nucleus ambiguus, the ventrolateral medulla, the ventromedial medulla, and the medullary tegmental field (Thayer and Lane, 2000). Because this system is linked to cardiac control via the vagus nerve, its output is theoretically measurable by HRV techniques. Another functional unit associated with goal-directed behaviours is the anterior executive region (AER) (Devinsky et al., 1995), comprising the anterior, insular, and orbitofrontal cortices, the amygdala, the periaquaductal grey, the ventral striatum, and autonomic brainstem motor nuclei.

Structures in the prefrontal cortex play an inhibitory role of subcortical cardiac control circuits via a vagal pathway (Ter Horst, 1999). These circuits are predominantly right-sided (Thayer and Lane, 2009). It has been argued that the right hemisphere’s greater involvement in emotion is due to the localization of autonomic control circuits in that hemisphere and the relative right hemisphere innervation of the heart (Ahern et al., 2001). The cortical innervation of the myocardium is predominantly mediated by right-sided neural fibres (Ter Horst and Postema, 1997; Chuang et al., 2004). The prefrontal cortex thus has control over HRV changes via vagal pathways, particularly via right-sided anterior neural structures (Thayer and Lane, 2009). However, this evidence is in part derived from neuroimaging studies (Thayer and Lane, 2009), which have a complex methodology and can be subject to confounders, such as physiological noise artefacts (e.g. see Napadow et al., 2008).

It has been suggested that attentional regulation and affective regulation function as an integrated system to allow an organism to self-regulate and adapt to environmental changes (Heilman, 1997). The neurovisceral integration theory proposes that during threat situations the pre-frontal cortex disengages, allowing subcortical neural structures such as the amygdala to respond more rapidly to these situations (Arnsten and Goldman-Rakic, 1998). However, these responses are also more automatic and non-volitional, lacking flexibility, which could be a disadvantage in situations of continual stress (Thayer and Lane, 2009).

Given that cardiac vagal tone has been related to attentional control and emotional regulation (Thayer and Lane, 2000), vagal function (or dysfunction) is thus related directly to MDD. It is thought that high vagal tone relates to the ability to self regulate, allowing greater adaptability and behavioural flexibility to respond to environmental changes or stressors, whereas low vagal tone is associated with poor flexibility and adaptability (Porges, 1992). Depressive mental illness represents a dysregulation of these processes, leaving the organism trapped in an emotional state which renders it less adaptable to environmental stressors and less able to respond to them (Thayer and Lane, 2000). The neurovisceral integration theory thus links the regulation of key physiological systems that are important for health and disease to vagal function and HRV (Thayer and Lane, 2009). Further, Thayer and Lane (2009) suggest that all the risk factors for cardiovascular disease are associated with decreased vagal function as indexed by HRV.

HRV in major depression and in CHD

HRV has emerged as a useful, non-invasive tool for exploring physiological changes in a wide variety of illnesses (Sztajzel, 2004; Winchell and Hoyt, 1997). Both MDD and CHD have independently been linked with reduced HRV and are both theorised to disrupt autonomic control feedback loops acting on the heart, causing decreased HRV (Carney et al., 1995). Historically, HRV was initially linked to cardiac disease outcomes such as sudden cardiac death (SCD), myocardial infarction (MI) or angina (e.g. Kleiger et al., 1987). Only a few years later, HRV was also linked to psychological states such as depression (Dalack and Roose, 1990; Lehofer et al., 1999; Rechlin et al., 1994a; Roose et al., 1989). Therefore, HRV is one of the investigative modalities that potentially provide a link between cardiac function (and indeed cardiac disease) and psychological conditions such as MDD.

HRV and CHD

Early HRV changes were shown to occur following MI and were then linked prognostically to mortality risk (Bigger et al., 1996; Casolo et al., 1992; Farrell et al., 1991; Kleiger et al., 1987; Malik et al., 1990; Pedretti et al., 1993). It was found that within 2 months following MI, there is a significant recovery of HRV, which has been linked to the re-establishment of autonomic cardiac control (Lombardi et al., 1987). After 12 months there is further significant recovery, but HRV remains reduced compared to non-MI sufferers (Bigger et al., 1991; Mazzuero et al., 1992; Schwartz et al., 1988). Over periods greater than 1 year, several studies demonstrated that HRV remains lowered post-MI, and is associated with an increased risk of death (Bigger et al., 1992). The relative risk of mortality after MI is significantly higher in patients with decreased HRV (Kleiger et al., 1987; Bigger et al., 1988). A decline in HRV increases the risk of MI and coronary insufficiency (Tsuji et al., 1996). Low HRV also increases the relative risk of death from cardiovascular disease (Dekker et al., 1997, 2000) and increases the risk for sudden cardiac death (Goldberger et al., 1984; Myers et al., 1986). Finally, HRV is an independent predictor of mortality after MI (Bigger et al., 1992; Kleiger et al., 1987; Malik et al., 1989).

HRV and MDD

In the 1990s, several studies examined the relationship between HRV and depression (Dalack and Roose, 1990; Lehofer et al., 1999; Rechlin et al., 1994b; Roose et al., 1989). Studies initially showed mixed findings (Agelink et al., 2002; Bar et al., 2004). Some studies reported decreased HRV in people with depression, compared to non-depressed controls (Dalack and Roose, 1990; Lehofer et al., 1999; Rechlin et al., 1994c; Roose et al., 1989). Other studies, however, reported no differences in HRV (Jakobsen et al., 1984; Lehofer et al., 1997; O’Connor et al., 2002; Yeragani et al., 1991). For example, Dalack and Roose (1990) studied HRV in a group of depressed patients versus normal controls. They did not find any significant difference in the overall HRV between the groups. They found, however, that the depressed cohort had significantly decreased high-frequency variability. The authors linked this variability to decreased parasympathetic tone and suggested an association with increased risk of cardiovascular disease.

The heterogeneity of findings in the relationship between HRV and depression was found to be associated with methodological issues such as reporting of a variety of different HRV measures and small sample sizes, as well as confounders such as the effects of antidepressant medications and anxiety on HRV (Kemp et al., 2010). A meta-analysis of 18 studies relating HRV to MDD (Kemp et al., 2010) subsequently clarified the effect of small sample sizes and heterogeneity in samples and measures. It also examined the impact of antidepressant therapy on HRV. The meta-analysis compared 673 depressed participants with 407 non-depressed people and found that depression does result in reduced HRV. Furthermore, the severity of depression correlates negatively with HRV; that is, HRV is lower the more severe the depression.

Confounders in HRV measurements

Psychotropic medications

Several medications can affect HRV and have the potential to confound studies utilising HRV measures. Of particular relevance are antidepressant medications used in the treatment of MDD. However, other psychotropic medications can also influence HRV and are briefly discussed. In addition, cardiac medications are of importance in patients with comorbid MDD and CHD, as these may also influence HRV.

Tricyclic antidepressants (TCAs) suppress HRV in both depressed subjects (Rechlin, 1994; Rechlin et al., 1994a, 1994b) and in patients with anxiety symptoms (McLeod et al., 1992). TCAs have cardiac effects such as anticholinergic effects acting at the sino-atrial node, causing alterations in HRV (Rottenberg, 2007). In addition, TCAs have alpha-1 adrenergic properties which may also contribute to a reduction in HRV (Jakobsen et al., 1984).

Several studies have shown a significant reduction in HRV with the use of TCAs, to the point where it was questioned whether the reduced HRV seen in depression was a confounder due to antidepressant use. Lehofer et al. (1997) demonstrated that when depressed patients taking TCAs were compared with both unmedicated depressed patients and healthy control subjects, only the TCA group had lower HRV. Rechlin et al. (1994b) showed that depressed patients did not exhibit lower HRV than controls before TCA therapy, but had lowered HRV after TCA therapy was commenced. A meta-analysis by Kemp et al. (2010) confirmed a reduction in HRV associated with TCA treatment and also found that the reduction in HRV with TCA treatment was greater than the pre-existing HRV measures in depressed patients before treatment. The meta-analysis did, however, find a difference between HRV in depressed and non-depressed people.

Several studies on the effects of TCAs have used short recording times, which may point to an initial sharp fall in HRV (Van Zyl et al., 2008). Studies with longer recording times show smaller HRV changes and were not consistent with each other (Lederbogen et al., 2001; Van Zyl et al., 2008). Thus, while studies to date indicate that TCAs may significantly confound the effect of HRV in depressed patients, studies with longer recording times are needed to more fully understand the effects of TCAs on HRV, especially over long follow-up periods.

Selective serotonin reuptake inhibitors (SSRIs) can also affect HRV. Initial studies on the effects of SSRIs on HRV were contradictory. Some studies showed that SSRIs did not influence HRV (Rechlin, 1994; Rechlin et al., 1994b; Roose et al., 1998) and some studies showed an increase in HRV with SSRIs (Tucker et al., 1997). Other authors showed a decrease in HRV with SSRIs (Bar et al., 2004; Rissanen et al., 1998; Volkers et al., 2004). A review by Van Zyl et al. (2008) pointed out that some studies using shorter duration cardiac recordings showed a small increase in HRV, but longer-term studies were contradictory in their results. A more recent cross-sectional analysis of a large cohort study (2373 participants) evaluated whether HRV was lower in depressed individuals than in healthy controls (Licht et al., 2008). It was found that depressed participants did have lower HRV than control subjects, although it was concluded that the association was driven by the effects of antidepressant medication, and not MDD, which the subsequent meta-analysis by Kemp et al. (2010) refuted. The meta-analysis also found that SSRIs neither increased nor decreased HRV, clarifying earlier contradictory findings (Kemp et al., 2010).

Apart from SSRIs and TCAs, other antidepressant drugs like mirtazapine also have the potential to lower HRV (Agelink et al., 2001b; Bar et al., 2004; Straneva-Meuse et al., 2004; Tulen et al., 1996a). Seratonergic and noradrenaline reuptake inhibitors (SNRIs) were also shown to decrease HRV (Licht et al., 2010). This large study followed-up 2114 participants over 2 years and tracked changes in RSA as a measure of HRV in patients commencing, routinely using, and also ceasing TCAs, SSRIs and SNRIs. It was found that TCAs, SSRIs and SNRIs all decreased HRV, possibly even accounting for the lowering of HRV previously attributed to MDD. However, the findings were questioned on the basis of study design, statistical methods and concerns over examination of confounds in the SSRI class, amongst other concerns (Kemp et al., 2011). The clinical relevance of the small changes in RSA that were found was also questioned (Kemp et al., 2011), although these concerns were responded to by Licht et al. (2011).

Other psychotropic medications have also been shown to have an impact on HRV. Carbamazepine and lithium, used as mood stabilisers, have been associated with low HRV. In the study by Henry et al. (2010), seven participants treated with lithium showed evidence of a decrease in the LF/HF ratio. However, in the same study, sodium valproate had no effect on HRV. Tomson and Kenneback (1997) reviewed the available studies regarding HRV and carbamazepine and reported that carbamazepine is associated with reduced HRV.

Antipsychotic medications have long been known to have an effect on the QTc interval. In typical antipsychotic agents this has the potential for fatal cardiac arrythmias such as torsades de pointes (e.g. Zareba and Lin, 2003). In atypical antipsychotics, the QTc interval is also increased, but has thus far not been clearly associated with torsades de pointes (Glassman, 2005). Antipsychotic medications also affect HRV. Among antipsychotic medications, clozapine, olanzapine and haloperidol were shown to lower HRV in a study of 56 schizophrenic patients, although clozapine resulted in significantly lower HRV compared to the other drugs (Cohen et al., 2001). However, in a study of 16 healthy male volunteers, olanzapine administration increased HRV, thioridazine decreased HRV, while risperidone had no effect. The study was small and single doses of the medications were studied, not continuous administration over any length of time. Another study found that treatment with risperidone did not have any significant effect on HRV (Henry et al., 2010). There was also no significant difference in HRV between participants treated with antipsychotic medication alone as compared to people treated with a combination of antipsychotic and mood stabilising medications. Another study investigated the effects of four atypical antipsychotic medications on HRV (amisulpride, olanzapine, sertindole and clozapine) using 5-minute resting HRV measures (Agelink et al., 2001a). None of the patients treated with amisulpride or olanzapine had significant HRV changes. Clozapine again was found to reduce HRV significantly. The effect of clozepine on HRV has been attributed to its strong anticholinergic effects, whereas other neuroleptics (e.g. olanzapine) lack activity at cholinergic or adrenergic receptors (Agelink et al., 2001a). However, participant numbers were small (12–13 participants per medication), the HRV studies were only performed with a fixed, arbitrarily chosen dosage and there was only a 2-week surveillance of the cardiovascular effects of the drugs, which is relatively short.

Cardiac medications

Beta-adrenergic blockers affect HRV. Studies have shown an effect of beta blockers on HRV in normal subjects (Cook et al., 1991; Pagani et al., 1986) as well as in people with CHD (Bekheit et al., 1990; Lampert et al., 2003; Niemela et al., 1994). Using spectral analysis of HRV, it was found that beta-adrenergic blockers have a dampening effect on sympathetic activity (Bekheit et al., 1990). In this study the low-frequency range (0.04–0.12 Hz) was used as a measure of sympathetic activity. A similar decrease in the low-frequency component was found in people with essential hypertension taking atenolol (Guzzetti et al., 1988), as well as in patients with cardiac failure taking acebutolol (Coumel et al., 1991). Guzzetti et al. (1988) also found an increase in the high-frequency spectral band (around 0.25 Hz), which was used as a measure of vagal activity, with long-term use of beta blockers. A similar outcome was found in patients post-MI who were treated with beta blockers. Treatment with propranolol improved recovery of parasympathetic tone and decreased morning sympathetic predominance (Lampert et al., 2003).

In normal subjects, beta-adrenergic blockers also cause an increase in vagal tone (Cook et al., 1991; Pagani et al., 1986) as well as a reduction in sympathetic activity (Pagani et al., 1986). Beta-adrenergic blockade thus decreases sympathetic activity and increases parasympathetic or vagal activity in normal subjects and people with CHD. It has, however, been suggested that in patients with CHD, beta blockers restore the imbalance of sympathetic and parasympathetic activity which occurs in cardiovascular disease, possibly explaining their therapeutic effect (Rajendra et al., 2006). Overall, beta blockade was found to increase HRV in patients with CHD, which has been linked to the protective effects of beta blockers in CHD (Niemela et al., 1994).

Less information is available for other cardiac medications. In a study of 20 normal subjects given the angiotensin-converting enzyme inhibitor enalapril, the drug did not affect HRV (Kaufman et al., 1993). In the same study, treatment with digoxin significantly increased the high-frequency component of HRV (Kaufman et al., 1993). A study on 18 healthy people using the calcium channel blocker diltiazem, showed no effect on HRV (Cook et al., 1991). However, diltiazem was found to reduce the low-frequency power of HRV in a group of patients post-MI (Bekheit et al., 1990). The same study found that the calcium channel blocker nifedipine had no consistent effects on HRV. Amiodarone has been found to not affect vagal activity, whereas both flecainide and propafenone caused significant decreases in HRV (Zuanetti et al., 1991).

Anxiety as a confounder for low HRV in depression

Anxiety is significantly associated with decreased HRV (Friedman, 2007; Friedman and Thayer, 1998; Gorman and Sloan, 2000; Watkins et al., 1998; Yeragani et al., 1991, 1995). Comorbid anxiety is particularly common in people with depression (Clark et al., 1994) and occurs in about 30–40% of people with MDD between the ages of 18 and 65 years (Wittchen and Jacobi, 2005). In older people aged 55–85 years, 47.5% of those with a MDD also meet the criteria for at least one anxiety disorder (Beekman et al., 2000). Comorbid anxiety might thus be a significant confounder in the measurement of HRV in depressed patients.

It has been argued that there is a stronger link between anxiety and HRV than depression and HRV (Watkins et al., 1999). The conclusion was based on findings indicating that vagal control correlated with state anxiety rather than with depression severity in a group of depressed psychiatric patients. The study, however, had a small number of participants and women were over-represented. Women are both more prone to anxiety and have lower vagal tone than men (Carney et al., 2000). There was also no non-depressed control group. In addition, several studies on anxiety and HRV to date have been small or confounded (Carney et al., 2000).

The lower HRV seen in depression could also be due to anxiety-related behaviours (not a comorbid anxiety disorder), while subjects are being examined for a study (Rottenberg, 2007). Depressed subjects with anxious traits or comorbid anxiety may exhibit more rapid breathing with lower tidal volume, resulting in lower HRV being measured (Tulen et al., 1996b; Wilhelm et al., 2004). However, studies that have used specific methodology to control for respiratory rate and depth when measuring HRV, such as paced breathing (Grossman et al., 1991; Rottenberg et al., 2002; Wilhelm et al., 2004) still find an association.

Conclusions and recommendations

Vagal function represents a promising starting point for the quantitative elucidation of the network of causal mechanisms linking MDD and CHD. Polyvagal theory and the theory of neurovisceral integration demonstrate how vagal function is linked to both cardiac control and depression. Vagal function plays a central role in autonomic and inflammatory mechanisms in the causal network linking MDD and CHD, and is amenable to quantitative study using HRV methods. Given the global significance of both MDD and CHD and the importance of the vagal pathway and HRV in their inter-relationship, it is important to reflect on some of the implications for clinical practice. Recommendations are also suggested for future studies, which, by eliminating confounders, could allow a more reliable quantification of the contribution of vagal function to the causal network linking MDD and CHD.

HRV in MDD and CHD: clinical recommendations

HRV has emerged as an important measure which has been shown to be lowered in both MDD and CHD and has been shown to have predictive value; for example, in terms of mortality risk in CHD. One of the confounders of HRV measures, particularly in MDD, has been medication, where specific effects such as anticholinergic action can lower HRV (Rottenberg, 2007), although the specific mechanisms through which psychotropic medications impact on cardiac outcomes is currently still poorly understood (Sowden and Huffman, 2009). An important clinical question is whether lowering of HRV by such mechanisms presents a risk in terms of cardiac health or mental health.

The cardiac safety of some antidepressant drugs should prompt greater consideration and is increasingly important in older age groups, who may have an increased cardiovascular risk profile. There may be implications in taking psychotropic medications for cardiac health in terms of HRV. Tricyclic antidepressant medications have long been known to place patients at risk of QTc prolongation and cardiac arrhythmias. TCAs exhibit anticholinergic activity, direct myocardial depressant activity and adrenergic effects, resulting in potential arrhythmias, blood pressure abnormalities and congestive heart failure, even at therapeutic levels (Jefferson, 1975). But TCAs may also have longer-term cardiac effects arising from HRV changes which increase their risk when used in patients both with and without CHD. For example, Cohen et al. (2000) found that the use of TCAs doubled the risk of a first episode of MI. However, in a large case–control study of over 60,000 cases of first-time MI, where the impact of prior antidepressant administration was evaluated, patients were found to be at significantly increased risk of MI only within the initial 28 days of antidepressant use (Tata et al., 2005). Although people taking SSRIs and TCAs were studied, the observed increases were not found to be specific to TCA or SSRI exposure. Prolonged antidepressant exposure was not associated with increased risk of MI, suggesting that ultimately it is depression, rather than the antidepressant treatments, that confers the increased cardiovascular risk.

SNRIs have been shown to increase blood pressure at higher doses, which may be of clinical significance in patients with CHD (Sander, 2011) and they have also been linked to lower HRV (Licht et al., 2010). Mirtazapine has been shown to lower HRV (Agelink et al., 2001b; Bar et al., 2004; Straneva-Meuse et al., 2004; Tulen et al., 1996a). Interestingly, mirtazapine has limited evidence for efficacy in patients with CHD. The large Myocardial Infarction Depression Intervention Trial (MIND-IT) showed no change to depression and no change to cardiac outcomes with mirtazapine treatment in depressed patients with CHD (Van Melle et al., 2007). Mirtazapine can also cause increased blood pressure due to its antagonism of pre-synaptic noradrenaline alpha-2 receptors and has been associated with weight gain.

In the treatment of cardiac patients or patients with significant cardiac risk factors, SSRIs are considered safe and efficacious. The two SSRIs with the best evidence for cardiac safety as shown by large clinical studies are sertraline (Jiang et al., 2008) and citalopram (Lesperance et al., 2007). While it has been suggested that SSRIs as a class might decrease HRV (Licht et al., 2010), it has also been shown that the effect of SSRIs as a class on HRV is neutral (Kemp et al., 2010). SSRIs may in fact improve cardiac outcomes via platelet activation and modulation of the inflammatory response (Van Melle et al., 2006a). The study by Cohen et al. (2000) determined that use of SSRIs reduced the risk of MI, supporting this conclusion. While there is still some controversy, the findings of this review support the use of SSRIs as a first-line treatment for MDD and patients with both MDD and CHD compared to TCAs, SNRIs and mirtazapine.

Another consideration should be the effects of cardiac medications on MDD. For example, beta-adrenergic blockers were previously thought to cause MDD (e.g. Fodor et al., 1987), although a more recent study has refuted this. A study of 381 patients post-MI found that the prescription of beta blockers is not associated with an increase in depressive symptoms or depressive disorders in the first year after MI (Van Melle et al., 2006b). In addition to this, beta blockers increase HRV in CHD patients, again underlining their protective effects in CHD (Niemela et al., 1994). Beta-adrenergic blockers are thus safe and beneficial in the treatment of people with comorbid CHD and MDD.

The effects of other cardiac medications on HRV are varied and more research is needed to explore their effects, particularly in patients with MDD. It has been argued that exploring treatment modalities that specifically increase HRV would be desirable for patients post-MI and that such strategies might include physical exercise, beta-adrenergic blockade or low doses of the anticholinergic hyoscine hydrobromide (O’Brien and Oyebode, 2003). Similarly, future treatments for people with MDD might target mechanisms which increase HRV.

A final clinical consideration is the effect of anxiety on HRV. While most mental health workers would screen for symptoms of anxiety on routine assessment. While most mental health workers would screen for symptoms of anxiety on routine assessment, the links with decreased HRV should underline the importance of identifying anxiety symptoms, particularly in the context of occurring comorbidly with MDD.

HRV in MDD and CHD: recommendations for future studies

TCAs significantly decrease HRV and should be avoided, if possible, in future studies of HRV. The question of whether the use of SSRIs represents a potential confounder is less clear. Although the recent meta-analysis by Kemp et al. (2010) suggests that SSRIs do not affect HRV, longer-term studies are needed (Kemp et al., 2010; Van Zyl et al., 2008). The potential of SSRIs to alter HRV should be taken into account in any future study design. To entirely avoid this potential confounder, an ideal study might involve the recruitment of antidepressant-naïve participants. Such a study might recruit people with a first episode of mild to moderate depression, which could be treated with non-pharmacological therapies, which have a good evidence base, such as cognitive behavioural therapy (CBT) (Ellis, 2004). This approach may not be as generalisable to patients with severe MDD, but may contribute significantly to the further clarification of the relationship between HRV measurements and MDD.

The issue of other non-antidepressant medications such as beta blockers is equally complex. There is evidence to suggest that beta blockers do have an effect on HRV, and thus potentially act as a confounder, which needs to be taken into account in future studies. However, it may be ethically and clinically difficult to justify withholding certain cardiac medications in a clinical study on patients with CHD. Future studies could attempt to control for their effect, or recruit participants with CHD in whom such medications are not clinically indicated.

Finally, it is recommended that future studies involving depressed people should address the possibility of confounding by comorbid anxiety disorders. An ideal study would clearly identify patients with anxiety symptoms or a comorbid anxiety disorder, using a recognised set of diagnostic criteria. Participants with a comorbid anxiety disorder could then either be excluded, or statistical procedures used to control for the effect of anxiety symptoms.

Conclusion

MDD and CHD are both important diseases and they share a reciprocal relationship. The causal network linking MDD and CHD should be quantitatively studied and the investigation of vagal function, using HRV, is a logical starting point. Polyvagal theory and the theory of neurovisceral integration provide the theoretical basis for the relationship between cardiac function and emotional states, and HRV could provide a quantitative measure of the vagal component of this relationship. While HRV is a very simple and non-invasive means of gathering data, the data itself, and its meaning, remain difficult to interpret. While more research is needed to clarify the interpretation of HRV and to quantify the vagal link between MDD and CHD, such research is promising in terms of better understanding both diseases and also their treatments.

Footnotes

Funding

This research has been supported by a grant from the Gold Coast Hospital Foundation, Queensland, Australia. The funding organization had no role in the collection, management, analysis, or interpretation of the review information; or preparation, review, or approval of the manuscript.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

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Mind and heart: Heart rate variability in major depressive disorder and coronary heart disease - a review and recommendations

Abstract

Objective:

Methods:

Results:

Conclusions:

Keywords

Introduction

Objective

Methods

Results

Theories of vagal function in the relationship between major depression and CHD

Polyvagal theory

Functional anatomical evidence

Evolutionary phylogenetic evidence

RSA as a measure of the nA vagal branch

The theory of neurovisceral integration

HRV in major depression and in CHD

HRV and CHD

HRV and MDD

Confounders in HRV measurements

Psychotropic medications

Cardiac medications

Anxiety as a confounder for low HRV in depression

Conclusions and recommendations

HRV in MDD and CHD: clinical recommendations

HRV in MDD and CHD: recommendations for future studies

Conclusion

Footnotes

Funding

Declaration of interest

References