Evaluation of autonomic nervous system by heart rate variability and differential count of leukocytes in athletes

doi:10.4236/health.2010.210175

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Vol.2, No.10, 1191-1198 (2010) Health

doi:10.4236/health.2010.210175

Evaluation of autonomic nervous system by heart rate

variability and differential count of leukocytes in

athletes

Nobuhiro Suetake1,2*, Yukiko Morita2, Daichi Suzuki3, Keiko Lee1, Hiroyuki Kobayashi1

1Department of Hospital Administration, Juntendo University, School of Medicine, Tokyo, Japan

2Sakae Clinic, Aichi, Japan; *Corresponding Author: nobu666@d1.dion.ne.jp

3Department of Sports Science, Juntendo University, Graduate School of Health and Sports Science, Chiba, Japan

Received 22 May 2010; revised 15 June 2010; accepted 2 July 2010.

ABSTRACT

Top Japanese sprinters were evaluated for their

physical condition, autonomic function, blood

chemistry, differential leukocyte count and blo-

od lactate level before and after short, maximal

exercise to explore methods of quantifying their

conditioning level. Statistical analysis of data

obtained before and 10 min after exercise were

used to estimate the athletes’ autonomic capac-

ity during recovery. Pre and post exercise varia-

nces in differential leukocyte count revealed str-

ong correlations between neutrophil and symp-

athetic activity, and lymphocyte and parasympa-

thetic activity. The results of the study demon-

strated significant alterations in autonomic pa-

rameters and differential white blood cell count

in response to maximal exercise.

Keywords: Heart Rate Variability; Conditioning;

Differential Count of Leukocytes

1. INTRODUCTION

It is of paramount importance for high-performance ath-

letes to consistently train in a manner that preserves their

optimal conditioning level. Athletes regularly train at

high intensity and volume for extended periods such that

an imbalance between excessive workload and inade-

quate recovery renders them susceptible to mental and

physical depletion. Therefore, athletes` fitness level is an

important factor in designing training programs and for

preventing overtraining syndrome [1]. However, previ-

ous attempts to portray the blood lactate level and Pro-

file of Mood State (POMS) as respective indicators of

physical and mental fatigue have not been entirely concl-

usive. For this study, heart rate variability (HRV) analy-

sis [2] has been selected to quantitatively evaluate auto-

nomic capacity [3,4] for its greater accuracy in estimat-

ing physical fitness than earlier methods [5]. Cardiac

rhythm is modulated by the two limbs of the autonomic

nervous system (ANS), the sympathetic and parasympa-

thetic, which exert antagonistic effects. Sympathetic do-

minance occurs during stressful conditions such as ner-

vousness and excitement, whereas a shift in favor of va-

gal modulation calms the heart rate. Accordingly, heart

rate and RR interval fluctuation (HRV) permit analogi-

cal inference of autonomic influence as well as the eff-

ects of mental state and stress level on sympathetic and

vagal outputs (HRV analysis) [6,7].

Abo has previously reported that leukocytes are under

autonomic control [8]. More specifically, sympathetic

and parasympathetic stimulations have been shown to

activate adrenalin receptors on granulocytes, the most

prolific leukocytes, and acetylcholine receptors on lym-

phocytes, respectively [9]. Leukocytes have two major

biological defense activities. Granulocytes and macro-

phages incite phagocytic activities against foreign bacte-

ria and materials, whereas lymphocytes respond to viral

and abnormal protein infiltrations by mediating antigen-

antibody production and attacking cellular damage.

In this study we have focused on the proportion of

neutrophil, the representative granulocyte, and lympho-

cyte subpopulations. In short, we have explored whether

the alterations in autonomic parameters and granulo-

cyte/lymphocyte ratio serve as novel markers of physical

and mental exhaustion in sprinters after maximal high

knee lifts, and also act as potential indicators of athletes’

fitness level.

2. MATERIALS AND METHODS

2.1. Subjects

Five elite sprinters in their twenties (mean age 27 ± 1.4)

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with qualifications or titles in the Prefectural Track and

Field Championships participated in the study (1 female

and 4 male sprinters with personal bests ranking among

the top 20 in 2009). Weekly training program for the

athletes consisted of daily circuit and weight training for

>/= 3 hr/day for more than 5 days a week, punctuated

with a day of rest and participation in competitive and

time trials on Sundays. All participants routinely en-

gaged in physical exercise for >/= 3 hr/day for at least 5

times per week. Subjects were fully informed about the

objectives, specific test procedures, and mental and ph-

ysical burden of participating in the study. Test times

were scheduled to avoid conflict with competitions and

to prevent carryover effects on athletic performance.

Eligible participants provided full consent before enroll-

ing in the study. Subjects performed a light warm-up

before the test exercise to assess their condition. All st-

udy participants were nonsmokers and had no history of

hypertension, hyperlipidemia, cardiovascular disease, or

diabetes. None of the athletes were taking cardiovascular

medications and psychiatric agents such as sleeping pills

and anxiolytic drugs. On the day of the test, subjects

must have had a body temperature of >/= 37℃, absence

of significant malaise, >/= 6 hours of sound sleep and

abstinence from alcohol intake for at least 24 hr prior to

the test. Participants were instructed to complete voiding

and avoid food and drink for more than 3 hr before the

scheduled test time. Pre-exercise measurements were

taken in the sitting position after a 20-min rest. Subjects

were monitored to pace their respiration at approxi-

mately 13 breaths/min.

2.2. Method

Heart Rate Variability (HRV) Analysis: By measuring

heart rate and RR interval fluctuations (HRV), autono-

mic activity and the effects of mental balance and stress

level on this capacity can be analogically inferred. RR

interval is the distance between two consecutive R wa-

ves which are known as the largest spikes in EKG. Sp-

ectral transformation of this RR interval variability gene-

rates high frequency power called “HF” (> 0.15 Hz) and

low frequency power termed “LF” (0.04 ~ 0.15 Hz), wh-

ere HF power is regarded as the primary estimate of car-

diac vagal activity. HF power is also generally presumed

to correspond to respiratory sinus arrhythmia and there-

fore approximates to the frequency of respiration. In co-

ntrast, LF power is surmised as mirroring the activities

of the two autonomic nerves. For these reasons, the ratio

of HF and LF is considered as the index of sympathova-

gal activity. The LF/HF ratio is typically associated with

sympathetic activation and HF with vagal excitation. Th-

ese frequency domain indices are obtained from power

spectral analysis that has been calculated from the fast

Fourier transform (FFT) [10].

Primary outcome parameters for this study were freq-

uency domain parameters such as very low frequency

(VLF), high frequency (HF), low frequency (LF), LF/HF

ratio, total power (TP). Additionally, blood chemistry

(AST, ALT, LDH, CK, blood glucose, BUN); differen-

tial WBC count; and blood lactate levels were obtained

before and 10 min after all-out high knee lifts. HF Norm

(adjusted HF) and LF Norm (adjusted LF) were used in

lieu of HF and LF for statistical analyses.

HF Norm = HF/(Total Power − VLF) × 100

LF Norm = LF/(Total Power − VLF) × 100

The purpose of adjusting the values was to minimize

the impact of VLF alterations and to emphasize the sep-

arate fluctuations induced by parasympathetic and sym-

pathetic activities. VLF has recently garnered attention

as an important prognostic indicator of ischemic heart

disease [11]. Although VLF is considered to reflect the

very slow mechanistic activity of sympathetic control,

the underlying physiological mechanisms remain unclear.

Consequently, VLF measurements were omitted from

this study and the adjusted values were used for statisti-

cal analysis.

Based on the recommendation by The European Soci-

ety of Cardiology and the North American Society of

Pacing and Electrophysiology, resting HRV was meas-

ured with the Heart Rhythm Scanner (HRV analysis sy-

stem from Biocom, Inc.) equipped with software that

performs algorithms of short-term HRV analysis. Meas-

urements were taken from subjects in sitting in a quiet

room before the exercise. Biocom HRM-02 Pulse Wave

Sensor, the photoplethysmography (PPG) monitor used

in the study, was clipped to the right earlobe to measure

HRV for 5 minutes. The same procedure was repeated

after exercise. The PPG monitor was placed above the

converter (light  energy) for the light source and pho-

tocells and adjacent to both earlobes to direct the infra-

red beam towards the photocells. Since blood volume

fluctuations within the vasculature of the earlobe corre-

late to beat-to-beat changes, the PPG was employed to

capture the pulse waves to generate data on HRV. At a

designated area of a temperature (24℃) and humidity

(60%) controlled testing room, participants performed

two sets of 1-min all-out high knee lifts interspersed with

1-min of passive recovery. Tests were conducted be-

tween 12:00 PM – 18:00 PM when HRV was least vari-

able. In order to induce complete exhaustion, a super-

vising trainer provided verbal cues throughout the test

period to monitor and ensure the pace of the exercise.

Participants rested in standing during the 1-min interval

and in supine for 10 minutes during post-exercise recov-

ery. The same pre-exercise autonomic assessment and

blood tests were repeated 10 min after the exercise to

N. Suetake et al. / Health 2 (2010) 1191-1198

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1193

measure and quantitatively evaluate autonomic functions.

Participants were instructed to maintain a consistent res-

piration rate for the autonomic assessment during recov-

ery. Concomitantly with HRV analysis, routine blood

tests for assessing conditioning level have been evalu-

ated in this study, including: 1) blood chemistry aspar-

tate amino transferase (AST), alanine amino transferase

(ALT), lactate dehydrogenase (LDH), creatine kinase

(CK), blood urea nitrogen (BUN) to examine kidney

functions and protein metabolism; 2) blood lactate con-

centration to assess glucose metabolism; and 3) differen-

tial WBC count to investigate recent appraisal of the co-

rrelation between sympathovagal activity and leukocyte

subsets (neutrophils, lymphocytes, monocytes, eosinop-

hils and basophils). Pre and post exercise blood samples

were obtained from the same median cubital vein and

sent to FALCO biosystems Ltd to be tested. Subjects

were immediately asked about their fatigue rating after

the exercise. All laboratory tests and physical measure-

ments were taken while subjects sat calmly in the test

room.

Blood chemistry, differential WBC count, blood lacta-

te level: The following measurements were taken before

and after the stress exercise: 1) blood glucose (BG) to

observe energy expenditure during exercise; 2) aspartate

amino transferase (AST), alanine amino transferase (AL-

T), lactate dehydrogenase (LDH), and creatine kinase

(CK) to evaluate injury/inflammation of muscle tissues;

3) blood urea nitrogen (BUN) to assess alterations in ki-

dney functions and protein metabolism; 4) blood lactate

concentration to determine glucose metabolism; and 5)

differential WBC count (neutrophils, lymphocytes) to

assess autonomic capacity.

2.3. Statistical Analysis

T-test with the level of significance set at P < 0.05 was

used to assess pre and post exercise variations. All sta-

tistical analyses were carried out with PASW Statistics

17.0 (SPSS Inc.) software.

3. RESULTS

3.1. HRV Analysis (Figures 1 - 5)

The autonomic parameters of all subjects, including total

power (TP), very low frequency (VLF), high frequency

(HF), low frequency (LF) and LF/HF ratio during rest

were all within normal limits.

Figures 1-5 show the comparisons of mean TP, VLF,

LF Norm, HF Norm and LF/HF ratio among the five

sprinters.

Comparisons of mean TP, VLF, LF Norm, HF Norm,

and LF/HF ratio of the five sprinters before and 10 min-

ute after maximal high knee lifts demonstrated a signifi-

cant decrease in TP (p < 0.05), LF Norm(p < 0.01) and

LF/HF ratio (p < 0.05), while a considerable increase in

HF Norm (p < 0.05) was noted. VLF tended towards a

decline despite statistical insignificance (p < 0.1).

Figure 1. Comparison of mean total power among sprinters before

and 10 minute after all-out high knee lifts. A significant decrease

(p < 0.05) was observed after the exercise stress test.

N. Suetake et al. / Health 2 (2010) 1191-1198

1194

Figure 2. Comparison of mean VLF among sprinters before and

10 minute after all-out high knee lifts. A trend towards decline was

noted after the exercise stress test despite statistical insignificance

(p < 0.1).

Figure 3. Comparison of mean LF Norm among sprinters before

and 10 minute after all-out high knee lifts. A significant decrease

(p < 0.01) was observed after the exercise stress test.

3.2. Blood Chemistry, Blood Lactate

Concentration

Blood chemistry and blood lactate level were all within

normal limits before and after exercise. All aspects of

blood chemistry of pre and post exercise samples did not

demonstrate significant changes, except for creatine ki-

nase (CK). Creatine kinase (CK) and blood lactate levels

increased significantly 10 minutes after short, maximal

exercise (p < 0.01).

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1195

Figure 4. Comparison of mean HF Norm among sprinters before

and 10 minute after all-out high knee lifts. A marked increase (p <

0.05) was observed after the exercise stress test.

Figure 5. Comparison of mean LF/HF ratio among sprinters be-

fore and 10 minute after all-out high knee lifts. A significant de-

crease (p < 0.05) was observed after the exercise stress test.

3.3. Differential Leukocyte Count

(Figures 6-7)

Figures 6-7 illustrate the comparisons of mean neutro-

phil and lymphocyte ratios among the five sprinters be-

fore and after all-out high knee lifts. The proportions of

neutrophils and leukocytes in differential WBC count

were all within normal limits. Neutrophils reduced sig-

nificantly after exercise (p < 0.01), while lymphocytes

increased significantly after exercise (p < 0.01).

N. Suetake et al. / Health 2 (2010) 1191-1198

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Figure 6. Comparison of mean neutrophil count among sprinters

before and 10 minute after all-out high knee lifts. A significant

decrease (p < 0.01) was observed after the exercise stress test.

Figure 7. Comparison of mean leukocyte count among sprinters

before and 10 minute after all-out high knee lifts. A significant in-

crease (p < 0.01) was observed after the exercise stress test.

4. DISCUSSION

A battery of blood tests, psychological assessments and

autonomic evaluations are routinely administered to ath-

letes to objectively quantify their conditioning level. The

importance of autonomic capacity in athletic performa-

nce has been elucidated, and reports on autonomic ev-

aluation using HRV analysis in athletes across various

disciplines are available [12]. Despite recent accounts

underpinning the correlation between autonomic activity

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1197

and white blood cell count, data on this relationship in

the field of sports and training are practically nonexistent.

Although leukocytosis is a well-established phenomenon

following physical activity, and while reports on differ-

ential WBC alterations in response to exercise have been

published [13], the relationship between pre and post di-

fferential leukocyte and autonomic activity remains equ-

ivocal. The present study focused on quantitative evalu-

ation of pre and post exercise autonomic activities as

well as differential leukocyte count in athletes.

Because the study targeted elite athletes who train

regularly at high intensity and volume, all-out high knee

lifts were selected as the exercise stress test to induce

exhaustion. In the study, a prominent rise in peak lactate

after maximal high knee lifts was noted which served as

an objective marker of exhaustion in participants. Total

power significantly decreased after exercise, but this was

seen as a transient suppression of autonomic functions

under substantial physical stress. Caution must be exer-

cised when training athletes with reduced total power as

this could indicate autonomic dystonia. The association

between autonomic impairment and overtraining syndr-

ome, a chronic state of fatigue, has been reported else-

where. In the present study, significant post-exercise LF

reduction was attributed to the inhibition of baroreceptor

modulation in spite of sympathetic excitation after max-

imal exercise. In fact, LF appeared contingent not only

on sympathetic tone but baroreceptor reflex as well.

In response to a sudden increase in heart rate after sh-

ort maximal workload, parasympathetic tone is thought

to amplify 10 minutes after exercise to counteract the

sympathetic surge. On this basis, post-exercise measure-

ments for this study were taken 10 minutes after brief

maximal load to assess changes during recovery. Modu-

lation of acutely augmented heart rate after all-out exer-

cise has far-reaching ramifications for athletes. The aut-

onomic nervous system maintains physiological homeo-

stasis during abrupt changes in physical states and is sur-

mised to differ significantly between athletes and non-

athletes. In general, it has been suggested that non-athl-

etes have lower parasympathetic tone than athletes. Al-

though this could not be substantiated from this study as

data was obtained from high-performance athletes, ath-

letes and non-athletes are nonetheless expected to dem-

onstrate discrepant autonomic modulations after short

maximal exercise.

One sprinter was excluded from the study due to me-

ntal and physical exhaustion after participating in a 3-

day collegiate track and field competition as the key

player of his team. Resting autonomic tone of this athlete

fell below the normal range and albeit pronounced sub-

jective symptoms, the athlete failed to report his status

prior to the beginning of the study. Moreover, continu-

ous depression of parasympathetic activity was observed

in this athlete. These results suggested that additional

stress load on athletes suffering from overtraining syn-

drome could potentially prolong recovery. Despite rep-

orts of markedly higher vagal tone of athletes than non-

athletes at rest, recovery after exercise also depends lar-

gely on this branch`s activity. In principle, cardiac auto-

nomic assessment using HRV is analogous to the estim-

ation of varying velocity of a moving vehicle from the

coordination of the accelerator and brake. In other words,

HRV is akin to the changing speed of a vehicle, while

the operation of accelerator and brake corresponds to sy-

mpathovagal control of the heart. Because athletes must

rapidly modulate an acutely elevated heart rate during

rest, increasing the vagal tone has important implications.

Our results indicated that LF/HF ratio, an index of sym-

pathetic tone, following maximal high knee lifts declined,

and that HF, an index of parasympathetic function, elev-

ated 10 minutes after exercise. These results were con-

sistent with a shift in proportion of neutrophils and lym-

phocytes in the differential leukocyte count, thus imply-

ing an association between autonomic functions and

white blood cell count. In addition, these findings also

undergirded the potential interactions between sympat-

hetic activity and granulocytes, and parasympathetic ac-

tivity and lymphocytes as cited by Abo [14]. With con-

firmed significant alterations in HRV parameters and

differential leukocyte count in athletes following brief

maximal exercise, quantitative evaluation of autonomic

activity via HRV analysis and differential WBC emerge

as plausible indices of conditioning level and physical

capacity of athletes. The variance in neutrophil and lym-

phocyte ratios appears especially robust as an index, co-

mparable to the assessment of autonomic functions.

Participants of this study involved first-class athletes

who were anticipated to demonstrate superior autonomic

modulation following exercise. In the case of non-ath-

letes, however, post-exercise recovery was expected to

be more sluggish. Since our test date coincided with the

track and field season, recruitment of robust number of

top Japanese athletes for the study was difficult. Several

participants withdrew from the study due to fatigue from

regular training. The sample population fell below the

target size as great care was taken to prevent the physical

burden of participating in the study from ethically inter-

fering with competitions and training programs. More-

over, the nature and intensity of the exercise stress test

were such that only the very best athletes in the country

could perform them adequately, and the selection of

such athletes with comparable athletic capacity resulted

in a maximum sample size of five for this study. Despite

the small sample, this is the first study to evaluate auto-

nomic resilience in sprinters after maximal exercise, and

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therefore we believe that our results can serve as a basis

for continued exploration of autonomic modulations in

athletes. While different results may have been observed

had athletes from various disciplines participated in the

study, sprinters were specifically selected because of

their training emphasis on basic exercises and resulting

ability to demonstrate rapid changes in HRV.

According to our results, a greater sample size will

minimize the individual differences in pre and post exer-

cise parameters that were observed in this study. Addi-

tionally, future studies that provide a comparison with a

control group and analyses of graded exercise intensity

and post-exercise intervention will complement our stu-

dy to deepen the understanding of the correlation betw-

een the autonomic nervous system and differential leuk-

ocyte count in athletes.

REFERENCES

[1] Hedelin, R., Wiklund, U., Bjerle, P., et al. (2000) Car-

diac autonomic imbalance in an overtrained athlete.

Medicine and Science in Sports and Exercise, 32(9),

1531-1533.

[2] Hayano, J., Sakakibara, Y., Yamada, A. and Mukai, S.

(1991) Accuracy of assessment of cardiac vagal tone by

heart rate variability in normal subjects. American Jour-

nal of Cardiology, 67(2), 199-204.

[3] Tanabe, S., Terao, T. and Nakano, S. (1993) Sym-

pathovagal balance in young athletes. Tokai Journal of

Sports Science and Medicine, 5, 44-49.

[4] Tanabe, S., Terao, T. and Nakano, S. (1995) Comparison

of sympathovagal balance between the middle aged and

young athletes. Tokai Journal of Sports Science and

Medicine, 7, 75-82.

[5] Perini, R. and Veicsteinas, A. (2003) Heart rate variabil-

ity and autonomic activity at rest and during exercise in

various physiological conditions. European Journal of

Applied Physiology, 90(3-4), 317-325.

[6] Sawada, Y. (1999) Heart rate variability, Is it available in

psychophysiological research. Japanese Journal of Can-

cer Research, 26, 8-13.

[7] Yokoi, M. and Yamazaki, K. (1995) Cardiac autonomic

nervous activity interaction under mental stress. A study

using the corrected heart rate variability indexes. Tokai

Journal of Sports Science and Medicine, 7, 75-82.

[8] Abo, T. (2002) Autonomic nervous regulation of leuko-

cytes. Japanese Journal of Physical Fitness and Sports

Medicine, 51, 10-11.

[9] Abo, T. (1999) Regulation of leukocytes by the auto-

nomic nervous system, new rule on the cooperation of

neuro-endocrine-immune systems (on the functions of

the autonomic nervous system). Japanese Journal of

Psychosimatic Medicine, 39, 67-74.

[10] Goto, K., Matuura, H. and Muramoto, K. (2002) Esti-

mate of autonomic nervous system function by heart rate

variability analysis [in Japanese] IEICE technical report.

ME and Bio Cybernetics, 102(507), 13-16.

[11] Hadase, M., Azuma, A. and Zen, K. (2004) Very low

frequency power of heart rate variability is a powerful

predictor of clinical prognosis in patients with congestive

heart failure. Japanese Circulation Society, 68(4), 343-

347.

[12] Tanabe, S., Yoshioka, K. and Yamashita, Y. (1994) Sy-

mpathetic and parasympathetic activities at rest and after

exercise in judo athletes. Tokai Journal of Sports Science

and Medicine, 6, 35-42.

[13] Suzuki, K., Saoto, H. and Endo, T. (1995) Variation of

neutrophil active oxygen and differential count of leuko-

cyte’s during maximal exercise load in athletes. Japanese

Journal of Physical Fitness and Sports Medicine, 44(6),

747.

[14] Abo, T. (2002) Number and function of leukocytes are

regulated by the autonomic nervous system. Journal of

International Society of Life Information Science, 20(1),

171-189.