Circulating-free DNA: A promising tool for early detection of myocardial infarction

Abstract

Myocardial infarction (MI) is a leading global cause of mortality, necessitating novel biomarkers for early diagnosis and prognosis. This review explores circulating cell-free DNA (cfDNA) as a minimally invasive tool for MI detection, focusing on its mechanistic role, diagnostic accuracy, and potential in personalized medicine. CfDNA levels rise rapidly post-ischemic event, correlating with myocardial damage and complementing troponins. Liquid biopsies using cfDNA enable dynamic monitoring of disease progression, but methodological variability and low concentrations limit its standalone use. Standardizing protocols and integrating cfDNA into multi-marker panels could enhance its clinical utility, positioning it as a transformative cardiovascular diagnostic tool.

Graphical abstract

Highlights

• •Circulating cell-free DNA (cfDNA) has emerged as a promising non-invasive biomarker in cardiovascular studies, particularly for MI detection.
• •CfDNA levels increase in response to ischemic events, correlating with myocardial damage and clinical progression, offering potential for real-time monitoring.
• •Liquid biopsy based on cfDNA presents an alternative to traditional tissue biopsies, allowing for continuous monitoring of disease progression and therapeutic response.
• •cfDNA faces challenges, but its use in multi-marker panels may aid early MI detection and risk stratification.

1. Introduction

Ischemic heart disease (IHD) is the leading cause of mortality worldwide, contributing to over 9 million deaths annually, with myocardial infarction (MI) representing its most critical clinical manifestation [1]. MI, often referred to as a heart attack, occurs due to the abrupt interruption of blood flow to the myocardium, resulting in tissue necrosis and potential progression to heart failure [2]. The global burden of MI is particularly pronounced in low- and middle-income countries, where limited access to advanced diagnostic tools and timely interventions exacerbates morbidity and mortality [2]. Despite advancements in reperfusion therapies, such as percutaneous coronary intervention (PCI), approximately 30 % of MI patients experience delayed diagnosis, increasing the risk of adverse outcomes, including cardiac dysfunction [3,4]. These challenges highlight the urgent need for innovative biomarkers to facilitate earlier detection and more effective management of MI [5].

Conventional diagnostic strategies for MI rely primarily on cardiac troponins and electrocardiography (ECG), which, while widely used, have notable limitations [6]. Troponins, although highly sensitive for myocardial damage, often require 6–12 h post-symptom onset to reach detectable levels, delaying early diagnosis [7]. Moreover, troponins lack specificity in non-cardiac conditions, such as sepsis, renal failure, or chronic inflammatory diseases, leading to diagnostic ambiguity [8,9]. ECG, while rapid, may show non-specific changes, particularly in patients with atypical symptoms or pre-existing cardiac abnormalities [10]. These shortcomings underscore the need for complementary biomarkers that can enhance diagnostic precision and support timely clinical decision-making.

Circulating cell-free DNA (cfDNA), released through necrosis and apoptosis during ischemic myocardial events, has emerged as a promising biomarker for MI [11]. CfDNA levels increase rapidly, often detectable within 2 h of chest pain onset, and correlate strongly with infarct size and adverse clinical outcomes, offering a minimally invasive approach to monitor disease progression [11]. Unlike troponins, cfDNA provides insights into the molecular mechanisms of myocardial damage, potentially enabling early risk stratification and individualized clinical management strategies [12]. Studies have demonstrated that cfDNA concentrations are significantly higher in MI patients compared to healthy individuals, suggesting its potential to differentiate cardiac from non-cardiac causes of chest pain [[13], [14], [15]]. However, cfDNA's diagnostic utility is limited by interference from non-cardiac inflammatory conditions, which may reduce its specificity [16]. While plasma biomarkers like cardiac troponin (cTnT) and creatine kinase isoenzyme MB (CK-MB) provide important information regarding myocardial damage, they are not exclusively indicative of acute coronary syndrome (ACS) [17].

To fully realize cfDNA's potential, significant hurdles must be addressed, including methodological variability in detection techniques and the need for standardized protocols [18]. Validating cfDNA assays across diverse populations and overcoming regulatory and commercial barriers, such as obtaining FDA/EMA approval and ensuring cost-effectiveness, are critical steps toward clinical adoption [19]. This review comprehensively examines cfDNA's role in MI, focusing on its release mechanisms, detection methods, and clinical applications, while addressing current standardization and implementation challenges to support its integration into clinical cardiovascular diagnostics.

2. Understanding cfDNA

CfDNA has emerged as a versatile biomarker associated with various conditions, including cancer, cardiovascular diseases (CVDs) such as MI, stroke, and sepsis [15,20]. CVD is anticipated that it will become the primary cause of mortality globally by the year 2030 [21]. Originating from cellular processes like exosomes secretion, apoptosis, and necrosis [22], cfDNA is detectable in bodily fluids such as plasma [23], pleural fluid [24], urine [25,26], cerebrospinal fluid (CSF) [27], and saliva [28,29]. In plasma, cfDNA derives from diverse cell types: erythrocyte progenitors (30 %), granulocytes (32 %), lymphocytes (12 %), vascular endothelial cells (9 %), hepatocytes (1 %), and monocytes (11 %) [30]. Under physiological conditions, macrophages efficiently clear cfDNA fragments; however, in pathological states like cancer or MI, increased cellular turnover or necrosis elevates cfDNA levels [31]. Factors such as exercise, aging, and CVDs (e.g., hypertension, heart failure, MI) further contribute to these elevations [15,30], positioning cfDNA as a promising plasma biomarker [32], notably in cancer (i.e., liquid biopsy) [33].

Although cfDNA analysis is well-established in oncology as circulating tumor DNA (ctDNA) for mutation detection, its utility in cardiovascular contexts is limited due to the absence of tumor-specific mutations and greater biological variability [34]. Unlike ctDNA, cardiac-derived cfDNA lacks highly specific sequence markers, making quantification more reliant on fragment size, methylation patterns, and cell-type deconvolution algorithms

CfDNA fragments typically range from 120 to 220 base pairs (bp), with a characteristic 167 bp peak corresponding to DNA wrapped around a nucleosome plus linker DNA [35]. Fragment size reflects cell death mechanisms: apoptosis produces shorter fragments (180–200 bp) via endonuclease activity, while necrosis yields larger fragments (∼10,000 bp) due to cellular trauma [15]. Fig. 1 illustrates these mechanisms in the context of MI, showing how necrotic and apoptotic cells release cfDNA into the bloodstream within distinct timeframes (1–5 days for necrosis, 12–48 h for apoptosis). Active cells also contribute cfDNA through immune activation or neutrophil extracellular traps (NETs), detectable via techniques like qPCR, DNA sequencing, and digital droplet PCR (ddPCR) (Fig. 1). Digital PCR allows absolute quantification of cfDNA and has shown superior reproducibility and sensitivity in myocardial injury models compared to qPCR [36].

Fig. 1.

Mechanisms of cfDNA release following MI. The figure illustrates the processes of cellular fragmentation resulting from MI, leading to necrosis and apoptosis. Necrotic cells release cfDNA into the bloodstream within 1–5 days, while apoptotic cells contribute within 12–48 h. Additionally, active living cells can release cfDNA through various mechanisms, including the activation of the immune system and the formation of NETs. The assessment of cfDNA is performed using techniques such as qPCR, DNA sequencing, and digital droplet PCR (ddPCR). Created with BioRender.com/JQ27WAV50F, accessed on February 10, 2025.

First identified by Mandel and Metais in 1948 [14,37], cfDNA levels increase in pathological states, particularly in cancer and CVDs [15]. In healthy individuals, cfDNA primarily originates from blood cells, while in cancer patients, circulating tumor DNA (ctDNA) reflects tumor-specific genetic alterations, offering 60–80 % concordance with tumor tissue mutations [30,38]. This makes ctDNA valuable for noninvasive cancer diagnosis and monitoring [39]. However, cfDNA's diagnostic utility in MI is less consistent. Some studies report limited specificity due to cfDNA elevations in non-cardiac conditions like sepsis or exercise [15], necessitating a multi-marker approach (Table 1). Additionally, impaired phagocytic clearance in pathological states can lead to cfDNA accumulation, potentially triggering autoinflammatory responses via inflammasome activation [40].

Table 1.

The dynamics of established biomarkers associated with myocardial infarction.

Biomarker	Thresholds for detection	The procedure of removal
Cardiac troponin	6–48 h	Elevated for up to 14 days
cfDNA	0–2 h	Elevated for 24 h
CK	6–24 h	Decreases within 2–3 days
CRP	Peaks on Day 1–2	Elevated for several weeks
Inflammatory cytokines	Early rise at 45 min, peaks at 1–2 days	Above normal for 12 weeks
MMPs	First hours of MI	Elevated for up to 14 days

While cfDNA's rapid release (0–2 h post-MI) offers earlier detection compared to troponin (6–48 h) [Table 1], its specificity is compromised by elevations in non-cardiac conditions [15]. Studies also highlight variability in cfDNA clearance rates, influenced by factors like renal function or macrophage activity [31], which complicates its use as a standalone biomarker. Negative findings, such as inconsistent correlations between cfDNA levels and MI severity [15]. Regulatory barriers, including standardization of detection methods and validation of clinical utility, further hinder cfDNA's integration into routine MI diagnostics. Commercial challenges include high costs of advanced sequencing techniques and limited availability of cfDNA assays in clinical settings.

Fig. 2 Compares the diagnostic characteristics of cfDNA and troponin, highlighting cfDNA's earlier detection (0–2 h) but lower specificity compared to troponin's delayed peak (6–48 h) and higher specificity.

Fig. 2.

Comparison of cfDNA and troponin in MI diagnosis.

2.1. Techniques and challenges in cfDNA quantification

Quantifying cfDNA is critical for its application as a biomarker in MI and other conditions, but various techniques present distinct advantages and limitations [41]. The fragmented nature of cfDNA (120–220 bp) complicates accurate measurement, as methods differ in sensitivity to fragment size and sample conditions [35].

2.1.1. Quantification techniques

• •Spectrophotometry (e.g., NanoDrop): This method requires high cfDNA concentrations and extensive purification, limiting its sensitivity for low-abundance samples [42]. It is less suited for clinical settings due to its inability to detect fragmented cfDNA effectively.
• •Fluorescence-based assays (e.g., Qubit with PicoGreen): These assays offer improved sensitivity over spectrophotometry but are prone to interference from background fluorescence, particularly in inflammatory conditions common in MI [42]. This reduces their reliability in complex plasma samples. However, fluorescent cfDNA quantification suffers from background interference, particularly in inflammatory environments like sepsis or cardiovascular events [17].
• •Quantitative PCR (qPCR) and Digital PCR (dPCR): qPCR provides sequence-specific quantification, while dPCR enhances this with absolute quantification, better reproducibility, and reduced susceptibility to inhibitors [42]. dPCR is particularly valuable for detecting low-abundance cfDNA in MI diagnostics but requires specialized equipment.
• •Gel Electrophoresis (e.g., Agilent Bioanalyzer): This technique separates cfDNA by size, aiding fragment analysis, but involves labor-intensive sample processing, limiting its scalability [43].
• •Next-Generation Sequencing (NGS): NGS offers detailed sequence information, ideal for identifying specific mutations (e.g., in ctDNA), but is primarily qualitative and costly, restricting its routine use in MI diagnostics [44].

2.1.2. Analytical challenges and limitations

CfDNA quantification faces significant challenges, particularly PCR inhibition by plasma components like heparin and proteins [17]. Heparin, a common anticoagulant, disrupts PCR-based methods and reference gene normalization, though heparinase treatment can mitigate this [45]. However, residual heparin may persist, affecting accuracy. Inflammation, prevalent in MI, exacerbates fluorescence-based assay interference, leading to inconsistent results [17]. Negative findings from studies highlight that qPCR and fluorescence assays often fail to detect low cfDNA levels in early MI due to these interferences [17,42]. Adhering to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines is critical for ensuring reproducibility in cfDNA-based assays. However, most cardiovascular studies fail to report key parameters as outlined by Bustin et al. 2009 [46].

Regulatory and commercial barriers further complicate cfDNA quantification. The lack of standardized protocols for sample preparation and analysis hinders regulatory approval for clinical use. High costs of dPCR and NGS, coupled with the need for specialized equipment and trained personnel, pose commercial challenges for widespread adoption in MI diagnostics.

3. cfDNA in myocardial infarction: mechanisms and clinical implications

CVD is a leading global cause of mortality, with MI posing significant diagnostic and therapeutic challenges [17]. Traditional MI diagnostics often rely on invasive methods, but cfDNA offers a noninvasive alternative. Elevated cfDNA levels correlate with MI severity and provide prognostic insights [17,47]. While established in oncology as a liquid biopsy marker [48], cfDNA's role in MI is emerging, driven by its rapid release and association with myocardial damage [11]. This section examines cfDNA's mechanisms of release in MI and its diagnostic and prognostic potential, critically evaluating its limitations and clinical applicability.

3.1. Mechanisms of cfDNA release in myocardial infarction

Several mechanisms drive cfDNA release during MI, reflecting the complex interplay of cellular damage, inflammation, and immune responses. Oxidative stress and mitochondrial dysfunction act as upstream triggers of myocardial injury, disrupting endothelial integrity and accelerating cellular damage through reactive oxygen species (ROS)-mediated pathways [49]. These processes promote necrosis, immune activation, and impaired clearance mechanisms, all of which contribute to increased cfDNA levels during the acute phase of MI.

3.1.1. Necrotic cell death

Cardiomyocyte necrosis, triggered by ischemia, is the primary source of cfDNA in MI. Oxygen deprivation causes rapid cell death, releasing cfDNA into circulation within 0–2 h of chest pain onset, with concentrations increasing up to 50-fold [11,15]. This rise correlates with troponin and creatine kinase (CK) levels, supporting cfDNA's potential for early MI diagnosis, as tabulated in Table 1. Sources of cfDNA include necrotic cardiomyocytes, inflammatory cells (neutrophils and macrophages) infiltrating the myocardium, and damaged endothelial cells lining coronary arteries [11,50]. The extent of cfDNA elevation reflects myocardial damage severity, aiding prognosis [50]. However, studies note that cfDNA's specificity is limited, as similar elevations occur in non-cardiac conditions like sepsis, reducing its standalone diagnostic value [15].

3.1.2. Inflammatory response and neutrophil activation

Neutrophils, key players in the post-MI inflammatory response, are rapidly recruited to ischemic tissues to clear debris [51]. They release cfDNA through neutrophil extracellular traps (NETs), amplifying inflammation [15,52]. Elevated myeloperoxidase-DNA complexes in patients with coronary atherosclerosis link neutrophil activity to cfDNA levels [15]. While NETs facilitate debris clearance, excessive NET formation may exacerbate tissue damage, complicating recovery [52].

3.1.3. Modulation by circulating nucleases

Circulating nucleases degrade cfDNA systemically, but their activity varies in MI. Increased nuclease activity in blood promotes cfDNA fragmentation, while reduced activity near coronary lesions may allow high-molecular-weight cfDNA to accumulate locally, potentially intensifying inflammation [53].

3.1.4. Association with cardiac remodeling

Elevated cfDNA levels at hospital admission predict adverse cardiac remodeling post-MI, mediated by cfDNA's role in inflammation and tissue repair [54]. However, studies report inconsistent correlations between cfDNA levels and remodeling outcomes, possibly due to variability in patient comorbidities or timing of measurement [55,56]. Additionally, proteomic analyses in MI patients have identified biomarkers such as IL-18R1 and CSF-1 to be strongly associated with plaque burden, and ANGPTL3 with lipid-rich plaques, suggesting their involvement in post-MI vascular remodeling and therapeutic potential [57]. This limits cfDNA's prognostic reliability without complementary markers.

3.1.5. Interaction with Toll-like Receptors (TLRs)

CfDNA activates Toll-like Receptor 9 (TLR9), triggering inflammatory cell recruitment and potentially aggravating myocardial injury. This underscores cfDNA's dual role as both a damage biomarker and a pathogenic mediator [15,58]. Paradoxically, while TLR9 signaling exacerbates inflammation, its deletion leads to post-infarction cardiac rupture—not by altering acute inflammation, but by disrupting fibroblast-mediated repair [59].

3.2. Clinical implications of cfDNA in myocardial infarction

3.2.1. Diagnostic utility

Elevated cfDNA levels exhibit a strong correlation with acute MI, supported by a systematic review showing markedly higher cfDNA in AMI patients versus healthy controls (SMD = 3.47). As a diagnostic tool, cfDNA demonstrates high sensitivity (87 %) and specificity (96 %), positioning it as a promising noninvasive biomarker for early MI detection [11]. However, its specificity is limited by non-cardiac elevations (e.g., exercise, systemic inflammation), underscoring the need for a multi-marker strategy to improve accuracy [60]. Despite its potential, clinical adoption faces challenges, including lack of standardized assays and the high cost of advanced techniques like digital PCR (dPCR) [61].

3.2.2. Prognostic implications of cfDNA levels

CfDNA levels provide valuable prognostic insights for MI outcomes. In ST-elevation myocardial infarction (STEMI), cfDNA concentrations are 5.93 times higher than in healthy controls, correlating with 90-day survival rates and predicting adverse outcomes [50]. The possibility of serial cfDNA assessments for risk classification and treatment optimization is demonstrated by their correlation with 90-day survival rates following MI [50]. Combining cfDNA with troponin, mitochondrial DNA (mtDNA), and microRNAs (miRNAs) enhances prediction of major adverse cardiac events (MACE) in STEMI patients [62].

3.2.3. Integrated diagnostic algorithm for MI

To optimize MI diagnosis, an integrated diagnostic algorithm combining cfDNA with troponin, ECG, and clinical symptoms is proposed [11,63]. CfDNA's rapid detection (0–2 h post-chest pain) enables early screening, while troponin's high specificity (detectable 3–10 h) confirms myocardial injury [Table 1]. ECG identifies ischemic changes, and clinical symptoms (e.g., chest pain, dyspnea) provide contextual evaluation. This multi-marker approach leverages cfDNA's dynamic kinetics and complements troponin's delayed elevation, improving diagnostic accuracy [15]. We propose an integrated diagnostic algorithm (Fig. 3) incorporating cfDNA with ECG, troponin, and clinical symptoms. This approach leverages the early kinetics of cfDNA to complement traditional diagnostics and improve early MI detection.

Fig. 3.

Proposed diagnostic algorithm integrating cfDNA with troponin, ECG, and clinical symptoms to improve early MI detection. Patients presenting with chest pain undergo clinical and electrocardiographic evaluation. If ECG findings are non-specific or equivocal, cfDNA measurement (detectable within 0–2 h post-symptom onset) can support early diagnosis, especially before troponin becomes elevated. A combined multi-marker strategy may enhance diagnostic accuracy and facilitate early intervention.

4. Advantages of cfDNA for early detection of myocardial infarction

CfDNA has shown significant potential for enhancing early detection and management of MI due to its rapid dynamics and noninvasive nature [64]. While immunohistochemical markers [65] and machine learning models (accuracy >80 %, 13-min intervention window) [66] enhance rapid MI diagnosis, cfDNA's unique properties improve early intervention and patient outcomes. This section evaluates cfDNA's advantages, limitations, and clinical potential in MI diagnostics, addressing its role alongside traditional biomarkers.

4.1. Limitations of current diagnostic markers

The gold standard for MI diagnosis integrates a rise and fall in cardiac troponin levels with clinical symptoms (e.g., angina pectoris) and ECG changes [67]. However, troponin has notable limitations. Elevations can occur in non-ischemic conditions, such as post-major surgery, sepsis, trauma, or renal failure, complicating diagnosis and increasing morbidity and mortality risks [68]. Standard troponin assays (cardiac troponin I)cTnI(and T)cTnT(.) detect elevations 4–10 h post-symptom onset, while high-sensitivity assays (hs-cTnT, hs-cTnI) reduce this to 3 h [62]. Troponin remains elevated for up to 14 days, limiting its ability to reflect real-time cardiovascular status, especially in patients with chronic kidney disease (CKD) or after strenuous exercise [69].

In contrast, cfDNA's short half-life (16 min–2 h) allows dynamic monitoring of myocardial injury and treatment response [31]. Studies demonstrate a significant correlation between elevated cfDNA and peak troponin levels in MI patients, indicating comparable sensitivity to myocardial damage [11,69]. The cost-effectiveness and minimally invasive nature of cfDNA analysis via blood collection further enhance its clinical appeal [64].

4.2. Advantages of cfDNA as an MI biomarker

CfDNA offers several key advantages for MI detection.

• •Early detection: cfDNA levels rise within 0–2 h post-chest pain onset [15], enabling earlier diagnosis and intervention compared to troponin's elevation (3–10 h). This rapid response supports timely clinical decision-making.
• •Sensitivity and specificity: Studies report cfDNA sensitivity of 69–79 % and specificity of 83–89 % at a threshold of 0.20 mg/mL [15]. Another study demonstrated superior diagnostic efficacy (sensitivity of 87 %, specificity of 96 %, and AUC of 0.96) for MI. A systematic review by Tan et al. confirmed significantly higher cfDNA levels in AMI patients versus healthy controls, reinforcing its diagnostic robustness [11].
• •Rapid clearance: cfDNA returns to baseline within 1–2 days post-MI [15], allowing repeated measurements for dynamic monitoring of disease progression and treatment response.
• •Minimally invasive: cfDNA analysis requires only a blood, avoiding invasive tissue biopsies [70], which improves patient comfort and feasibility.
• •Correlation with necrosis: cfDNA levels correlate strongly with troponin (Spearman correlation coefficient 0.79) and CK [15,20]. Notably, cfDNA can be elevated even when CK levels are normal, indicating potential sensitivity in specific contexts [15].
• •Multi-marker panels: Integrating cfDNA with troponin and CK leverages their distinct release kinetics and clearance rates [15], enhancing diagnostic accuracy and providing a comprehensive assessment of myocardial damage.
• •Renal function independence: Unlike troponin, cfDNA levels are unaffected by renal function, making it a valuable for patients with kidney disease [15].
• •Dynamic changes: cfDNA's rapid fluctuations (half-life 4–30 min) [15] enable monitoring of therapeutic responses and disease progression, completing troponin's prolonged elevation.
• •Cost-effectiveness: cfDNA measurements via blood sampling are generally more cost-effective than other diagnostic methods, enhancing accessibility [71].
• •Risk stratification: Elevated cfDNA levels predict increased risk of post-MI complications [15], supporting its prognostic utility alongside troponin [11].

CfDNA's rapid kinetics—early rise and swift clearance—make it uniquely valuable for early MI detection and real-time monitoring, overcoming troponin's limitations of delayed elevation and prolonged persistence [72]. The strong correlation between cfDNA and troponin (both markers of necrotic cell death) supports their combined use for assessing injury severity and cardiomyocyte loss [68,69]. Elevated cfDNA also predicts adverse post-MI outcomes, enhancing its prognostic value [11]. Mechanistically, troponin and cfDNA both signal myocyte necrosis, reinforcing their complementary roles [68].

While high-sensitivity troponin assays improve earlier detection, their diagnostic gaps (e.g., in CKD or recurrent MI) and prolonged elevation persist as challenges. CfDNA's dynamic profile and tissue-agnostic origin offer a complementary approach, enabling earlier and more comprehensive injury assessment.

5. Current research and clinical applications of cfDNA in myocardial infarction

This section reviews key studies on cfDNA's role in MI, emphasizing its clinical potential and integration into diagnostic strategies.

5.1. cfDNA as a diagnostic marker for MI

Recent studies highlight cfDNA's diagnostic promise in MI, often outperforming or complementing traditional biomarkers. Jing et al. (2011) [73] developed a bDNA-based Alu assay, showing significantly higher cfDNA levels in MI patients than controls, with an earlier peak than cardiac troponin I (cTnI). This early detection (0–2 h post-chest pain) supports cfDNA's role as a complementary marker (referred to Table 1). Chang et al. (2003) and Xie et al. (2018) reported cfDNA levels 5–10 times higher in acute MI (AMI) patients compared to controls, with peaks later than CK-MB but correlating with disease severity and complications, reinforcing its utility in multi-marker strategies [14,74]. Kamal et al. (2018) used real-time PCR to demonstrate that specific cfDNA fragments peak on day 1 of AMI, correlating with lipid profiles and cardiac markers, enhancing its value as an early diagnostic tool [75].

Lou et al. (2015) validated a highly sensitive Alu-based real-time PCR method (Alu5), achieving superior diagnostic accuracy (AUC = 0.968) compared to cTnI, CK-MB, and lactate dehydrogenase (LDH) [76]. Alu4, Alu5, and Alu assays showed higher sensitivity and specificity for MI diagnosis, highlighting their reliability and precision for cfDNA quantification [76]. Shimony et al. employed a novel fluorometric assay, finding elevated cfDNA peaks in ST-elevation MI (STEMI) patients that correlated with CK and troponin-T, suggesting cfDNA's potential to enhance traditional biomarkers [77]. These findings underscore cfDNA's rapid detection and robust correlation with myocardial damage, making it a valuable addition to MI diagnostics.

5.2. cfDNA as a prognostic marker for MI

Beyond diagnosis, cfDNA has shown promise as a prognostic marker for MI. Antonatos et al. [78] observed persistently elevated cfDNA levels on day 2 in complicated post-infarction cases, indicating its value for monitoring acute MI (AMI) progression and predicting prognosis. Chu et al. [50] reported a strong correlation between serial cfDNA measurements over seven days and survival outcomes in ST-elevation MI (STEMI) patients, with an ROC cutoff value of 2.50 demonstrating high sensitivity and specificity for predicting survival. Zhang et al. [54] found that higher cfDNA levels at admission in AMI patients correlated with cTnI, sST2, and LDL cholesterol levels, predicting heart failure development.

5.3. Mechanisms and interplay with other factors

Several studies have investigated the mechanisms underlying cfDNA release and its interplay with other factors in MI, as summarized in Table 2. Dash et al. [47] analyzed cfDNA and genomic DNA (gDNA) methylation patterns, identifying cfDNA as a reliable marker for cardiac-specific changes, primarily from neutrophils (∼75 %) and cardiac tissues (∼10 %). Methylation profiles linked to relevant pathways highlight cfDNA's specificity for MI-related damage [47]. Artner et al. (2018) found elevated high molecular weight cfDNA at coronary lesion sites, inversely correlated with nuclease activity, emphasizing nucleases' role in regulating cfDNA levels and fragment size in thrombotic cardiovascular diseases [17]. Sanchis et al. (2020) reported a small peripheral-coronary cfDNA gradient during angioplasty, associated with adverse outcomes, suggesting cfDNA's potential as a marker of angioplasty success [52].

Table 2.

Summary of key studies investigating the role of cfDNA in MI: Diagnostic and prognostic insights.

Type of experiment	Target	Study populations	Characteristic(s)	Key findings	Clinical applications	Ref.
Quantitative clinical study	cfDNA	130 CVD patients, 30 healthy controls	Elevated cfDNA levels in AMI; trends linked to disease severity and recovery patterns.	5-fold increase in cfDNA during onset.	Potential biomarker for high-risk patients.	[14]
Quantitative clinical study	cfDNA	13 AMI patients, 30 healthy controls	cfDNA correlated with CK, TnI, and clinical complications post-infarction.	Elevated cfDNA in complicated cases.	Prognostic marker for post-AMI outcomes	[78]
Epigenetic study	cfDNA methylation patterns	25 AMI patients	Global methylome profiles of cfDNA and gDNA compared; cfDNA predominantly from cardiac and neutrophil sources.	cfDNA methylation linked to cardiac-specific pathways (e.g., cAMP signaling).	Potential biomarker for cardiac-specific processes and therapeutic targets in AMI.	[47]
Quantitative clinical study	cfDNA	150 STEMI patients, 50 controls	Serial cfDNA monitoring using fluorescence assay; daily changes tracked over 7 days.	cfDNA levels 5.93 times higher in STEMI; ROC cutoff value predicts survival.	Early prognostic factor for survival in STEMI patients	[50]
Quantitative clinical study	cfDNA	55 MI patients, 274 controls	Serum cfDNA levels in MI patients quantified using QIAamp and PicoGreen kits; gel electrophoresis performed.	cfDNA levels >10-fold higher in MI patients; peaked behind CK-MB.	Complementary marker to CK-MB and troponin in MI diagnosis.	[83]
Quantitative clinical study	cfDNA	16 STEMI patients, 47 controls	CFD measured via novel fluorometric assay; correlated with CK and troponin-T but not EF.	CFD levels significantly higher in STEMI patients; correlated with necrosis markers	May complement traditional biomarkers; kinetic pattern requires further study.	[77]
Quantitative clinical study	cfDNA	50 AMI patients, 30 controls	cfDNA levels assessed using PCR; peak levels of specific cfDNA fragments on day 1 of AMI	.Elevated cfDNA correlated with lipid profiles and cardiac markers	Early biomarker for AMI; complements troponin-I and CK-MB in diagnosis.	[75]
Quantitative clinical study	cfDNA	116 STEMI patients	Peripheral and coronary cfDNA gradients analyzed during primary angioplasty with thrombus aspiration.	Small cfDNA gradient linked to no STR and reduced TIMI 3 flow.	Reflects neutrophil activation; potential marker for angioplasty outcomes.	[52]
Quantitative clinical study	cfDNA	59 MI coronary aspirates, 96 peripheral arterial sites, 363 controls	Total cfDNA, elongated DNA, and nuclease activity analyzed; DNA length and integrity studied as biomarkers.	Elevated high-molecular-weight cfDNA accumulates at culprit lesion; inversely correlated with nuclease activity.	DNA length and integrity are novel biomarkers in thrombotic cardiovascular disease	[53]
Prospective cohort study	cfDNA; cardiac troponin I (cTnI), and soluble ST2 (sST2)	98 AMI patients	cfDNA measured at admission; correlation with risk factors for heart failure (HF) post-AMI.	High cfDNA correlated with cTnI, sST2, and LDL; predicts HF risk with HR of 2.805.	Early predictor for HF development in AMI patients; potential clinical biomarker.	[54]
Epigenetic study	Heart-derived cfDNA	∼176 MI patients, 25 controls	MCTA-seq analysis of dynamic cfDNA changes; identified hypermethylated loci and heart-released cfDNA	CORO6 marker detected myocardial damage via ddPCR; cfDNA originated from heart and WBCs post-PCI.	ddPCR assay for myocardial damage detection; insights into MI pathologies.	[84]
Animal model and human study	cfDNA	1798 patients with stroke	NETosis-derived cfDNA triggers AIM2 inflammasome activation, destabilizing plaques and causing recurrent stroke	Neutralizing cfDNA or inhibiting inflammasome activation reduces stroke recurrence and plaque destabilization	Targeting cfDNA-mediated inflammation offers new strategies to prevent recurrent strokes and ischemic events.	[3]
Animal and clinical study	Splenic NLRP3 activation	MI/R mouse model, CPB patients	Splenic NLRP3 inflammasome activated by mitochondrial cfDNA via TLR9, exacerbating inflammation and injury.	NLRP3 inhibition or adoptive transfer of NLRP3−/− splenocytes reduced infarct size and inflammation	Potential target for reducing MI/R injury via mitochondrial cfDNA and TLR9 modulation.	[80]
Quantitative clinical study	cfDNA and MPO (neutrophil activation) levels	59 cardiac disease patients (MI and other cardiac diseases), healthy controls	Plasma levels of cfDNA, M30 (apoptosis), M65, CyPA (necrosis), and MPO assayed. MPO linked to neutrophil activation and NETosis.	cfDNA significantly higher in cardiac disease patients, especially MI. MPO levels were elevated in MI cases.	Supports cfDNA and MPO as diagnostic markers, especially for myocardial infarction.	[79]
Quantitative clinical study	cfDNA, citH3−DNA, and rs2431697 of miR-146a	359 young ACS patients (<45 years)	Analysis of NET markers (cfDNA and citH3−DNA), miR-146a SNP (rs2431697), and cardiovascular outcomes.	cfDNA levels were elevated in all patients. CitH3−DNA was higher during the first ACS event. T allele correlated with higher NET markers. Patients with elevated markers had a 2-fold risk of recurrence.	Highlights thromboinflammatory mechanisms in young ACS and identifies rs2431697 and NET markers as predictors of recurrence.	[81]
Quantitative clinical study	cfDNA	80 STEMI patients, 50 controls	Measured cfDNA levels in AMI using Qubit 3.0 (ss-DNA and ds-DNA kits), NanoDrop, and qPCR	cfDNA significantly elevated in AMI patients compared to controls. Qubit ss-DNA kit provided the highest accuracy, comparable to qPCR	Novel cfDNA quantification methods may improve AMI diagnosis and clinical management	[85]
Animal study	HMGB1 and cfDNA	C57BL/6 wild-type, RAGE KO, TLR9 KO mice	Investigated HMGB1 and cfDNA release during myocardial ischemia-reperfusion injury (IRI) and their interaction via RAGE-TLR9.	HMGB1 and cfDNA are released during IRI and exacerbate infarct size via RAGE-TLR9. Depleting either marker reduced infarct size by ∼50 %	Highlights the therapeutic potential of targeting HMGB1 or cfDNA to reduce myocardial injury in IRI	[82]
Quantitative clinical study	Alu-based cfDNA detection	120 MI patients, 60 healthy controls	Developed and validated an Alu-based real-time PCR method for cfDNA quantification.	cfDNA levels higher in MI patients than controls. Alu5 showed the highest diagnostic accuracy (AUC = 0.968).	Reliable and sensitive method for cfDNA detection; Alu5 is a superior biomarker for MI diagnosis.	[76]
Quantitative clinical study	bDNA-based Alu assay for cfDNA	22 MI patients, 60 controls	Quantified cfDNA using a novel branched DNA (bDNA)-based Alu assay and compared it with conventional biomarkers.	cfDNA was significantly higher in MI patients and peaked earlier than cTnI. No correlation with CK-MB, cTnI, or MYO	Supports cfDNA as a complementary biomarker to conventional cardiac markers in MI	[73]

CyPA: Cyclophilin A; MPO: myeloperoxidase.

CfDNA interacts significantly with inflammatory pathways in MI. Fujihara et al. [79] observed elevated cfDNA and myeloperoxidase (MPO) levels, a marker of neutrophil extracellular trap (NET) formation, in MI patients, supporting their combined use as diagnostic markers. Cao et al. [3] demonstrated that NETosis-derived cfDNA activates the AIM2 inflammasome in vulnerable plaques post-stroke, contributing to inflammation and MI recurrence, positioning cfDNA as a therapeutic target. Xie et al. (2023) showed that mitochondrial cfDNA activates the splenic NLRP3 inflammasome via TLR9 during myocardial ischemia/reperfusion, exacerbating MI and highlighting mitochondrial cfDNA as a potential therapeutic target [80]. De Los Reyes-Garcia et al. (2022) found elevated cfDNA and citH3-DNA levels in young acute coronary syndrome (ACS) patients (<45 years), correlating with worse cardiovascular outcomes. The miR-146a SNP rs2431697 (T allele) was linked to increased NET markers, with high cfDNA, citH3-DNA, and T allele levels associated with a two-fold higher risk of recurrence [81]. Tian et al. [82] demonstrated that HMGB1 and cfDNA released during ischemia-reperfusion injury amplify myocardial damage via a RAGE-TLR9-dependent mechanism.

To develop and validate a fast and sensitive method, Lou et al. (2015) developed a novel Alu-based real-time PCR method for sensitive and reliable detection of cfDNA. This method showed that cfDNA levels were significantly higher in patients with MI than in controls, with Alu5 demonstrating superior diagnostic accuracy.

6. Challenges and limitations of cfDNA as an MI biomarker

CfDNA shows significant promise as a biomarker for MI, but its widespread clinical adoption is hindered by pre-analytical, analytical, and biological challenges that affect reliability and reproducibility.

6.1. Pre-analytical and analytical variability

A primary obstacle to cfDNA's clinical use in MI diagnosis is the lack of standardized pre-analytical procedures across laboratories. Variations in sample collection (e.g., anticoagulant type), processing delays, and storage conditions significantly impact cfDNA yield, integrity, and fragment length [64]. For instance, improper pre-analytical management can lead to cfDNA degradation and modified nucleosides, potentially causing misclassification of mutations and affecting diagnostic accuracy [29]. Only 12.5 % of laboratories can reliably amplify DNA fragments larger than 400 bp, highlighting the urgent need for standardized protocols to ensure consistent results [64].

Analytical variability further complicates cfDNA quantification. Methodological differences across studies, such as the use of digital PCR (dPCR) versus other techniques, contribute to heterogeneity in reported cfDNA levels in AMI patients, limiting data comparability in meta-analyses [11]. Digital PCR, particularly Bio-Rad Droplet Digital PCR (ddPCR), offers precise quantification of known mutations through end-point PCR across thousands of droplets without calibration reactions, providing high sensitivity and reproducibility [36]. However, the absence of a universal protocol for cfDNA collection, processing, and analysis tailored to AMI diagnosis remains a significant barrier [11]. Standardization across all platforms is critical to ensure reliable and reproducible results.

6.2. Biological variability and low cfDNA concentration

CfDNA exists at low concentrations in plasma (1–50 ng/mL in healthy individuals), which poses analytical challenges for accurate detection and quantification [86,87]. Fragmentation and degradation of cfDNA further hinder molecular analyses, as the small fragment sizes (120–220 bp) require highly sensitive assays. In contexts like cancer, low variant allele frequencies (VAFs) of mutations lead to Poisson sampling noise, reducing the reproducibility of VAF profiling and the accuracy of detecting specific alterations. For MI, similar issues arise when targeting cardiac-specific cfDNA, as low concentrations limit assay sensitivity. Increasing the analyzed cfDNA volume is a primary strategy to improve detection, but this requires optimized sample collection and processing protocols [13].

Biological factors significantly influence cfDNA levels and characteristics. Urinary excretion, modulated by fluid intake, affects cfDNA clearance rates, while overall health, impacted by exercise or infections, alters cfDNA concentrations. In cancer, tumor size, location, and vascular access further modify cfDNA profiles, and similar variability is likely in MI due to differences in myocardial damage extent and inflammatory responses. The presence of abundant wild-type cfDNA can dilute disease-specific molecules, reducing assay sensitivity for detecting MI-related alterations [86,88]. These factors add complexity to cfDNA's use as a reliable MI biomarker, necessitating robust analytical methods to account for variability.

6.3. Contamination and technical limitations

Contamination and technical limitations pose significant challenges to the reliable use of cfDNA as a biomarker for MI, complicating its clinical implementation [86,88]. Cellular DNA contamination during sample collection and processing can introduce false positives and misinterpretations in cfDNA analysis, undermining diagnostic accuracy for MI [86]. Strict protocols, such as prompt double centrifugation of fresh venous blood to separate plasma, are essential to minimize contamination [88]. Environmental factors, including temperature and pH during storage, further affect cfDNA stability and quality, potentially altering fragment integrity and quantification results [89]. The absence of a definitive gold standard for cfDNA analysis results in interlaboratory discrepancies, hindering reproducibility and clinical adoption [90]. Older technologies often lack the sensitivity and specificity needed to detect low-frequency variants, limiting their effectiveness for MI diagnostics [88]. These technical limitations necessitate the development of advanced, reliable techniques to ensure accurate cfDNA analysis.

6.4. Other confounding factors and dynamic nature

Several factors confound cfDNA interpretation in MI diagnostics. Genetic variability among patients, particularly in diverse populations, adds complexity to result interpretation, as individual genetic profiles influence cfDNA levels and characteristics. Conditions like obesity can elevate cfDNA levels, potentially complicating diagnostic specificity [31]. The dynamic nature of cfDNA levels post-MI, with a rapid peak around 2 h and subsequent decline [11,31], complicates the standardization of the measurement timing. Limited longitudinal data on cfDNA fluctuations after MI further hinder our understanding of its long-term clinical utility. Furthermore, studies have suggested that variations in telomeric sequences in cfDNA may influence the immune response to diseases [31]. The question of whether elevated cfDNA reflects larger myocardial injury or contributes to regulating wound healing underscores the need for cautious interpretation and further research into its origins, pathways, and genetic sequences [31].

6.5. Addressing the challenges

The primary barrier to cfDNA's clinical adoption for MI diagnosis is inconsistency in biospecimen handling during the pre-analytical phase. Strict adherence to validated standard operating procedures (SOPs) for sample collection, labeling, processing, and extraction is critical to minimize variability in cfDNA yield, integrity, and fragment length. These SOPs ensure reproducible results across laboratories, addressing issues like contamination and degradation [64]. Despite these challenges, ongoing research continues to explore the potential of cfDNA as an MI biomarker and assess associated complications. Addressing these limitations through standardized protocols, larger prospective studies and mechanistic investigations are essential to establish cfDNA's diagnostic reliability and elucidate its role in MI pathology [11].

7. Future directions and perspectives

CfDNA has shown significant potential in prenatal testing and liquid cancer biopsies, but its application in CVD, particularly MI, requires further exploration [15]. To realize cfDNA's clinical utility in MI management, several research areas merit attention.

Harmonizing pre-analytical and analytical methodologies is critical for reliable and reproducible cfDNA measurements. Diverse protocols for cfDNA extraction and quantification currently lead to inconsistent results, complicating interlaboratory comparisons [11,15]. Standardized procedures for sample handling and analysis are essential to ensure consistency. Addressing pre-analytical variables, such as sample collection and storage, will enhance cfDNA's reliability as a diagnostic tool.

Integrating cfDNA with established biomarkers like troponin and creatine kinase-MB (CK-MB) could improve diagnostic accuracy for myocardial injury [15,83]. Longitudinal studies are needed to elucidate cfDNA release dynamics and identify optimal intervention windows [15]. The development of rapid point-of-care testing devices for cfDNA analysis could enable immediate decision-making in emergency settings, facilitating timely interventions for patients with chest pain or other MI symptoms [15,91].

Further research should explore the mechanisms of cfDNA release during myocardial injury, including contributions from cardiomyocytes and inflammatory cells [92]. Analyzing cfDNA methylation patterns may reveal indicators of cardiac stress and injury, aiding CVD risk stratification. Advanced genomic and transcriptomic analyses of cfDNA could identify novel MI-associated biomarkers and genetic signatures predicting susceptibility to myocardial injury or recovery outcomes [15]. The interplay between cfDNA, troponin, and other biomarkers needs further investigation to clarify the mechanisms responsible for cardiomyocyte death and to establish combined biomarker panels for improved diagnostic and prognostic accuracy.

To effectively translate cfDNA into clinical practice for MI diagnosis, several key steps are necessary. First, it is crucial to establish well-defined clinical guidelines, including specific diagnostic thresholds and seamless integration into existing diagnostic protocols, is crucial [93]. Furthermore, robust, large-scale clinical trials across diverse patient populations are required to validate the clinical utility of cfDNA and to thoroughly assess its impact on patient outcomes. Finally, comprehensive cost-effectiveness analyses comparing cfDNA testing with established diagnostic methods are essential to justify its widespread adoption in routine clinical settings [15]. Furthermore, addressing pre-analytical variables related to sample handling and storage is critical for ensuring the reliability of cfDNA as a diagnostic tool. Ethical considerations regarding patient consent and data privacy must also be addressed as cfDNA testing becomes more prevalent [94].

Despite the promising potential of cfDNA as an early biomarker in MI, its integration into clinical workflows faces several regulatory and commercial challenges. From a regulatory standpoint, cfDNA assays must undergo rigorous validation to meet standards set by authorities such as the FDA or EMA, particularly for analytical sensitivity, specificity, and reproducibility in the acute care setting. Currently, most cfDNA-based platforms are optimized for oncology or prenatal diagnostics, and none are yet approved specifically for cardiovascular applications, creating a translational gap [95]. Commercial barriers also hinder adoption. These include the high cost of cfDNA sequencing or quantitative PCR-based platforms, limited availability of point-of-care-compatible cfDNA technologies, and the need for rapid turnaround times in emergency settings—an area where troponin assays already excel. Additionally, reimbursement frameworks for cfDNA-based diagnostics in cardiology are not yet established, deterring clinical laboratories and healthcare systems from adopting the technology [96].

Future research on cfDNA in MI diagnosis should focus on standardizing pre-analytical and analytical methods, enhancing test sensitivity and specificity, and developing point-of-care testing [15,91]. Integrating cfDNA with combinatorial biomarkers like TyGi could improve diagnostic accuracy [97]. Comprehensive AMI management programs may incorporate cfDNA to enhance clinical protocols [98]. Exploring cfDNA's role in post-MI complications, such as cardiomyopathy, and analyzing its methylation patterns could identify novel biomarkers and predict outcomes [15,99]. Large-scale clinical trials and cost-effectiveness analyses are essential to validate cfDNA's clinical utility.

8. Conclusion

CfDNA has emerged as a significant biomarker due to its non-invasive nature and ability to reflect real-time physiological status. This review highlights cfDNA's potential in diverse applications, including infectious diseases, cancer, organ transplantation, prenatal diagnostics, and particularly MI. Research underscores cfDNA's promise for improving patient management and health outcomes through early detection and dynamic monitoring. Despite challenges in data interpretation and procedure standardization, advancements in sequencing technologies, bioinformatics, and nanotechnology are expected to enhance cfDNA's clinical utility, transforming personalized medicine. Ongoing research and development are essential to fully realize cfDNA's potential as a versatile biomarker and translate these innovations into meaningful improvements in human health.

CRediT authorship contribution statement

Sajjad Rafiei: Writing – original draft, Investigation. Amir Modarresi Chahardehi: Writing – original draft, Project administration, Investigation. Vuanghao Lim: Writing – review & editing, Project administration, Funding acquisition, Conceptualization.

Funding

We would like to thank Universiti Sains Malaysia for funding support for this review article.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Handling Editor: Dr D Levy