Abstract
Background
Cardiac involvement of the disease is a leading cause of death and disability in Fabry disease characterized by pathological accumulation of globotriaosylceramide (Gb3) and lyso-globotriaosylceramide (lyso-Gb3) in multiple organs. In this study, we sought to investigate the electrocardiographic (ECG) changes in different clinical stages and evaluate the value of these parameters in assessing cardiac involvement.
Methods
62 patients with Fabry disease and 45 healthy controls were recruited in this study. ECG assessment, echocardiographic assessment and cardiac magnetic resonance (CMR) were recorded at rest in the same day. We divided Fabry disease patients into 4 groups according to echocardiographic assessment and CMR: Pre-detectable group, Non-hypertrophic group, Hypertrophic and pre-fibrotic group as well as Hypertrophic and fibrotic group.
Results
Our results showed that Tp-e/QT was significantly decreased and Sokolow-Lyon index was markedly increased following the development of disease. QRS width and Tp-e/QT was associated with the severity of cardiac involvement in Fabry disease.
Conclusions
Our results demonstrated that QRS width and Tp-e/QT were associated with the severity of cardiac involvement in patients with Fabry disease and contributed to define the optimal intervention timepoint and assess the severity of cardiac involvement and response to disease-specific therapies.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12872-026-06279-6.
Keywords: Electrocardiograph, Cardiomyopathy, Echocardiograph, Fabry Disease
Background
Fabry disease is a X-linked lysosomal storage disorder characterized by pathogenic variants in the galactosidase-α (GLA) gene, deficiency α-galactosidase A activity and abnormal accumulation of globotriaosylceramide (Gb3) and globotriaosylsphingosine (lyso-Gb3) [1]. Progressive accumulation of Gb3 and lyso-Gb3 in the cardiac, vascular, renal, neural, ocular, aural or skin tissues leads to activated immune system and increased fibrosis in these organs, culminating in multisystem dysfunction. Nowadays, cardiac involvement is the leading cause of death and disability worldwide. Recent studies showed that except for accumulation of Gb3 and lyso-Gb3 in nearly all cardiac cells, increased myocardial inflammation, microvascular dysfunction as well as myocardial fibrosis contributed to the development of Fabry disease [2, 3]. Despite a wide spectrum of promising therapies currently available, the therapeutic efficacy of these treatments is insufficient to reverse cardiac damage [4–7]. During the last decades, enzyme replacement therapy and chaperone therapy have been approved for Fabry disease-specific treatment and substrate reduction therapy as well as gene therapies are under clinical translation [7]. With recent advance achieved in Fabry disease-specific therapies, studies on defining the progression of Fabry disease and evaluating treatment response are of paramount important in this field. Currently, echocardiographic assessment and cardiovascular magnetic resonance (CMR) are the key tools to assess cardiac involvement of Fabry disease. The typical echocardiographic changes include concentric left ventricular hypertrophy, reduced global longitudinal strain, disproportionate hypertrophy of papillary muscles and thickened right ventricular walls without functional impairment [7, 8]. CMR has been widely applied in differential diagnosis and staging of cardiac involvement in Fabry disease. Low native T1 and late gadolinium enhancement (LGE) are two common features of CMR in Fabry disease [7, 9]. Prior studies showed that a wide spectrum of electrocardiographic (ECG) changes were detected in cardiac Fabry disease patients including short PR interval, reduced P wave duration, increased QRS duration, high QRS voltages, fractionated QRS, altered atrial depolarization and ventricular repolarization, ST-T segment depression and T-wave inversion in the inferolateral and precordial leads [7, 9–11]. Most of these studies focused on early recognition of pre-clinical Fabry disease. [10, 11] There is a paucity of work focusing on ECG changes in different stages of Fabry disease and the correlation of these changes with echocardiographic parameters and CMR parameters. Very little is known about whether there are any typical features of ECG changes in the development of Fabry disease and whether these changes are associated with severity of Fabry disease. In the current study, we sought to investigate the ECG changes to evaluate the progression of Fabry disease.
Methods
Study patients
Sixty-two patients with Fabry disease and 45 healthy controls were included in the current study. All Fabry disease patients were confirmed by genetic detection of GLA mutation with or without reduced α-galactosidase A activity. The inclusion criteria were as follows: (1) Genetic analysis confirmed Fabry disease patients; (2) Fabry disease patients received ECG examination, echocardiographic assessment with or without CMR assessment. The exclusion criteria were as follows: (1) Patients under the age of 18; (2) Patients received Fabry disease-specific therapies; (3) Patients with coronary artery disease or chronic ischemic heart disease; (4) Patients with a history of cardiac surgery or cardiac arrhythmia ablation; (5) Patients with pacemaker implantation. The health controls that without any medical history of cardiovascular disease and free of medical treatment were also received ECG examination and echocardiographic assessment at the same day. The basic characteristics recorded included gender, age, systolic and diastolic blood pressure, body surface area (BSA), GLA variant, activity of α-galactosidase A and serum level of lyso-Gb3.
ECG analysis
Twelve-lead ECG examination was performed at rest with recording at a sweep of 25 mm/s and an amplitude of 1mV/10 mm (GE Healthcare, MAC 2000 Electrocardiograph) and analyzed manually with the aid of calipers for all parameters by two experts (Y.W. and J.K.) blinded to clinical status, echocardiographic assessment and CMR assessment.
Heart Rate (HR), P wave and AV conduction
Heart rate was recorded by calculating 60 divided by the average of R-R interval. Duration of P wave, PR interval and Pe-Q interval were recorded in lead II. Duration of P wave was measured from the beginning of P wave to the end of P wave and PR interval was measured from the beginning of P wave to the beginning of QRS wave. To better describing AV conduction, Pe-Q interval was measured from the end of P wave to the beginning of QRS wave.
QRS complex form
Duration of QRS wave was recorded in lead II and measured from the beginning of QRS complex to the end of QRS complex. The presence of delta wave at the beginning of QRS complex, left bundle block (LBBB), right bundle branch block (RBBB) and fractionated QRS were recorded. Sokolow-Lyon index was employed to detect left ventricular hypertrophy. In brief, Sokolow-Lyon index was calculated by S wave voltage in V1 plus R wave voltage in V5 or V6 (which larger). The left ventricular hypertrophy (LVH) positive criteria were 3.5mV for female and 4.0mV for male.
T wave and ST segment
The presence of negative or biphasic T wave in lead II or lead V5, ST segment depression in lead II or lead V5 or U wave in lead V1-V6 were recorded. The time interval from the peak of T wave to the end of T wave (Tp-e) was recorded in lead II or lead V5 (which T wave was larger). The peak was measured from the nadir of the T wave in case of negative or biphasic T wave. Duration of QT interval was recorded and corrected by heart rate. The ratio of Tp-e and QT interval was also calculated and recorded.
Echocardiographic analysis
Standardized transthoracic echocardiographic assessment was performed using a GE Vivid E95 echocardiographic system (GE Vingmed Ultrasound AS, Horten, Norway) with a 3.5-MHz phased-array transducer and off-line analysis was conducted using the EchoPAC system (GE Healthcare) by two experts (J.-L. F. and H.W.) independently, blinded to clinical status, ECG assessment and CMR. All measurement were conducted in accordance with American Society of Echocardiography and the European Association of Cardiovascular Imaging guidelines [12]. Inter-ventricular septal dimension at end-diastole (IVSd), posterior wall thickness (PWT), left ventricular ejection fraction (LVEF), left ventricular end-diastolic dimension (LVEDD) and left ventricular end-systolic dimension (LVESD) were recorded in the parasternal long-axis and short-axis views. Left ventricular mass was calculated based on the following formula: LV mass = 0.8*1.04*[(IVSd + LVEDD + PWT)3 - LVEDD3] + 0.6 and LV mass index (LVMI) was represented as LV mass divided by BSA (BSA = 0.0057*Height + 0.0121*Weight + 0.0882 for male or BSA = 0.0073*Height + 0.0127*Weight – 0.2106 for female). The LVEF was measured using the biplane method. Additionally, two-dimensional speckle tracking echocardiography (2D-STE) was performed offline with EchoPAC software (GE Healthcare) to evaluate the global longitudinal strain (GLS) of the LV. GLS was derived using a 17-segment model, averaging strain values from the apical four-chamber, two-chamber, and three-chamber views, with an emphasis on peak systolic strain values.
CMR assessment
All participants underwent standard CMR on a 3.0T scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) using an anterior 18-channel phased-array surface coil. The LGE images were visually analyzed for the presence or absence of enhancement by two experts (J. W. and J.-F. Z.) independently, blinded to clinical status, ECG assessment and echocardiographic analysis. Native T1 mapping (3 short-axis images, including basal, mid-ventricular, and apical) were acquired using the shortened modified look-locker inversion recovery sequence (shMOLLI) in 11 cardiac cycles with varying inversion times. Then the images were transferred to a dedicated research software package (CVI42 v5.11.3, Circle Cardiovascular Imaging, Alberta, Canada) to create parametric T1 maps and corresponding values. All the analysis was conducted following the recommendations of the Society for Cardiovascular Magnetic Resonance [13]. In the current study, 55 patients received CMR assessment. Among these patients, LGE images analysis were not performed in eleven patients due to their reluctance or contrast contraindication.
Patients grouping
To analyze the ECG changes in different clinical stages, we divided the Fabry disease patients into 4 groups according to echocardiographic assessment and CMR results. Pre-detectable group: Fabry disease patients with normal native T1 value, normal LVMI and negative LGE; Non-hypertrophic group: Fabry disease patients with low native T1 value, normal LVMI and negative LGE; hypertrophic and pre-fibrotic group: Fabry disease patients with hypertrophic ventricle and negative LGE; Hypertrophic and Fibrotic group: Fabry disease patients with positive LGE. We defined hypertrophic ventricle according to LVMI (male: LVMI > 115; female: LVMI > 95).
Statistical analysis
All data were analyzed by SPSS Statistics (version 27.0, IBM Corporation, Armonk, NY, USA). The results are presented as the mean±standard error of the mean (SEM) (continuous variables and normally distribution), the median and interquartile ranges (continuous variables and abnormally distribution) or frequencies of patients with percentages (discrete variables). Kolmogorov-Smirnov test and visual Q-Q plots assessment were adopted for normal distribution test. Reproducibility analysis of ECG data was adopted using intraclass correlation coefficients. Our results showed interobserver variability of ECG parameters was good (Supplemental Table 1). Parametric continuous variables were evaluated using independent Students’ t-test or Mann-Whitney U test as appropriate. Categorical variables were evaluated using Pearson’s chi-square test or Fisher’s exact test. Bivariate correlation analysis was performed using the Pearson correlation coefficient or Spearman’s rank correlation coefficient. For multiple groups analysis, one-way ANOVA with Tukey post hoc test or Kruskal-Wallis test with Bonferroni post hoc test were adopted as appreciate. A two-sided p < 0.05 was regarded as a significant difference. Linear regression analysis was adopted to assess the correlation between ECG parameters and GLS or LVMI. Demographics (age and gender) and all the ECG parameters were included in the univariate analysis and significant factors in univariable analysis were selected for the following multivariate model and inputted using an “stepwise” method. Receiver-operator characteristics (ROC) was adopted to test the performance of parameters in the final multivariate linear regression model to assess the degree of cardiac involvement. Logistic regression analysis was adopted to assess the correlation between ECG parameters and Low T1 or LGE positive in CMR. Demographics (age and gender) and all the ECG parameters were included in the univariate analysis and significant factors in univariable analysis were selected for the following multivariate model and inputted using an “stepwise” method.
Results
Patient characteristics
In this study, sixty-two Fabry disease patients and forty-five healthy controls were recruited (Table 1). The percentage of female (35% vs. 27%, p > 0.05), age (40.5 years vs. 43 years, p > 0.05), systolic blood pressure (121mmHg vs. 118mmHg, p > 0.05) and diastolic blood pressure (78mmHg vs. 72mmHg, p > 0.05) were similar between Fabry disease and Control groups. For ECG analysis, compared with control group, decreased PR interval, Pe-Q interval and Tp-e/QT as well as increased QRS width, percentage of Delta wave, Sokolow-Lyon index, percentage of fractionated QRS and percentage of U wave were observed in Fabry disease group (all p < 0.05). There was no significant difference regarding heart rate, P wave width, percentage of atrial fibrillation, percentage of LBBB or RBBB and duration of QTc between control and Fabry disease groups. For echocardiographic analysis, compared with control group, increased ventricular wall thickness and LVMI were detected in Fabry disease group (all p < 0.05) and lower GLS was also observed in Fabry disease group (p < 0.05). LVEF, LVEDD and LVESD were similar between these two groups. Moreover, 56.36% patients were observed low native T1 value and 38.64% patients showed positive LGE in Fabry disease group.
Table 1.
The characteristics of patients
| Variable | Control (n = 45) | Fabry Disease (n = 62) | p | |
|---|---|---|---|---|
| Female, n (%) | 27 (60.00%) | 35 (56.45%) | 0.714 | |
| Age (years) | 43 (36.5, 50.5) | 40.5 (33.75, 51.25) | 0.270 | |
| SBP (mmHg) | 118 (108, 128.5) | 121 (113.5, 134.5) | 0.391 | |
| DBP (mmHg) | 72 (68, 82) | 78 (71, 86) | 0.153 | |
| Electrocardiographic Data | ||||
| HR (bpm) | 67 (63, 80.5) | 68 (60.5, 78) (n = 59) | 0.143 | |
| P wave width (msec) | 102.47 ± 1.37 | 99.31 ± 1.74 (n = 59) | 0.155 | |
| PR interval (msec) | 156.16 ± 2.77 | 139.49 ± 3.12 (n = 59) | < 0.001 | |
| Pe-Q interval (msec) | 53.69 ± 2.76 | 40.19 ± 2.04 (n = 59) | < 0.001 | |
| Atrial fibrillation (%) | 0 (0.00%) | 3 (0.05%) | 0.262 | |
| QRS width (without LBBB or RBBB) (msec) | 90 (88, 93) (n = 43) | 92 (86, 106) (n = 58) | 0.020 | |
| Delta wave (%) | 0 (0.00%) | 6 (10.17%) | 0.035 | |
| LBBB (%) | 0 (0.00%) | 1 (0.02%) | 1.000 | |
| RBBB (%) | 2 (0.04%) | 3 (0.05%) | 1.000 | |
| QTc (msec) | 424.33 ± 3.99 | 428.69 ± 4.11 (n = 59) | 0.458 | |
| Tp-e/QT | 0.24 ± 0.01 | 0.19 ± 0.00 | < 0.001 | |
| Sokolow-Lyon index (mV) | 2.00 (1.51, 2.50) | 3.38 (2.65, 4.93) | < 0.001 | |
| fQRS (%) | 8 (17.78%) | 26 (41.94%) | 0.008 | |
| U wave (%) | 0 (0.00%) | 18 (29.03%) | < 0.001 | |
| Echocardiographic Data | ||||
| LVEF (%) | 64.29 ± 0.67 | 64.27 ± 0.62 | 0.987 | |
| IVS (mm) | 9 (8, 9) | 13 (10, 15.5) | < 0.001 | |
| PWT (mm) | 8 (8, 9) | 11 (9, 14) | < 0.001 | |
| LVEDD (mm) | 46 (43, 48) | 45 (43, 49) | 0.957 | |
| LVESD (mm) | 30 (28, 32) | 30 (28, 32) | 0.987 | |
| LVMI | 70.57 (63.36, 76.20) | 109.16 (84.43, 160.80) | < 0.001 | |
| GLS (%) | -22.09 ± 0.34 | -16.75 ± 0.65 | < 0.001 | |
| CMR Data | ||||
| Low T1 (%) | - | 31/55 (56.36%) | - | |
| LGE (%) | - | 17/44 (38.64%) | - | |
Gene mutations and activity of enzyme
All Fabry disease patients under gene mutation analysis, activation of α-galactosidase A test and detection of the level of lyso-Gb3. Patients with pathogenic variant under gene analysis and patients with uncertain variant together with reduced α-galactosidase A activation as well as elevated lyso-Gb3 level were diagnosed as Fabry disease. The mutations and types of variants in Fabry disease patients were listed in Supplemental Fig. 2.
To determine whether the activation of α-galactosidase A and the serum lyso-Gb3 level were associated the severity of cardiac involvement in Fabry disease, the correlation analysis between α-galactosidase A or globotriaosylsphingosine with GLS, LVMI, Low T1 or LGE were performed. Our results showed that the activation of enzyme and accumulation of lyso-Gb3 were only corelated with low native T1 value (Supplemental Table 3). Activation of enzyme and accumulation of lyso-Gb3 have been well documented to be associated with the severity of the Fabry disease. Nonetheless, increased myocardial inflammation and fibrosis as well as microvascular dysfunction were all the key factors to assess the cardiac involvement in Fabry disease. Therefore, we performed this study to better describe the progression of Fabry disease in the heart.
ECG findings in different groups
The echocardiographic, MRI and ECG characteristics in different groups were shown in Fig. 1. To determine the ECG changes in different groups, we summarized the ECG parameters based on different groups in Table 2; Fig. 2. Our results showed that no significant difference on P wave width, Pe-Q interval or QRS width was observed between different groups (Fig. 2A-C). The duration of QTc markedly reduced in the Non-hypertrophic group compared with the Hypertrophic and pre-fibrotic group as well as the Hypertrophic and fibrotic group. There was no significant difference on the duration of QTc between the Control group, the Pre-detectable group, the Hypertrophic group and pre-fibrotic as well as the Hypertrophic and fibrotic group (Fig. 2D). Compared with the control group, Tp-e/QT significant decreased in the Hypertrophic and pre-fibrotic group as well as the Hypertrophic and fibrotic group. There was no significant difference between the Control group, the Pre-detectable group and the Non-hypertrophic group (Fig. 2E). Compared with the Control group, Sokolow-Lyon index significantly increased in the Non-hypertrophic group, the Hypertrophic and pre-fibrotic group as well as the Hypertrophic and fibrotic group (all p < 0.05, Fig. 2F). In addition, Sokolow-Lyon index in the Hypertrophic and pre-fibrotic group was higher than the Pre-detectable group (p < 0.05, Fig. 2F).
Fig. 1.
Clinical stages and electrocardiographic parameters in different clinical groups. Fabry disease patients were divided into 4 groups according to echocardiographic assessment and CMR. Pre-detectable group: normal LVMI, normal T1 and LGE negative; Non-hypertrophic group: low T1, normal LVMI and LGE negative; Hypertrophic and pre-fibrotic group: increased LVMI and LGE negative; Hypertrophic and fibrotic group: increased LVMI and LGE positive. Following the development of Fabry disease, reduced Pe-Q interval, negative or biphasic T waves in anterior and inferior leads, ST segment depression in anterior and inferior leads, increased QRS width, increased Sokolow-Lyon index and decreased Tp-e/QT were observed in patients with Fabry disease
Table 2.
The ECG findings of patients
| Variable | Control (n = 45) | Pre-detectable stage (n = 6) | Non-hypertrophic stage (n = 15) | Hypertrophic and pre-fibrotic stage (n = 6) | Hypertrophic and Fibrotic stage (n = 17) |
|---|---|---|---|---|---|
| P wave width (msec) | 102.47 ± 1.37 | 103.17 ± 6.74 | 99.87 ± 2.93 | 93.50 ± 4.34 | 98.63 ± 3.64 |
| PR interval (msec) | 156.16 ± 2.77 | 149.67 ± 11.71 | 141.20 ± 4.88 | 128.00 ± 10.25 | 138.31 ± 7.08 |
| Pe-Q interval (msec) | 53.69 ± 2.76 | 46.50 ± 6.99 | 41.33 ± 3.70 | 34.50 ± 6.09 | 39.69 ± 4.40 |
| QRS width (msec) | 92 (88, 97) | 91 (84, 96) | 90 (82, 102) | 100 (93, 113) | 104 (86, 120) |
| Delta wave (%) | 0 (0.00%) | 0 (0.00%) | 1 (6.67%) | 2 (33.33%) | 2 (11.76%) |
| LBBB (%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | 1 (5.88%) |
| RBBB (%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | 1 (5.88%) |
| QTc (msec) | 424.33 ± 3.99 | 431.67 ± 6.90 | 402.80 ± 7.38 | 447.50 ± 9.75 | 436.13 ± 8.31 |
| Tp-e/QT | 0.24 ± 0.01 | 0.23 ± 0.02 | 0.21 ± 0.01 | 0.17 ± 0.02 | 0.18 ± 0.00 |
| Sokolow-Lyon index (mV) | 2.00 (1.51. 2.50) | 2.37 (1.85, 2.80) | 3.29 (2.59, 4.11) | 5.94 (4.88, 7.13) | 2.91 (2.75, 5.51) |
| II ST depression (%) | 0 (0.00%) | 1 (16.67%) | 3 (20.00%) | 4 (66.67%) | 9 (52.94%) |
| II negative or biphasic T (%) | 0 (0.00%) | 1 (16.67%) | 1 (6.67%) | 5 (83.33%) | 10 (58.82%) |
| V5 ST depression (%) | 0 (0.00%) | 1 (16.67%) | 2 (13.33%) | 5 (83.33%) | 6 (35.29%) |
| V5 negative or biphasic T (%) | 0 (0.00%) | 1 (16.67%) | 2 (13.33%) | 5 (83.33%) | 11 (64.71%) |
| fQRS (%) | 8 (17.78%) | 1 (16.67%) | 6 (40.00%) | 1 (16.67%) | 8 (47.06%) |
| U wave (%) | 0 (0.00%) | 0 (0.00%) | 1 (6.67%) | 5 (83.33%) | 5 (29.41%) |
Fig. 2.
Electrocardiographic changes in the development of Fabry disease. There was no significant difference on P wave width, Pe-Q interval and QRS width between different groups (A-C). Compared with Hypertrophic and pre-fibrotic group as well as Hypertrophic and fibrotic group, a decreased QTc duration was observed in Non-hypertrophic stage (D). Compared with control group, a decreased Tp-e/QT was observed in Hypertrophic and pre-fibrotic group as well as Hypertrophic and fibrotic group (E). Compared with control group, Sokolow-Lyon index was significantly increased in Non-hypertrophic group, Hypertrophic and pre-fibrotic group as well as Hypertrophic and fibrotic group (F). Moreover, Sokolow-Lyon index was higher in Hypertrophic and pre-fibrotic group than that in Pre-detectable group (F)
Determinants of cardiac involvement
Echocardiographic parameters including GLS and LVMI as well as CMR parameters including low native T1 value and LGE are widely used to evaluate cardiac involvement and disease progression. To determine which ECG change was associated with cardiac involvement and disease progression of Fabry disease, bivariate correlation analysis, univariate and multivariate analysis were performed between ECG parameters and GLS, LVMI, low native T1 value or LGE.
Our results showed that gender, age, Tp-e/QT, QRS width, ST segment depression or negative or biphasic T wave in lead II or lead V5, Sokolow-Lyon index and U wave were significantly associated with GLS in the correlation coefficient analysis and univariate model (Table 3). Nonetheless, in multivariate model, gender, age, Tp-e/QT, QRS width and Sokolow-Lyon index were significantly related to GLS (Table 3). The final multivariate model was showed in Fig. 3A and Supplemental Table 4. Moreover, our results demonstrated that gender, age, Tp-e/QT, QRS width, ST segment depression or negative or biphasic T wave in lead II or lead V5, Sokolow-Lyon index and U wave were also significantly associated with LVMI in the correlation coefficient analysis and univariate model (Table 4). Nevertheless, in multivariate analysis, gender, Tp-e/QT, QRS width were associated with LVMI (Table 4). The final multivariate model was showed in Fig. 3B and Supplemental Table 4. To assess the robustness of these changes, the significant factors in multivariate models were computed in ROC curve analysis. A ROC curve of Tp-e/QT had the best discriminative ability in both ROC curve analysis of GLS and ROC curve analysis of LVMI with area under the curve (AUC) 0.83 and 0.82 respectively (Fig. 3C-D).
Table 3.
Predictors for GLS
| Variable | Correlation Coefficient analysis | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|---|
| R | P | B | P | B | P | |
| Gender (Female) | -0.294 | 0.021 | -2.923 | 0.025 | -2.609 | 0.003 |
| age | 0.479 | < 0.001 | 0.220 | < 0.001 | 0.107 | 0.014 |
| P wave width | -0.049 | 0.712 | -0.018 | 0.712 | ||
| Pe-Q interval | -0.155 | 0.242 | -0.048 | 0.242 | ||
| Tp-e/QT | -0.574 | < 0.001 | -85.408 | < 0.001 | -35.818 | 0.011 |
| QRS width | 0.582 | < 0.001 | 0.186 | < 0.001 | 0.109 | < 0.001 |
| II ST depression | 0.479 | < 0.001 | 4.701 | < 0.001 | ||
| II negative or biphasic T | 0.517 | < 0.001 | 5.108 | < 0.001 | ||
| fQRS | 0.188 | 0.143 | 1.649 | 0.215 | ||
| Sokolow-Lyon index | 0.495 | < 0.001 | 1.447 | < 0.001 | 0.710 | 0.006 |
| V5 ST depression | 0.453 | < 0.001 | 4.655 | < 0.001 | ||
| V5 negative or biphasic T | 0.569 | < 0.001 | 5.732 | < 0.001 | ||
| U wave | 0.384 | 0.002 | 4.564 | 0.001 | ||
Fig. 3.
Tp-e/QT and QRS width were associated with the severity of cardiac involvement. Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS. Linear regression analysis showed that GLS = 26.49–2.61*Gender + 0.11*age-35.82*Tp-e/QT-0.11*QRS width + 0.71*Sokolow-Lyon index (A). Tp-e/QT and QRS width were associated with LVMI. Linear regression analysis showed that LVMI = 27.94–36.64*Gender-559.65*Tp-e/QT + 2.34*QRS width (B). ROC curve analysis showed that the area under curve (AUC) of GLS were listed below: Tp-e/QT 0.83; Sokolow-Lyon index 0.81; QRS width 0.79 (C). ROC curve analysis showed that the AUC of LVMI were listed below: Tp-e/QT 0.82; QRS width 0.78 (D)
Table 4.
Predictors for LVMI
| Variable | Correlation Coefficient analysis | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|---|
| R | P | B | P | B | P | |
| Gender (Female) | -0.299 | 0.018 | -42.704 | 0.014 | -36.644 | 0.002 |
| age | 0.561 | < 0.001 | 2.694 | < 0.001 | ||
| P wave width | -0.009 | 0.943 | -0.564 | 0.407 | ||
| Pe-Q interval | -0.161 | 0.224 | -0.852 | 0.138 | ||
| Tp-e/QT | -0.581 | < 0.001 | -977.959 | < 0.001 | -559.648 | 0.002 |
| QRS width | 0.570 | < 0.001 | 2.769 | < 0.001 | 2.343 | < 0.001 |
| II ST depression | 0.468 | < 0.001 | 49.402 | < 0.001 | ||
| II negative or biphasic T | 0.519 | < 0.001 | 56.855 | < 0.001 | ||
| fQRS | 0.208 | 0.104 | 33.453 | 0.058 | ||
| Sokolow-Lyon index | 0.429 | < 0.001 | 13.558 | 0.006 | ||
| V5 ST depression | 0.440 | < 0.001 | 43.972 | 0.012 | ||
| V5 negative or biphasic T | 0.585 | < 0.001 | 65.393 | < 0.001 | ||
| U wave | 0.367 | 0.003 | 45.761 | 0.016 | ||
Next, in correlation coefficient analysis, gender and Sokolow-Lyon index were associated with low native T1 value (Table 5). Nonetheless, no ECG parameter was significantly related to low native T1 value (Table 5). Age, Tp-e/QT, negative and biphasic T wave in lead II or lead V5 were associated with LGE positive in correlation coefficient analysis (Table 6). Age, Tp-e/QT, QRS width, negative and biphasic T wave in lead II or lead V5 were associated with LGE positive in univariate analysis (Table 6). Nevertheless, none of ECG parameters was significantly related to LGE positive in multivariate analysis (Table 6).
Table 5.
Predictors for Low T1
| Variable | Correlation Coefficient analysis | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|---|
| R | P | Exp(B)(95%CI) | P | Exp(B)(95%CI) | P | |
| Gender (Female) | -0.405 | 0.002 | 0.166 (0.049–0.564) | 0.004 | 6.017 (1.773–20.416) | 0.004 |
| age | -0.086 | 0.535 | 0.985 (0.941–1.031) | 0.512 | ||
| P wave width | 0.041 | 0.771 | 1.002 (0.961–1.044) | 0.926 | ||
| Pe-Q interval | -0.025 | 0.863 | 0.998 (0.963–1.034) | 0.900 | ||
| Tp-e/QT | 0.136 | 0.321 | 1307.154 (0.000-7.805*109) | 0.367 | ||
| QRS width | -0.064 | 0.644 | 0.986 (0.954–1.018) | 0.390 | ||
| II ST depression | -0.030 | 0.828 | 0.884 (0.298–2.621) | 0.824 | ||
| II negative or biphasic T | -0.146 | 0.288 | 0.550 (0.185–1.631) | 0.281 | ||
| fQRS | 0.012 | 0.929 | 1.053 (0.351–3.155) | 0.927 | ||
| Sokolow-Lyon index | 0.281 | 0.038 | 1.321 (0.938–1.860) | 0.111 | ||
| V5 ST depression | 0.012 | 0.929 | 1.053 (0.351–3.155) | 0.927 | ||
| V5 negative or biphasic T | -0.121 | 0.377 | 0.611 (0.209–1.789) | 0.369 | ||
| U wave | -0.001 | 0.992 | 0.994 (0.307–3.211) | 0.991 | ||
Table 6.
Predictors for LGE
| Variable | Correlation Coefficient analysis | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|---|
| R | P | Exp(B)(95%CI) | P | Exp(B)(95%CI) | P | |
| Gender (Female) | 0.091 | 0.559 | 0.682 (0.195–2.383) | 0.549 | ||
| age | 0.495 | < 0.001 | 1.106 (1.034–1.184) | 0.003 | 1.106 (1.034–1.184) | 0.003 |
| P wave width | 0.021 | 0.892 | 0.997 (0.950–1.045) | 0.891 | ||
| Pe-Q interval | 0.004 | 0.980 | 0.995 (0.956–1.035) | 0.796 | ||
| Tp-e/QT | -0.340 | 0.024 | 0.000 (0.000-0.513) | 0.043 | ||
| QRS width | 0.247 | 0.106 | 1.041 (1.000 -1.084) | 0.048 | ||
| II ST depression | 0.233 | 0.128 | 2.672 (0.757–9.426) | 0.127 | ||
| II negative or biphasic T | 0.329 | 0.029 | 4.082 (1.119–14.883) | 0.033 | ||
| fQRS | 0.176 | 0.252 | 2.111 (0.598–7.448) | 0.245 | ||
| Sokolow-Lyon index | 0.055 | 0.722 | 1.100 (0.781–1.548) | 0.585 | ||
| V5 ST depression | 0.059 | 0.703 | 1.295 (0.356–4.720) | 0.695 | ||
| V5 negative or biphasic T | 0.345 | 0.022 | 4.354 (1.195–15.865) | 0.026 | ||
| U wave | 0.081 | 0.602 | 1.458 (0.366–5.812) | 0.593 | ||
In addition, we performed comparison between patients’ presence or absence of impaired GLS, increased LVMI, low T1 or LGE. Compared with patients with normal GLS, decreased Tp-e/QT and increased Sokolow-Lyon index were observed in patients with impaired GLS. Moreover, increased ST depression and negative, biphasic T wave or U wave in lead II or lead V5 were noted in patients with impaired GLS (Supplemental Table 5). Compared with patients with normal LVMI, decreased Tp-e/QT, increased Sokolow-Lyon index and QTc interval were observed in patients with increased LVMI. Moreover, increased ST depression and negative, biphasic T wave or U wave in lead II or lead V5 were noted in patients with increased LVMI (Supplemental Table 6). Compared with patients with normal T1, decreased QTc interval was observed in patients with low T1 (Supplemental Table 7). Compared with patients without LGE, decreased Tp-e/QT were observed in patients with LGE. Moreover, biphasic T wave in lead V5 were noted in patients with LGE (Supplemental Table 8). Nonetheless, no significant difference in ECG was observed between patients with circumferential hypertrophy and patients with non-circumferential hypertrophy (Supplemental Table 9).
Taken together, our results demonstrated that Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS and Tp-e/QT and QRS width were associated with LVMI. Moreover, Tp-e/QT had the best ability to discriminate patients with impaired GLS or increased LVMI from normal controls.
Discussions
Main findings
In this study, we summarized the ECG changes in different clinical groups of Fabry disease. Our results demonstrated that compared with Control group, decreased PR interval, Pe-Q interval and Tp-e/QT as well as increased QRS width, delta wave, Sokolow-Lyon index, fractionated QRS wave and U wave were observed in Fabry disease group. Following the progression of cardiac involvement, Tp-e/QT progressively decreased whereas Sokolow-Lyon index gradually increased from Pre-detectable stage to Hypertrophic and pre-fibrotic stage and tended to reduce in Hypertrophic and fibrotic stage. In addition, our results provide the proof-of-principle evidence the Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS and LVMI. Tp-e/QT had the best discrimination ability in cardiac involvement.
Clinical stage
In this study, we divided cardiac involvement of Fabry disease into four groups: Pre-detectable group, Non-hypertrophic group, Hypertrophic and pre-fibrotic group as well as Hypertrophic and fibrotic group. Previous study defined cardiac involvement into four stages, including non-hypertrophic, hypertrophic-pre-fibrotic, hypertrophic-fibrotic and overt dysfunction stages [14]. Nevertheless, recent studies showed that earlier detection of Fabry disease and earlier beginning of Fabry disease-specific therapies could benefit the progression of cardiac involvement of Fabry disease. Therefore, we included a pre-detectable group in our study. As few Fabry disease patients with severe systolic dysfunction or diastolic dysfunction in our study, we did not include an overt dysfunction group in current study. Recent studies showed that lysosomal storage was insufficient to represent the severity of cardiac involvement as cardiac inflammation and fibrosis were all contributed to cardiac involvement of Fabry disease [7, 11, 14]. Therefore, we did not include lysosomal storage and activity of enzyme in staging of Fabry disease. In this study, we divided cardiac involvement of Fabry disease mainly according to the results of echocardiographic assessment and CMR.
Previous study showed that RBBB, Sokolow-Lyon index and repolarization abnormalities were associated with ventricular hypertrophy [15]. Nonetheless, our result showed that repolarization abnormalities and QRS width were associated with ventricular hypertrophy. Ventricular fibrosis in patients with Fabry disease might lead to a decrease in Sokolow-Lyon index. Previous study demonstrated that Sokolow-Lyon index, ratio between P-wave and PR-segment duration, QRS width and QRS duration were predictors of low T1 value [16]. In our study, there was no ECG parameter associate with low T1 value. The T1 values of some Fabry disease patients with increased LVMI, decreased GLS and LGE positive were normal. Increased myocardial inflammation and fibrosis might influence the T1 value. Therefore, in this study, we sought to investigate whether any ECG changes could be detected prior to appearance of echocardiographic and CMR changes. Fortunately, there was no significant difference on ECG parameters between Control and Pre-detected stage in current study. Prior study showed decreased P wave duration and Pe-Q interval in pre-hypertrophic Fabry disease patient with normal T1 compared with control [9]. Nonetheless, in our study, the duration of P wave was similar between Control and Pre-detectable stage. Although a decreasing tendency of Pe-Q interval was observed in Pre-detectable stage compared with control group, no statistic difference was detected. Augusto JB, et al. included Fabry disease patients with or without Fabry disease-specific therapies in their study and only two groups including pre-hypertrophy with normal native T1 and pre-hypertrophy with low T1 groups were included in their study [9]. Nevertheless, only Fabry disease patients without any Fabry disease-specific therapies was recruited in our studies and both pre-hypertrophic as well as hypertrophic and fibrotic patents was included in current study. Whether any ECG changes could be detected prior to echocardiographic and CMR detections remains unclear. Future studies can be launched to explore different ECG changes in different clinical staging.
The ECG parameters related with cardiac involvement of Fabry disease
Cardiac involvement of Fabry disease starts prior to the appearance of clinical symptoms. Previous studies demonstrated that LVMI, GLS, native T1 value and LGE were associated with the progression of cardiac involvement [7]. Interestingly, we performed correlation coefficient analysis between the activity of α-galactosidase A and the serum level of Gb3 with GLS, LVMI, Low T1 and LGE. Only low native T1 value was associated with decreased activity of α-galactosidase A and increased serum level of Gb3. Accumulation of Gb3, microvascular dysfunction, myocardial inflammation and cardiac fibrosis are all involved in the progression of cardiac involvement of Fabry disease [7]. That accounts for why Fabry disease-specific therapies targeting on the activity of enzyme has limited effect on cardiac involvement and why only echocardiographic assessment or CMR is insufficient to define cardiac involvement of Fabry disease. Therefore, studies on ECG parameters in Fabry disease is of parameter important to define the progression of cardiac changes and evaluate cardiac response to Fabry disease-specific therapies.
Prior studies demonstrated that short Pe-Q interval, high QRS voltages and pathological repolarization contributed to the diagnosis of Fabry disease [7, 10]. Consistent with previous studies, reduced Pe-Q interval and Tp-e/QT as well as increased QRS width and Sokolow-Lyon index were detected in Fabry disease patients in our study. Moreover, increased presence of delta wave, fractionated QRS wave and U wave were also observed in patients with Fabry disease. To better describe the progression of cardiac involvement in Fabry disease, we sought to investigate which ECG parameters were relevant to cardiac involvement of Fabry disease. Correlation coeffective analysis was performed between parameters mentioned above and ECG changes. Our results showed that Tp-e/QT, Sokolow-Lyon index and QRS width were associated with GLS whereas Tp-e/QT and QRS width were associated with LVMI. The area under curve (AUC) showed that Tp-e/QT was the best ECG parameters to predict impaired GLS and increased LVMI. As the CMR parameters in different cardiovascular center is different, we define low native T1 value and LGE positive according to the recommendation commercially available. Unfortunately, our results demonstrated that there was no significant difference between ECG parameters and CMR parameters.
Prior studies demonstrated that progressive accumulation of Gb3 and lyso-Gb3 in AV node resulted in accelerated AV conduction and reduced Pe-Q interval [11, 17]. As cardiac involvement progressed, increased cardiac inflammation and fibrosis decreased AV conduction, culminating in normal Pe-Q interval even AV blockage [11]. That is why short Pe-Q interval was observed in Fabry disease patients, whereas no significant relationship was detected between the severity of cardiac involvement and Pe-Q interval. Recent studies discussed the value of echocardiographic assessment and CMR in evaluation of cardiac damage of Fabry disease [18, 19]. Our study demonstrated that Tp-e/QT and QRS width were of value in assessing cardiac damage and cardiac involvement in Fabry disease.
Limitations
First of all, this is a single center cross-sectional study. How ECG parameters changed during the development of Fabry disease was hypothesized rather than detected. Longitudinal studies would be helpful to confirm the ECG changes. Moreover, the small sample size in the Pre-detectable stage and Hypertrophic and pre-fibrotic stage limited the robustness of subgroup analysis. Secondly, Fabry disease patients without disease-specific therapies were recruited in our study. It remains unclear how disease-specific therapies influence the ECG changes. Thirdly, native T2 value of CMR were not included in this study. Previous studies showed that native T2 value was associated with cardiac inflammation [20, 21]. Further model could include native T1/T2 value, LGE, LVMI, GLS as well as ECG parameters, such as QRS width and Tp-e/QT to predict cardiac involvement and damage in patients with Fabry disease. Fourthly, our study showed that no significant difference on regular ECG assessment was observed between Pre-detectable stage and Non-hypertrophic stages. Holter examination which includes more ECG information would be benefit to detect subtle ECG changes in Pre-detectable stage and might be helpful in early diagnosis of Fabry disease. Fifthly, in this study, we did not perform the comparison between Fabry disease and other cardiomyopathies.
Conclusion
This study summarized ECG changes in different stages of cardiac involvement of Fabry disease patients. QRS width and Tp-e/QT were associated with the severity of cardiac involvement in patients with Fabry disease. Future studies can be launched to investigate the value of these ECG parameters in defining the optimal intervention timepoint and assessing the severity of cardiac involvement and response to disease-specific therapies.
Supplementary Information
Acknowledgements
No.
Abbreviations
- AUC
Area under curve
- BSA
Body surface area
- CMR
Cardiovascular magnetic resonance
- ECG
Electrocardiographic
- Gb3
Globotriaosylceramide
- GLA
Galactosidase-α
- GLS
Global longitudinal strain
- HR
Heart rate
- IVSd
Inter-ventricular septal dimension
- LBBB
Left bundle branch block
- LGE
Late gadolinium enhancement
- LV
Left ventricle
- LVEDD
Left ventricular end-diastolic dimension
- LVEF
Left ventricular ejection fraction
- LVH
Left ventricular hypertrophy
- LVMI
Left ventricular mass index
- LVESD
Left ventricular end-systolic dimension
- Lyso-Gb3
Globotriaosylsphingosine
- PWT
Posterior wall thickness
- RBBB
Right bundle branch block
- ROC
Receiver-operator characteristics
- SEM
Standard error of the mean
- Tp-e
The peak of T wave to the end of T wave
- 2D-STE
Two-dimensional speckle tracking echocardiography
Authors’ contributions
Y.W. and J.K. performed ECG data collection and analysis. J.W. and J.F.Z. performed CMR recording and anaylsis. R.Z. and S.J.S. checked the ECG data. H.W. and C.S.M. performed echocardiographic data collection. B.Y.Z. and J.L.F. performed echocardiographic data analysis. C.Z., T.B.J., J.L.F. and S.J.S. designed study. Y.W., J.K. wrote the manuscript. J.K. and J.W performed the figures and tables. S.J.S and J.L.F. revised the manuscript, figures and tables.
Funding
This research was supported by the Suzhou Municipal Pilot Project for Basic Research (SSD2025054), the National Natural Science Foundation of China (82200283), the Scientific Research Project of Gusu Health Talents Program of Suzhou (GSWS2022017), the Innovation and Entrepreneurship Team in Jiangsu Province (JSSCT202353), the Multi-center Clinical Research Project for Major Diseases in Suzhou (DZXYJ202302). The funder had no roles in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data availability
All the data are available from the corresponding authors (Dr. S.-J. S.) upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (2024 − 468). Patients were recruited in our cardiovascular center from January 2021 to June 2024 and Written informed consent was obtained from all patients. All experiments were performed in accordance with the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Yu Wang, Jie Kong and Jun Wang contributed equally to this work.
Contributor Information
Jia-Li Fan, Email: Fanjiali3@163.com.
Si-Jia Sun, Email: u3005150@connect.hku.hk.
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Associated Data
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Supplementary Materials
Data Availability Statement
All the data are available from the corresponding authors (Dr. S.-J. S.) upon reasonable request.