Effects of concentrated ambient particles on heart rate variability in spontaneously hypertensive rats

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(1)J Occup Health 2005; 47: 471–480. Journal of Occupational Health. Effects of Concentrated Ambient Particles on Heart Rate Variability in Spontaneously Hypertensive Rats Chuen-Chau C HANG 1, 2, Jing-Shiang HWANG 3, Chang-Chuan C HAN 1, Peng-Yau W ANG 4, Tsuey-Hwa HU3 and Tsun-Jen CHENG1 1. Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, 2Department of Anesthesiology, China Medical College Hospital, 3Institute of Statistical Science, Academia Sinica and 4Graduate Institute of Environmental Engineering, National Central University, Taiwan. Abstract: Effects of Concentrated Ambient Particles on Heart Rate Variability in Spontaneously Hypertensive Rats: Chuen-Chau C HANG , et al . Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Taiwan—In the present study, the cardiovascular toxicity of PM2.5 was determined in spontaneously hypertensive (SH) rats using the standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences of adjacent normal-to-normal intervals (RMSSD) as outcome measurements. Four SH rats implanted with radiotelemetry transmitters were repeatedly exposed to concentrated PM2.5 in nose-only exposure chambers. Gravimetric analysis revealed the mean post-concentrating mass concentration of particles during the 5 h of exposure was 202 µg/m3. Using each animal as its own control and linear mixedeffects model, to adjust for circadian nature and individual differences, we found that SDNN decreased by 15% initially then gradually decreased to 60% of the initial value at the end of exposure. Our results indicate that concentrated PM2.5 may decrease SDNN on SH rats during PM exposure. The study also showed that SDNN is more sensitive to PM induced effects than RMSSD. (J Occup Health 2005; 47: 471–480) Key words: Air pollution, Ambient particles, Ultra-fine particle concentrator, Spontaneously hypertensive rats, Heart rate variability. Epidemiological studies have shown that increased concentrations of ambient particles are associated with Received Jan 21, 2005; Accepted Aug 24, 2005 Correspondence to: T.J. Cheng, Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, 1 Jen-Ai Rd. Sec. 1, Taipei, Taiwan 100 (e-mail: tcheng@ha.mc.ntu.edu.tw). cardiovascular morbidity and mortality1, 2). However, the mechanisms underlying such associations have not been clearly defined. Recent epidemiological studies have shown the associations of increased air particles with elevated heart rate, blood pressure, and arrhythmias3–7). It has been speculated that particles induce dysfunction of the autonomic nervous system leading to the above noted changes 8). Recently, several epidemiological studies have used heart rate variability as an indicator of altered autonomic function to investigate particulate matter (PM)-induced cardiac toxicity3, 9–15). Decreased 5-min standard deviation of normal-to-normal intervals (SDNN), a parameter indicative of heart rate variability, has been observed in susceptible subjects exposed to increased levels of PM in these studies3, 12, 13, 15). Since epidemiological studies cannot draw a firm conclusion on the causal relationship, animal models have been used to investigate the effects of particles 16–22). However, only a few studies have focused on the heart rate variability outcomes. Residual oil fly ash (ROFA)23), oxides and sulfates of certain transitional metals24), and carbon black (CB)25) are the PM substitutes that have been used to evaluate heart rate variability effects. The limited information, inconsistent results, and composition differences between PM substitutes and the “real world” ambient particles make the interpretations and inferences difficult. Thus, more research is needed in this field. Spontaneously hypertensive (SH) rats have been characterized as a sensitive cardiovascular model26), and have been widely used in studies of PM-associated cardiovascular toxicity 27–29). In SH rats, heart rate variability measurements were found reliable30), and were used as indices of pharmacologic and pathologic outcomes31). It was our objective in the present study to use SDNN to assess autonomic nervous system dysfunction in SH rats exposed to concentrated ambient particles (CAPs), “real world” ambient particles, which.

(2) 472. J Occup Health, Vol. 47, 2005. have not yet been used to evaluate heart rate variability effects. Additionally, some epidemiological studies using root mean square of successive differences of adjacent normal-to-normal intervals (RMSSD) as an indicator of parasympathetic activity have shown inconsistent results for PM toxicity3, 15). Thus, the effect of CAPs on RMSSD was also examined in this study. A large number of animals were required to delineate the actual effects of ambient particles, because of the variations among diseased animals 20). Furthermore, variations in the circadian cycle of hemodynamic parameters also make such studies more difficult. To overcome these problems, we used each animal as its own control by exposing the individual animals repeatedly to concentrated particulate matter in air and filtered air, and successfully detected the effects of particles on the heart rate and blood pressure in three pulmonary hypertensive Sprague-Dawley (SD) rats32). This methodology has also been proved effective for analyzing cardiac contractility in SH rats exposed to CAPs33). In this report, the tactic was applied to test its applicability to delineating the heart rate variability effects of CAPs.. Methods Experimental design Male SH rats, weighing around 200 g, were obtained from the National Laboratory Animal Breeding and Research Center in Taiwan. They were housed individually on Aspen chip bedding and provided with Lab Diet 5001 and water ad libitum. A 12-h light/dark cycle, a constant room temperature, and a constant relative humidity were maintained in the animal room during the study. A systolic pressure over 150 mmHg developed spontaneously in the population by the age of 5 weeks, and was maintained at even higher levels throughout their lives. Four SH rats were implanted with radiotelemetry transmitters (model TL11M2-C50-PXT, Data Sciences International, St. Paul, MN, USA) at the age of 10 weeks. Starting from the 18th post-operation day, ECG signals were collected continuously throughout the experimental period. The one week long data collected on unanesthetized, unrestrained animals, immediately before the experiment were defined as the baseline data. Ambient particles in the Chung-Li area, a suburb of Taipei, were concentrated using an ultra-fine particle concentrator (UFPC) 34) modified for better automatic. Fig. 1. Schematic representation of the experimental procedure. Upper panel shows the experimental designs for data collection. Lower panel shows the procedures during each experimental day. See text for detailed information. Expo= Exposure group. Ctrl= Control group. CAPs= Concentrated ambient particles. A–D: SH rats A–D, respectively..

(3) Chuen-Chau CHANG, et al.: Particle Effects on Heart Rate Variability in SH Rats. control by computer algorithms. The theory of virtual impaction was utilized to concentrate ambient particles of 0.1–2.5 µm. CAPs remained in suspension without physical or chemical alteration for inhalation exposures or for collection onto filters for mass concentration analyses. A condensation particle counter (CPC, model 3022A, TSITM, Shoreview, MN, USA), located on both input and output arms, was used to analyze the particle concentrations before and after the UFPC every 30 s. Placed in one of the two output arms, polycarbonate filter paper was used to collect the particles for mass concentration calculation. As shown in Fig. 1, there were totally 4 d of exposure in the experiment, specifically, on Tuesdays and Thursdays in the second and third weeks, following baseline data collection in the first week. On the days of experimentation, the animals were accommodated for about 1 h (10:00 to 11:00) in closed type animal holders (model CH-2500, CH Technologies (USA), Westwood, NJ, USA) before the animals were fitted to the connector cones of nose-only exposure systems (12 Port Nose-Only Modular, CH Technologies) at 11:00. Two SH rats were then exposed to CAPs (exposure group), while the other two were exposed to HEPA filtered air (control group) for 5 h (11:00 to 16:00). SH rats serving as an exposure group in the second week were switched to the control group in the third week, and vice versa. RR interval measurement All signals from the telemetry system throughout the study were collected continuously. The sampling rate for ECG signals was set at 1,000 points per second (1,000 Hz) for better temporal discrimination. Time intervals between adjacent R waves in the ECG channel (RR) were calculated on a beat-to-beat basis using the computer package of Dataquest A.R.T.TM Analysis, version 2.20 (Data Sciences International, St. Paul, MN, USA). In this typical cardiac data acquisition system, signals from ECG were fed through a threshold detector, which triggered if it detected voltage level and/or slope change characteristics of the R-waves in ECG. Under this working system, two types of errors may occur. Errors resulting from a prematurely triggered Rwave detector may subdivide an RR interval into two successive intervals, which are much shorter compared with other normally recorded RR intervals (Type A errors), and errors resulting from trigger failure of the Rwave detector may merge consecutive RR intervals into intervals that are exceptionally long (Type B errors). In order to obtain normal-to-normal (NN) intervals, a computer algorithm based on the recommendation by Cheung was used to eliminate type A and type B errors in the NN calculation35). Basically the NN calculation followed a two-step procedure. The increase or decrease of any RR compared with the previous RR was limited. 473. to 33% in a first step correction. Data points with distances to the median greater than 1.5 standard deviation on Lorenz plots were eliminated in the second step for every 30 min. On average, 5.9 ± 1.7 % (Mean ± SD) of the original RR intervals were eliminated during the error correction. Standard deviation of NN (SDNN), and root mean square of successive differences of adjacent NN (RMSSD) were then calculated from NN at 5 min intervals. Statistic analysis The series of 5-min measurements of SDNN and RMSSD were transformed to natural logarithm scale and denoted as LnSDNN and LnRMSSD, respectively, so that distributions of the new response variables were symmetric. The measurements were classified into three categories using experimental conditions as baseline, control and exposure group data. The circadian baselines were estimated using medians of hourly measurements obtained from the baseline data. The circadian baselines were then subtracted from the LnSDNN and LnRMSSD data for the corresponding hours to obtain crude effects in log scale for each rat. To examine the PM effects, the crude effects on LnSDNN and the crude effects on LnRMSSD during the experimental period, i.e. from 10:00 to 16:00, were analyzed with a linear mixed-effects model. Chamber effects were modeled using a quadratic polynomial, while the PM effects were modeled using a line. If Yijkt is the crude effect for the ith SH rat in the jth condition (0 for baseline group, 1 for control group, 2 for exposure group) during the kth experiment at time t (1 to 72 for each 5min section during the 6 h of experiment), the mixedeffects model is given by Yijkt = (α1+a1i) • (Iin)ijkt + (α2+a2i) • (tin)ijkt + (α3+a3i) • [(tin)ijkt]2 + (β1+b1i) • (IPM)ijkt + (β2+b2i) • (tPM)ijkt + εijkt where (Iin)ijkt =1 and (tin)ijkt =t-1, when the ith rat was in the chamber during the kth experiment and 0 otherwise; (IPM)ijkt =1 and (tPM)ijkt =t-13, when the ith rat during the kth experiment was receiving CAPs and 0 otherwise. The error term εijkt was chosen to be an autoregressive process with second order to model time dependence. In the control group, when the fixed chamber effects were assumed to be the only stress source during the 6 h of experiments, the mean LnSDNN and/or LnRMSSD behaved like a quadratic curve of α1 + a2 • (tin) + α3 • (tin)2, where (tin) denoted the time staying in the closed type animal holders. For the exposure group on the other hand, after adjusting for the chambering effects, the mean LnSDNN and/or LnRMSSD shifted β1 units away from original levels at first, and changed linearly with a slop.

(4) 474. J Occup Health, Vol. 47, 2005. Table 1. Characterization of PM and Co-pollutants during Exposure. PM data were calculated according to the UFPC recordings. Data of co-pollutants were retrieved from an EPA monitoring station nearest to the experimental site. All data were expressed as time-weighted averages during the 5 × 4 h of experimenting Parameters Data Sources. Pollutant Items. UFPC. Mass (µg/m3) Particles (p/cm3) (before UFPC) Particles (p/cm3) (after UFPC) PM10 (µg/m3) SO2 (ppb) CO (ppm) O3 (ppb) NOx (ppb) NO (ppb) NO2 (ppb) THC (ppm). EPA Monitoring Station. Mean. SE. 202.0 1.59 × 104. 68.8 3.8 × 102. 2.30 × 105. 3.9 × 103. 67.1 4.1 0.7 69.4 19.7 1.8 17.9 2.1. 6.8 0.5 0.03 2.6 2.0 0.2 1.9 0.04. UFPC: Ultrafine Particle Concentrator, THC: Total Hydrocarbons. of β2 during the 5 h of exposure, behaving like a line of β 1 + β 2 • (t PM), where (t PM) denotes the time of PM exposure. Since the 4 SH rats were randomly selected from a population, random components a1i, a 2i, a3i, b1i and b2i were added to show the rat-to-rat variation of these effects. All of the random coefficients were assumed to be normally distributed with a mean of 0 and some constant variances. Statistical software package, S-PLUS 2000 (MathSoft Inc., Cambridge, MA, USA) was used to estimate the parameters and standard errors of the estimates in the model.. Results During exposure, condensation particle counter (CPC) readings showed an average pre-concentration particle concentration of 1.59 × 104 (range, 5.28 × 103 to 5.08 × 104) p/cm3 and a post-concentration level of 2.30 × 105 (range, 7.12 × 103 to 8.26 × 105) p/cm3, with an average concentration factor of around 14. Gravimetric analysis revealed the post-concentration mass concentration of particles during the 5 h of exposure as 202.0 ± 68.8 (Mean ± SE) µg/m3. Ambient gaseous co-pollutant data were derived from the nearest monitoring station of the Environmental Protection Agency, Taiwan (Table 1). The exposure temperature and humidity of this modified UFPC were shown to be consistently physiological, with temperature ranging from 16.9°C to 22.4°C, and relative humidity from 59% to 65%. As shown in Fig. 2, during the inhalation stage (11:00 to 16:00), crude effects of both LnSDNN and LnRMSSD for the exposure and control groups decreased from the. Fig. 2. The averages of crude effects across all 4 SH rats plotted against clock hours. LnSDNN is in the upper panel and LnRMSSD is in the lower panel. Dashed vertical lines at 10:00 denote the entrance of SH rats into closed-type animal holders, and at 11:00 and 16:00 denote the beginning and conclusion of experiments, respectively. Baseline data are in thin black lines ( ), the control group is in thick gray lines ( ), and the exposure group is in thick black lines ( )..

(5) Chuen-Chau CHANG, et al.: Particle Effects on Heart Rate Variability in SH Rats. 475. Table 2. Regression Results of Fixed Effects on LnSDNN and LnRMSSD Using a Linear Mixed-effect Model. LnSDNN. Coefficient α1 α2 α3 β1 β2. LnRMSSD. Value. S.E.. p value. Value. S.E.. p value. 0.010 –0.010 <0.001 –0.165 –0.006. 0.049 0.004 <0.001 0.083 0.002. 0.837 0.009 0.007 0.048 0.001. 0.202 –0.010 <0.001 0.078 –0.005. 0.075 0.005 <0.001 0.088 0.002. 0.007 0.034 0.080 0.375 0.021. The chamber effects were fitted to a binomial curve with intercept α1, time constants of α2 and α3. The PM effects were fitted to a linear model with intercept β1 and slope β2.. Fig. 3. The averages of PM effects across all 4 SH rats plotted against clock hours. LnSDNN is in the upper panel and LnRMSSD is in the lower panel. Dashed vertical lines at 11:00 and 16:00 denote the beginning and conclusion of experiments, respectively. Thin solid lines represent the crude averaged PM effects. Thick solid lines during the inhalation stage (11:00 to 16:00) represent the mean PM effects estimated from linear mixed-effect models. Thick solid lines after the experiments (after 16:00) represent the smoothed curve of log-transformed heart rate variability parameters estimated by robust local linear fits.. baseline values. Immediately after the experiments, both LnSDNN and LnRMSSD decreased due to stresses produced by release from the exposure system, then returned to the baseline values. The data were further analyzed using a linear mixedeffects model (Table 2). The chambering effects fitted. Fig. 4. The estimated mean PM effects during exposure with 95% CI in their original scales plotted against clock hours. SDNN is in the upper panel and RMSSD is in the lower panel.. quadratic curves well, with significant coefficients of α2 and α3. After controlling for the chambering effects, decreased or decreasing LnSDNN and LnRMSSD (significantly negative β1, or β2, or both) was observed during the PM exposure. The regression lines in Fig. 3 were calculated from Table 2 (shown in solid lines between 11:00 and 16:00) and revealed a decreased or decreasing trend during the PM exposure. After the experiments (after 16:00), the PM effects diminished and the heart rate variability parameters returned to their baseline level. This recovery course was better manifested using a smoothing technique utilizing robust local linear fits (shown in solid lines after.

(6) 476. 16:00). For better illustration, the linear regressions of LnSDNN and LnRMSSD for the PM effects were transformed back to their original scales, and plotted against the clock hours in Fig. 4, with 95% confidence intervals (CI). It appears that, during CAPs exposure, SDNN decreased from 85% to 60% of the base line. All of the decrements were statistically significant at an α level of 5%. In contrast, the CAPs effects on RMSSD were not significant though the trend of RMSSD changes with time was significant.. Discussion In the current study, our data demonstrated that CAPs exposure decreased SDNN of experimental animals. However, the effects of CAPs on RMSSD were less prominent. Heart rate variability has recently been used in epidemiologic air pollution studies to explore cardiovascular pathogenesis. As a time domain parameter of heart rate variability reflecting global heart rate variability, SDNN has been used the most extensively. In elderly populations, consistent decreases of SDNN have been observed with exposures to PM1036, 37), to PM 2.53, 11, 15, 38), to ambient submicrometer particles with a size range of 0.02–1 microns (NC0.02–1)39), and to CAPs10). Decreased SDNN have also been observed in young and healthy subjects exposed to environmental and occupational ambient PM12, 13, 40), and to ambient NC0.02–139). Nevertheless, heatrt rate responses inconsistent with increased PM levels were also noted, which precluded the conclusion of an overall decrease in vagal tone or increase in sympathetic tone accompanying a high pollution episode3). In a human trial, a modest increase in parasympathetic stimulation of heart rate variability was demonstrated with CAPs exposures41). Lately, heart rate variability has also been used to demonstrate the PM effects on experimental animals. In an animal study, high dose ROFA exposure decreased SDNN, but did not change the heart rate significantly, in sedated SD rats with acute myocardial infarction (MI)23). On the other hand, exposure to CB decreased heart rate and increased SDNN significantly in both healthy and terminally senescent conscious mice25). However, short term oral exposure to oxides and sulfates of transitional metals in old conscious beagle dogs did not present significant heart rate variability changes24). Thus, no firm conclusion could be drawn because of the short duration of the observations, pharmacological sedation, inadequate control for individual variation and circadian cycles, differences in animal species, and inconsistent findings. On the other hand, although these PM substitutes are more homogenous in composition and result in more reproducible responses, they are different from “real world” ambient particles and pose another challenge for extrapolating to human observations in natural. J Occup Health, Vol. 47, 2005. environments. Compared with frequency domain counterparts, time domain measurements are considered as simple and practical tools for assessing autonomic function. Though coefficient of variance (CV R-R) is sometimes calculated to detect overall variability independent of changes in mean NN intervals, it is strongly correlated with SDNN and usually adds little additional information42). Thus SDNN and RMSSD were chosen for this study. With careful design and analysis, we demonstrated that CAPs exposure decreased SDNN in the present study. In our previous study, CAPs generated under the same conditions increased heart rate, blood pressure, and cardiac contractility during the exposure hours 33) . These findings, altogether, are consistent and compatible with a picture of autonomic nervous system activation43). Conventionally, decreased SDNN has been associated with increased morbidity and mortality, and is commonly used as a tool for health risks stratification. Cardiac deaths in patients with recent MI44), and deaths due to progressive heart failure in congestive heart failure (CHF) patients 45–47) are both reasonably predictable through decreased SDNN. SDNN is also indicative of long term cardiovascular events in young populations with structural heart diseases 48, 49) . Decreased SDNN in subjects who were generally young and healthy were demonstrated to predict the development of hypertension50), coronary arterial heart disease and cardiac mortality51). Decreased SDNN is even predictive of death from all causes in a middle-aged general population52). Our current findings are consistent with epidemiological and toxicological air pollution studies, and may show a link between PM air pollution and increased cardiovascular risks. In contrast, the risk predictive value of RMSSD, a time domain heart rate variability parameter that stands for short-cycled variability reflecting parasympathetic activity, has been inconsistent in recent studies. One researcher concluded that RMSSD was unsuitable for evaluating the autonomic nervous system function in autoneuropathy because of low reproducibility 53) . Furthermore, RMSSD was also unsatisfactory in the predictive value of cardiac death due to CHF54) and acute MI 55). However, Rapenne et al.56) demonstrated that increased RMSSD was the most powerful heart rate variability parameter predicting the deterioration to brain death of patients with severe head trauma. Application of RMSSD in air pollution studies has shown inconsistent results. While Pope III et al.15) observed an increase in RMSSD during PM air pollution, the opposite responses were also demonstrated in epidemiological studies3, 39, 57). Though increased RMSSD was observed in an animal study using CB exposed senescent mice as the subjective model25), our study showed a less prominent decrease of RMSSD to CAPs during the exposure hours. Hence, the.

(7) Chuen-Chau CHANG, et al.: Particle Effects on Heart Rate Variability in SH Rats. role of RMSSD in CAP-related cardiac toxicity needs further assessment. Various types of receptors and neurons in mammalian airways have been associated with autonomic nervous system functioning. Vagal pulmonary C fibers58) and the olfactory bulb as a whole59) have been demonstrated in anesthetized SD rats as an important afferent port and integral center for cardiovascular sympathoexcitatory reflexes. It was speculated that CAPs might influence the autonomic nervous system function via these pathways, and thereby link to its cardiovascular pathogenesis. Epidemiological studies have documented the health effects of PM air pollution mostly in susceptible subjects while its effects on healthy groups are generally of limited scale. Diseased animals have therefore been used in PM toxicity studies to investigate the credibility of the epidemiological findings. However, selections are limited for susceptible animals in this relatively new field. SH rats have been proven to be an effective model of cardiovascular diseases (CVD) because they develop heart failure 60, 61) and artherosclerosis 62), which may contribute to the PM-related cardiovascular toxicity. Although representative of only a portion of human counterparts, SH rats have been widely used as rat models in studies of PM-related CVD. SH rats have been demonstrated as susceptible to air pollutants in the field of pulmonary outcomes 26). Aside from their airway sensitivity to PM and pathologic ANS dysfunction, SH rats also possess a higher level of oxidative stress than their cogenic controls63). All of these characteristics make SH rats prone to adverse cardiovascular outcomes induced by PM inhalation16). Therefore, SH rats have been used in the most recent toxicological studies which have explored the relationship between air pollution and cardiovascular effects27–29, 32, 64). Thus we chose this widely used rodent model not only for its biological relevance, but also for comparability with the results of other researches. However, wide variation among diseased inbred subjects still presents difficulties in data analysis. To overcome the common problems of wide variation among diseased subjects, each animal was used as its own control in our study by exposing the individual animals repeatedly to CAPs and filtered air. The proposed mixedeffects model is a commonly used approach for analyzing these kinds of repeated measurement data3, 12, 14, 65). Our model also included random components for animal-toanimal variation and autocorrelations of each animal’s repeated measurements besides the fixed effects for CAPs exposure. Owing to the varying concentrations of CAPs, and differences in animal responses, day-to-day variations of responses were wide. The wide day-to-day variation blurred the dose-response relationship, and justified the pooling of data so as to treat exposure as a binary descriptor in this study, instead of regressing heart rate. 477. variability measurements on concurrent CAPs levels. Our results demonstrated that exposure to CAPs induced heart rate variability alterations during the period of exposure. To the best of our knowledge, this is the first study to demonstrate the heart rate variability effects of CAPs on unanaesthetized experimental animals. This may have some implications for explaining the epidemiological findings. The results of the study also showed that SDNN was more sensitive to PM effects than RMSSD. Acknowledgments: The authors are grateful to Mr. Ming-Chih Chen and Ms. Yu-Chen Lei for their technical assistance. The authors also thank the National Institute of Environmental Analysis, EPA, and National Science Council (NSC) Taiwan for their helpful assistance on this project. 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