Association between Serum Apolipoprotein A1 and Atrial Fibrillation: A Case-Control Study

doi:10.21203/rs.3.rs-1755811/v1

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Association between Serum Apolipoprotein A1 and Atrial Fibrillation: A Case-Control Study

https://doi.org/10.21203/rs.3.rs-1755811/v1

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Background: The relationship between apolipoprotein A1(APOA1) and atrial fibrillation (AF) is not known. Therefore, we sought to investigate the associations between APOA1 and AF by sex in the Chinese population.

Methods: This case-control study included 950 patients with AF (29-83 years old, 50.42 % male) who were hospitalized consecutively between January 2019 and September 2021. Controls with sinus rhythm and without AF were matched (1:1) to cases by sex and age. Pearson correlation analysis was performed to investigate the correlation between APOA1 and blood lipid profiles. Multivariate regression models were used to explore the association between APOA1 and AF. Receiver operator characteristic (ROC) curve was constructed to examine the performances of the APOA1.

Results: Low APOA1 in male and female patients with AF patients was significantly associated with AF (OR=0.261, 95% CI:0.162-0.422, P＜0.001), regardless of statin use. Pearson correlation analysis indicated serum APOA1 was positively correlated with total cholesterol (TC) (r=0.456, p＜0.001), low-density lipoprotein cholesterol (LDL-C) (r=0.825, p＜0.001), high-density lipoprotein cholesterol (HDL-C) (r=0.238, p＜0.001) , and apolipoprotein B(APOB) (r=0.083, p=0.011). ROC curve analysis showed APOA1 levels=1.105 g/L in men and APOA1 levels=1.205 g/L were the most optimal cut-off values for predicting AF.

Conclusion: Low APOA1 in male and female patients is significantly associated with AF in the Chinese population. APOA1 may be a potential biomarker for AF and contribute to the pathological progress of AF along with low blood lipid profiles. The potential mechanisms remain to be further explored.

Atrial Fibrillation

Apolipoprotein A1

Blood Lipid Profiles

Inflammation

Sex

Atrial fibrillation (AF), the most common clinically significant sustained arrhythmia, is affecting 33 million population worldwide[1-3] and is associated with an increased risk of heart failure, stroke, systemic embolism, cognitive impairment, and even death[4-8]. Currently, there are about 2.3 million patients with AF, and this number will increase to 5.6 million by 2050[9]. As a burgeoning health threat, AF has resulted in significant morbidity, mortality, and a considerable healthcare burden[10]. Although catheter ablation is an effective treatment for AF, the success rate of a single operation is only 60-70%, and potential complications also may exist[11-14]. There is increasing evidence that risk factors screening strategies may contribute to reducing the incidence of AF[15-16]. Therefore, exploring available blood biomarkers associated with early pathological changes in patients with AF may help us identify potential risk factors and better understand the pathogenesis of AF.

Apolipoprotein A1 (APOA1), a multifunctional apolipoprotein and the key protein structural component in high-density lipoprotein (HDL) particles with well-documented cardioprotective properties, especially atheroprotective function, and has been considered as a significant serum biomarker for predicting multiple cardiovascular events[17-18]. Although previous studies have reported that there was almost no relationship between lipids and inflammatory markers[19-21], it has still suggested that HDL-C and APOA1 had important anti-inflammatory, and anti-oxidative properties[22]. In addition, current evidence suggested the effects of dyslipidemia on AF remain controversial. Several studies showed the negative correlation between HDL-C and AF[23-25], a study indicated that HDL-C was positively related to ischemic stroke in patients with AF[26], and another study suggested there was no significant association between HDL-C and AF[27]. The relationship between blood lipid profiles and AF and its potential mechanisms deserve further exploration.

To the best of our knowledge, few studies have been conducted to explore the association between serum APOA1 and sex in patients with AF. Therefore, we conducted a case-control study to investigate the association between serum APOA1 and AF stratified by sex and investigated the correlation between APOA1 and blood lipid profiles to help explore the early potential serum biomarkers for AF.

Study design

We collected and analyzed clinical data of 1900 consecutive hospitalized patients (Male/Female: 949/951, 68.42±10.87 years) from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine between January 2019 and September 2021. 950 AF patients were included in the AF group, and 950 age-, sex-matched non-AF patients with sinus rhythm were served as controls. Specifically, we included patients aged 29-85 years with complete data on both paroxysmal AF(n=332) and permanent AF(n=618). Meanwhile, We also excluded patients with cardiac surgery, heart failure, valvular disease, liver and kidney dysfunction, malignancy, hyperthyroidism, use of uric acid-lowering drugs, and pregnant women. We investigated the clinical characteristics of all participants in an electronic medical record review, including sex, age, laboratory data, AF subtypes, and complications. In addition, we stratified the information of patients with AF primarily by sex and APOB levels. We declare that this study has been reviewed by the Medical Research Ethics Committee of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine based on the principles of the Helsinki Declaration. The data are anonymous, and the Ethics Committee of Affiliated Hospital of Shandong University of Traditional Chinese Medicine (NO.20200512FA62) waived the requirement for informed consent.

Screened variables

We selected the baseline data of all participants including sex, age, AF type, AF complication, and laboratory data including serum apolipoprotein A1(APOA1), serum apolipoprotein B (APOB), blood lipid profiles, aspartate aminotransferase(AST), alanine aminotransferase (ALT), lipoprotein (a) (Lp (a)), serum uric acid (SUA), serum creatinine (SCr), serum albumin (ALB), pre-albumin (PAB), as well as medication situation including statins, CCBs, β-blockers, ACEI/ARB.

Statistical analysis

All statistical analyses were implemented by SPSS software (version 26.0; SPSS Inc., Chicago, IL, USA) or GraphPad Prism software (version 9.0.0). Continuous variables were expressed as mean±standard deviations (SD) and compared by analysis of Student's t-test and analysis of variance (ANOVA). Categorical variables were presented as n(%) and compared by chi-square testings. Pearson correlation analyses were used to evaluate interrelationships and visualized as scatter plots. Additionally, multivariate regression analyses were performed to adjust for covariates, shown as odds ratios (ORs) and 95% confidence intervals (95% CIs). A p-value < 0.05 with two-tailed was considered significant.

Baseline clinical characteristics of participants

As shown in Table1, a total of 1900 consecutive hospitalized patients (M/F: 949/951, 68.42±10.87 years) were divided into two groups, including 950 AF patients(M/F: 479/471, 68.61±10.34 years) and 950 controls(M/F: 470/480, 68.23 ± 11.37 years). Compared with controls, AF patients were more likely to experience hypertension, CHD, diabetes and had a history of using statins, CCBs, β-blockers, and ACEI/ARB (p<0.001), as well as significantly lower levels of APOAl, APOB, TG, TC, LDL-C, HDL-C, ALB, and PAB(P＜0.05), significantly higher levels of AST, SCr and SUA(P＜0.05), but no significant difference in serum levels of Lp (a), FBG and ALT between the two groups (P＞0.05).

Table 1: Baseline clinical characteristics of participants.

Variable	AF group(n=950)	Control group (n=950)	P value
Age, years	68.61±10.34	68.23 ± 11.37	0.446
Male, n (%)	479（50.42）	470（49.47）	0.680
APOA1, g/L	1.13±0.26	1.23 ± 0.25	＜0.001*
Men, g/L	1.07±0.25	1.15±0.24	＜0.001*
Women, g/L	1.19±0.27	1.30±0.23	＜0.001*
APOB, g/L	0.80±0.38	0.99 ± 0.24	＜0.001*
Lp (a), mg/L	23.55±26.88	22.58± 24.40	0.410
TC, mmol/L	4.19±1.10	5.02 ± 1.10	＜0.001*
TG, mmol/L	1.24±0.88	1.38 ± 1.25	0.004*
LDL-C, mmol/L	1.07±0.30	1.20± 0.32	＜0.001*
HDL-C, mmol/L	2.50±0.90	2.96 ± 0.86	＜0.001*
FBG, mmol/l	6.22±2.11	6.23±1.94	0.914
AST, U/L	25.30 ± 45.62	20.81± 10.87	0.003*
ALT, U/L	22.30 ± 27.37	20.35 ± 13.70	0.05
ALB, g/L	38.05± 4.64	40.09 ± 4.12	＜0.001*
PAB, g/L	19.56±5.94	22.25±5.52	＜0.001*
SCr, μmoI/L	78.46 ± 51.47	64.97 ± 26.65	＜0.001*
SUA, mg/dL	5.89±1.75	5.11 ± 1.37	＜0.001*
Hypertension, n (%)	638（67.16）	324（34.11）	＜0.001*
CHD, n (%)	840（88.42）	240（25.26）	＜0.001*
Diabetes, n (%)	280（29.47）	157（16.53）	＜0.001*
Statins, n (%)	627（66.00）	217（22.84）	＜0.001*
CCBs, n (%)	343（36.11）	166（17.47）	＜0.001*
β-blockers, n (%)	743（78.21）	159（16.74）	＜0.001*
ACEI/ARB, n (%)	533（56.11）	139（14.63）	＜0.001*

Data were presented as mean±SD or n(％).

Abbreviations: AF: atrial fibrillation; CHD: coronary heart disease; APOA1: serum apolipoprotein A1; APOB: serum apolipoprotein B; Lp (a): lipoprotein (a); TC: total cholesterol; TG: triglyceride; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; AST: aspartate aminotransferase; ALT: alanine aminotransferase; ALB: serum albumin; PAB: pre-albumin; SCr: serum creatinine; SUA: serum uric acid.

*Statistically significant value (P<0.05).

Correlation between serum APOA1 and AF

As shown in Table 2, after adjusting for APOB, LDL-C, and AST, serum APOA1 was considered to be a related factor for AF (OR=0.232, 95% CI:0.154-0.350, P＜0.001). Further after adjusting for hypertension, diabetes, CCBs, ACEI/ARB, and statins, serum APOA1 was still an associated factor for AF (OR=0.269, 95% CI:0.175-0.414, P＜0.001). Finally, after adjusting for all confounding factors, serum APOA1 remained a significant factor for AF(OR=0.261, 95% CI:0.162-0.422, P＜0.001). Moreover, serum APOA1 was negatively correlated with AF in both sexs (P＜0.05).

Table 2: Correlation between serum APOA1 and AF.

	Total		Men		Women
	OR 95% CI	P value	OR 95% CI	P value	OR 95% CI	P value
Model1	0.230（0.160-0.332）	＜0.001*	0.241（0.140-0.416）	＜0.001*	0.241（0.140-0.416）	＜0.001*
Model2	0.232（0.154-0.350）	＜0.001*	0.318（0.176-0.575）	＜0.001*	0.123（0.066-0.230）	＜0.001*
Model3	0.269（0.175-0.414）	＜0.001*	0.297（0.154-0.574）	＜0.001*	0.224（0.121-0.415）	＜0.001*
Model4	0.261（0.162-0.422）	＜0.001*	0.398（0.198-0.798）	0.009*	0.120（0.057-0.252）	＜0.001*

Model 1: crude, no adjustment; Model 2: adjusting for APOB, LDL-C, and AST; Model 3: adjusting for hypertension, diabetes, CCB, ACEI/ARB, and statins; Model 4: adjusting for all these factors. Abbreviations as in Table 1. *Statistically significant value (P<0.05).

Association between APOA1 and AF in patients with non-receiving statins

As shown in Table 3, the multivariate regression analysis showed that after adjusting for APOB, LDL-C, and AST, APOA1 was related to AF (OR=0.078, 95% CI:0.041-0.149, P＜0.001). After further adjusting for hypertension, diabetes, β-blockers, CCB, and ACEI/ARB, APOA1 remained associated with AF (OR=0.153, 95% CI:0.073-0.322, P＜0.001). After adjustment for all confounding factors, APOA1 remained a significant relevant factor for AF(OR=0.081, 95% CI:0.034-0.193, P＜0.001). Additionally, the independent association between APOA1 and AF in patients with non-receiving statins was also significant in both sexes(P＜0.05).

Table 3: Correlation between APOA1 and AF in patients with non-receiving statins.

	Total		Men		Women
	OR 95% CI	P value	OR 95% CI	P value	OR 95% CI	P value
Model1	0.114（0.065-0.199）	＜0.001*	0.065（0.027-0.159）	＜0.001*	0.112（0.050-0.248）	＜0.001*
Model2	0.078（0.041-0.149）	＜0.001*	0.078（0.029-0.209）	＜0.001*	0.048（0.018-0.123）	＜0.001*
Model3	0.153（0.073-0.322）	＜0.001*	0.075（0.023-0.248）	＜0.001*	0.193（0.066-0.565）	0.003*
Model4	0.081（0.034-0.193）	＜0.001*	0.090（0.025-0.331）	0.037*	0.038（0.010-0.149）	＜0.001*

Model 1: crude, no adjustment; Model 2: adjusting for APOB, LDL-C, and AST; Model 3: adjusting for hypertension, diabetes, β-blockers, CCB, and ACEI/ARB; Model 4: adjusting for all these factors. Abbreviations as in Table 1. *Statistically significant value (P<0.05).

The difference in APOA1 levels between AF patients and controls by sex and age

Figure 1 showed the difference in APOA1 levels between AF patients and controls by sex and age. Compared with controls, APOA1 levels in the AF patients were significantly lower in the men( 1.07±0.25 vs.1.15±0.24 g/L, P＜0.001; Figure 1(A)) and women (1.19±0.27 vs. 1.30±0.23 g/L, P＜0.001; Figure 1(A)), significantly lower in the patients with age≤60 years (1.14±0.26 vs. 1.17±0.22 g/L, P＜0.001; Figure 1(B)) and age＞60 years (1.13±0.27 vs. 1.24±0.25 g/L, P＜0.001; Figure 1(B)).

The difference in APOA1 levels between AF patients and controls by type and complication of AF

Figure 2 showed the difference in APOA1 levels between AF patients and controls by type and complication of AF. Compared with the permanent AF group and controls, APOA1 levels in the paroxysmal AF group were significantly lower in the men ( 1.05 ± 0. 26 vs.1.08 ± 0.24 vs. 1.15±0.24 g/L, P＜0.001; Figure 2(A)) and women ( 1.18 ± 0.28 vs.1.19 ± 0.26 vs. 1.30±0.23 g/L, P＜0.001; Figure 2(A)). However, there was no significant difference in APOA1 levels between male and female patients with AF complications (P＞0.05; Figure 2(B)).

Correlation between serum APOA1 and AF-related metabolic factors

Figure 3 showed the correlation between serum APOA1 and blood lipid profiles. Serum APOA1 was positively correlated with TC ( r= 0.456, p＜0.001; Figure 3(A)), LDL-C (r=0.825, p＜0.001; Figure 3(B)), HDL-C (r= 0.238, p＜0.001; Figure 3(C)) , and APOB ( r=0.083, p=0.011; Figure 3(D) ).

Subgroup analysis of the relationship between serum APOA1 levels and blood lipid profiles in patients with paroxysmal AF

Table 4 showed the relationship between serum APOA1 levels and blood lipid profiles in patients with paroxysmal AF. The present results suggested that lower serum APOA1 had lower TC, LDL-C, and HDL-C in both sexes (P<0.001).

Table 4: The relationship between APOA1 levels and blood lipid profiles in patients with paroxysmal AF.

Variable	Men（n=180)				Women（n=152)
Variable	≤0.97g/L	0.97-1.16g/L	≥1.16g/L	P value	≤1.10g/L	1.10-1.27g/L	≥1.27g/L	P value
Number, n	73	48	59		53	47	52
TG, mmol/L	1.05±0.54	1.12±0.59	1.15±0.68	0.619	1.25±0.64	1.60±2.33	1.20±0.68	0.313
TC, mmol/L	3.47±0.90	4.05±0.83	4.56±0.94	＜0.001*	3.69±1.02	4.62±1.10	5.10±1.23	＜0.001*
LDL-C, mmol/L	0.77±1.29	1.01±0.15	1.33±0.31	0.001*	0.89±0.39	1.15±0.21	1.41±0.23	＜0.001*
HDL-C, mmol/L	2.20±0.73	2.43±0.74	2.59±0.88	0.018*	2.15±0.85	2.68±0.93	3.16±1.28	＜0.001*
APOB, g/L	0.73±0.21	0.98±1.31	0.80±0.24	0.157	0.76±0.22	0.83±0.25	0.90±0.31	0.026*

Data were presented as mean±SD.

Abbreviations as in Table 1.

*Statistically significant value (P<0.05).

Subgroup analysis of the relationship between serum APOA1 levels and blood lipid profiles in patients with permanent AF

Table 5 showed the relationship between serum APOA1 levels and blood lipid profiles in patients with permanent AF. The present results showed that lower serum APOA1 had lower TC, LDL-C, and HDL-C in both sexs (P<0.001).

Table 5: The relationship between APOA1 levels and blood lipid profiles in patients with permanent AF.

Variable	Men（n=299)				Women（n=319)
Variable	≤0.99 g/L	0.99-1.17g/L	≥1.17g/L	P value	≤1.08 g/L	1.08-1.32g/L	≥1.32g/L	P value
Number, n	102	94	103		108	104	107
TG, mmol/L	1.18±0.66	1.31±0.83	1.28±1.19	0.583	1.30±0.74	1.26±0.52	1.19±0.45	0.378
TC, mmol/L	3.62±1.03	4.05±1.07	4.39±1.01	＜0.001*	3.86±0.99	4.38±1.00	4.80±0.89	＜0.001*
LDL-C, mmol/L	0.81±0.13	0.99±0.12	1.24±0.24	＜0.001*	0.86±0.19	1.12±0.16	1.39±0.22	＜0.001*
HDL-C, mmol/L	2.23±0.81	2.43±0.90	2.53±0.86	0.040*	2.42±0.83	2.61±0.87	2.74±0.81	0.020*
APOB, g/L	0.74±0.24	0.77±0.26	0.78±0.23	0.475	0.78±0.22	0.81±0.24	0.82±0.21	0.395

Data were presented as mean±SD.

Abbreviations as in Table 1.

*Statistically significant value (P<0.05).
ROC curve model for APOA1 levels predicting AF.

Figure 4 showed the ROC curve model for APOA1 levels predicting AF. The ROC curve analysis suggested that APOB levels=1.105 g/L in men was the most optimal cut-off value for predicting AF; area under the ROC curve for the model was 0.592 (95％CI:0.556-0.628, P＜0.05; Figure 4(A)), the sensitivity was 0.591, the specificity was 0.551. The ROC curve analysis showed that APOB levels=1.205 g/L in women was the most optimal cut-off value for predicting AF; area under the ROC curve for the model was 0.611 (95％CI:0.576-0.647, P＜0.05; Figure4(B)), the sensitivity was 0.520, the specificity was 0.640.

This study is the first to explore the association between serum APOA1 and sex in patients with AF in the Chinese population. The present results indicated low serum APOA1 in male and female patients was associated with AF, regardless of statin use. Serum APOA1 in male patients was significantly lower than in female patients with AF. Further results showed serum APOA1 was positively correlated with TC, LDL-C, HDL-C, and APOB. Subgroup analysis showed lower serum APOA1 in male and female patients who had lower TC, LDL-C, and HDL-C with paroxysmal AF and permanent AF. These detailed findings may contribute to our understanding of the relationship between serum APOA1 and sex in patients with AF. When the most optimal cut-off value of APOA1 level was 1.105 g/L in men and 1.205 g/L in women, and the sensitivity was 0.591 and 0.520, the specificity was 0.551 and 0.640, respectively. These findings may contribute to a better understanding of the development of AF.

As a principal protein element of HDL, APOA1 played an important role in the synthesis of HDL. Cholesterol acyltransferase (LCAT) is an enzyme secreted by the liver that circulates with HDL and increases HDL carrying capacity by esterifying cholesterol. Studies have shown that APOA1 not only mediated HDL synthesis but also participated in the activation of LCAT[28]. Clinical evidence indicated that HDL was atheroprotective, as well as had anti-inflammatory, anti-oxidative, and anti-thrombotic properties[29-31]. The oxidation of HDL mainly occurs in the inflammatory microenvironment and HDL-related paraoxonase activity may reduce systemic oxidative stress, which may be associated with the reduced risk of cardiovascular events[32-33]. Moreover, tryptophan oxidation of APOA1 may also contribute to promoting inflammation[34-36]. There is growing evidence that inflammation and oxidative stress played a significant role in the pathogenesis of AF[37-39]. In addition, oxidative modification of lipoproteins was considered to be key to atherosclerosis formation[40]. Lipid peroxidation induced myocardial cell damage and electrophysiological changes formed the matrix of AF[41-43]. From this perspective, APOA1 may maintain the pathological process of AF through pro-inflammatory and pro-oxidation chains and HDL-C.

Until now, few studies have reported the association between APOA1 and AF. A prospective cohort study based on 35 PAF patients and 34 healthy participants showed that PAF participants had lower serum APOA1 levels[44]. Another study based on 11 female patients with paroxysmal lone AF and 10 female patients with non- AF indicated compared with controls, there was an approximately 30% lower expression of serum APOA1 in women with AF[45]. Compared to previous studies, the present study was conducted in larger sample size and more systematically investigated the association between serum APOA1 and AF by sex, as well as blood lipid profiles. Our current results indicated an independent negative correlation between serum APOA1 and AF in both sexs after adjustment for confounding factors. Compared to women, APOA1 levels were significantly lower in men with AF, regardless of AF types, or AF complications. Three explanations may be suggested for this significant difference: sex hormones, arterial biochemical characteristics, and body shape[46].

In addition, we also found serum APOA1 was correlated with blood lipid profiles. Current results showed blood lipid profiles were lower in patients with AF, which was consistent with previous findings[47]. The use of lipid-lowering drugs may help explain the results. Pearson correlation analysis indicated serum APOA1 was positively correlated with TC, LDL-C, HDL-C, and APOB. Moreover, subgroup analysis showed lower serum APOA1 in male and female patients who had lower TC, LDL-C, and HDL-C with paroxysmal AF and permanent AF. These findings imply that the "cholesterol paradox" remains. Currently, the relationship between blood lipid profiles and AF, as well as sex differences is still controversial. A meta-analysis of large cohort studies reported that TC, LDL-C, and HDL-C were negatively correlated with AF risk[48]. Another longitudinal study in Japan showed that low HDL-C was associated with a higher risk of new-onset AF only in women[49]. Moreover, a large study from the Swedish database suggested that TC was negatively correlated with new-onset AF in male and female patients with hypertension[50]. Our partial results are supported by these studies, while there are some differences. Several possible reasons are worth mentioning. First, study populations are heterogeneous, such as regional differences. Second, the research methods and statistical methods used are different. Third, there were some confounding factors that interfered with the results. Finally, our patients were hospitalized with several complications, including hypertension, coronary heart disease, and diabetes. Additionally, a relationship between low APOB and inflammation has also been established[51]. It is known that low HDL-C is associated with an increased risk of arteriosclerosis, inflammatory disorders, diabetes, and other diseases, which may lead to the pathogenesis and risk factors of AF[52]. Certainly, it remains to be shown the specific mechanism in further research.

Certainly, there were several potential limitations worth considering. First, this single-center case-control study can’t confirm causality. Second, we only investigated the population with paroxysmal AF and permanent AF, lacked a comparison of the data of patients with persistent AF. Third, participants' status of inflammation and oxidative stress was not assessed. Fourth, some significant confounding factors may also be missing. In addition, the limited sample size was not friendly to our findings. However, it did provide us with a new perspective for understanding the pathology of AF. Further prospective cohort studies were encouraged to perform, which may contribute to further evaluating the association between serum APOA1and AF. The effects of AF-related metabolic factors on serum APOA1 were also worth considering.

In Conclusion, low serum APOA1 in male and female patients with AF is independently associated with AF in the Chinese population. Serum APOA1 levels are positively correlated with blood lipid profiles. These findings imply that low APOA1 and blood lipid profiles may be involved in the initiation and maintenance of AF. Prospective cohort designs are essential to explore the causal relationships and potential mechanisms.

Ethics approval and consent to participate

Ethics approval was approved by the Ethics Committee of Affiliated Hospital of Shandong University of Traditional Chinese Medicine. The data are anonymous, and the Ethics Committee of Affiliated Hospital of Shandong University of Traditional Chinese Medicine (NO.20200512FA62) waived the requirement for informed consent.

Consent for publication

All of the participants agreed and provided written informed consent.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by a study on the expression of the pacing gene regulated by the autonomic nerve in atrial fibrillation syndrome with phlegm fire and heart disturbance based on nonlinear theory, National Natural Science Foundation of China (81603609). The funding bodies had no role in the research design, data collection, analysis, interpretation, manuscript writing, and submission.

Authors' contributions

Huachen Jiao was the main coordinator of the project and was responsible for the study design. Xia Zhong and Huachen Jiao drafted the manuscript of the present paper. Mengqi Yang and Jing Teng were involved in the supervising of data collection and stratification. Xia Zhong and Dongsheng Zhao contributed to data assembly and analysis. All authors contributed intellectually to this manuscript and have approved this final version.

Acknowledgments

I would like to express my special thanks to my partners and our funding agency for the encouragement and support they gave me during this study.

Authors' information

Department of First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China

Huachen Jiao

Department of Cardiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, PR China

Xia Zhong &Dongsheng Zhao & Mengqi Yang & Jing Teng

Corresponding author’s information:

Huachen Jiao, Professor, MD, is the chief physician of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine. Address: Room 101, Unit 3, Building 1, No. 125, Huanshan Road, Lixia District, Jinan, Shandong, PR China. Email: [email protected], Telephone: +86-13789813736.

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Association between Serum Apolipoprotein A1 and Atrial Fibrillation: A Case-Control Study

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