Impact of Metabolic Dysfunction-Associated Fatty Liver Disease on Atrial Fibrillation Recurrence After Ablation　― A Retrospective Study in Japanese Patients ―

Abstract

Background: Metabolic derangements are associated with incident and recurrent atrial fibrillation (AF), in addition to the development of metabolic dysfunction-associated fatty liver disease (MAFLD). A recent study reported MAFLD was associated with significantly increased arrhythmia recurrence rates following AF ablation in Western patients. However, in Asian patients with a higher prevalence of non-obese MAFLD, it is not clear whether MAFLD affects recurrence after AF ablation regardless of obesity. This study investigated the impact of MAFLD on AF recurrence in Japanese patients.

Methods and Results: We enrolled 872 patients who underwent AF ablation and assessed the relationship between MAFLD and AF recurrence. The prevalence of MAFLD was significantly higher in the group with than without AF recurrence. Although the liver/spleen ratio was significantly lower among patients with than without AF recurrence, the liver fibrosis score did not differ significantly between the 2 groups. Multivariate Cox proportional hazards regression analysis identified MAFLD, but not body mass index, as a factor independently associated with AF recurrence (adjusted hazard ratio 2.62; 95% confidence interval 1.44–4.80; P=0.002). We found a significant interaction between MAFLD and homeostasis model assessment of insulin resistance (HOMA-IR; P for interaction=0.034).

Conclusions: MAFLD is an independent risk factor for recurrence after AF ablation in Japanese patients regardless of obesity, and its effects are likely heterogeneous, with a greater impact in the presence of insulin resistance.

Atrial fibrillation (AF) is the most common arrhythmia worldwide.¹ Numerous factors, including age, genetic predisposition, body mass index (BMI), hypertension, diabetes, obstructive sleep apnea, heart failure, myocardial infarction, and smoking, have been proposed to contribute to the marked increase in the prevalence of AF.^2,3 Evidence accumulated to date shows that targeting these risk factors contributes to a reduction in the AF burden and AF recurrence after ablation.^4,5 International guidelines strongly endorse risk factor modification as a key component of AF management, alongside anticoagulation, rate control, and rhythm control strategies.^6,7 Nevertheless, AF recurrence after ablation cannot be fully explained by these well-established risk factors, and it is necessary to identify residual unrecognized risk factors.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most prevalent metabolic liver disease worldwide, with the increase in prevalence thought to be due to increased rates of obesity and diabetes.⁸ MAFLD has been reported as an independent risk factor for incident AF.⁹ A recent study reported that MAFLD was associated with significantly increased arrhythmia recurrence rates after AF ablation in Western patients.¹⁰ However, the mean BMI of the study subjects was approximately 33 kg/m², and it is well known that obesity is closely correlated with incident AF.² Among Asian populations, the prevalence of non-obese MAFLD is higher,¹¹ and it is not clear whether MAFLD affects recurrence after AF ablation in Asian patients regardless of obesity.

The aim of this retrospective and observational study was to investigate the impact of MAFLD on AF recurrence after radiofrequency ablation or cryoablation in Japanese patients.

Methods

Study Population and Design

We enrolled 872 consecutive patients with paroxysmal or persistent AF who underwent first-time single-catheter ablation at Tottori University Hospital between March 2013 and December 2021, and retrospectively assessed the relationship between MAFLD and AF recurrence (Figure 1). The diagnosis of MAFLD was based on computed tomography (CT) or ultrasonography according to previous studies.^12,13 Sonographic features of MAFLD include increased echogenicity in the liver relative to that in the renal cortex, hepatomegaly, and intrahepatic vascular blurring. CT parameters to evaluate fatty liver include: (1) the absolute attenuation value (Hounsfield units); (2) the difference in attenuation values between the liver and spleen; and (3) the liver to spleen (L/S) attenuation values ratio. To exclude cases of secondary hepatic fat accumulation, patients with daily alcohol consumption >30 g/day in men and 20 g/day in women, as well as other secondary causes of liver disease, including chronic viral hepatitis, autoimmune hepatitis, and primary biliary cholangitis, were excluded from the study.

Figure 1.

Study flowchart.

Study Protocol

All patients underwent pulmonary vein isolation via radiofrequency ablation or cryoablation, with a bidirectional conduction block line created at the cavotricuspid isthmus. The ablation procedure details have been described in our previous report.¹⁴ Patients were followed up at 1, 3, 6, 12, and 24 months after the ablation procedure, which included physical examinations and 12-lead electrocardiograms (ECGs). Patients were instructed to self-monitor their pulse daily and to immediately report any pulse irregularity, which was followed by event monitoring or Holter monitoring. Furthermore, AF recurrence was assessed using implantable loop recorders or pacemakers/defibrillators, when available. Any documented AF lasting >30 s detected using a 12-lead ECG or other appropriate test was considered to be recurrence.

All patients underwent abdominal CT scanning and the L/S ratio (attenuation values) was calculated. Blood samples were collected at the time of admission for catheter ablation.

Three non-invasive liver fibrosis scores were calculated for each participant based on the parameters collected before ablation. Liver fibrosis was evaluated by calculating the Fibrosis-4 (FIB-4) index, Non-Alcoholic Fatty Liver Disease Fibrosis Score (NFS), and the Aspartate Aminotransferase to Platelet Ratio Index (APRI), as follows:¹⁵

  

$$\text{FIB-4}\text{=}\text{(AST}\text{×}\text{age) / (platelet count}{\text{[×10}}^{\text{9}}\text{/L]}\text{×}\sqrt{\text{ALT}}\text{)}$$

where AST is aspartate transaminase (U/L), ALT is alanine aminotransferase (U/L), and age is given in years. Patients were categorized into low-, intermediate-, and high-risk categories using FIB-4 cut-off values of 1.30 and 2.67, respectively.

  

$$\begin{array}{l}\text{NFS}\text{=}\text{0}\text{.094}\text{×}\text{BMI}\text{+}\text{0}\text{.037}\text{×}\text{age}\text{+}\text{0}\text{.99}\text{×}\text{(AST / ALT)}\\ \text{+}\text{1}\text{.13}\text{×}\text{hyperglycemia}\text{/}\text{diabetes (yes=1, no=0)}-\text{0}\text{.66}\\ \text{×}\text{albumin (g/dL)}-\text{0}\text{.013}\text{×}{\text{platelet count (×10}}^{\text{9}}\text{/L)}-\text{1}\text{.675}\end{array}$$

where hyperglycemia/diabetes was dichotomized as yes (=1) or no (=0), and albumin is given in g/dL. Two cut-off values were used, namely −1.455 and 0.676, to discriminate between low-, intermediate-, and high-risk categories. Advanced liver fibrosis was defined as an NFS >0.676.

  

$$\begin{array}{l}\text{APRI}\text{=}\text{100}\text{×}\text{(AST level}\text{/}\text{upper limit of normal)}\text{/}\text{platelet}\\ {\text{count (×10}}^{\text{9}}\text{/L)}\end{array}$$

Because no clear definitions for risk classification using the APRI have been established, patients were divided into 3 groups with an equal number of patients in each group. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the formula (fasting glucose × fasting insulin) / 405, with a value of ≥2.5 defined as insulin resistant.¹⁶

The study protocol was approved by the Institutional Review Board of Tottori University Hospital (Reference no. 18A034), and written informed consent was obtained from each patient for the use of their data in this retrospective study. This investigation conformed to the principles outlined in the Declaration of Helsinki.

Statistical Analysis

Categorical data are presented as frequencies (%) and were compared using Fisher’s exact test. Continuous data with a skewed distribution are presented as the median with interquartile range (IQR), and were compared using the non-parametric Mann-Whitney U test.

Freedom from AF was reported as crude event rates and by means of a time-to-event analysis using the Kaplan-Meier method. Variables with P<0.10 in the group comparison were further evaluated by Cox proportional hazards regression analyses to determine their associations with AF recurrence. Variables with P<0.10 in the univariate analysis were further evaluated by multivariate Cox proportional hazards regression analysis using a forced entry model and backward stepwise selection method. Hazard ratios (HRs) are presented with 95% confidence intervals (CIs). A trend analysis was performed using the Cochran-Armitage test. All statistical analyses were performed using R version 3.4.0 (R Foundation for Statistical Computing, Vienna, Austria), and P<0.05 (two-tailed) was considered statistically significant.

Results

Of the 818 patients with AF (median age 67 years; 65.2% with paroxysmal AF, 34.8% with persistent AF; all first session) included in the study, 154 (18.8%) were diagnosed with MAFLD based on hepatic steatosis detected using previously established criteria.¹² All ablation procedures were successful. The median length of follow-up for censored cases was 730 days. Characteristics of patients with and without MAFLD are presented in Table 1. MAFLD patients were significantly younger, had a higher BMI, and a higher prevalence of diabetes. AST and ALT were significantly higher and the L/S ratio was lower in patients with MAFLD.

Table 1.

Characteristics of All Patients and Those With and Without MAFLD Separately

	All patients (n=818)	MAFLD (n=154)	No MAFLD (n=664)	P value
Age (years)	67 [60, 72]	63 [57, 68]	68 [61, 73]	<0.001
Female sex	240 (29.3)	46 (29.9)	194 (29.2)	0.922
BMI (kg/m2)	23 [22, 26]	26 [24, 28]	23 [21, 25]	<0.001
CHA2DS2-VASc score	2 [1, 3]	2 [1, 3]	2 [1, 3]	0.068
Heart failure	267 (32.6)	43 (27.9)	224 (33.7)	0.182
Hypertension	442 (54.0)	92 (59.7)	350 (52.7)	0.127
Diabetes	168 (20.5)	54 (35.1)	114 (17.2)	<0.001
Obstructive sleep apnea	11 (1.3)	3 (1.9)	8 (1.2)	0.443
Stroke or TIA	53 (6.5)	9 (5.8)	44 (6.6)	0.856
Paroxysmal AF	533 (65.2)	95 (61.7)	438 (66.0)	0.348
BNP (pg/mL)	90 [40, 176]	79 [33, 157]	93 [41, 186]	0.057
Creatinine (mg/dL)	0.80 [0.67, 0.92]	0.80 [0.66, 0.91]	0.79 [0.67, 0.92]	0.73
HbA1c (%)	5.8 [5.6, 6.2]	6.0 [5.7, 6.5]	5.8 [5.6, 6.1]	<0.001
HOMA-IR (n=239)	1.37 [0.82, 2.35]	1.83 [1.20, 2.99]	1.28 [0.76, 2.02]	0.001
ALT (U/L)	21 [16, 29]	27 [20, 36]	20 [15, 27]	<0.001
AST (U/L)	23 [19, 28]	24 [20, 30]	22 [19, 27]	0.004
LDL (mg/dL)	117 [98, 137]	118 [97, 141]	116 [98, 136]	0.722
Platelets (×104/L)	21 [18, 25]	22 [19, 25]	21 [18, 25]	0.043
Albumin (g/dL)	4.3 [4.1, 4.5]	4.4 [4.2, 4.6]	4.3 [4.1, 4.5]	<0.001
CRP (mg/dL)	0.05 [0.03, 0.10]	0.07 [0.04, 0.12]	0.05 [0.03, 0.09]	<0.001
Liver/spleen ratio (attenuation)	1.27 [1.16, 1.39]	0.99 [0.91, 1.18]	1.29 [1.21, 1.41]	<0.001
APRI	0.36 [0.27, 0.48]	0.36 [0.29, 0.51]	0.35 [0.27, 0.48]	0.292
FIB-4	1.51 [1.35, 2.10]	1.33 [1.05, 1.68]	1.59 [1.16, 2.13]	<0.001
NFS	−1.31 [−2.13, −0.56]	−1.40 [−2.19, −0.60]	−1.29 [−2.08, −0.56]	0.369
LAVI (mL/m2)	39 [31, 50]	37 [31, 49]	39 [30, 51]	0.468
LVEF (%)	63 [57, 68]	63 [57, 69]	63 [57, 67]	0.136
ACEi/ARB	327 (40.0)	70 (45.5)	257 (38.7)	0.144
β-blockers	328 (40.1)	69 (44.8)	259 (39.0)	0.202
Statin	207 (25.3)	43 (27.9)	164 (24.7)	0.412
Anti-arrhythmic drugs	286 (35.0)	46 (29.9)	240 (36.1)	0.16
Radiofrequency ablation	366 (44.7)	65 (42.2)	301 (45.3)	0.529

Unless indicated otherwise, data are given as the median [interquartile range] or n (%). ACEi, angiotensin-converting enzyme inhibitor; AF, atrial fibrillation; ALT, alanine aminotransferase; APRI, Aspartate Aminotransferase to Platelet Ratio Index; ARB, angiotensin receptor blocker; AST, aspartate transaminase; BNP, B-type natriuretic peptide; BMI, body mass index; CRP, C-reactive protein; FIB-4, Fibrosis-4 Index; HOMA-IR, homeostasis model assessment of insulin resistance; LAVI, left atrial volume index; LDL, low-density lipoprotein; LVEF, left ventricular ejection fraction; MAFLD, metabolic dysfunction-associated fatty liver disease; NFS, Non-alcoholic Fatty Liver Disease Fibrosis Score; TIA, transient ischemic attack.

The prevalence of MAFLD was significantly higher in the group with than without AF recurrence (Table 2). The median BMI was significantly higher in among those with than without AF recurrence (24.0 [IQR 21.6–26.2] vs. 23.2 [IQR 21.5–25.6] kg/m², respectively; P=0.037). There was no significant difference in the prevalence of diabetes between the 2 groups, but there was a trend towards higher HOMA-IR in the group with AF recurrence. Although the L/S ratio was significantly lower among those with AF recurrence, liver fibrosis scores were not significantly different between the 2 groups. There were significant differences in the type of AF (paroxysmal vs. persistent), left atrial volume index (LAVI), C-reactive protein, and B-type natriuretic peptide (BNP) between patients with and without AF recurrence. Moreover, a higher proportion of patients were treated with radiofrequency ablation in the group with than without AF recurrence (P<0.05). In the study cohort as a whole, AF recurrence was not related to the degrees of liver fibrosis as determined by the NFS (P for trend=0.940), FIB-4 (P for trend=0.075), and APRI (P for trend=0.694; Figure 2). Similarly, the degree of liver fibrosis did not affect AF recurrence in patients with MAFLD (Figure 3).

Table 2.

Characteristics of Patients With and Without AF Recurrence

Variables	AF recurrence (n=208)	No AF recurrence (n=610)	P value
Age (years)	66 [59, 72]	67 [61, 73]	0.188
Female sex	69 (33.2)	171 (28.0)	0.160
BMI (kg/m2)	24 [22, 26]	23 [22, 26]	0.037
CHA2DS2-VASc score	2 [1, 3]	2 [1, 3]	0.735
Heart failure	85 (40.9)	182 (29.8)	0.005
Hypertension	117 (56.2)	325 (53.3)	0.469
Diabetes	37 (17.8)	131 (21.5)	0.275
Obstructive sleep apnea	3 (1.4)	8 (1.3)	1.000
Stroke or TIA	12 (5.8)	41 (6.7)	0.745
MAFLD	59 (28.4)	95 (15.6)	<0.001
Paroxysmal AF	122 (58.7)	411 (67.4)	0.028
BNP (pg/mL)	116 [55, 217]	80 [36, 169]	<0.001
Creatinine (mg/dL)	0.81 [0.66, 0.96]	0.79 [0.67, 0.91]	0.377
HbA1c (%)	5.8 [5.5, 6.1]	5.8 [5.6, 6.2]	0.175
HOMA-IR (n=239)	1.48 [0.87, 2.95]	1.32 [0.81, 2.00]	0.088
ALT (U/L)	23 [19, 28]	23 [19, 28]	0.890
AST (U/L)	21 [16, 30]	21 [16, 29]	0.839
LDL (mg/dL)	118 [97, 140]	116 [98, 136]	0.802
Platelets (×104/L)	21 [19, 25]	21 [18, 25]	0.240
Albumin (g/dL)	4.3 [4.1, 4.5]	4.3 [4.1, 4.5]	0.511
CRP (mg/dL)	0.06 [0.03, 0.11]	0.05 [0.03, 0.09]	0.035
Liver/spleen ratio (attenuation)	1.25 [1.13, 1.36]	1.27 [1.17, 1.39]	0.033
APRI	0.36 [0.28, 0.47]	0.36 [0.27, 0.49]	0.448
FIB-4	1.46 [1.13, 2.02]	1.55 [1.14, 2.10]	0.183
NFS	−1.27 [−2.19, −0.65]	−1.32 [−2.10, −0.54]	0.553
LAVI (mL/m2)	43 [32, 55]	38 [30, 48]	0.004
LVEF (%)	63 [56, 68]	63 [57, 68]	0.596
ACEi/ARB	90 (43.3)	237 (38.9)	0.287
β-blockers	92 (44.2)	236 (38.7)	0.164
Statin	55 (26.4)	152 (24.9)	0.712
Anti-arrhythmic drugs	82 (39.4)	204 (33.4)	0.13
Radiofrequency ablation	123 (59.1)	243 (39.8)	<0.001

Unless indicated otherwise, data are given as the median [interquartile range] or n (%). Abbreviations as in Table 1.

Figure 2.

Atrial fibrillation recurrence in all patients according to the extent of liver fibrosis, as determined using the Non-alcoholic Fatty Liver Disease Fibrosis Score (NFS), Fibrosis-4 Index (FIB-4), and the Aspartate Aminotransferase to Platelet Ratio Index (APRI).

Figure 3.

Atrial fibrillation recurrence in patients with metabolic dysfunction-associated fatty liver disease (MAFLD) according to the extent of liver fibrosis, as determined using the Non-alcoholic Fatty Liver Disease Fibrosis Score (NFS), Fibrosis-4 Index (FIB-4), and the Aspartate Aminotransferase to Platelet Ratio Index (APRI).

In univariate Cox proportional hazards regression analyses, MAFLD (unadjusted HR=1.72; 95% CI=1.27–2.33; P<0.001), LAVI, BMI, BNP, HOMA-IR, type of AF, history of heart failure, and radiofrequency ablation were significantly associated with AF recurrence. Based on the results of univariate Cox proportional hazards regression analyses, multivariable analysis was performed using a forced entry and backward stepwise model to determine the association between MALFD and AF recurrence after adjusting for confounding factors (Table 3). Multivariate Cox proportional hazards regression analysis revealed that MAFLD (adjusted HR 2.62; 95% CI 1.44–4.80; P=0.002) was an independent factor associated with AF recurrence. Although LAVI and the particular scores that were calculated of the liver fibrosis index were significantly correlated with AF recurrence (Supplementary Figure), they were independently associated with AF recurrence.

Table 3.

Multivariate Cox Regression Analyses for Independent Association of AF Recurrence

	Univariate analysis			Multivariate analysis (forced entry)			Multivariate analysis (backward stepwise method)
	HR	95% CI	P value	HR	95% CI	P value	HR	95%CI	P value
Age	0.99	0.98–1.01	0.479	0.99	0.96–1.04	0.887
Female sex	1.24	0.93–1.64	0.148	1.60	0.80–3.17	0.182
BMI	1.04	1.00–1.08	0.050	1.05	0.95–1.16	0.374
Heart failure	1.55	1.17–2.04	0.002	1.11	0.52–2.36	0.789
Diabetes	0.88	0.62–1.26	0.482	0.79	0.23–2.75	0.714
MAFLD	1.72	1.27–2.33	<0.001	3.04	1.33–6.99	0.009	2.62	1.44–4.80	0.002
Paroxysmal AF	0.73	0.56–0.97	0.030	0.84	0.40–1.77	0.640
BNP	1.00	0.99–1.00	0.084	1.00	0.99–1.00	0.552
HbA1c	0.86	0.68–1.10	0.228	1.16	0.50–2.68	0.736
HOMA-IR	1.10	1.01–1.20	0.031	1.11	0.96–1.28	0.163
ALT	1.00	0.99–1.01	0.737	1.01	0.97–1.05	0.767
AST	0.99	0.98–1.01	0.658	0.96	0.89–1.04	0.301
Platelet count	1.01	0.99–1.04	0.243	0.99	0.93–1.06	0.933
Albumin	0.97	0.64–1.49	0.906	1.98	0.62–6.31	0.251
CRP	2.12	0.75–6.04	0.159	0.77	0.06–10.09	0.840
Liver/spleen ratio (attenuation )	0.68	0.34–1.36	0.275	2.67	0.59–12.11	0.204
FIB-4	0.87	0.72–1.05	0.132	0.62	0.14–2.76	0.527
LAVI	1.02	1.01–1.03	<0.001	1.01	0.99–1.04	0.310
Radiofrequency ablation	1.54	1.17–2.05	0.003	1.78	0.80–3.98	0.158

CI, confidence interval; HR, hazard ratio. Other abreviations as in Table 1.

Patients with AF recurrence were divided into 2 groups according to the type of AF: paroxysmal and persistent AF (Supplementary Table 1). Forced entry multivariate analysis revealed that MAFLD was an independent risk factor for AF recurrence in both the paroxysmal and persistent AF groups (Supplementary Table 2). Because MAFLD was most strongly associated with AF recurrence, patients were divided into 2 groups (with and without MAFLD) and the probability of remaining free of AF recurrence after the ablation procedure was evaluated in each of the 2 groups. As shown in Figure 4, patients without MAFLD had a greater probability of remaining free of AF recurrence than those with MAFLD (P<0.05 log-rank test).

Figure 4.

Kaplan-Meier analysis of the rate of atrial fibrillation (AF) recurrence in patients with and without metabolic dysfunction-associated fatty liver disease (MAFLD).

We performed further subgroup analyses of the risk of AF recurrence according to the presence of MAFLD and different risk variables (LAVI, BMI, BNP, HOMA-IR, ablation procedure, and AF type) and their interaction. To this end, we used Cox regression analysis to calculate HRs for MAFLD after adjusting for each of these variables and compared the adjusted HRs with the crude HR for MAFLD (Figure 5). To evaluate interactions between MAFLD and the different risk variables on the risk of AF recurrence, the HR for MAFLD was evaluated in subgroups to dichotomized variables of LAVI, BMI, BNP, HOMA-IR, ablation procedure, and AF type. Although we did not find any confounding effect of HOMA-IR, a significant interaction between MAFLD and HOMA-IR was identified (P for interaction=0.034; Figure 5).

Figure 5.

Subgroup analyses of hazard ratios (HRs) for metabolic dysfunction-associated fatty liver disease (MAFLD) for the recurrence of atrial fibrillation (AF). BNP, B-type natriuretic peptide; BMI, body mass index; CI, confidence interval; HOMA-IR, homeostasis model assessment of insulin resistance; LAVI, left atrial volume index.

Discussion

Our findings indicate that MAFLD is an independent risk factor for AF recurrence following ablation in Japanese patients with a mean BMI of 23.40 kg/m², regardless of the degree of fibrosis. However, the effects of MAFLD are likely heterogeneous, with a greater impact in the presence of insulin resistance.

MAFLD is considered a hepatic manifestation of metabolic syndrome, with a relatively high incidence among patients with type 2 diabetes or obesity.¹⁷ It has been reported that Asian individuals have relatively lower BMI values than Western populations, and it has been suggested that a BMI of ≥25 kg/m² in Asian individuals is similar to a BMI of ≥30 kg/m² in Western individuals.¹⁸ There is a higher prevalence of non-obese MAFLD among Asian individuals, which has been reported to involve genetic polymorphisms.¹¹ Thus, the impact of MAFLD on AF may differ depending on race.

Although epidemiological studies indicate that MAFLD is a risk factor for AF,¹⁹ its effects are likely heterogeneous.²⁰ The possible intervening factors linking MAFLD and AF, in particular obesity, diabetes, and systemic inflammation, are diverse and form a complex network. A recent study reported MAFLD was associated with significantly increased arrhythmia recurrence rates following AF ablation in Western patients.¹⁰ In addition, several studies have investigated the relationship between liver fibrosis and AF recurrence, but the conclusions have not been consistent.^10,21,22 In the present study, we found no relationship between the degree of liver fibrosis and AF recurrence. These conflicting results may be explained by differences in study subjects. For example, in the present study only 3% of patients had advanced fibrosis, whereas the Western study included approximately 25% of patients with advance fibrosis.¹⁰ In addition, MAFLD in the present study was diagnosed on the basis of CT scans, potentially capturing a broader spectrum of undiagnosed and less severe MAFLD. In the present study, the BMI of the patients was within the normal weight range, regardless of the presence of MAFLD. The mechanism underlying the impact of MAFLD on AF recurrence in Japanese patients needs to be considered as independent of obesity. With respect to laboratory markers of inflammation, C-reactive protein did not differ significantly between those with and without AF recurrence in this study, which is consistent with previous reports.^10,23 However, it has been suggested that activation of the nuclear factor-κB pathway in MAFLD patients results in the transcription of several inflammatory cytokines and low-grade systemic inflammation, which may contribute to atrial arrhythmias;²⁴ thus, inflammatory factors need to be studied in more detail.

Organ fibrosis, including both atrial and liver fibrosis, is a hallmark of chronic metabolic and inflammatory conditions, such as MAFLD. Although both types of fibrosis are driven by shared upstream mechanisms (e.g., systemic inflammation, oxidative stress, and profibrotic cytokines such as transforming growth factor-β), the key effector cells and extracellular matrix components differ between the atria and liver. In liver fibrosis, activated hepatic stellate cells produce extracellular matrix proteins, notably type IV collagen, which is integral to basement membrane remodeling and portal hypertension. Circulating type IV collagen levels are recognized as a non-invasive biomarker of hepatic fibrosis.²⁵ In contrast, atrial fibrosis is mediated by cardiac fibroblasts that secrete primarily type I and type III collagen into the interstitial space.²⁶ These structural changes increase myocardial stiffness and disrupt electrical conduction, forming the arrhythmogenic substrate that facilitates reentrant circuits. In our cohort, liver fibrosis indices were correlated with LAVI, a surrogate of atrial fibrosis, yet neither was independently associated with AF recurrence. A previous study reported insulin resistance-induced electrical remodeling caused by a delay in left atrial conduction velocity without anatomical remodeling.²³ The mechanism of increased risk of AF recurrence in the present study that is independent of liver fibrosis or systemic inflammation may be explained, in part, by a delay in left atrial conduction velocity.

The key question remains as to whether AF recurrence is directly attributable to fatty liver fibrosis or not. The present study showed that MAFLD, even in the absence of advanced fibrosis, was related to AF recurrence, particularly in patients with high insulin resistance. These results suggest the need for future trials to examine the effectiveness of early metabolic intervention in MAFLD patients with insulin resistance to avoid AF recurrence.

Our study has some limitations that should be noted. First, it was a cross-sectional retrospective study from a single center and did not represent the Japanese population. In addition, it remains unclear whether AF recurrence is directly attributable to MAFLD. Second, CT scans, not biopsies, were used to diagnose fatty liver. However, the role of liver biopsy is becoming limited, with the use of non-invasive diagnosis based on serum biomarkers or imaging modalities becoming acceptable.²⁷ Third, the study is limited by the potential for unmeasured confounding variables. Fourth, data regarding insulin resistance were only available for 46 of 154 (29.9%) patients with MAFLD and 193 of 664 (29.1%) patients without MAFLD.

Conclusions

MAFLD is an independent risk factor for AF recurrence after ablation in Japanese patients, regardless of obesity, and its effects are likely heterogeneous, with a greater impact in the presence of insulin resistance.

Sources of Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Disclosures

K.Y. has received lecturer fees from Otsuka Pharmaceutical Co., Ltd., Daiichi-Sankyo Co., Ltd., Boehringer Ingelheim Co. Ltd., Boston Scientific Co. Ltd., Viatris Inc., Bayer Yakuhin, Ltd, Ono Pharmaceutical Co. Ltd., and Novartis; research grants from Abbott, Otsuka Pharmaceutical Co., Ltd., Medtronic Japan Co., Ltd., Boston Scientific Co., Ltd., Biotronik Japan Inc., Japan Lifeline Co., Ltd., and Fukuda Denshi; and is a member of Circulation Journal Editorial Board. M.K. has received research grants from Medtronic Japan Co., Ltd.

The contents of this manuscript have not been copyrighted or published previously and are not under consideration for publication elsewhere.

Author Contributions

All the authors contributed to and take responsibility for the work.

IRB Information

This study was approved by the Institutional Review Board of Tottori University Hospital (Reference no. 18A034).

Data Availability

The deidentified participant data will be shared on a request basis. Please contact the corresponding author directly to request data sharing. The entire dataset used will be available, including the study protocol. Data will be shared as soon as the IRB at Tottori University School of Medicine approves it, and will be available until end of March 2028. The data will be shared with anyone wishing to access the data. Any analyses on the data will be approved and data will be shared as Excel file via email.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-25-0169

References

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