Exploring the Relationship Between Thymosin β4 Protein and First Myocardial Infarction on the Basis of Proteomics

Abstract

Background

Plasma protein alterations may occur in patients with acute myocardial infarction (AMI). In this study, we investigated the plasma proteomics of patients with first‐onset AMI to identify a novel diagnostic target for myocardial infarction.

Methods

Using a case–control design, we recruited 6 patients with first‐onset AMI and 6 age‐ and sex‐matched healthy controls. Mass spectrometry was used to analyze their plasma proteomics. Additionally, we enrolled 156 patients with AMI and 232 healthy individuals to validate the differentially expressed proteins using ELISA.

Results

A total of 58 differentially expressed proteins were identified between the 2 groups (P<0.05, fold change ≥2 or ≤1/2), including 36 upregulated and 22 downregulated proteins. Notably, we discovered a clinically significant protein, thymosin β4 (TMSB4), which was subsequently validated by ELISA. Plasma TMSB4 levels were significantly elevated in patients with first‐onset AMI compared with the control group (1093 [701–1608] ng/mL versus 421 [245–658] ng/mL; P<0.001). Univariate and multivariate logistic regression analyses indicated that TMSB4 is a risk factor for first‐onset AMI. The receiver operating characteristic curve yielded an area under the curve value of 0.849, with an optimal cutoff of 682 ng/mL, sensitivity of 0.808, and specificity of 0.793. A robust correlation was observed between TMSB4 and cardiac troponin I (r=0.9044, P<0.0001), and the κ test yielded a moderate concordance value (κ=0.590 [95% CI, 0.509–0.671]; P<0.001).

Conclusions

TMSB4 holds diagnostic value for first‐onset myocardial infarction and may therefore be considered a potential diagnostic marker for infarction.

Registration

URL: https://www.chictr.org.cn/; unique identifier: ChiCTR2300078144.

Nonstandard Abbreviations and Acronyms

cTnI

cardiac troponin I

TMSB4

thymosin β4

Clinical Perspective.

What Is New?

• The present study used proteomics and ELISA methods to verify that thymosin β4 (TMSB4) is significantly upregulated in patients with first‐onset acute myocardial infarction.

• The level of TMSB4 was quantified, and the relationship between TMSB4 and troponin was evaluated in patients with first‐onset acute myocardial infarction.

• The diagnostic value of TMSB4 was determined.

What Are the Clinical Implications?

• The results of our research indicate that TMSB4 may serve as a potential indicator for the diagnosis of acute myocardial infarction.

• Further research is required to elucidate the dynamic evolution law and mechanism of action of TMSB4 in the occurrence and development of acute myocardial infarction.

Acute coronary syndrome is a severe ischemic heart disease that includes acute myocardial infarction (AMI) and unstable angina. ¹ Myocardial cells are permanent and, when subjected to ischemia and hypoxia, can undergo necrosis. Extensive infarction is life threatening and can lead to malignant arrhythmias (such as ventricular fibrillation), resulting in rapid death. Therefore, the prompt and precise diagnosis of an AMI is of paramount importance.

Thymosin β4 (TMSB4), originally extracted from bovine thymus tissue, has been identified in cardiac tissue. ² This protein has been demonstrated to exhibit antifibrotic properties, promote angiogenesis, inhibit cell apoptosis, and reduce toxic‐induced cellular damage. ³ Most research has focused on its functional roles, but controversy remains regarding its expression in patients with myocardial infarction (MI). Additionally, whether TMSB4 could serve as a novel biomarker for first‐onset AMI has not been thoroughly investigated. To minimize the impact of microenvironmental factors in patients with secondary infarction, we recruited a cohort of patients with first‐onset AMI and conducted proteomic studies, revealing upregulation of TMSB4 in this group.

Methods

This study used a case–control design. The raw data and analytical methods of this article are not publicly available for purposes of reproducing the results or replicating the procedures. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Case Selection

A total of 6 patients who had been admitted to the Second Affiliated Hospital of Shandong First Medical University with a diagnosis of first‐time AMI between September 1, 2023, and September 15, 2023, were recruited for this study. Blood samples were collected within 5 hours after the onset of AMI. The control group comprised 6 age‐ and sex‐matched healthy individuals, with an age difference of no more than 2 years. Furthermore, 156 patients with first‐time AMI admitted to the Second Affiliated Hospital of Shandong First Medical University between September 16, 2023, and June 30, 2024, were included in the study, with blood samples collected within 5 hours after the onset of AMI. The control group for the specified period comprised 232 individuals in a state of good health. The differential protein validation was conducted using ELISA.

AMI diagnosis relied on persistent chest pain symptoms, elevated creatine kinase‐MB and cardiac troponin levels, and ST‐segment depression ≥0.1 mV or ST‐segment elevation with a convex upward pattern. All inclusion criteria were met for study enrollment. All participants in the study provided written informed consent before their involvement. The study was approved by the relevant institutional review board. This research was registered with the Chinese Clinical Trial Registry (https://www.chictr.org.cn/; Registration No. ChiCTR2300078144).

Plasma Collection

Venous blood was collected upon admission using EDTA tubes, which were then gently mixed and centrifuged at 3000 rpm for 10 minutes. Subsequently, the plasma was separated, cleared of residual cells, and stored at −40 °C.

Protein Extraction Method

The extraction of proteins from frozen samples was conducted using High‐Select Top14 Abundant Protein Depletion Resin (Thermo Fisher Scientific, Waltham, MA). The protocol entailed the removal of high‐abundance proteins and the subsequent collection of the protein solution. Subsequently, the samples underwent concentration and buffer exchange, and the protein content was quantified using the bicinchoninic acid assay method, in accordance with the instructions provided in the kit.

Sample Concentration Detection

The bicinchoninic acid assay method was used for the purpose of measuring protein concentration. The process entailed the preparation of standard solutions with varying concentrations of BSA using the Thermo Scientific Pierce BCA Protein Assay Kit. Subsequently, a standard curve was then plotted using a SPECTRA MAX microplate reader (Molecular Devices, Sunnyvale, CA), with absorbance at 562 nm used to ascertain sample concentrations.

SDS‐PAGE Electrophoresis

Following depletion of high‐abundance plasma proteins, SDS‐PAGE electrophoresis was conducted to profile the remaining proteins. Each well was loaded with a sample volume of 10 μg, clearly demonstrating the effective removal of high‐abundance proteins.

Reduction, Alkylation, and Digestion

The protein solution was subjected to the following processing steps: A solution of 100 μg of protein sample was prepared by mixing with tetraethylammonium bromide, resulting in a final concentration of 100 mmol/L. Tris(2‐carboxyethyl)phosphine was then added to achieve a concentration of 10 mmol/L and the mixture was incubated at 37 °C for 60 minutes. Iodoacetamide was introduced to a final concentration of 40 mmol/L and allowed to react in the absence of light at room temperature for 40 minutes. Precooled acetone was added to the mixture (acetone: sample v/v=6:1) and precipitated at −20 °C for 4 hours. After centrifugation at 10 000g for 20 minutes, the precipitate was collected, dissolved in 100 μL of 100 mmol/L tetraethylammonium bromide, and digested overnight at 37 °C with trypsin at an enzyme:protein ratio (m/m) of 1:50.

Peptide Desalting and Quantification

Following trypsin digestion, peptides were dried using a vacuum pump and resolubilized in 0.1% trifluoroacetic acid. Desalting was performed using Hydrophilic–Lipophilic Balance, after which each sample was divided, dried using a vacuum concentrator, and quantified using the Thermo Fisher Scientific Peptide Quantitation Kit.

Liquid Chromatography–Tandem Mass Spectrometry Analysis

Peptides were dissolved in mass spectrometry loading buffer and analyzed via liquid chromatography–tandem mass spectrometry using the EASY‐nLC 1200 system (Thermo Fisher Scientific) coupled with the timsTOF Pro2 mass spectrometer (Bruker, Billerica, MA). Separation was achieved on a C18 column with a mobile phase gradient, and peptides were eluted at a flow rate of 300 nL/min. The timsTOF Pro2 mass spectrometer operated in data‐dependent acquisition mode with positive ion detection, scanning a mass range of 100 to 1700 m/z. Parallel accumulation serial fragmentation mode was used for data collection, with dynamic exclusion set to 24 seconds to prevent redundant parent ion scans.

Protein Qualitative and Quantitative Analysis

The mass spectrometry raw files were imported into MaxQuant software version 2.0.3.1 for database analysis, using the Uniprot database. The following parameters were set: The carbamidomethyl modification was set as a fixed parameter, while oxidation was designated as a variable modification. Trypsin was selected as the protease, and a maximum parent ion mass error of ±10 ppm was permitted. The identification of peptides was constrained by a false discovery rate of no greater than 0.01, with each identified protein requiring at least 1 unique peptide. We used it for multiple validation of differential proteins by applying the Benjamini–Hochberg method for false discovery rate correction.

ELISA Validation of Differential Proteins

The objective of this study was to assess plasma protein levels using the ELISA method to gain further insight into their potential association with first‐time AMI and to explore their diagnostic value for AMI.

Statistical Analysis

A statistical analysis was conducted using the SPSS 25.0 software (IBM, Armonk, NY). To ascertain the normality of the continuous data, the Shapiro–Wilk test was used. Normally distributed data were expressed as mean±SD, and we used independent sample t tests for group comparisons. Nonnormally distributed data were represented by median (interquartile range), and group comparisons were conducted using the Mann–Whitney U test. Furthermore, a univariate/multivariable logistic regression analysis was conducted to ascertain the risk factors associated with the initial occurrence of AMI. Whether a first AMI occurred was used as the dependent variable. We considered sex, smoking, age, hypertension status, white blood cell count, red blood cell distribution width, aspartate aminotransferase (AST), glucose, total cholesterol, triglycerides, high‐density lipoprotein, low‐density lipoprotein (LDL), and TMSB4 as independent variables in a univariate logistic regression analysis. The diagnostic efficacy of differential proteins was also evaluated using the area under the receiver operating characteristic curve. For quantitative data that conformed to a normal distribution, Pearson correlation analysis was used. For ordinal data or data with a skewed distribution, Spearman correlation analysis was used. Additionally, the κ test was used to investigate the consistency between TMSB4 and cardiac troponin I (cTnI). A significance level of P<0.05 was considered statistically significant.

Results

Patient Characteristics

Table 1 presents the basic characteristics of 6 patients with AMI (aged 35–72 years; mean age, 53.67±12.29 years) and 6 healthy individuals (aged 36–74 years; mean age, 54.00±13.28 years). No statistically significant differences were observed between patients with AMI and healthy controls in terms of age, height, weight, body mass index, white blood cell count, hemoglobin, red blood cell distribution width, urea, creatinine, total protein, albumin, total bilirubin, glucose, cholesterol, triglycerides, high‐density lipoprotein, and LDL.

Table 1.

Basic Characteristics of Patients and Healthy People

Variable	AMI group (n=6)	Healthy group (n=6)	P value
Age, y	53.67±12.29	54.00±13.28	0.965
Height, cm	164.17±6.30	166.17±7.99	0.423
Weight, kg	67.83±9.89	63.50±12.66	0.524
Body mass index, kg/m2	25.16±3.10	22.82±2.94	0.21
WBC, ×109/L	10.20±5.49	4.78±0.62	0.06
RBC, ×1012/L	5.04±0.54	4.29±0.44	0.025
Hemoglobin, g/L	145.50 (128.50156.75)	129.00 (125.00165.00)	0.749
Platelets, ×109/L	249.00±39.15	174.17±38.15	0.007
RDW, %	12.15 (11.98–15.23)	12.00 (11.63–12.78)	0.296
BUN, mmol/L	4.09 (3.84–6.16)	4.67 (3.915.83)	0.699
Creatinine, μmol/L	55.40±17.89	52.65±9.43	0.746
STP, g/L	65.90 (62.73–75.86)	68.3 (67.68–74.40)	0.394
Albumin, g/L	39.97±2.84	43.37±0.98	0.02
TB, μmol/L	11.58±4.04	13.05±5.87	0.625
ALT, U/L	33.94±14.53	13.16±1.83	0.017
AST, U/L	57.50 (32.43202.50)	16.00 (13.75, 18.25)	0.016
Glucose, mmol/L	5.19 (4.70–6.32)	4.93 (4.74–5.19)	0.423
TC, mmol/L	5.31 (4.58–6.08)	4.83 (4.31–4.91)	0.128
Triglyceride, mmol/L	1.61±0.98	0.97±0.43	0.186
High‐density lipoprotein, mmol/L	1.22 (1.13–1.46)	1.39 (1.17–1.53)	0.423
LDL, mmol/L	3.16±0.59	2.57±0.34	0.06
cTnI, ng/mL	3.60 (1.59–5.02)	0.2 (0.1–0.32)	0.004

ALT indicates alanine aminotransferase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; cTnI, cardiac troponin I; LDL, low‐density lipoprotein; RBC, red blood cell count; RDW, red blood cell distribution width; STP, serum total protein; TB, total bilirubin; TC, total cholesterol; and WBC, white blood cell count.

Table 2 displays the basic characteristics of 156 first‐onset patients with AMI and 232 controls. Statistical analysis revealed significant differences (P<0.05) in age, smoking, hypertension status, white blood cell count, red blood cell distribution width, alanine aminotransferase, AST, glucose, total cholesterol, triglycerides, high‐density lipoprotein, cTnI, and LDL between the first‐onset AMI group and controls.

Table 2.

Demographic Characteristics of the Validation Group Patients

Variable	AMI group (n=156)	Healthy group (n=232)	P value
Sex, n (%)	Male, 110 (70.5)	156 (67.2)	0.496
	Female, 46 (29.5)	76 (22.8)
Smoking, n (%)	Yes, 106 (76.3)	33 (23.7)	<0.001
(Yes or no)	No, 50 (20.1)	199 (79.9)
Hypertension, n (%)	Yes, 120 (72.3)	46 (27.7)	<0.001
(Yes or no)	No, 36 (16.2)	186 (83.8)
Age, y	66 (56–71)	61 (51–69)	<0.001
WBC, ×109/L	8.675 (6.61, 11.09)	5.805 (5.04, 6.99)	<0.001
RDW, %	13.2 (12.6–14.3)	12.4 (12.1–12.7)	<0.001
ALT, U/L	26.35 (17–42.53)	17 (13–24.75)	<0.001
AST, U/L	37 (23110.75)	19 (16–21)	<0.001
Glucose, mmol/L	6.17 (5.53–7.7)	5.33 (5–5.6575)	<0.001
TC, mmol/L	4.955 (4.1225–7.9)	4.88 (4.39–5.17)	0.04
Triglyceride, mmol/L	1.47 (1.09–2.60)	1.21 (0.78–1.56)	<0.001
High‐density lipoprotein, mmol/L	1.02 (0.87–1.31)	1.34 (1.21–1.34)	<0.001
LDL, mmol/L	3.7 (2.79–5.6)	2.71 (2.39–3.045)	<0.001
cTnI, ng/mL	1.86 (0.48–6.38)	0.049 (0.027–0.074)	<0.001

ALT indicates alanine aminotransferase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; cTnI, cardiac troponin I; LDL, low‐density lipoprotein; RBC, red blood cell count; RDW, red blood cell distribution width; TC, total cholesterol; and WBC, white blood cell count.

Differential Protein Identification in the AMI Group

Following sample preparation, 4‐dimensional label‐free technology was used for liquid chromatography–tandem mass spectrometry analysis, which identified 391 proteins. Of these, 376 proteins exhibited differential expression between the 2 groups (Figure 1). Subsequently, 58 proteins exhibiting notable disparities (fold change ≥2 or ≤1/2, that is, log₂ fold change ≥1 or log₂ fold change ≤−1) were selected for further examination, as illustrated in the volcano plots (Figure 2) and heat maps (Figure 3). Of these, 36 proteins (see Table 3) were found to be upregulated, while 22 were found to be downregulated in patients with AMI.

Figure 1. Venn diagram of differential proteins between AMI and healthy individuals.

The overlapping section of the diagram indicates the number of proteins shared between groups, while the nonoverlapping sections represent the number of proteins unique to each group. The numbers correspond to the count of proteins. ACS indicates acute coronary syndrome; and NOR, normal people.

Figure 2. Differential protein volcano plot.

The volcano plot shows that the values on both axes have been logarithmically transformed. Each point on the plot represents a specific protein. Thirty‐six proteins were upregulated, and 22 proteins were downregulated compared with the 2 patient groups. The blue and red dots represent downregulated and upregulated proteins, respectively, and the gray dots represent no change, with dots closer to the left and upper and upper edges indicating more significant expression differences. FC indicates fold change.

Figure 3. Differential protein clustering heat map.

Each column in the figure represents a sample, and each row represents a protein. The colors in the figure indicate the relative expression levels of the proteins in that group of samples, with red indicating higher expression levels in the sample, and green indicating lower levels. For specific trends in expression level changes, please refer to the numerical annotations below the color bar at the top left. On the left side is a dendrogram representing protein clustering, and on the right side are the names of the proteins. The closer 2 protein branches are, the more similar their expression levels; the dendrogram above represents sample clustering, and the names of the samples are listed below. The closer 2 sample branches are, the more similar the expression patterns of all proteins in those samples, meaning the trends in protein expression level changes are more alike. ACS indicates acute coronary syndrome; and NOR, normal people.

Table 3.

Upregulated Protein Information in AMI Group

Number	Accession	Protein name	Fold change
1	A0A384NYN5	Vinculin	169.28
2	A0A3Q8TLE1	CD59	169.28
3	A0A890W0L6		169.28
4	A8K061		169.28
5	B4DDT1	Hepatic triacylglycerol lipase	169.28
6	F2Z2F1	Myoglobin	169.28
7	P05164	Myeloperoxidase	169.28
8	P08319	All‐trans‐retinol dehydrogenase (NAD [+]) ADH4	169.28
9	P17174	Aspartate aminotransferase, cytoplasmic	169.28
10	Q68GS6	Receptor protein‐tyrosine kinase	169.28
11	F5GY03	SPARC	84.64
12	B4DNF8	Creatine kinase	54.47
13	P07737	Profilin‐1	45.11
14	O00602	Ficolin‐1	37.07
15	P12109	Collagen α‐1 (VI) chain	30.76
16	A0A384MDM4		23.97
17	Q59EE5		15.71
18	O95479	GDH/6PGL endoplasmic bifunctional protein	10.59
19	Q16853	Membrane primary amine oxidase	10.43
20	D6RH03	IL6ST	9.093
21	Q53HF2		7.836
22	B4E2S7		5.962
23	A0A7P0T904	CTSS	5.859
24	P62328	TMSB4	5.632
25	A0A804HHS7	TRIM5	5.514
26	P30041	PRDX6	5.471
27	P04275	von Willebrand factor	3.499
28	P04196	Histidine‐rich glycoprotein	3.388
29	A0A3B3IS80	Fructose‐bisphosphate aldolase	3.249
30	E9PQD6	Serum amyloid A protein	3.093
31	A0A7P0T9S6	Angiotensinogen	2.761
32	P59666	Neutrophil defensin 3	2.598
33	A0A5C2G558		2.558
34	Q53GK6		2.401
35	H0Y4U3	FCGR3B	2.327
36	B2RBZ5		2.25

AMI indicates acute myocardial infarction.

Screening of TMSB4

TMSB4 was upregulated 5.632‐fold in first‐onset MI, suggesting its potential diagnostic value and warranting further investigation.

TMSB4 Expression Levels

Plasma TMSB4 levels were significantly higher in the first‐onset AMI group compared with controls (1093 [701–1608] ng/mL versus 421 [245–658] ng/mL; P<0.001; Table 4, Figure 4).

Table 4.

Plasma TMSB4 Levels in First‐Onset AMI Group and Control Group

	AMI group	Healthy group	P value
TMSB4, ng/mL	1093 (701–1608)	421 (245–658)	<0.001

AMI indicates acute myocardial infarction; and TMSBR, thymosin β4.

Figure 4. Expression levels of TMSB4.

**** indicates P<0.001. TMSB4 is significantly elevated in patients with first‐time AMI. AMI indicates acute myocardial infarction; and TMSBR, thymosin β4.

Diagnostic Value of TMSB4

The result of univariate logistic regression analysis indicated that age, hypertension, white blood cell count, red blood cell distribution width, AST, glucose, total cholesterol, triglycerides, LDL, smoking, and TMSB4 were all significant risk factors for first AMI (P<0.05; Table 5).

Table 5.

Univariate Logistic Regression Analysis for Initial AMI

	B	Wald	OR	95% CI	P value
Smoking	2.548	100.265	12.784	7.764–21.052	<0.01
Sex	−0.153	0.463	0.858	0.553–1.333	0.496
Age	0.032	16.212	1.032	1.017–1.049	<0.01
Hypertension	2.601	107.006	13.478	8.234–22.063	<0.01
WBC	0.724	73.39	2.064	1.748–2.436	<0.01
RDW	1.031	53.168	2.803	2.125–3.698	<0.01
AST	0.135	46.555	1.144	1.101–1.189	<0.01
Glucose	1.495	50.378	4.461	2.952–6.742	<0.01
TC	0.463	32.123	1.589	1.354–1.865	<0.01
Triglyceride	0.97	29.212	2.638	1.856–3.75	<0.01
High‐density lipoprotein	−3.123	59.028	0.044	0.02–0.098	<0.01
LDL	1.179	59.179	3.251	2.408–4.39	<0.01
TMSB4	0.003	85.426	1.003	1.002–1.004	<0.01

AMI indicates acute myocardial infarction; AST, aspartate aminotransferase; LDL, low‐density lipoprotein; OR, odds ratio; RDW, red blood cell distribution width; TC, total cholesterol; TMSB4, thymosin β4; and WBC, white blood cell count.

To further investigate the risk factors, we performed a multivariable logistic regression analysis using significant variables from the univariate analysis (Table 6). Our study revealed that age, smoking, red blood cell distribution width, AST, glucose levels, total cholesterol, and TMSB4 were independent risk factors for first AMI (P<0.05). Additionally, high‐density lipoprotein was a protective factor (P<0.05).

Table 6.

Multivariable Logistic Regression Analysis for Initial AMI

	B	Wald	OR	95% CI	P value
Age	0.083	4.875	1.087	1.009–1.170	0.027
Sex	−0.858	0.729	0.424	0.059–3.04	0.393
Smoking	2.956	5.036	19.213	1.454–253.877	0.025
Hypertension	1.106	0.853	3.024	0.289–31.645	0.356
WBC	0.428	2.539	1.535	0.906–2.6	0.111
RDW	2.132	12.608	8.434	2.6–27.365	<0.001
AST	0.416	10.173	1.516	1.174–1.958	0.001
Glucose	3.529	8.443	34.104	3.154–368.747	0.004
TC	2.731	6.681	15.346	1.935–121.703	0.010
Triglyceride	0.189	0.298	1.208	0.613–2.379	0.585
High‐density lipoprotein	−9.185	8.650	0.001	0–0.047	0.003
LDL	1.027	3.612	2.793	0.968–8.055	0.057
TMSB4	0.003	6.504	1.003	1.001–1. 004	0.011
Constant	−74.271	14.128	0.001		<0.001

AMI indicates acute myocardial infarction; AST, aspartate aminotransferase; LDL, low‐density lipoprotein; OR, odds ratio; RDW, red blood cell distribution width; TC, total cholesterol; TMSB4, thymosin β4; and WBC, white blood cell count.

TMSB4 Diagnostic Performance for First AMI (Receiver Operating Characteristic Curve Area)

The area under the curve of the receiver operating characteristic curve for diagnosing first‐onset AMI using TMSB4 was 0.849 (Figure 5). The optimal cutoff value of 682 ng/mL was selected by maximum Youden's index with a sensitivity of 0.808 and a specificity of 0.793 (Table 7).

Figure 5. ROC curve for TMSB4 in diagnosing first‐time AMI.

The diagnostic value of plasma TMSB4 for first‐onset AMI was assessed using an ROC curve. The area under the curve was 0.849 (95% CI, 0.810–0.888; P<0.001), with ≈80.8% sensitivity and 79.3% specificity. AMI indicates acute myocardial infarction; ROC, receiver operating characteristic; and TMSBR, thymosin β4.

Table 7.

Receiver Operating Characteristic Curve for TMSB4 in Diagnosing Initial AMI

	Area under the curve	95% CI	P value	Optimal threshold	Sensitivity	Specificity
TMSB4	0.849	0.810–0.888	<0.001	682	0.808	0.793

AMI indicates acute myocardial infarction; and TMSBR, thymosin β4.

Evaluation of TMSB4's Diagnostic Ability for First‐Time AMI Compared With cTnI

To gain further insight into the diagnostic potential of TMSB4 for AMI, we conducted a correlation analysis between TMSB4 and cTnI. The results demonstrated a robust correlation between TMSB4 and cTnI (r=0.9044, P<0.0001; Figure 6). This study identified the optimal cutoff value for diagnosing AMI with TMSB4 as 682 ng/mL, while the cutoff value for cTnI used in our hospital is 0.1 ng/mL. To further investigate the consistency between the changes in these 2 markers, a κ test was conducted, which demonstrated moderate consistency between TMSB4 and cTnI (κ=0.590, P<0.001 [95% CI, 0.509–0.671]).

Figure 6. Correlation test between TMSB4 and cTnI.

TMSB4 is positively correlated with cTnI, and the difference is statistically significant (r=0.9044, P<0.0001). cTnI indicates cardiac troponin I; and TMSBR, thymosin β4.

Discussion

The present study is based on proteomic analysis, which identified 376 proteins exhibiting differential expression between the 2 groups under consideration. The criteria for differential expression were set at a P value of <0.05 and a fold change of ≥2 or <1/2. Of the identified proteins, 58 exhibited notable differences, with 36 being upregulated and 22 being downregulated in the plasma. Of particular interest is the identification of a promising protein, TMSB4. Despite the demonstrated significance of TMSB4 in the treatment of AMI, it has yet to be clinically applied.

The proteomic analysis demonstrated that TMSB4 was upregulated in patients presenting with first‐onset AMI. To validate this finding, the study used ELISA verification. The findings demonstrated a markedly elevated plasma TMSB4 concentration in patients with first‐onset AMI in comparison with the control group (P<0.001). In light of these findings, it can be concluded that the results are universally applicable. Furthermore, the diagnostic efficacy of TMSB4 for first‐onset AMI was evaluated using a receiver operating characteristic curve. The area under the curve was 0.849 (95% CI, 0.810–0.888; P<0.001), with ≈80.8% sensitivity and 79.3% specificity. TMSB4 has been identified as a promising biomarker for the early diagnosis of acute myocardial infarction.

Furthermore, the study performed both univariate and multivariate logistic regression analyses. Univariate analysis identified age, hypertension, smoking, white blood cell count, red blood cell distribution width, AST, glucose, total cholesterol, triglycerides, LDL, and TMSB4 as risk factors for first‐onset AMI (P<0.05). Multivariate analysis confirmed that age, smoking, red blood cell distribution width, AST, glucose levels, total cholesterol, and TMSB4 remained significant risk factors (P<0.05).

As outlined in the fourth edition of the “Global Definition of Myocardial Infarction,” elevated troponin levels remain the primary diagnostic criterion for AMI. In accordance with this methodology, the study selected patients within 5 hours of AMI onset for blood sampling, thereby ensuring elevated troponin levels and confirming the diagnosis of AMI.

It is an irrefutable fact that each biomarker is constrained by inherent limitations. For instance, the temporal aspect of cTnI can result in a delayed diagnosis of AMI. Accordingly, our objective is to identify a novel biomarker for the diagnosis of AMI or to use it in conjunction with existing traditional biomarkers to enhance the timeliness of AMI diagnosis.

A correlation test was conducted between cTnI and TMSB4 in patients with AMI, and the results demonstrated a robust correlation between TMSB4 and cTnI. Furthermore, the κ test indicated moderate consistency between the 2 variables. Our findings revealed a significant elevation in both cTnI and TMSB4 levels in patients presenting with first‐onset AMI. This may be attributed to the fact that both cTnI and TMSB4 are present in myocardial cells. In the event of necrosis in these cells, both are released into the bloodstream, resulting in elevated plasma levels.

As an inflammatory disease, AMI triggers the production of various inflammatory‐related factors, including highly sensitive C‐reactive protein, while also inducing the production of anti‐inflammatory substances. TMSB4, an anti‐inflammatory protein, is elevated in patients with AMI, which is to be expected. This suggests that TMSB4 may serve as a novel biomarker for the diagnosis of AMI.

TMSB4 and Its Significance

TMSB4 was initially prepared, assayed, and partially purified by Goldstein et al. ⁴ Our study focused exclusively on patients experiencing their first AMI to avoid potential confounding effects from recurrent AMIs. In 2004, Bock and colleagues corroborated the cardioprotective effects of TMSB4 following injection, ²² thereby stimulating interest in its potential therapeutic applications. Lv et al ⁵ identified an association between TMSB4 and coronary collateral circulation, with significantly elevated expression observed in patients exhibiting well‐developed coronary collaterals. These findings were corroborated by Biçer et al, ⁶ who demonstrated that serum TMSB4 levels were significantly elevated in patients with well‐developed collaterals compared with those with poor collateral development. This indicates the possibility of TMSB4 playing a role in the promotion of coronary collateral circulation.

TMSB4 and Angiogenesis

TMSB4 plays a crucial role in promoting angiogenesis. Researchers have long observed that different concentrations of TMSB4 can enhance blood vessel formation in the chorioallantoic membrane of chicken embryos. ⁷ Bock‐Marquette et al ⁸ found that TMSB4 promotes capillary formation in coronary artery endothelial cells, accompanied by increased expression of vascular endothelial growth factor and other related proteins. This effect may be mediated by TMSB4's ability to stabilize hypoxia‐inducible factor‐1α, leading to enhanced vascular endothelial growth factor transcription even under normoxic conditions. ⁹

Additionally, TMSB4 has been linked to epicardium‐derived progenitor cells, which possess the capacity to regenerate myocardium and coronary vasculature. In vitro studies have demonstrated that TMSB4 induces adult human epicardium‐derived progenitor cells to form vascular precursors with angiogenic potential, thereby ensuring the formation of new vessels to support postinjury cardiac survival. ¹⁰ It is noteworthy that TMSB4 treatment in mice with AMI has been observed to result in increased vascularization. ¹⁰

Moreover, TMSB4 has been demonstrated to modulate purinergic signaling by increasing cell‐surface ATP levels through ATP synthase, thereby acting as a regulator of purinergic signal transduction. ¹¹ Moreover, TMSB4 forms functional complexes with palladin‐associated protein and integrin‐linked kinase, thereby activating protein kinase B, a kinase that has been demonstrated to promote angiogenesis. ¹²

It is important to note that reperfusion of occluded coronary arteries itself can cause ischemia–reperfusion injury. This is characterized by elevated reactive oxygen species, enhanced inflammation, and cell apoptosis. As a result, additional myocardial damage may offset some of the benefits of reperfusion. ¹³ Therefore, proangiogenic therapy appears to be a promising avenue for further investigation. Chronic ischemic cardiomyopathy is typified by impaired left ventricular function, diminished capillary density, and myocardial hibernation. ¹⁴ Revascularization has the potential to reactivate hibernating myocardium; however, not all hibernating cells are suitable for revascularization. Therefore, the promotion of angiogenesis remains a viable approach. Furthermore, TMSB4 can be released from platelets and, through factor XIIIa, adhere to fibrin and collagen, thereby facilitating wound healing and vascular formation. ¹⁵

Antifibrotic Effects of TMSB4

TMSB4 has antifibrotic properties. In vivo, TMSB4 is consistently acetylated at its N‐terminus and additionally acetylated on several internal lysine residues. Subsequently, endogenous proteolytic cleavage generates the acetylated tetrapeptide alanine–cysteine–serine–aspartate–lysine–proline, which has been found to exhibit significant antifibrotic effects in animal models. ⁵ Alanine–cysteine–serine–aspartate–lysine–proline circulates in the bloodstream and is produced by TMSB4 through cleavage involving enkephalinase (also known as aminopeptidase N) and prolyl oligopeptidase (a serine peptidase). Although angiotensin‐converting enzyme can degrade alanine–cysteine–serine–aspartate–lysine–proline, angiotensin‐converting enzyme inhibitors increase serum levels of serine–aspartate–lysine–proline, thereby protecting organs such as the heart and kidneys. ¹⁶

Researchers, including Yang et al, ¹⁷ have discovered that acetyl–serine–aspartate–lysine–proline can reverse inflammation and fibrosis in rats with heart failure following myocardial infarction. In an AMI model, TMSB4 enhances cardiac function by inhibiting nuclear factor‐kB activity, thereby attenuating cardiac fibrosis. ³ Additionally, studies indicate that TMSB4 can reduce the number of fibroblasts in wounds, leading to decreased fibrosis and scar formation. ¹⁶ Higher TMSB4 levels correlate with better prognoses in fibrotic diseases. ¹⁶

TMSB4 has anti‐inflammatory effects and has been confirmed in multiple models. Zhang et al ¹⁸ found that TMSB4 treatment reduced inflammatory cells in meningitis. In a liver injury model, TMSB4 inhibited the phosphorylation of IκB to prevent activation of nuclear factor‐κB, thereby blocking proinflammatory cytokine production. ¹⁹ Research in mice with myocardial infarction showed that continuous infusion of TMSB4 reduced inflammatory cell infiltration. In pig experiments, viral‐transduced TMSB4 extended the survival of transplanted hearts, partly due to reduced inflammation, and reintroducing TMSB4 into infarcted hearts reduced inflammatory cell infiltration.

In atherosclerotic lesions, increased inflammatory cell numbers destabilize plaques. Once a plaque ruptures, atheromatous material is released into the blood, leading to AMI. During AMI, white blood cells and highly sensitive C‐reactive protein levels significantly increase, indicating pronounced inflammation. Using TMSB4 to mitigate inflammation appears to be a viable option. TMSB4 selectively upregulates heme oxygenase, protecting against oxidative damage induced by hydrogen peroxide. ³ Because TMSB4 activation promotes survival of epicardium‐derived cells in response to inflammation‐induced injury, it is considered a promoter of myocardial cell survival. ²⁰

Coronary atherosclerotic heart disease is a chronic inflammatory condition involving macrophages and a multitude of inflammatory factors. TMSB4 appears to confer cardioprotective effects through its anti‐inflammatory properties. Moreover, in the context of AMI, the abrupt occlusion of the coronary artery results in prolonged ischemia in myocardial cells, which are characterized by permanent and nonregenerative damage. TMSB4 has been demonstrated to promote angiogenesis, thereby potentially restoring the blood supply to myocardial cells and reducing ischemia, thus preventing infarct expansion. It is noteworthy that TMSB4 may also play a role in myocardial cell regeneration, which challenges conventional beliefs and merits further investigation.

Additionally, TMSB4 has been demonstrated to mitigate ventricular hypertrophy by inhibiting the WNT1‐induced signaling pathway protein 1. ²¹ As hypertensive heart disease progresses from concentric to eccentric hypertrophy, TMSB4 may prove to be a valuable addition to the treatment armamentarium, particularly in light of the limited options beyond β blockers.

To date, research on TMSB4 has primarily focused on its therapeutic potential for atherosclerosis and MI, with a paucity of studies exploring its potential value in diagnosing AMI. The principal finding of this study is the robust correlation between plasma TMSB4 levels and troponin in patients presenting with an initial episode of AMI, thereby indicating that TMSB4 may serve as a promising biomarker for the diagnosis of AMI. It is postulated that elevated TMSB4 plays a protective role in AMI, analogous to the endogenous compensatory increase of B‐type natriuretic peptide observed in patients with heart failure. Nevertheless, there is currently a paucity of research examining the dynamic evolution and mechanisms of TMSB4 in the occurrence and development of AMI.

Limitations

Our research also has limitations. First, the conclusions of this study require testing on a larger sample. Second, there is a paucity of in‐depth studies examining the dynamic evolution and mechanism of TMSB4 in the context of the onset and progression of AMI.

Conclusions

In conclusion, TMSB4 may represent a promising novel biomarker for the diagnosis of initial AMI, exhibiting high sensitivity and specificity.

Sources of Funding

This work was funded by a grant from the Shandong Province “Double‐Hundred Talent Plan” (WSR2023073).

Disclosures

None.