Heart rate variability in facioscapulohumeral muscular dystrophy

 

 

Giacomo Della Marca, MD, PhDa,1

Roberto Frusciante MD, PhDa,1

Michele Scatenaa

Serena Dittoni, MDa

Elisa Testani, MDa

Catello Vollono, MD, PhDb

Anna Losurdo, MDa

Emanuele Scarano, MDc

Salvatore Colicchio, MDa

Benedetto Farina, MDa

Valentina Gnoni, MDa

Salvatore Mazza, MDa

Pietro A. Tonali, MDd

Enzo Ricci, MDa

 

a Department of Neurosciences, Catholic University, Rome, Italy

b IRCCS “Bambino Gesù” Pediatric Hospital, Rome, Italy

c Institute of Otorhinolaryngology, Catholic University, Rome, Italy

d “Pro Juventute” Don Carlo Gnocchi Foundation, Rome, Italy

 

Corresponding author: Giacomo Della Marca

Department of Neurosciences, Catholic University,

Largo Agostino Gemelli n° 8, 00168 Rome, Italy

E-mail: dellamarca@rm.unicatt.it

 

 

Summary

 

Facioscapulohumeral muscular dystrophy (FSHD) is the third most frequent form of muscular dystrophy. Heart rate variability (HRV) analysis is a means of evaluating the activity of the autonomic nervous system. The aim of this study was to evaluate HRV in FSHD patients.

Fifty-five consecutive FSHD patients were enrolled (31 men, age 26-72 years). Muscular impairment was measured using a clinical severity scale (CSS). Patients were compared with a control group of 55 healthy subjects, matched for age and sex. HRV was analyzed in the time domain and in the frequency domain.

Patients showed increased spectral power of the low-frequency band. Spectral power of the high-frequency band was inversely correlated with CSS score.

FSHD is associated with a slight increase in sympathetic output and with a decrease in parasympathetic output. These modifications become more evident with the progression of the disease and could increase the risk of arrhythmias and other cardiovascular events.

 

Key words: arrhythmias, autonomic nervous system, ECG, facioscapulohumeral muscular dystrophy, heart rate variability

 

 

Introduction

 

Facioscapulohumeral muscular dystrophy (FSHD) is the third most frequent form of muscular dystrophy after Duchenne muscular dystrophy and myotonic dystrophy (1). FSHD is an autosomal dominant genetic disorder, caused by the heterozygous partial deletion of a critical number of repetitive elements (D4Z4) on chromosome 4q35. The number of KpnI repeats left on the shortened chromosome 4 inversely correlates with the severity of the disease, particularly in the presence of EcoRI fragment size ranging from 10 to 13 kb (2,3). Tupler and Gabellini provided a detailed review of the genetics of FSHD (4).

The phenotypic spectrum of FSHD is wide and heterogeneous. The clinical picture ranges from mild forms, in which the patient can be unaware of the disease, to severe muscular impairment in wheelchair-bound patients. Age at onset of the disease is variable, ranging from childhood-onset to adulthood-onset forms; most patients become symptomatic in the second decade of life.

Involvement of the heart and of the autonomic nervous system (ANS) is frequent in muscular dystrophies and can cause severe morbidity (5-10). As regards FSHD, clinically significant cardiac disease is present in 5-27% of patients (11-15) and a variety of rhythm and conduction disorders have occasionally been described, including elevated P waves, intraventricular conduction delay, supraventricular arrhythmias, ventricular tachycardia, atrioventricular block and long QT syndrome (7,12,16,17).

The activity of the ANS can be functionally explored and quantified by heart rate variability (HRV) analysis, which involves measuring and then analyzing variations in heart rate. These variations can be analyzed both in the time domain and in the frequency domain. A detailed description of HRV and its analysis (theory, methods and limitations) is provided by the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (18,19). HRV provides a quantitative marker of autonomic activity and has proved able to detect and measure modifications in sympathetic or vagal activity. Moreover, it can be used to estimate the propensity for arrhythmias. HRV has been extensively studied in Duchenne (9,20,21), Becker (22) and myotonic muscular dystrophies (6,7), but not in FSHD. The aim of the present study was to evaluate HRV in a large population of adult patients with genetically confirmed FSHD.

 

 

Materials and methods

Patients

 

Over a period of 18 months, 55 consecutive FSHD patients (31 men and 24 women; mean age 45.6±12.7, range: 26-72 years) were enrolled in the HRV study; these patients were already taking part in a polysomnographic study of FSHD (23,24). No patient reported heart disease, arrhythmias or intake of cardiovascular active drugs. No patient presented diabetes, uncontrolled hypertension, smoking, obesity, chronic respiratory disease or thyroid diseases. The diagnosis of FSHD was made on a clinical basis and confirmed by genetic tests. In particular, restriction of genomic DNA, 32P-labeling, and hybridization with L1LA5 (D4S163), pH30 (D4S139), and p13E-11 (D4F104S1) were performed as described elsewhere (25,26), as was pulsed-field gel electrophoresis analysis of p13E-11 alleles (25). All the patients underwent a full medical and neurological evaluation. Muscle strength was evaluated by means of manual muscle testing (MMT) and a score was assigned according to the Medical Research Council (MRC) scale (27). Using this scale, MMT scores may range from 0 = “no movement, no visible or palpable contraction” to 5 = “segment movement through full range of motion against gravity and ability to hold against resistance”. In order to measure the clinical severity of the disease, a ten-point clinical severity scale (CSS) (3) was adopted. Scores on this scale range from 0.5 = “facial weakness”, to 5 = “wheelchair-bound”; a CSS score ≤2 was assigned to patients with facial and shoulder muscle weakness, whereas higher scores (>2) were assigned to patients showing also pelvic and lower limb muscle weakness.

Controls

 

The patients were compared with a control group of 55 healthy subjects, matched for age and sex: 31 men and 24 women, mean age 46.8±14.4, range: 19-72 years. The control subjects were randomly extracted from the database of our sleep laboratory.

The study, which was designed in accordance with the Helsinki Declaration of 1975, was approved by the local ethics committee. All the patients and control subjects were fully informed of the study aims and procedures and all gave their written consent to participate.

 

 

Heart rate variability

 

Heart rate variability studies were carried out in a semi-darkened, temperature-controlled (23±1 °C) room. All patients and controls were evaluated at the same time of day (8 p.m.). Each subject had a 10-minute rest, after which a five-minute surface ECG from a thoracic lead was obtained while the subject rested in the supine position. During the ECG recording, we measured blood pressure and monitored EEG (in order to exclude epochs of sleep), respiratory rate (airflow, thoracic and abdominal effort), peripheral hemoglobin saturation and surface EMG. Periods of ECG recording displaying extrasystoles, movement artifacts or sleep were excluded from the analysis. The fact that this investigation was performed within the context of a polysomnographic study influenced the decision to perform short-lasting (5-minute) ECG recordings, and also determined the timing of the studies (8 p.m.). However, this context allowed careful monitoring of vigilance (by means of the EEG), body movements (by means of video-recording and surface EMG) and respiratory function (by means of pulse oximetry, airflow and respiratory effort). All these variables, in particular changes in respiratory rate, can affect the results of HRV analysis (28,29). Moreover, the full polysomnographic monitoring allowed more careful artifact rejection.

A dedicated software, designed by one of the authors (M.S.), identified the individual electrocardiographic R wave peaks and calculated the RR intervals (tachogram). Another software program was used for the automatic evaluation of the HRV parameters (HRV Analysis Software, Biomedical Signal analysis Group, Dept of Applied Physics, University of Kuopio, Finland) (30). HRV analysis was performed both in the time domain and in the frequency domain.

In the time domain, the parameters calculated were: RR interval mean and standard deviation; mean and standard deviation of heart rate; root mean square of the differences between consecutive RR intervals (RMSSD); number of consecutive RR intervals differing by more than 50 ms (NN50); percentage value of NN50 intervals (pNN50); geometric measures: the HRV triangular index and the triangular index N-N, determined from the histogram of RR intervals, in which N-N stands for normal-to-normal intervals (i.e. intervals between consecutive QRS complexes resulting from sinus node depolarization).

In the frequency domain, HRV was analyzed using Fast Fourier Transform (FFT) and a non-parametric autoregressive model. The frequency bands considered were the low-frequency (LF, 0.04-0.15 Hz) and high-frequency (HF, 0.15-0.4 Hz) ones. The frequency domain parameters included the absolute and relative (%) powers of the LF and HF bands, the power of the LF and HF bands expressed in normalized units, and the LF/HF ratio. Also, the peak frequencies were determined for each frequency band.

 

 

Statistical analysis

 

Statistical comparisons were performed between FSHD patients and controls. HRV parameters showed a non-normal distribution and the non-parametric Mann-Whitney U-test was thus used for their comparison; the level of significance was set at p<0.05. Correlations between CSS score and HRV parameters were tested by means of the Spearman’s correlation index. The critical value of the Spearman’s correlation coefficient was set at r(53)=0.266, corresponding to a significance level of p<0.05. Statistics were performed using the SYSTAT 12 software, version 12.02.00 for Windows® (copyright SYSTAT® Software Inc. 2007).

Results

The results of the HRV analysis in the time domain in patients and controls are reported in table 1. No differences between the patient and the control groups were observed in this analysis, with the exception of a decreased standard deviation of heart rate in the patient group. The results of the HRV analysis in the frequency domain in patients and controls are reported in table 2. The patients showed an increased relative power of the LF band in the FFT analysis. In the autoregressive model analysis, an increase in normalized power of the LF band was observed in the patients. The HF/LF ratio showed a trend to decrease in the patient group, which however did not reach statistical significance.

The results of the correlation analysis are summarized in table 3 (over). A significant inverse correlation was observed between CSS and RMSSD [r(53)=-0.299; p<0.05], CSS and NN50 [r(53)=-0.284; p<0.05], CSS and pNN50 [r(53)=-0.297; p<0.05], and CSS and SD1 [r(53)=-0.299; p<0.05]. Moreover, the absolute and the relative powers of the HF band were inversely related with the clinical severity of the disease, as expressed by the CSS score. This finding was confirmed both in the analysis performed using FFT and by the autoregressive model (Table 3).

 

 

Discussion

 

Our study did not detect major modifications of HRV indexes in FSHD patients compared with controls, with the sole exception of a slight increase of the LF component in the patient group. The main finding of the study was the demonstration of a significant inverse correlation between the severity of the disease (measured by the CSS score) and the power of the HF component: the more severe the disease, the lower the HF power values. This correlation was confirmed by the FFT analysis and the autoregressive model; moreover, it was present when HF was measured both in absolute power and in relative power.

In the literature concerning HRV analysis, the interpretation of the functional meaning of the LF component remains to some extent controversial (18,19). The LF is considered by some authors (31) as a marker of sympathetic modulation and by others (32) as a parameter that includes both orthosympathetic and parasympathetic influences. This discrepancy is due to the fact that in some conditions associated with sympathetic excitation, a decrease in the absolute power of the LF component is observed. Conversely, a wide consensus has been reached on the functional meaning of the HF component, which is clearly the expression of efferent vagal activity (18,19). The negative correlation between the CSS score and HF values indicates a progressive decrease in parasympathetic activity with the progression of muscular impairment. The negative correlation between the CSS score and several time-domain parameters (RMSSD, NN50, pNN50) represents a further confirmation of this finding (33-35). Therefore, our data suggest that in FSHD patients the progression of the disease is paralleled by a decline in parasympathetic activity.

No conclusive explanation is available either for the slight increase in sympathetic activity or for the progressive reduction of the vagal component in FSHD. Parasympathetic tone is increased by physical exercise, therefore in FSHD a decline in vagal activity could result from progressive reduction of physical activity due to muscular impairment. Alternatively, reduction of vagal activity could be the expression of autonomic modifications which occur in the course of the disease. Similar HRV modifications (increased sympathetic activity and progressive reduction of vagal tone) have been observed in other muscular dystrophies, characterized by frequent cardiac involvement and high cardiovascular risk. An increased sympathetic output and decreased vagal activity, with alteration of the circadian rhythm, have been observed in Duchenne muscular dystrophy; these modifications became more marked with the progression of the disease (9,21). A mixed, but especially parasympathetic, autonomic dysfunction has also been observed in myotonic dystrophy (36); this dysfunction becomes more evident with the progression of the disease (6,7). In Becker’s muscular dystrophy, HRV analysis showed an increment of sympathetic tone, and proved to be a reliable index for assessing sympathovagal balance and for stratifying arrhythmic risk (22). In fact, the authors of all the above studies agree that this autonomic dysfunction could play a role in the occurrence of cardiac abnormalities, and increase the risk of sudden cardiovascular events.

Cardiac and autonomic involvement have been described in FSHD. A clinically significant cardiac involvement was described in 5-27% of FSHD patients (11-15). In particular, Stevenson et al. (14) suggested that patients with FSHD have a high prevalence of arrhythmias; this finding was confirmed by other authors (37). An echocardiography study performed on 24 FSHD patients suggested a subclinical cardiac involvement which could represent a substrate for ventricular arrhythmias and heart failure (17).

In conclusion, autonomic modifications seem to occur in FSHD, characterized by a slight increase in sympathetic activity and a progressive decrease in parasympathetic output, which become more evident with the progression of the disease. Even though no arrhythmic or cardiovascular event was reported in our series, this dysfunction could in theory play a role in the occurrence of cardiac abnormalities, or increase the risk of sudden cardiovascular events. A clinical follow up is needed to investigate whether the progression of FSHD causes disruption of the autonomic control of the cardiovascular system and to determine the clinical value of the parasympathetic output decrease.

 

 

References

 

1.         Padberg G. Facioscapulohumeral Disease. Leyden, the Netherlands; Leyden University 1982

2.         Lunt PW, Jardine PE, Koch MC et al. Correlation between fragment size at D4F104S1 and age at onset or at wheelchair use, with a possible generational effect, accounts for much phenotypic variation in 4q35-facioscapulohumeral muscular dystrophy (FSHD). Hum Mol Genet 1995;4:951-958

3.         Ricci E, Galluzzi G, Deidda G, Cacurri S, Colantoni L, Merico B, et al. Progress in the molecular diagnosis of facioscapulohumeral muscular dystrophy and correlation between the number of KpnI repeats at the 4q35 locus and clinical phenotype. Ann Neurol 1999;45:751-757

4.         Tupler R, Gabellini D. Molecular basis of facioscapulohumeral muscular dystrophy. Cell Mol Life Sci 2004;61:557-566

5.         Finsterer J, Stöllberger C. Primary myopathies and the heart. Scand Cardiovasc J 2008;42:9-24

6.         Hardin BA, Lowe MR, Bhakta D, Groh WJ. Heart rate variability declines with increasing age and CTG repeat length in patients with myotonic dystrophy type 1. Ann Noninvasive Electrocardiol 2003;8:227-232

7.         Inoue K, Ogata H, Matsui M et al. Assessment of autonomic function in myotonic dystrophy by spectral analysis of heart-rate variability. J Auton Nerv Syst 1995;55:131-134

8.         Pelargonio G, Dello Russo A, Sanna T, De Martino G, Bellocci F. Myotonic dystrophy and the heart. Heart 2002;88: 665-670

9.         Yotsukura M, Sasaki K, Kachi E, Sasaki A, Ishihara T, Ishikawa K. Circadian rhythm and variability of heart rate in Duchenne-type progressive muscular dystrophy. Am J Cardiol 1995;76:947-951

10.       Katz A, Meites I, Bornstein N, Escher J, Korczyn AD. Cardiac manifestations of myotonic dystrophy. Funct Neurol 1989;4:355-361

11.       de Visser M, de Voogt WG, la Riviere GV. The heart in Becker muscular dystrophy, facioscapulohumeral dystrophy, and Bethlem myopathy. Muscle Nerve 1992;15: 591-596

12.       Berlit P, Stegaru-Hellring B. The heart in muscular dystrophy: an electrocardiographic and ultrasound study of 20 patients. Eur Arch Psychiatry Clin Neurosci 1991;241: 177-180

13.       Laforêt P, de Toma C, Eymard B et al. Cardiac involvement in genetically confirmed facioscapulohumeral muscular dystrophy. Neurology 1998;51:1454-1456

14.       Stevenson WG, Perloff JK, Weiss JN, Anderson TL. Facioscapulohumeral muscular dystrophy: evidence for selective, genetic electrophysiologic cardiac involvement. J Am Coll Cardiol 1990;15:292-299

15.       Finsterer J, Stöllberger C, Meng G. Cardiac involvement in facioscapulohumeral muscular dystrophy. Cardiology 2005;103:81-83

16.       Fitzsimons RB. Facioscapulohumeral muscular dystrophy. Curr Opin Neurol 1999;12:501-511

17.       Galetta F, Franzoni F, Sposito R et al. Subclinical cardiac involvement in patients with facioscapulohumeral muscular dystrophy. Neuromuscul Disord 2005;15:403-408

18.       Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Eur Heart J 1996;17:354-381

19.       Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996;93:1043-1065

20.       Mochizuki H, Okahashi S, Ugawa Y et al. Heart rate variability and hypercapnia in Duchenne muscular dystrophy. Intern Med 2008;47:1893-1897

21.       Yotsukura M, Fujii K, Katayama A et al. Nine-year follow-up study of heart rate variability in patients with Duchenne-type progressive muscular dystrophy. Am Heart J 1998;136:289-296

22.       Ammendola E, Russo V, Politano L, Santangelo L, Calabrò R. Is heart rate variability a valid parameter to predict sudden death in patients with Becker’s muscular dystrophy? Heart 2006;92:1686-1687

23.       Della Marca G, Frusciante R, Dittoni S et al. Decreased nocturnal movements in patients with facioscapulohumeral muscular dystrophy. J Clin Sleep Med 2010;6:276-280

24.       Della Marca G, Frusciante R, Dittoni S et al. Sleep disordered breathing in facioscapulohumeral muscular dystrophy. J Neurol Sci 2009;285:54-58

25.       Cacurri S, Piazzo N, Deidda G, Vigneti E, Galluzzi G, Colantoni L, et al. Sequence homology between 4qter and 10qter loci facilitates the instability of subtelomeric KpnI repeat units implicated in facioscapulohumeral muscular dystrophy. Am J Hum Genet 1998;63:181-190

26.       Deidda G, Cacurri S, Piazzo N, Felicetti L. Direct detection of 4q35 rearrangements implicated in facioscapulohumeral muscular dystrophy (FSHD). J Med Genet 1996;33:361-365

27.       Medical Research Council. Aids to examination of the peripheral nervous system. London; Her Majesty’s Stationery Office 1976

28.       Bernardi L, Wdowczyk-Szulc J, Valenti C, Castoldi S, Passino C, Spadacini G, Sleight P. Effects of controlled breathing, mental activity and mental stress with or without verbalization on heart rate variability. J Am Coll Cardiol 2000;35:1462-1469

29.       Kobayashi H. Does paced breathing improve the reproducibility of heart rate variability measurements? J Physiol Anthropol 2009;28:225-230

30.       Niskanen JP, Tarvainen MP, Ranta-Aho PO, Karjalainen PA. Software for advanced HRV analysis. Comput Methods Programs Biomed 2004;76:73-81

31.       Montano N, Ruscone TG, Porta A, Lombardi F, Pagani M, Malliani A. Power spectrum analysis of heart rate variability to assess the changes in sympathovagal balance during graded orthostatic tilt. Circulation 1994;90:1826-1831

32.       Appel ML, Berger RD, Saul JP, Smith JM, Cohen RJ. Beat to beat variability in cardiovascular variables: noise or music? J Am Coll Cardiol 1989;14:1139-1148

33.       Manfrini O, Pizzi C, Trere D, Fontana F, Bugiardini R. Parasympathetic failure and risk of subsequent coronary events in unstable angina and non-ST-segment elevation myocardial infarction. Eur Heart J 2003;24:1560-1566

34.       Sztajzel J, Jung M, Bayes de Luna A. Reproducibility and gender-related differences of heart rate variability during all-day activity in young men and women. Ann Noninvasive Electrocardiol 2008;13:270-277

35.       Sztajzel J, Jung M, Sievert K, Bayes De Luna A. Cardiac autonomic profile in different sports disciplines during all-day activity. J Sports Med Phys Fitness 2008;48: 495-501

36.       Di Leo R, Rodolico C, De Gregorio C et al. Cardiovascular autonomic control in myotonic dystrophy type 1: a correlative study with clinical and genetic data. Neuromuscul Disord 2004;14:136-141

37.       Trevisan CP, Pastorello E, Armani M et al. Facioscapulohumeral muscular dystrophy and occurrence of heart arrhythmia. Eur Neurol 2006;56:1-5