Original Article Arthritis Care & Research DOI 10.1002/acr.21669 Dysregulation of the autonomic nervous system is associated with pain intensity, not with the presence of chronic widespread pain

Ansam Barakat MSc 1, Nicole Vogelzangs PhD1 , Carmilla M.M. Licht PhD1, Rinie Geenen PhD 2, Gary J. Macfarlane MD, PhD 3 , Eco de Geus PhD4 , Johannes H. Smit PhD 1, Brenda W.J.H. Penninx PhD 1,5,6, Joost Dekker PhD 1, 7 $

1. Department of Psychiatry and EMGO Institute for Health and Care Research , VU University Medical Center, Amsterdam, the Netherlands 2. Department of Clinical and Health Psychology, Utrecht University, Utrecht, the Netherlands 3. Aberdeen Pain Research Collaboration (Epidemiology Group), University of Aberdeen, UK 4 Department of Biological Psychology, VU University, Amsterdam, the Netherlands. 5. Department of Psychiatry, University Medical Center Groningen, Groningen, the Netherlands 6. Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands 7. Department of Rehabilitation Medicine and EMGO Institute for Health and Care Research , VU University Medical Center, Amsterdam, the Netherlands

$ Address correspondence to Joost Dekker, PhD, Department of Rehabilitation Medicine, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam The Netherlands. Phone: +31.20.44.44.256 Fax: +31.20.44.40.787 E-mail: [email protected]

We declare that we did not receive any financial support or other benefits from commercial sources for the work reported on in the manuscript, and that there were no other financial interests of any of the authors, which could create a potential conflict of interest or the appearance of conflict of interest with regard to the work.

Word count: 3784

Tables: 3

Version: 6 March 2012 This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/acr.21669

© 2012 American College of Rheumatology Received: Oct 03, 2011; Revised: Mar 06, 2012; Accepted: Mar 08, 2012 Arthritis Care & Research Page 2 of 23

Abstract

Objective. To test the hypotheses: (i) dysregulation of the autonomic nervous system (ANS) is associated with the presence of Chronic Widespread Pain (CWP); and (ii) dysregulation of the ANS is associated with higher pain intensity in CWP.

Methods. Cross-sectional data were obtained from 1574 subjects –healthy controls as well as persons with depressive and anxiety disorders– participating in the Netherlands Study of

Depression and Anxiety. The Chronic Pain Grade was used to assess pain intensity and pain-related disability. rate (HR), standard deviation of the normal-to-normal interval (SDNN), the pre- ejection period (PEP) and respiratory sinus arrhythmia (RSA) were used to assess the ANS. Logistic regression analyses and linear regression analyses were conducted with adjustment for potential confounders.

Results. No differences in HR, PEP, SDNN or RSA values were found between CWP subjects and controls after adjustment for confounders. However, lower SDNN and lower RSA were associated with higher pain intensity in subjects with CWP.

Conclusion. Lower parasympathetic activity, as assessed with SDNN and RSA, is associated with higher pain intensity in subjects with CWP. This large and well controlled study does not provide evidence for an association between dysregulation of the ANS and the presence of CWP.

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Significance and Innovations

1. The results from this large and well controlled study are not in line with a role of

dysregulation of the ANS in the development of CWP.

2. Lower parasympathetic activity is associated with higher pain intensity in subjects

with CWP.

3. A longitudinal study is required to examine the direction of the association between

low parasympathetic activity and pain intensity in CWP.

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Introduction

Chronic widespread pain (CWP), one of the cardinal symptoms of fibromyalgia, is defined as pain, lasting at least 3 months, above and below the waist, on the right and left sides of the body and in the axial skeleton (1). CWP is one of the most common reasons for referral to a rheumatologist: it is highly prevalent and disabling, and has a large impact on the individual and society (2). Treatment modalities for CWP include both pharmacological and non-pharmacological interventions.

Currently, the effects of these interventions are moderate: the mean effect size of the efficacy of 120 treatments was 0.49, which is considered as a medium size effect (3). Better knowledge on risk factors and explanatory mechanisms for the development and perpetuation of CWP is highly crucial to identify targets for effective prevention and treatment.

One of the possible risk factors for CWP is dysregulation of the autonomic nervous system

(ANS). Emerging evidence points towards an association between dysfunction of the ANS and CWP.

A recent review of Maletic and Raison (4) summarized evidence suggesting that dysregulation of the

ANS (i.e. increased sympathetic and/or decreased parasympathetic tone) has a crucial role in initiating and perpetuating central sensitization in the cortico-limbic circuitry. In turn, central sensitization predisposes individuals for the development of chronic pain in response to trigger events (i.e. daily hassles and major life events). Several other studies, not included in the review of

Maletic and Raison, have also found alterations in the ANS activity of fibromyalgia patients. These studies indicated increased tonic sympathetic and/or decreased parasympathetic nervous system activity (5-14), as well as hypo-reactive ANS response to applied stressors (10) in patients with fibromyalgia.

Although these studies suggest a link, the evidence for an association between ANS activity and CWP is still limited. One of the methodological weaknesses of the currently available studies is the limited number of participants (the largest study had n = 60; (12)). Furthermore, confounders

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such as sociodemographic characteristics, lifestyle and health variables were generally not

sufficiently taken into account. The present study reports analyses from a large cohort study; this

study also offers the possibility to adjust for potential confounders (15).

The aim of the present study was to assess the association between activity of the ANS and

CWP. The hypotheses were: (i) dysregulation of ANS is associated with the presence of CWP; and (ii)

dysregulation of ANS is associated with higher pain intensity in subjects with CWP. We examined

whether heart rate (HR), standard deviation of the normal-to-normal interval (SDNN), the pre-

ejection period (PEP), and respiratory sinus arrhythmia (RSA) differed between subjects with CWP

and controls, and whether these variables were associated with pain intensity in subjects with CWP.

Subjects and Methods

Study population

Study data came from the NESDA study (Netherlands Study of Depression and Anxiety), a large

cohort study conducted among 2981 adults, age between 18–65 years, at the baseline assessment in

2004–2007. The study examines the long-term course and consequences of depressive and anxiety

disorders and included persons with depressive and anxiety disorders as well as controls without a

psychiatric diagnosis. To ensure representative healthcare settings, respondents were recruited

from the community, general practice and secondary mental health care. Further details of the study

have been described elsewhere (15). For the present study both subjects with CWP and controls

were selected (see below). The research protocol was approved by the ethical committees of

participating universities. All respondents provided written informed consent.

Measurements

Chronic widespread pain

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The Chronic Pain Grade (CPG) was used to assess pain intensity and pain-related disability (16) .

The CPG first inquires about the presence of pain in the prior 6 months on several locations, i.e. extremities (joint of arms, hands, legs, or feet), back, neck, head, abdomen, chest, and orofacial. The pain measures employed in the CPG all refer to the most painful location and include: a) days in pain in the prior 6 months (scale 0 -180); b) pain at this moment (scale 0-10); c) worst pain in the prior

6 months (scale 0-10); d) average pain in the prior 6 months (scale 0-10); e) disability days in the prior 6 months (score 0 -180); f) disability in daily activities (scale 0 -10); g) disability in spare time, social life and family activities (scale 0 -10); h) disability in work ( scale 0 -10). From these measures, five grades are categorized, according to the CPG protocol (16): Grade 0 (Pain free, no pain problem in the prior 6 months); Grade I: Low disability-low intensity; Grade II: Low disability- high intensity; Grade III: High disability-moderately limiting; and Grade IV: High disability-severely limiting. The CPG has been extensively tested and found to be reliable, valid and responsive to change (16-18).

We used CPG to select subjects with CWP and controls. Subjects were classified as CWP if they met both of the following criteria: (i) grade I, II, III or IV on the CPG; and (ii) pain present in extremities, back and neck. CWP subjects were further differentiated as grade I, II, III or IV. Subjects were classified as control if they met both of the following criteria: (i) grade 0 or I on the CPG; and

(ii) pain in ≤2 locations. Subjects with grade I, and pain in 3 or more locations other than extremities, back and neck were excluded, as well as subjects with grade II, III or IV, and pain elsewhere than extremities, back and neck.

To assess pain intensity in subjects with CWP, three questions on the GCP were used

(question b, c and d, see above). The total pain intensity of a subject was the average of 0-10 ratings of the three questions multiplied by 10 to yield a 0 to 100 score (16).

Autonomic Nervous System 6

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The autonomic nervous system (ANS) was assessed with the VU University Ambulatory Monitoring

System (VU-AMS). The VU-AMS is a simple, non-invasive, lightweight ambulatory device recording

the electrocardiogram (ECG) and changes in thorax impedance from 6 electrodes placed at chest

and back of the subjects, of which recording methodology has been described previously (19;20).

Subjects wore the VU-AMS monitor during the assessment unobtrusively underneath clothing for

about two hours. The start of the various assessments was indicated by an event marker to divide

the total recording into fixed periods (resting baseline, breaks, interview 1, computer task, and

interview 2). Movement registration by a vertical accelerometer was used to excise periods in which

subjects were not stationary. Removal of breaks and non-stationary moments (~15 minutes) left an

average registration of 97.2 (SD = 24.7) minutes (duration concerns subjects in the present study).

The registration consisted of a supine resting condition (with 3 blood pressure measurements;

mean time, 9.7 minutes, SD, 3.0 minutes) and 3 test conditions in which the participants were sitting

upright: interview session 1 (investigating somatic health, functioning, and health care use; mean,

37.7 minutes, SD, 13.5 minutes), interview session 2 (investigating family and personal history and

life events; mean, 35.1 minutes, SD, 12.7 minutes), and a computer task (Implicit Association Task;

mean, 16.3 minutes, SD, 4.2 minutes).

From the electrocardiogram and the thorax impedance data, the following variables were

obtained: mean heart rate (HR); pre-ejection period (PEP): the time from the beginning of electrical

activity to the beginning of left ventricular ejection (longer PEP reflecting lower sympathetic

activity); standard deviation of the normal-to-normal interval (SDNN; a parasympathetic dominated

mixture of parasympathetic and sympathetic nervous activity; high SDNN reflecting high

parasympathetic activity); and respiratory sinus arrhythmia (RSA; high RSA reflecting high

parasympathetic activity). Reliability and validity of these measures of cardiac ANS activity have

been demonstrated previously (21-26). Details of the ANS assessment procedures in NESDA have

been described elsewhere (25;27;28). 7

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Covariates

Potential confounders included socio-demographic characteristics (age, gender and years of education), and lifestyle and health variables. Alcohol use was assessed using the first two questions of the Alcohol Use Disorders Identification Test (AUDIT) (29). Alcohol use was categorized into no drinker, mild/moderate drinker (men: 1-21 glasses/week; women: 1-14 glasses/week) and heavy drinker (men: > 21 glasses/week; women: > 14 glasses/week). Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Smoking, which was assessed by self-report, was categorized into never smoked – former smoker – current smoker.

Heart disease (including coronary disease, cardiac arrhythmia, angina, heart failure, and myocardial infarction) and other chronic conditions (epilepsy, diabetes, osteoarthritis, stroke, cancer, chronic lung disease, thyroid disease, liver disease, chronic fatigue syndrome, intestinal disorders, and ulcer) were assessed by self-report and considered present if persons received treatment.

Medication use was assessed based on drug container inspection of all drugs used in the past month and classified according to the WHO’s anatomical therapeutic chemical (ATC) classification (30).

Heart was divided in two categories 1) beta blocking agents (ATC code C07) and 2) and other heart medication (cardiac therapy (ATC code C01), antihypertensives (ATC code C02), (ATC code C03), peripheral vasodilators (ATC code C04), (ATC code C05), , calcium channel blockers (ATC code C08) and agents acting on the renin-angiotensin system (ATC code C09)),. Pain medication included (ATC code M01A, M02, M03A, N02, N03AX12 and N03AX16)

(31;32). In addition, frequent use (daily or > 50% of the time) of antidepressant

(tricyclic antidepressants [TCA; ATC code N06AA], selective serotonin reuptake inhibitors [SSRI;

ATC code N06AB], and other antidepressant medication [ATC codes N06AF/AG/AX]) were considered as covariates because of the previously reported impact of antidepressants on heart rate, SDNN and RSA in depressed patients (28). Respiration rate (breaths/min) was obtained from 8

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the thorax impedance data as it has been asserted that research investigating RSA should take

respiration rate into account (19).

Another set of potential confounders was evaluated as well: physical activity, insomnia, and

diagnosis and severity of depressive and anxiety disorders. Physical activity was assessed with the

International Physical Activity Questionnaire (33), and expressed in metabolic equivalent minutes

per week. Insomnia was evaluated with the Insomnia Rating Scale (range 0-20), with 9 as a cut-off

point (34). Although we found diagnoses and severity to be largely unrelated to ANS activity

(25;27), depressive and anxiety disorders were considered as potential confounders as well.

Lifetime depressive and anxiety disorders were established with the Composite International

Diagnostic Interview (CIDI, WHO version 2.1) (35). Severity of depressive symptoms was measured

with the Inventory of Depressive Symptomatology (IDS) self-report version (range 0 -84) (36).

Severity of anxiety and panic symptoms was measured using the 21-item Beck Anxiety Inventory

(range 0 -63) (BAI) (37). These variables are not merely potential confounders but could also be

mediators, explaining the link between ANS activity and pain: for this reason, these potential

confounders/mediators were analyzed in a separate step (38).

Statistical analyses

Descriptive baseline characteristics were tabulated as mean and SD, or as percentages. Between-

group differences at baseline were examined using Chi-square tests for categorical variables and

analyses of variance (ANOVA) for continuous variables. Binary (no CWP vs. CWP) and multinomial

(no CWP, CWP-grade I, CWP-grade II, CWP-grade III, and CWP-grade IV) logistic regression analyses

were performed to analyse associations between ANS functioning and the presence of CWP. To

examine whether ANS activity was associated with pain intensity in subjects with CWP, we

conducted linear regression analyses in subjects with CWP. In all analyses, ANS functioning was the

independent variable; presence of CWP and intensity of pain were the dependent variables, 9

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respectively.

Three models were used in binary and multinomial logistic regression and linear regression analyses. First an unadjusted model was used. In the second model, we adjusted for potential confounders, i.e. gender, age, education, BMI, smoking, alcohol use, heart disease, number of chronic diseases, beta blocking agents, other heart medication, pain medication, TCA, SSRI, and antidepressant medication. In the third model we additionally adjusted for the potential confounders/mediators, i.e. physical activity, insomnia, diagnosis of lifetime depressive or anxiety disorders, and depression and anxiety severity. For all statistical tests, a probability level of equal or less than 5% was regarded as significant. The statistical calculations were performed using SPSS version 15.0.

Results

Subjects

The total study sample consisted of 1574 subjects. In total 1654 subjects met the selection criteria for the CWP group (N= 767) or the control group (N= 887). Of these subjects, 80 persons were excluded because no ANS data were available, leaving 843 control subjects and 731 subjects with

CWP. The excluded subjects (N=80) did not differ from the included subjects with regard to the presence of CWP (data not shown). Included subjects were younger (43.1 versus 46.4; P=0.03), more often a smoker (37.5% versus 33.8%, P= 0.02), had a lower BMI (25.6 versus 26.8; P=0.04), had less heart disease (5.8% versus 15.0%, P= 0.003), and more often used pain medication (45.3% versus 35.0%; P=0.04), compared to excluded subjects. For all other baseline characteristics there were no significant differences between excluded and included subjects.

Baseline characteristics of the study population are shown in Table 1. In subjects with CWP, the mean days in pain in the prior 6 months was 108.2 (SD= 69.7) and the mean pain intensity was

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53.1 (SD= 18.0). Compared to controls, subjects with CWP were significantly older, more often

women, had less education, more often non-alcohol drinkers, had higher BMI, were more often

current smokers, used more other heart medication, pain medication, SSRIs and other

antidepressant medication, had more heart disease and other chronic diseases, suffered more

frequently from insomnia, had more frequently lifetime depressive and/or anxiety disorders.

Differences between controls and CWP subjects in the use of beta-blocking agents, TCA use and

physical activity were not significant. With regard to ANS measures, SDNN and RSA were

significantly higher in the control group compared to the CWP group, but HR and PEP did not differ

between controls and CWP subjects.

ANS activity and the presence of chronic widespread pain

Table 2 shows the results of the unadjusted and adjusted binary and multinomial logistic

regression analyses assessing the association between ANS activity and the presence of CWP. In the

binary logistic regression model, before adjustment, SDNN and RSA were significantly associated

with the presence of CWP: lower SDNN and RSA were associated with a higher odds of CWP. All

potential confounders and confounders/mediators were separately tested: each individually

resulted in a change in the beta of more than 10%. After adjustment for confounders, SDNN and RSA

were not significantly associated with the presence of CWP. Further adjustment for potential

confounder/mediators had no further impact.

In the unadjusted multinomial logistic model HR, SDNN and RSA showed a significant

association with the presence of CWP: higher HR, lower SDNN and lower RSA were associated with

higher odds of having “High disability-moderately limiting CWP” or “High disability-severely

limiting CWP”. After adjustment for confounders these associations became weaker and were no

longer significant. In fact, adjustment for age only reduced all associations to non-significance (data

not shown). Adjusting for the potential confounder/mediators hardly affected these results. PEP did 11

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not show a statistically significant effect in any CWP group, before or after adjustment for confounders and confounders/mediators. Thus, overall, there were no associations between ANS measurements and the presence of CWP, after adjustment for confounders.

ANS activity and pain intensity in CWP

Table 3 shows the results of the unadjusted and adjusted linear regression analyses assessing the association between ANS activity and pain intensity in subjects with CWP (N=731). Both SDNN and

RSA were significantly associated with pain intensity, before and after full adjustment for potential confounders and confounders/mediators (SDNN: unadjusted: B -3.25, 95% CI= -4.60 -1.89, P<0.001; fully adjusted: B= -2.25, 95% CI= -3.52 -0.97, P = 0.001) (RSA: unadjusted: B= -2.58, 95% CI= -3.99 -

1.17, P<0.001; fully adjusted: B= -1.95, CI = -3.44 -0.46, P=0.01). Neither HR nor PEP was associated with pain intensity, in the unadjusted and fully adjusted analyses, although PEP tended to be shorter in the CWP group after adjustments. Thus, lower SDNN and RSA were significantly associated with higher pain intensity in subjects with CWP, before and after correction for all potential confounders and confounders/mediators.

Discussion

In this well controlled study with a large sample, we examined the association between functioning of the autonomic nervous system and chronic widespread pain. We found that (i) ANS activity is not associated with the presence of CWP, and (ii) lower parasympathetic activity, as assessed with

SDNN and RSA, is associated with higher pain intensity in subjects with CWP.

Our findings do not confirm our first hypothesis, that dysregulation of ANS is associated with the presence of CWP. This negative finding applies to the presence of CWP treated as a dichotomy

(presence vs absence) as well as to CWP treated as a ordinal variable (grades 0 – IV), making a dose

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response relationship unlikely. Our findings are in contradiction with other studies, which have

suggested that ANS activity is altered in CWP (4). Previous studies which suggested an association

between ANS activity and CWP suffered from limited sample size and insufficient control of

potential confounders. In unadjusted analyses, we observed several significant associations

between dysregulation of the ANS and the presence of CWP. These associations were not significant

after controlling for confounders; in fact, controlling for age eliminated significant associations: age

has been shown to be correlated with both ANS activity and CWP (39-41) and is therefore a

potential confounder which should be controlled for. Previous studies have mostly examined

fibromyalgia patients: it is still a possibility that dysregulation of the ANS is a factor in the

development or persistence of fibromyalgia, as opposed to the broader category of CWP.

We did find an association between SDNN and RSA and pain intensity in subjects with CWP,

confirming our second hypothesis. These associations remained significant, after controlling for

confounders and even potential confounder/mediators. These findings are in line with other studies

(e.g. (7;42)) which have shown a decrease in parasympathetic activity in fibromyalgia patients. In

the present cross-sectional study, the causality of this relationship cannot be determined. Yet, lower

parasympathetic activity was not associated with the presence of CWP (hypothesis 1), while it was

associated with pain intensity in subjects with CWP (hypothesis 2): this pattern of results suggests

that intense pain is a chronic stressor, interfering with parasympathetic activity, as has been

suggested previously (10). Longitudinal studies are required to determine the direction of the

relationship between parasympathetic activity and pain intensity.

HR and PEP did not show a significant association with pain intensity in subjects with CWP.

This suggests that there is no association between dysregulated sympathetic tone and pain intensity

in CWP subjects, which is in line with the results in fibromyalgia patients (9;43). Thus, our study

does not support the idea that stress-related sympathetic tone is a driver of pain intensity, or that

pain intensity enhances sympathetic tone. 13

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For this study the NESDA data has been used. The NESDA data has a high rate of subjects with lifetime depressive and anxiety disorders. One could argue that the statistical adjustment to account for depression and anxiety has affected our conclusions. We do not think that this is a likely explanation for our conclusions. In unadjusted analyses, we found SDNN and RSA to be associated with the presence of CWP. After adjustment for confounders (i.e. gender, age, education, BMI, smoking, alcohol use, heart disease, chronic diseases, and medication), these associations became weaker and were no longer significant (see Table 2). Further adjustment for depression and anxiety did not have much influence on the associations (see Table 2). Therefore, it is unlikely that the statistical adjustment for the nature of the NESDA study population explains our conclusions. The same reasoning applies to the results with regard to parasympathetic activity and pain intensity: it is unlikely that our conclusions are due to the adjustment for depression and anxiety. Furthermore, we repeated the binary logistic and linear regression analyses, excluding subjects with a life-time diagnosis of depression or anxiety. The regression estimates derived from these analyses confirmed our conclusions, although p-values showed some change as result of the lower number of subjects

(N= 408 , of whom N= 86 had CWP; data not shown).

In a similar vein, one could argue that incorporating chronic fatigue syndrome and intestinal disorders among the potential confounders resulted in over-adjustment: like chronic widespread pain, chronic fatigue syndrome and intestinal disorders could be the result of central sensitization in the cortico-limbic circuitry. Again, we think that this is an unlikely explanation of our findings: adjustment for age only reduced all associations to non-significance.

Several methodological issues need to be taken into account when considering the conclusion of our study. First, one of the criteria for CWP is pain for more than 3 months, while we used the CPG, which asks about the number of days in pain in the prior 6 months. As shown in Table

1, subjects with CWP had on average 108 days of pain (~3.5 months) in the prior 180 days: it is likely that these subjects meet the criterion of pain for more than 3 months. Therefore, it is unlikely 14

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that the slight deviation with regard to the criterion of pain, explains our findings. Second, we

excluded from the control group subjects with grade I on the CPG and pain in 3 or more locations

other than extremities, back and neck. These subjects were excluded in order to enhance the

contrast between CWP and control. We did not exclude subjects with Grade I and pain in ≤2

locations, limiting the control group to subjects with Grade 0 only: this would have left us with little

subjects in the control group (only n = 170 had Grade 0). Including subjects with CPG level 1 and

pain in ≤2 locations in the control group weakens the contrast between controls and subjects with

CWP and increases the possibility of false negative findings. On the other hand, chronic pain in 1 or

2 locations is quite common in the population (44): our controls resemble the population in this

respect. Third, because the analyses were cross-sectional, the results do not indicate any causal

direction of the associations found. As mentioned before, a longitudinal study is recommended to

elucidate the directionality of the association between ANS activity and CWP. Fourth, we used HR,

PEP, SDNN and RSA as measures of ANS activity. It should be noted that, strictly speaking, HR, PEP,

SDNN and RSA are measures of the impact of ANS activity on the heart, instead of direct measures of

ANS activity.

In conclusion, this large scale and well controlled study shows that lower parasympathetic

activity, as assessed with SDNN and RSA, is associated with higher pain intensity in subjects with

CWP. No evidence was found for an association between dysregulation of the ANS and the presence

of CWP. A longitudinal study is required to examine the direction of the relationship between low

parasympathetic activity and pain intensity in CWP.

Acknowledgement

The present study is based on the NESDA cohort. Data gathering was funded by Netherlands

Organisation for Health Research and Development (ZonMW; Geestkracht progam); Netherlands

Organisation for Scientific Research (NOW; VIDI grant to Dr. Penninx); EMGO Institute for Health 15

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and Care Research, VU University Medical Center, Amsterdam; and Neuroscience Campus

Amsterdam, VU University Amsterdam, the Netherlands.

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Table 1: Baseline characteristics

Control CWP CHARACTERISTIC P-value A N=843 N=731

Days of pain in the prior 6 months, mean (SD) 27.6 (49.0) 108.2 (69.7) <0.001 Pain intensity, mean (SD) 21.5 (15.2) 53.1 (18.0) <0.001

Potential confounders

Age, years, mean (SD) 41.9 (13.6) 44.5 (12.2) <0.001 Gender,% women 56.7 74.1 <0.001 Education in years, mean (SD) 13.0 (3.3) 11.3 (3.2) <0.001

Alcohol use, % yes Nondrinker 23.6 40.5 <0.001 Mildmoderate drinker 63.9 48.4 Heavy drinker 12.5 11.1

BMI, mean (SD) 25.0 (4.2) 26.4 (5.2) <0.001

Smoking, % yes Nonsmoker 31.9 26.5 <0.001 Former smoker 35.2 30.5 Current smoker 32.9 43.0

Medication use, yes% Betablocking agents 7.7 9.8 0.08 Other heart medication 11.0 14.1 0.04 Pain medication 31.2 61.6 <0.001 SSRI 12.1 21.2 <0.001 TCA 2.0 3.0 0.14 Other antidepressant medication 3.8 7.7 0.001 Heart disease, % yes 4.5 7.4 0.01 Number of other chronic diseases, mean (SD) 0.5 (0.8) 1.4 (1.2) <0.001

Potential confounders/mediators

Physical activity, MET min a week, mean (SD) 3309 (3027) 3584 (3345) 0.09 Insomnia, % yes 28.2 55.1 <0.001 Depressive disorder, % yes 48.0 78.7 <0.001 Anxiety disorder, % yes 43.7 71.3 <0.001 Depression or anxiety disorder, % yes 61.8 88.2 <0.001 Depressive symptoms (IDS), mean (SD) 13.7 (11.5) 28.5 (13.8) <0.001 Anxiety symptoms (BAI), mean (SD) 6.6 (7.6) 17.6 (11.7) <0.001

Autonomic nervous system measures

HR, beats/min, mean (SD) 72.5 (9.6) 73.0 (9.5) 0.29 PEP, ms, mean (SD) 119.6 (18.9) 120.5 (18.3) 0.36 SDNN, ms, mean (SD) 66.4 (26.4) 63.3 (24.1) 0.02 RSA, ms, mean (SD) 44.3 (26.9) 41.3 (23.3) 0.02 Respiration rate, breaths/min, mean (SD) 16.9 (1.2) 16.8 (1.1) 0.12 A: Based on X2 test for dichotomous and categorical variables and ANOVA for continuous variables.

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Table 2: Association between ANS activity and the presence of chronic widespread pain

Control (N= 843) vs. Control (N=843) vs. grades of CWP2 CWP (N= 731) 1 Parameters autonomic Low disability-low intensity2 Low disability-high intensity2 High disability-moderately limiting2 High disability-severely limiting2 nervous system (N= 251) (N=230) (N=116) (N=134) ORc 95% CI P ORc 95% CI P ORc 95% CI P ORc 95% CI P ORc 95% CI P

HR unadjusted 1.06 0.96 1.17 0.29 1.05 0.92 1.21 0.47 0.94 0.81 1.09 0.40 1.25 1.03 1.51 0.02 1.11 0.93 1.33 0.25 adjusted A 0.99 0.87 1.11 0.81 1.0 0.85 1.17 0.97 0.90 0.76 1.07 0.24 1.20 0.96 1.50 0.12 1.03 0.82 1.29 0.80 adjusted B 0.94 0.87 1.14 0.99 1.04 0.88 1.21 0.67 0.95 0.81 1.14 0.58 1.27 1.0 1.60 0.05 1.09 0.86 1.37 0.49

PEP unadjusted 1.05 0.95 1.16 0.36 1.07 0.93 1.23 0.35 1.03 0.89 1.19 0.69 1.00 0.83 1.22 0.99 1.08 0.90 1.30 0.41 adjusted A 1.09 0.97 1.23 0.18 1.08 0.93 1.26 0.30 1.04 0.88 1.24 0.62 1.02 0.81 1.30 0.85 1.08 0.87 1.34 0.51 adjusted B 1.05 0.91 1.20 0.52 1.06 0.91 1.25 0.45 1.01 0.84 1.22 0.89 0.95 0.74 1.22 0.69 0.98 0.76 1.25 0.87

SDNN unadjusted 0.88 0.80 0.98 0.02 1.00 0.88 1.15 0.96 0.90 0.77 1.05 0.16 0.76 0.61 0.95 0.02 0.72 0.58 0.89 0.003 adjusted A 1.09 0.97 1.24 0.17 1.13 0.97 1.23 0.11 1.11 0.93 1.32 0.26 0.93 0.72 1.20 0.59 0.99 0.78 1.27 0.95 adjusted B 1.10 0.95 1.26 0.20 1.12 0.96 1.32 0.16 1.09 0.90 1.32 0.39 0.94 0.72 1.23 0.64 1.00 0.77 1.33 0.99

RSA+ unadjusted 0.88 0.80 0.98 0.02 1.01 0.89 1.16 0.85 0.90 0.76 1.03 0.14 0.72 0.56 0.92 0.01 0.69 0.55 0.88 0.002 adjusted A 1.02 0.89 1.17 0.80 1.10 0.93 1.30 0.25 1.01 0.83 1.24 0.90 0.79 0.57 1.08 0.14 0.84 0.62 1.14 0.25 adjusted B 1.06 0.90 1.24 0.50 1.12 0.94 1.33 0.22 1.02 0.81 1.27 0.90 0.81 0.57 1.15 0.24 0.84 0.60 1.19 0.34

1: Based on logistic regression analysis, total N= 1574. 2: Based on multinomial logistic regression analysis, total N= 1574. Control group as reference group. : Adjusted for confounders: age, gender, education, alcohol use, BMI, smoking, heart disease, chronic disease, betablocking agents, other heart medication, pain medication, TCA, SSRI and other antidepressant medication. : Additionally adjusted for physical activity, insomnia, lifetime depressive or anxiety disorder, IDS and BAI. : Per SD increase. + :Also adjusted for respiration rate.

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Table 3: Association between ANS activity and pain intensity in subjects with chronic widespread pain

Pain intensity1 Parameters autonomic βc 95% CI P nervous system

HR unadjusted 0.85 0.47 2.17 0.21 adjusted A 0.94 0.35 2.24 0.15 adjusted B 0.92 0.31 2.16 0.14

PEP unadjusted 0.77 2.10 0.56 0.26 adjusted A 1.09 2.38 0.19 0.10 adjusted B 1.11 2.33 0.11 0.07

SDNN unadjusted 3.25 4.60 1.89 < 0.001 adjusted A 2.14 3.50 0.80 0.002 adjusted B 2.25 3.52 0.97 0.001

RSA+ unadjusted 2.58 3.99 1.17 < 0.001 adjusted A 2.24 3.81 0.67 0.005 adjusted B 1.95 3.44 0.46 0.01

1: Based on linear regression, N= 731. A: Adjusted for confounders: age, gender, education, alcohol use, BMI, smoking, heart disease, chronic diseases, betablocking agents, other heart medication, pain medication, TCA, SSRI and other antidepressant medication. B: Additionally adjusted for physical activity, insomnia, lifetime anxiety or depression disorder, IDS and BAI. c : Per SD increase. + Also adjusted for respiration rate.

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Reference List

(1) Wolfe F, Smythe HA, Yunus MB, Bennett RM, Bombardier C, Goldenberg DL et al. The American College of Rheumatology 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum 1990; 33(2):160-172.

(2) Elliott AM, Smith BH, Penny KI, Smith WC, Chambers WA. The epidemiology of chronic pain in the community. Lancet 1999; 354(9186):1248-1252.

(3) Garcia-Campayo J, Magdalena J, Magallon R, Fernandez-Garcia E, Salas M, Andres E. A meta- analysis of the efficacy of fibromyalgia treatment according to level of care. Arthritis Res Ther 2008; 10(4):R81.

(4) Maletic V, Raison CL. Neurobiology of depression, fibromyalgia and neuropathic pain. Front Biosci 2009; 14:5291-5338.

(5) Bengtsson A, Bengtsson M. Regional sympathetic blockade in primary fibromyalgia. Pain 1988; 33(2):161-167.

(6) Bou-Holaigah I, Calkins H, Flynn JA, Tunin C, Chang HC, Kan JS et al. Provocation of hypotension and pain during upright tilt table testing in adults with fibromyalgia. Clin Exp Rheumatol 1997; 15(3):239-246.

(7) Cohen H, Neumann L, Shore M, Amir M, Cassuto Y, Buskila D. Autonomic dysfunction in patients with fibromyalgia: application of power spectral analysis of heart rate variability. Semin Arthritis Rheum 2000; 29(4):217-227.

(8) Di FM, Iannuccelli C, Alessandri C, Paradiso M, Riccieri V, Libri F et al. Autonomic dysfunction and neuropeptide Y in fibromyalgia. Clin Exp Rheumatol 2009; 27(5 Suppl 56):S75-S78.

(9) Elam M, Johansson G, Wallin BG. Do patients with primary fibromyalgia have an altered muscle sympathetic nerve activity? Pain 1992; 48(3):371-375.

(10) Geenen R, Bijlsma JW. Deviations in the endocrine system and brain of patienst with fibromyalgia: cause or consequences of pain and associated features ? Annals of the New York Academy of Sciences 2010;(1193):98-110.

(11) Martinez-Lavin M, Hermosillo AG, Mendoza C, Ortiz R, Cajigas JC, Pineda C et al. Orthostatic sympathetic derangement in subjects with fibromyalgia. J Rheumatol 1997; 24(4):714-718.

(12) Martinez-Lavin M, Hermosillo AG, Rosas M, Soto ME. Circadian studies of autonomic nervous balance in patients with fibromyalgia: a heart rate variability analysis. Arthritis Rheum 1998; 41(11):1966-1971.

20

John Wiley & Sons, Inc. Page 21 of 23 Arthritis Care & Research

(13) Raj SR, Brouillard D, Simpson CS, Hopman WM, Abdollah H. Dysautonomia among patients with fibromyalgia: a noninvasive assessment. J Rheumatol 2000; 27(11):2660-2665.

(14) Vaeroy H, Qiao ZG, Morkrid L, Forre O. Altered sympathetic nervous system response in patients with fibromyalgia (fibrositis syndrome). J Rheumatol 1989; 16(11):1460-1465.

(15) Penninx BW, Beekman AT, Smit JH, Zitman FG, Nolen WA, Spinhoven P et al. The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods. Int J Methods Psychiatr Res 2008; 17(3):121-140.

(16) Von KM, Ormel J, Keefe FJ, Dworkin SF. Grading the severity of chronic pain. Pain 1992; 50(2):133-149.

(17) Elliott AM, Smith BH, Smith WC, Chambers WA. Changes in chronic pain severity over time: the Chronic Pain Grade as a valid measure. Pain 2000; 88(3):303-308.

(18) Smith BH, Penny KI, Purves AM, Munro C, Wilson B, Grimshaw J et al. The Chronic Pain Grade questionnaire: validation and reliability in postal research. Pain 1997; 71(2):141-147.

(19) de Geus EJ, Willemsen GH, Klaver CH, van Doornen LJ. Ambulatory measurement of respiratory sinus arrhythmia and respiration rate. Biol Psychol 1995; 41(3):205-227.

(20) Willemsen GH, de Geus EJ, Klaver CH, van Doornen LJ, Carroll D. Ambulatory monitoring of the impedance cardiogram. Psychophysiology 1996; 33(2):184-193.

(21) Berntson GG, Cacioppo JT, Quigley KS. Autonomic cardiac control. I. Estimation and validation from pharmacological blockades. Psychophysiology 1994; 31(6):572-585.

(22) Cacioppo JT, Berntson GG, Binkley PF, Quigley KS, Uchino BN, Fieldstone A. Autonomic cardiac control. II. Noninvasive indices and basal response as revealed by autonomic blockades. Psychophysiology 1994; 31(6):586-598.

(23) Goedhart AD, van der SS, Houtveen JH, Willemsen G, de Geus EJ. Comparison of time and frequency domain measures of RSA in ambulatory recordings. Psychophysiology 2007; 44(2):203- 215.

(24) Vrijkotte TG, van Doornen LJ, de Geus EJ. Overcommitment to work is associated with changes in cardiac sympathetic regulation. Psychosom Med 2004; 66(5):656-663.

(25) Licht CM, de Geus EJ, Zitman FG, Hoogendijk WJ, Van DR, Penninx BW. Association between major depressive disorder and heart rate variability in the Netherlands Study of Depression and Anxiety (NESDA). Arch Gen Psychiatry 2008; 65(12):1358-1367.

(26) Ginsburg P, Bartur G, Peleg S, Vatine JJ, Katz-Leurer M. Reproducibility of heart rate variability during rest, paced breathing and light-to-moderate intense exercise in patients one month after stroke. Eur Neurol 2011; 66(2):117-122.

21

John Wiley & Sons, Inc. Arthritis Care & Research Page 22 of 23

(27) Licht CM, de Geus EJ, Van DR, Penninx BW. Association between anxiety disorders and heart rate variability in The Netherlands Study of Depression and Anxiety (NESDA). Psychosom Med 2009; 71(5):508-518.

(28) Licht CM, de Geus EJ, Van DR, Penninx BW. Longitudinal evidence for unfavorable effects of antidepressants on heart rate variability. Biol Psychiatry 2010; 68(9):861-868.

(29) World Health Organization. The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Care. World Health Organization; 2001.

(30) World Health Organization Collaborating Center for Drugs Statistics Methodology. Anatomical Therapeutic Chemical (ATC) Classification. World Health Organization; 2007.

(31) Dworkin RH, O'Connor AB, Audette J, Baron R, Gourlay GK, Haanpaa ML et al. Recommendations for the pharmacological management of neuropathic pain: an overview and literature update. Mayo Clin Proc 2010; 85(3 Suppl):S3-14.

(32) Skurtveit S, Selmer R, Tverdal A, Furu K. The validity of self-reported prescription medication use among adolescents varied by therapeutic class. J Clin Epidemiol 2008; 61(7):714-717.

(33) Ainsworth BE, Bassett DR, Jr., Strath SJ, Swartz AM, O'Brien WL, Thompson RW et al. Comparison of three methods for measuring the time spent in physical activity. Med Sci Sports Exerc 2000; 32(9 Suppl):S457-S464.

(34) Levine DW, Kripke DF, Kaplan RM, Lewis MA, Naughton MJ, Bowen DJ et al. Reliability and validity of the Women's Health Initiative Insomnia Rating Scale. Psychol Assess 2003; 15(2):137- 148.

(35) Robins LN, Wing J, Wittchen HU, Helzer JE, Babor TF, Burke J et al. The Composite International Diagnostic Interview. An epidemiologic Instrument suitable for use in conjunction with different diagnostic systems and in different cultures. Arch Gen Psychiatry 1988; 45(12):1069-1077.

(36) Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. The Inventory of Depressive Symptomatology (IDS): psychometric properties. Psychol Med 1996; 26(3):477-486.

(37) Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol 1988; 56(6):893-897.

(38) Babyak MA. Understanding confounding and mediation. Evid Based Ment Health 2009; 12(3):68- 71.

(39) Rustoen T, Wahl AK, Hanestad BR, Lerdal A, Paul S, Miaskowski C. Age and the experience of chronic pain: differences in health and quality of life among younger, middle-aged, and older adults. Clin J Pain 2005; 21(6):513-523.

(40) Tsuji H, Venditti FJ, Jr., Manders ES, Evans JC, Larson MG, Feldman CL et al. Determinants of heart rate variability. J Am Coll Cardiol 1996; 28(6):1539-1546.

22

John Wiley & Sons, Inc. Page 23 of 23 Arthritis Care & Research

(41) Umetani K, Singer DH, McCraty R, Atkinson M. Twenty-four hour time domain heart rate variability and heart rate: relations to age and gender over nine decades. J Am Coll Cardiol 1998; 31(3):593-601.

(42) Cohen H, Neumann L, Alhosshle A, Kotler M, bu-Shakra M, Buskila D. Abnormal sympathovagal balance in men with fibromyalgia. J Rheumatol 2001; 28(3):581-589.

(43) Yunus MB, Dailey JW, Aldag JC, Masi AT, Jobe PC. Plasma and urinary catecholamines in primary fibromyalgia: a controlled study. J Rheumatol 1992; 19(1):95-97.

(44) Verhaak PF, Kerssens JJ, Dekker J, Sorbi MJ, Bensing JM. Prevalence of chronic benign pain disorder among adults: a review of the literature. Pain 1998; 77(3):231-239.

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