The Role of triggering receptor expressed on myeloid cells (TREM) like transcript-1 (TLT-1) in left atrial spontaneous echo contrast in patients with non-valvular atrial fibrillation

doi:10.21203/rs.3.rs-5248842/v1

Objectives

Trigger receptor expressed on myeloid cells(TREM) like transcript-1 (TLT-1) is present in megakaryocytes and platelets. We assessed levels of membrane and soluble TLT-1 in patients with nonvalvular atrial fibrillation (NVAF) to confirm the role of TLT-1 left atrial spontaneous echo contrast (LASEC) in atrial fibrillation.

Methods

A total of 113 NVAF patients underwent transesophageal echocardiography (TEE) were enrolled and divided into non LASEC group (n = 78) and LASEC group (n = 35). Patients with supraventricular tachycardia and health examinees were served as control (n = 50).TLT-1 and soluble TLT-1 levels of all subjects were determined using flow cytometry and enzyme-linked immunosorbent (ELISA) assay. The risk factors for LASEC were assessed by logistic regression analyses.

Results

Expressions of TLT-1 and plasma sTLT-1 in platelet and plasma were increased in LASEC group, compared to non LASEC group. At receiver operating characteristic curve analysis, TLT-1 and sTLT-1 significantly predicted the risk of LASEC (AUC, 0.708, 0.662).Multivariate logistic regression model showed that N-terminal pro-brain natriuretic peptide (NT-proBNP) and TLT-1 were independently associated with LASEC (1.00 (1.00–1.00), p = 0.004; 2.74 (1.05–7.11), p = 0.039).

Conclusion

Aberrant high expression of TLT-1 and NT-proBNP indicated the presence of LASEC in AF patients. TLT-1 could be a new useful predictor of LASEC in NVAF.

TLT-1

atrial fibrillation

platelet

left atrial spontaneous echo contrast

Atrial fibrillation(AF) is the most common cardiac arrhythmia, with a risk of ischemic stroke (IS) five times higher than other arrhythmias. The global prevalence of atrial fibrillation in adults was 1% in 2012[1]. The incidence of atrial fibrillation increases with age, typically higher in males and independent of ethnicity. The prevalence of atrial fibrillation is steadily increasing, with an estimated 1.1% of the global population projected to be affected by 2050[2]. Particularly in China, where the proportion of elderly population is high, the prevalence of atrial fibrillation in elderly individuals will be nearly 2.3 times that of the United States[3].

It has been shown that LASEC can be observed by TEE in 2.3–20% of patients with AF, although this percentage may vary by race, region, and method of examination [4]. Low blood flow velocities, AF, elevated fibrinogen, and structural abnormalities of the cardiovascular system may all contribute to the formation of LASEC. To the best of our knowledge, the Virchow's triad of thrombosis is facilitated by vessel wall abnormalities, blood flow abnormalities, and blood composition abnormalities present in AF [5]. Although some controversy remains, a large body of literature reports that the CHADS2 and CHA2DS2VASc scores are commonly used as reliable stratification models for NVAF-related spontaneous echo contrast [6,7,8]. In view of these limitations, there is an urgent need to investigate biomarkers that can balance simplicity, practicality, cost and effectiveness in order to reduce thromboembolic events.

Due to the hypercoagulable state of AF, platelets play a crucial role in the pathophysiology of thromboembolism in both valvular and nonvalvular AF [9]. Platelets, particularly as the principal component of thrombosis, exhibit abnormal changes in patients with AF. TLT-1 is expressed in both megakaryocytes and platelets, and upon activation, it migrates to the platelet membrane. [10].

In addition, soluble TLT-1 is released into the bloodstream before the membrane-bound TLT-1 receptor is displayed. Prior research indicates that TLT-1, found in abundance within platelets, is a more robust marker of platelet activation compared to P-selectin [11]. While studies have identified D-dimer and NT-proBNP as reliable predictors of non-valvular atrial fibrillation (NVAF), the specific relevance of TLT-1 and NT-proBNP in NVAF patients with left atrial spontaneous echo contrast (LASEC) remains unclear. Our prospective study aims to investigate the expression of platelet-derived TLT-1 and its significance in individuals with AF and concurrent LASEC.

Study population

Between July 2022 and July 2023, patients with AF diagnosed at the First Affiliated Hospital of Soochow University and sinus rhythm control patients were included. Patients were recruited consecutively according to non-valvular AF guidelines [12]. All patients underwent 12-lead ECG and echocardiography. Exclusion criteria included incomplete medical records, structural heart disease, and moderate or severe hepatic or renal dysfunction. We collected clinical characteristics and performed laboratory tests on each subject. Prior to catheter ablation, patients with atrial fibrillation will undergo TEE to identify ‘smoky’ LASEC dynamic echoes characterised by swirling motion [13]. All participants provided informed consent, and the study protocol received approval from the Ethics Committee of the First Affiliated Hospital of Soochow University. Fifty sinus rhythm patients with supraventricular tachycardia or healthy individuals were recruited into the study as a control group.

Sample collection

Two blood samples were obtained from the median cubital vein of all participants. To prevent platelet activation and aggregation, the initial 2.4mL blood sample was collected without a tourniquet and subjected to flow cytometry analysis within 2 hours. The blood samples were collected in tubes with EDTA-K2 anticoagulant (BD, Biosciences, San Jose, CA, USA). The second 2.4mL blood sample was collected in tubes containing 0.105 M buffered sodium citrate (BD, Biosciences, San Jose, CA, USA). Platelet-poor plasma was obtained by centrifuging the blood at 1500 rpm for 10 minutes, then divided into aliquots and stored at -80°C until testing.

Flow Cytometry Assay

A 50 μL aliquot of whole blood was diluted in 450 μL of PBS. Subsequently, this diluted whole blood sample was incubated with 5 μL of fluorescein isothiocyanate (FITC)-conjugated TLT-1 antibody obtained from R&D Systems (Minneapolis, MN, USA). Following the incubation period, flow cytometry analysis was carried out using an FC500 flow cytometer from Beckman Coulter Life Sciences (USA) and the data were analyzed with CXP software version 2.3. Platelet events were identified based on forward scatter/side scatter patterns, with results presented as the percentage of positive platelets. The mean fluorescence intensity (MFI) was also measured.

Enzyme-Linked Immunosorbent Assay (ELISA)

The plasma concentrations of sTLT-1 were quantified using an enzyme-linked immunosorbent assay (ELISA). The ELISA kit and a microplate reader (SpectraMax M2, Molecular Devices) equipped with SoftMax Pro software were employed following the manufacturer's guidelines. The experimental procedures were carried out as described previously.

Statistical analysis

The data analysis was conducted utilizing SPSS Statistics 22.0 (IBM) and GraphPad Prism 9 (GraphPad Inc.). Data are presented as n (%), mean ± SD, or median with interquartile range (IQR). Statistical comparisons of human samples were performed using either the paired t-test or Mann-Whitney U-test depending on the distribution of the data. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic utility of platelet TLT-1 in identifying left atrial spontaneous echo contrast. Statistical significance was set at p < 0.05, indicating significant differences.

Baseline Characteristics

A total of 113 patients with atrial fibrillation (AF) and 50 control subjects with sinus rhythm were initially identified. The baseline characteristics of both AF patients and sinus rhythm controls are summarized in Table 1. AF patients were more likely to have hypertension(p<0.001), diabetes mellitus(p=0.029), lower platelet counts(p<0.001), eGFR (p=0.006)and higher BMI(p=0.047),blood glucose(p=0.014), NT-proBNP(p<0.001), cTnI(p<0.001), Left atrial dimension(p<0.001), LVDD(p=0.001), LVSD(p<0.001) and attenuated Ejection fraction(p<0.001).

Baseline Characteristics of AF patients with or without LASEC were shown in Table 2. Among the AF patients, 31.0% of them developed LASEC. The platelet counts in AF patients were significantly higher than that in control group, while no significant difference was found between non LASEC group and LASEC group. Compared to the non LASEC group, LASEC group had less males (p=0.046), higher rate of heart failure (p=0.025) and persistent AF (p<0.001), more medications of β-blocker (p=0.033), cordarone (p=0.030), ACEI/ARB/ARNI (p=0.006),higher blood glucose(p=0.019), NT-proBNP(p<0.001), cTnI(p=0.007),Left atrial dimension(p=0.003), and lower Ejection fraction (p=0.002).

Levels of TLT-1 and sTLT-1 in patients vs. controls

In Table 3 and Figure 1, the proportion and mean fluorescence intensity (MFI) levels of TLT-1 were found to be significantly elevated in patients with atrial fibrillation (AF) compared to the control group. Furthermore, within the AF group, individuals in the left atrial spontaneous echo contrast (LASEC) subgroup displayed notably higher TLT-1 levels in terms of MFI (p=0.005).

Individual plasma sTLT-1 values were determined in both patients and controls. Consistently, sTLT-1 expressions were upregulated in AF patients compared to the control group (p<0.001, p<0.001). Moreover, the levels of soluble TLT-1 in the LASEC subgroup were significantly elevated in comparison to the non-LASEC subgroup (p=0.039).

Receiver Operating Characteristic (ROC) Analysis

After constructing the receiver operating characteristic (ROC) curves for the biomarkers, the results indicated that the area under the curve (AUC) for TLT-1 and sTLT-1 were 0.708 (95% CI: 0.615-0.789) with a sensitivity of 68.57% and specificity of 67.95%, and 0.662 (95% CI: 0.567-0.748) with a sensitivity of 45.71% and specificity of 87.18%, respectively. The critical value for sTLT-1 levels was determined to be 2478.9 pg/mL. When combining TLT-1 and sTLT-1, the joint AUC was calculated to be 0.745 (95% CI: 0.654-0.822) with a sensitivity of 51.43% and specificity of 88.46%. However, the DeLong's test results suggested that the diagnostic value of the combined biomarkers was not superior to using TLT-1 or sTLT-1 individually.

Risk Factors for LASEC

We further confirmed the potential factors of LASEC (Table 4). Multivariate analysis enrolled variables including gender, age, hypertension, heart failure, CHA2DS2-VASc score, GLU, NT-proBNP, cTnI, TLT-1, LA dimension and EF. Results of multivariate analysis showed NT-proBNP (OR:1.00; 95%CI: 1.00-1.00; p=0.004) and TLT-1 (OR:2.74; 95%CI: 1.05-7.11; p=0.039) were extracted as positive predictors of LASEC.

The prevalence of LASEC was 31.0% in this contemporary NVAF population undergoing TEE examination, which is in line with previous researches^[14,15,16]. In our study, the mean CHA2DS2-VASc of the subject was 2.9 ± 1.5, which is more likely to develop LASEC. In addition, the presence of LASEC was significantly associated with other clinical factors such as age, comorbidities, and echocardiographic parameters in the study population. Further analysis revealed a correlation between LASEC and increased risk of thromboembolic events, highlighting the importance of early detection and appropriate management strategies in individuals with NVAF. These findings underscore the need for tailored therapeutic interventions and closer monitoring of high-risk patients to prevent adverse outcomes associated with LASEC.

Recent research has uncovered a correlation between increased TLT-1 levels and the likelihood of developing acute coronary syndrome and preeclampsia. TLT-1 is situated in conjunction with P-selectin within the alpha granules of both inactive and activated platelets. When platelets are activated, TLT-1's extracellular segment is liberated from the platelet surface. The intracellular portion of TLT-1 comprises 118 amino acid residues and contains several domains facilitating protein-protein interactions[19]. Our study has provided initial evidence indicating heightened TLT-1 expression on platelets in individuals with non-valvular atrial fibrillation (NVAF) and left atrial spontaneous echo contrast (LASEC), suggesting alterations in platelet function in pathological conditions. Furthermore, our findings demonstrate significantly increased levels of soluble TLT-1 (sTLT-1) in patients with atrial fibrillation as compared to the control group. Moreover, the levels of sTLT-1 were notably elevated in LASEC patients compared to those without LASEC.

Washington AV et al. [20] discovered that TLT-1 can interact with fibrinogen and may serve as a biomarker for disseminated intravascular coagulation (DIC). In this study, we assessed the diagnostic accuracy of TLT-1 levels and sTLT-1 concentrations. ROC curve analysis revealed that sTLT-1 at a threshold of 2478.9 pg/mL exhibited excellent sensitivity and specificity in predicting the occurrence of LASEC. Surprisingly, the combined use of TLT-1 and sTLT-1 did not enhance diagnostic efficacy compared to utilizing TLT-1 or sTLT-1 individually. The study also investigated the potential mechanisms underlying the association between TLT-1/sTLT-1 levels and the occurrence of LASEC. It was found that TLT-1's interaction with fibrinogen could influence the coagulation cascade and contribute to the pathogenesis of LASEC. Moreover, the diagnostic value of sTLT-1 in predicting LASEC suggests its potential role as a biomarker for thromboembolic events in patients with NVAF. Further research exploring the molecular pathways involved in TLT-1's interaction with fibrinogen and its impact on thrombotic events could provide valuable insights for the development of targeted therapeutic strategies for LASEC prevention and management.

NT-proBNP is secreted bycardiomyocytes and reflects atrial dysfunction. According to Zhou X et al.^[21], NT-proBNP expressions acts as a fierce predictor for left atrial (LA) or left atrial appendage (LAA) thrombosis in NVAF patients. Consistent with our hypothesis, we found a close relation of high levels of TLT-1 and NT pro-BNP in the presence of LASEC in NVAF patients. This correlation highlights the potential synergistic effects of TLT-1 and NT-proBNP in identifying NVAF patients at higher risk of thromboembolic events, particularly LASEC. The combined assessment of TLT-1 and NT-proBNP levels may provide a more comprehensive approach to risk stratification and management strategies for thromboembolic complications in NVAF patients. Further exploration of the interplay between these biomarkers and their implications in the pathogenesis of LASEC could enhance our understanding of the underlying mechanisms and guide personalized therapeutic interventions for this high-risk patient population.

Of course, the present study has some limitations. This is a monocentric study, therefore the numbers of patients were small. Larger numbers of individuals are required to validate the correlation of TLT-1 expression and LASEC severity. Furthermore, the variables were monitored at a single time point. The variation of TLT-1 levels over time is required in future studies. Moreover, considering that various factors such as genetic predisposition, environmental influences, and lifestyle choices can impact TLT-1 levels, future investigations should also delve into these aspects to paint a more complete picture of its role in the pathogenesis of LASEC. Beyond this, exploring potential therapeutic interventions targeting TLT-1 could have significant implications for the management and prevention of LASEC. Ultimately, a multifaceted approach encompassing diverse research methodologies and interdisciplinary collaboration is crucial in advancing our knowledge of the intricate relationship between TLT-1 and LASEC.

In summary, this study yielded TLT-1 and NT pro-BNP as the risk factors for LASEC presence. We proved, for the first time, that TL-T-1 provided an independent predictor of LASEC occurrence and maybe a decision-making aid for detecting LASEC in NVAF in clinical practice.

Ethics approval and consent to participate

This study involving experiments on humans and the use of human blood samples was conducted in accordance with ethical standards, and all experimental protocols were approved by the First Affiliated Hospital of Soochow University of Ethics Committee . Clinical trial number: 308.

Informed consent was obtained from all human subjects involved in the study. The consent process was conducted in accordance with the First Affiliated Hospital of Soochow University of Ethics Committee. Each participant was provided with detailed information about the study objectives, procedures, potential risks, and benefits, and written consent was obtained before their participation.

Consent for publication

Not applicable, as our study does not involve the collection or publication of any revealing information about individual participants.

Availability of data and materials

Data is provided within the manuscript or supplementary information files.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was funded by Scientific research project of Jiangsu Provincial Health Commission, K2023080.

Authors' contributions

B.D. designed the research and prepared figures and tables; B.D. and C.S.M. collected and analyzed data; L.Y.H. wrote the main manuscript text; L.Y.H. C.S.M. and B.D. performed experiments; C.Z. initiated and supervised the project, analyzed and interpreted results. All authors reviewed the manuscript.

Lip GYH, Brechin CM, Lane DA. The global burden of atrial fibrillation and stroke: a systematic review of the epidemiology of atrial fibrillation in regions outside North America and Europe. Chest. 2012;142(6):1489-1498.
Ueno H, Imamura T, Tanaka S, et al. Left atrial appendage closure for stroke prevention in nonvalvular atrial fibrillation: A current overview. J Cardiol. 2023;81(5):420-428.
Tse HF, Wang YJ, Ahmed Ai-Abdullah M, et al. Stroke prevention in atrial fibrillation--an Asian stroke perspective. Heart Rhythm. 2013;10(7):1082-1088.
Wang H, Xi S, Chen J, et al. Severe Left Atrial Spontaneous Echo Contrast in Nonvalvular Atrial Fibrillation: Clinical Characteristics and Impact on Ischemic Risk Postablation. Thromb Haemost. 2023;123(5):522-534.
Khan AA, Lip GYH. The prothrombotic state in atrial fibrillation: pathophysiological and management implications. Cardiovasc Res. 2019;115(1):31-45.
Chen J, Zhou M, Wang H, et al. Risk factors for left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients with low CHA2DS2-VASc score. J Thromb Thrombolysis. 2022;53(2):523-531.
Akamatsu K, Ito T, Ozeki M, et al. Left atrial spontaneous echo contrast occurring in patients with low CHADS2 or CHA2DS2-VASc scores. Cardiovasc Ultrasound. 2020;18(1):31.
Zhang E, Liu T, Li Z, et al. High CHA2DS2-VASc score predicts left atrial thrombus or spontaneous echo contrast detected by transesophageal echocardiography. Int J Cardiol. 2015;184:540-542.
Healey JS, Amit G, Field TS. Atrial fibrillation and stroke: how much atrial fibrillation is enough to cause a stroke?. Curr Opin Neurol. 2020;33(1):17-23.
Schmoker AM, Perez Pearson LM, Cruz C, et al. Defining the TLT-1 interactome from resting and activated human platelets. J Proteomics. 2020;215:103638.
Smith CW, Raslan Z, Parfitt L, et al. TREM-like transcript 1: a more sensitive marker of platelet activation than P-selectin in humans and mice. Blood Adv. 2018;2(16):2072-2078.
January CT, Wann LS, Calkins H, et al. 2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society in Collaboration With the Society of Thoracic Surgeons [published correction appears in Circulation. 2019 Aug 6;140(6):e285]. Circulation. 2019;140(2):e125-e151.
Ito T, Suwa M. Left atrial spontaneous echo contrast: relationship with clinical and echocardiographic parameters. Echo Res Pract. 2019;6(2):R65-R73.
Rader VJ, Khumri TM, Idupulapati M, et al. Clinical predictors of left atrial thrombus and spontaneous echocardiographic contrast in patients with atrial fibrillation. J Am Soc Echocardiogr. 2007;20(10):1181-1185.
Ito T, Suwa M, Kobashi A, et al. Integrated backscatter assessment of left atrial spontaneous echo contrast in chronic nonvalvular atrial fibrillation: relation with clinical and echocardiographic parameters. J Am Soc Echocardiogr. 2000;13(7):666-673.
Sun S, Ma C, Li Y, et al. Development and validation of a nomogram superior to CHADS2 and CHA2DS2-VASc models for predicting left atrial appendage dense spontaneous echo contrast/left atrial appendage thrombus. J Thorac Dis. 2024;16(3):2102-2114.
He L, Zhang Y, Hou C, et al. Triggering receptor expressed on myeloid cells (TREM) like transcript-1 (TLT-1) reveals platelet activation in preeclampsia. Platelets. 2022;33(8):1132-1138.
Das AA, Chakravarty D, Bhunia D, et al. Elevated level of circulatory sTLT1 induces inflammation through SYK/MEK/ERK signalling in coronary artery disease. Clin Sci (Lond). 2019;133(22):2283-2299.
Washington AV, Quigley L, McVicar DW. Initial characterization of TREM-like transcript (TLT)-1: a putative inhibitory receptor within the TREM cluster. Blood. 2002;100(10):3822-3824.
Washington AV, Gibot S, Acevedo I, et al. TREM-like transcript-1 protects against inflammation-associated hemorrhage by facilitating platelet aggregation in mice and humans. J Clin Invest. 2009;119(6):1489-1501.
Zhou X, Wang Z, Dou S, et al. Biomarkers for Predicting Left Atrial or Left Atrial Appendage Thrombus in Anticoagulated Patients with Nonvalvular Atrial Fibrillation. Cardiol Res Pract. 2020;2020:1683142.

Table 1. Baseline Characteristics of patients with AF and control

Variable	AF group (n=113)	Control group (n=50)	p Value
Male[n(%)]	61 (54)	22 (44)	0.240
Age (year)	67(57-72)	52 (35-59)	<0.001
BMI (kg/m²)	25.05 (22.54-26.90)	23.26 (21.10-25.86)	0.047
Smoking	17 (15)	6 (12)	0.607
Hypertension	67 (59.3)	13(26.0)	<0.001
Diabetes Mellitus	17(15)	1(2)	0.029
Laboratory parameters
PLT(10⁹/μl)	184.0±56.1	218.5±46.3	<0.001
LDL-C(mmol/L)	2.47±0.81	2.60±0.75	0.330
Hs-CRP(mg/L)	1.10 (0.56-3.22)	0.89 (0.56-1.93)	0.269
GLU(mmol/L)	4.96(4.45-5.36)	4.65(4.19-5.02)	0.014
eGFR(mL/min)	87.82±31.09	101.54±24.00	0.006
UA(μmol/L)	357.50±96.75	342.16±78.75	0.326
NT-proBNP(pg/mL)	264.5 (115.9-1268.5)	39.8 (26.8-61.2)	<0.001
cTnI(pg/mL)	8.85 (6.46-13.71)	6.05 (3.68-9.93)	<0.001
Echocardiography
Left atrial dimension (mm)	43.6±5.4	35.7±4.3	<0.001
LVDD (mm)	49(47-51)	47(45-49)	0.001
LVSD (mm)	34 (31-36)	31 (28-32)	<0.001
Ejection fraction (%)	59 (56-62)	65 (60-67)	<0.001

Values are presented as n (%), mean ± SD, or median (Interquartile range). BMI: body mass index; Hs-CRP; high sensitive C-reactive protein; LVDD: left ventricular end diastolic dimension;LVSD:Left ventricular end systolic diameter;PLT:Platelet;LDL-C:low-density lipoprotein cholesterol;GLU:glucose;eGFR:estimated glomerular filtration rate;UA:uric acid;NT-proBNP:N-terminal Pro-Brain Natriuretic Peptide;cTnI:cardiac troponin I.

Table 2 Baseline Characteristics in patients with AF

Variable	non LASEC group (n=78)	LASEC group (n=35)	p Value
Male[n(%)]	47 (60.3)	14 (40.0)	0.046
Age(year)	67 (56-69)	69 (58-74)	0.078
BMI (kg/m²)	24.77(22.49-26.95)	25.36 (23.30-26.47)	0.618
Smoking	12 (15.4)	5 (14.3)	0.880
Hypertension	42 (53.8)	25 (71.4)	0.079
Diabetes mellitus	10 (12.8)	7 (20)	0.324
Coronary artery disease	12 (15.4)	2 (5.7)	0.257
Cerebral infarction	9 (11.5)	3 (8.6)	0.886
Heart failure	9 (11.5)	10 (28.6)	0.025
CHA2DS2-VASc	2.3±1.7	2.9±1.5	0.096
0	13 (16.7)	1 (2.9)
1	15(19.2)	6 (17.1)
≥2	50 (64.1)	28 (80.0)
AF type (n,%)			<0.001
Paroxysmal	51 (65.4)	8 (22.9)
Persistent	27 (34.6)	27 (71.1)
Anticoagulants (n,%)			0.607
Pradaxa	1 (1.3)	0 (0)
Rivaroxaban	71 (91.0)	34 (97.1)
Edoxaban	6 (7.7)	1 (2.9)
Other Medications (n,%)
β-blocker	30 (38.5)	21 (60.0)	0.033
Cordarone	46 (59.0)	28 (80.0)	0.030
Propafenone	11 (14.1)	5 (14.3)	0.979
Dronedarone	1（1.3）	0（0）	1.000
ACEI/ARB/ARNI	34 (43.6)	25 (71.4)	0.006
CCB	22 (28.2)	13 (37.1)	0.342
Laboratory parameters
PLT(10⁹/μl)	186.9±50.6	179.4±67.9	0.613
LDL-C(mmol/L)	2.43±0.83	2.60±0.81	0.403
Hs-CRP(mg/L)	0.97 (0.56-2.94)	1.34 (0.56-4.42)	0.262
GLU(mmol/L)	4.67(4.42-5.26)	5.21(4.78-5.71)	0.019
eGFR(mL/min)	90.25±27.40	86.89±33.33	0.617
UA(μmol/L)	347.69±101.80	381.29±82.43	0.248
NT-proBNP(pg/mL)	202.4 (75.6-560.6)	1352.5 (387.2-2135.3)	<0.001
cTnI(pg/mL)	8.25 (5.77-13.37)	11.71 (8.50-15.46)	0.007
Echocardiography
Left atrial dimension (mm)	42.6±5.3	46.1±4.7	0.003
LVDD (mm)	49(48-51)	48(45-52)	0.436
LVSD (mm)	33 (31-35)	34 (31-36)	0.219
Ejection fraction (%)	60 (57-63)	56 (52-61)	0.002

Values are presented as n (%), mean ± SD, or median (Interquartile range). ARB: angiotensin Ⅱ receptor blocker; ARNI: Angiotensin receptor enkephalase inhibitors; ACEI: angiotensin-converting enzyme inhibitor; BMI: body mass index; CCB: calcium channel blocker; Hs-CRP; high sensitive C-reactive protein; LVDD: left ventricular end diastolic dimension; LVSD:Left Ventricular End Systolic Diameter. PLT:Platelet;LDL-C:low-density lipoprotein cholesterol;GLU:glucose;eGFR:estimated glomerular filtration rate;UA:uric acid;NT-proBNP:N-terminal Pro-Brain Natriuretic Peptide;cTnI:cardiac troponin I.

Table 3. Expressions of TLT-1 and sTLT-1 in patients with AF and control

Parameters	Control (n=50)	Non LASEC (n=78)	LASEC (n=35)	*p^a*	*p^b*	*p^c*
TLT-1 (%)	74.41(54.38-87.44)	86.26(75.06-91.09)	90.05(83.29-91.41)	0.007	<0.001	0.423
TLT-1 (MFI)	2.11(1.83-2.91)	2.65(2.28-3.00)	3.04(2.73-3.35)	0.019	<0.001	0.005
sTLT-1 (pg/ml)	1445.5(1358.9-1641.6)	1608.4(1507.3-1894.2)	1739.7(1608.5-4163.6)	<0.001	<0.001	0.039

MFI: mean fluorescence intensity

Values are presented as Median (Interquartile range). Compared by Mann–Whitney U test.

P^a: Control vs Non LASEC ; P^b: Control vs LASEC ; P^c: Non LASEC vs LASEC.

Table 4. Multivariate analysis:Predictors of spontaneous echo contrast.

	Odds ratio (95% CI)	p
Gender	2.38 (0.75-7.63)	0.143
Age	1.01 (0.93-1.09)	0.908
Hypertension	2.30 (0.65-8.16)	0.197
Heart failure	0.69 (0.06-7.62)	0.765
CHA2DS2-VASc	0.67 (0.33-1.35)	0.260
GLU	1.28 (0.73-2.24)	0.396
NT-proBNP	1.00 (1.00-1.00)	0.004
cTnI	1.00 (0.98-1.02)	0.764
TLT-1(%)	1.02 (0.99-1.06)	0.238
TLT-1 (MFI)	2.74 (1.05-7.11)	0.039
sTLT-1	1.00 (1.00-1.00)	0.078
LA dimension	1.10 (0.98-1.23)	0.126
EF(%)	1.01 (0.93-1.09)	0.897

No competing interests reported.

The Role of triggering receptor expressed on myeloid cells (TREM) like transcript-1 (TLT-1) in left atrial spontaneous echo contrast in patients with non-valvular atrial fibrillation

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