Noncoding RNAs as Prognostic Biomarkers After Myocardial Infarction: A Scoping Review

Abstract

Background

Prognosis after myocardial infarction (MI) remains heterogeneous despite contemporary reperfusion and secondary prevention, and biomarkers that capture post‐MI recovery, treatment response, and long‐term risk are still limited. Noncoding RNAs have therefore attracted interest as biomarkers of post‐MI risk and recovery.

Methods

We conducted a scoping review of human studies evaluating circulating or blood‐derived noncoding RNAs, including microRNAs, long noncoding RNAs, circular RNAs, and tRNA‐derived small RNAs/tRNA‐derived fragments, measured after MI in relation to prognostic phenotypes, clinical outcomes, or treatment‐response end points.

Results

Forty‐six studies were included. Most were observational, focused on plasma or serum microRNAs, and used quantitative reverse transcription–polymerase chain reaction, but sample size, sampling phase, normalization strategy, end point definition, follow‐up duration, and validation approaches varied substantially. Reported associations clustered around reperfusion‐related injury/no reflow or microvascular obstruction, left ventricular remodeling or dysfunction, clinical events, including major adverse cardiovascular events and mortality, and a smaller group of treatment‐response phenotypes. Directional signals included miR‐30e, miR‐660‐5p, TUG1, and MALAT1 for no reflow; LIPCAR, MICRA, miR‐320a, miR‐1254, and miR‐22‐3p for remodeling or ventricular recovery; miR‐145, miR‐223‐3p, miR‐126‐3p/miR‐223‐3p, HCG11/miR‐532‐3p, and exosomal miR‐186‐5p dynamics for clinical events; and BANCR or selected tRNA‐derived small RNAs/tRNA‐derived fragments for treatment‐response heterogeneity. The most plausible candidates were phenotype specific rather than universal, with event‐related microRNA models, imaging‐linked remodeling markers, and no‐reflow/microvascular obstruction–associated candidates appearing more mature than isolated injury‐linked diagnostic microRNAs or single‐study treatment‐response signals.

Conclusions

Overall, noncoding RNAs show promise as adjunctive post‐MI biomarkers, but clinical translation requires phase‐aligned sampling, assay standardization, external validation, and direct testing of incremental value beyond established clinical, imaging, and protein‐biomarker models.

Nonstandard Abbreviations and Acronyms

circRNA

circular RNA

lncRNA

long noncoding RNA

LVR

left ventricular remodeling

MACE

major adverse cardiovascular event

MVO

microvascular obstruction

ncRNA

noncoding RNA

tRF

tRNA‐derived fragment

tsRNA

tRNA‐derived small RNA

Clinical Perspective.

What Is New?

• This is the first scoping review to comprehensively synthesize post–myocardial infarction noncoding RNA biomarkers across multiple noncoding RNA classes, including microRNAs, long noncoding RNAs, circular RNAs, and tRNA‐derived small RNAs/tRNA‐derived fragments, and across clinically distinct domains, such as no reflow/microvascular obstruction, left ventricular remodeling or dysfunction, clinical events, and treatment‐response phenotypes.

• The review adds a directional summary and qualitative evidence hierarchy showing that the most plausible candidates are phenotype specific rather than universal, with event‐related noncoding RNA models, imaging‐linked remodeling markers, and no‐reflow/microvascular obstruction–associated noncoding RNAs appearing more mature than isolated injury‐linked or single‐study treatment‐response signals.

What Are the Clinical Implications?

• Noncoding RNAs may eventually support post–myocardial infarction risk stratification as adjunctive biomarkers, but current evidence does not support clinical implementation without standardized sampling and assays, external validation, and demonstration of incremental value beyond established clinical, imaging, and protein‐biomarker models.

Myocardial infarction (MI) remains a leading cause of death and long‐term disability worldwide, despite major advances in prevention, emergency systems of care, and pharmacotherapy. Cardiovascular diseases are the foremost global cause of mortality, accounting for an estimated 19.8 million deaths each year, with most deaths attributable to heart attack and stroke. ¹ At the same time, population aging and the persistence of modifiable risk factors sustain a high incidence of acute coronary events. In the United States alone, contemporary estimates indicate that ≈805 000 people experience an MI each year, underscoring the ongoing public‐health impact even in high‐resource settings. ² Beyond short‐term mortality, MI survivors frequently face recurrent ischemic events, arrhythmias, and progressive heart failure (HF), driving repeated hospitalizations and substantial societal costs. ³

Conceptually, MI is defined as acute myocardial injury with clinical evidence of acute myocardial ischemia, most commonly precipitated by an atherothrombotic event (type 1 MI) resulting from coronary plaque rupture or erosion. ⁴ A large proportion of the global MI burden is attributable to modifiable exposures. The INTERHEART study, spanning 52 countries, demonstrated that a limited set of potentially modifiable risk factors, particularly dyslipidemia, smoking, hypertension, diabetes, abdominal obesity, psychosocial factors, diet, physical activity, and alcohol patterns, accounts for the vast majority of MI risk across diverse regions and populations. ⁵

From a clinical perspective, MI is embedded within the spectrum of acute coronary syndromes (ACSs), traditionally categorized into ST‐segment–elevation MI (STEMI), non–ST‐segment–elevation MI (NSTEMI), and unstable angina. ⁶ Diagnostic pathways integrate: clinical assessment of ischemic symptoms and hemodynamic stability, electrocardiography to identify persistent ST‐segment elevation or dynamic ischemic changes, and serial measurement of cardiac troponins to document an increase or decrease above the 99th percentile upper reference limit in a setting consistent with myocardial ischemia. ⁴ The widespread adoption of high‐sensitivity cardiac troponin (hs‐cTn) assays has improved early rule in/rule out of MI and refined risk stratification, while also increasing recognition of myocardial injury and type 2 MI (supply–demand oxygen imbalance). ⁷ Imaging (eg, echocardiography) and invasive coronary angiography are then used selectively to confirm diagnosis, guide revascularization, and evaluate complications. ⁶

Therapeutic management is time critical, with goals of restoring coronary perfusion, limiting infarct size, preventing recurrent thrombosis, and reducing adverse remodeling. ⁸ Contemporary guidelines emphasize prompt reperfusion (primary percutaneous coronary intervention [PCI] when feasible, and fibrinolysis in selected settings), early antithrombotic therapy (aspirin plus a P2Y12 inhibitor and appropriate anticoagulation), and rapid initiation of secondary‐prevention pharmacotherapy (high‐intensity lipid lowering, β‐blockade, and renin–angiotensin system inhibition when indicated), followed by structured cardiac rehabilitation and long‐term risk‐factor management. ⁶ Despite standardized care pathways, treatment response and outcomes remain heterogeneous: patients with seemingly similar index presentations can diverge markedly in infarct healing, ventricular function, and long‐term event risk. ⁹

This heterogeneity reflects the complex pathophysiology of MI and postinfarction repair. Left ventricular remodeling (LVR), a dynamic process involving infarct expansion, neurohormonal activation, inflammation, fibrosis, and geometric change, can occur even after successful revascularization and is a central substrate for later HF and mortality. ¹⁰ Beyond hs‐cTn, multiple biomarkers have been evaluated to improve prediction of post‐MI treatment outcomes, including adverse LVR, incident HF, recurrent ischemic events, mortality, and (in the context of intensified antithrombotic therapy) major bleeding. Natriuretic peptides, particularly NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) measured early or at discharge, reflect myocardial wall stress and show consistent associations with adverse outcomes after acute MI, supporting their role as a complementary prognostic axis beyond necrosis markers alone. ¹¹ In STEMI treated with primary PCI, admission copeptin has demonstrated independent prognostic value for 1‐year mortality and higher discrimination for 1‐year mortality than peak troponin I. ¹² Biomarkers integrating vascular dysfunction and systemic stress responses, such as midregional proadrenomedullin, have also been associated with prognosis in higher‐risk post‐MI populations (eg, those with HF after MI), suggesting incremental information beyond conventional clinical predictors. ¹³ Inflammatory biomarkers map residual inflammatory risk that persists despite guideline‐directed therapy: in post‐ACS cohorts, higher interleukin‐6 has been linked to increased risks of major adverse outcomes in adjusted analyses, ¹⁴ and evidence from anti‐inflammatory secondary prevention indicates that on‐treatment reductions in high‐sensitivity CRP (C‐reactive protein) can track with clinical benefit, illustrating how inflammatory biomarkers may also support response‐to‐therapy phenotyping rather than prognosis alone. ¹⁵ Remodeling/fibrosis pathways have been captured by soluble ST2, which predicted death and HF after acute MI ¹⁶ and, in a community incident‐MI cohort, was associated with a large excess risk of longer‐term death and incident HF, ¹⁷ and by galectin‐3, a profibrotic marker that predicted death and HF after MI in population‐based analyses. ¹⁸ Markers of extracellular‐matrix turnover and microvascular injury have also been tied to treatment‐relevant phenotypes: the temporal profile of plasma matrix metalloproteinase‐9 related to subsequent LVR and function after MI, ¹⁹ and culprit‐lesion myeloperoxidase levels were associated with the angiographic no‐reflow phenomenon after primary PCI, linking oxidative inflammation to impaired reperfusion. ²⁰ Finally, biomarker research in MI increasingly incorporates competing hazards under antithrombotic strategies: growth differentiation factor‐15 predicted major bleeding and cardiovascular events in ACS, ²¹ and measured at 1 month after ACS remained associated with subsequent major bleeding risk during dual antiplatelet therapy, supporting biomarker‐informed approaches to balancing ischemic versus bleeding risk in longer‐term management. ²²

Accordingly, there is strong interest in biomarkers that (1) reflect underlying pathophysiology rather than only necrosis or hemodynamic stress, (2) improve prediction of clinically meaningful outcomes, and (3) identify patients most likely to benefit from intensified or targeted therapies. ²³

Noncoding RNAs (ncRNAs) have emerged as promising candidates in this context. Large‐scale transcriptomic efforts have shown that a substantial proportion of the human genome is transcribed, expanding the functional landscape beyond protein‐coding genes. ²⁴ ncRNAs comprise multiple classes with distinct biogenesis and functions, including among others microRNAs (miRNAs; ~22 nucleotides, posttranscriptional gene regulation), ²⁵ long noncoding RNAs (lncRNAs; typically >200 nucleotides, diverse regulatory roles), ²⁶ and circular RNAs (circRNAs; covalently closed RNA molecules with notable stability and regulatory potential). ²⁷ Importantly for biomarker development, circulating ncRNAs can be detected in plasma/serum and other biofluids, often protected within extracellular vesicles or protein complexes, making them analytically accessible in clinical cohorts. ²⁸

Accordingly, this scoping review aimed to map and critically appraise the evidence on ncRNAs as post‐MI prognostic biomarkers, with a primary focus on clinical and imaging outcomes and treatment‐relevant phenotypes, while separately identifying the smaller subset of studies that evaluated true response‐to‐therapy end points. Specifically, we sought to summarize (1) the clinical settings, biospecimens, and sampling time points used; (2) the ncRNA candidates evaluated and the outcome definitions applied (from reperfusion injury and LVR to short‐ and long‐term major adverse cardiovascular events [MACEs]); and (3) key methodological features (platforms, normalization, and modeling/validation) to highlight gaps limiting reproducibility and clinical translation. Given the breadth and heterogeneity of the field, this review was not intended to identify a single universal ncRNA biomarker for all post‐MI outcomes. Instead, we structured the synthesis around clinically distinct post‐MI domains, reperfusion‐related injury/no reflow, LVR and dysfunction, clinical events, and treatment‐response phenotypes, to clarify where evidence is most coherent and where findings remain exploratory or unstable.

METHODS

This scoping review was undertaken to map and synthesize human evidence on ncRNA biomarkers evaluated for post‐MI prognostic phenotypes and clinical outcomes, while also capturing studies that assessed ncRNAs in relation to specific response‐to‐therapy end points. The data extracted and charted for this scoping review are available within this article and its Supplemental Material, including Table S1. The source materials consisted exclusively of previously published articles cited in this review, and the qualitative analytical approach is described in the Methods section. No new participant‐level data, biological materials, or analytic code was generated for this review. Because this study synthesized data from previously published literature and did not involve the collection of new human participant data or identifiable individual‐level information, institutional review board approval and informed consent were not required. The review followed methodological guidance for scoping reviews and was reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta‐Analyses 2020. ²⁹ A Preferred Reporting Items for Systematic Reviews and Meta‐Analyses flow diagram summarizing the study selection process is provided in Figure 1.

Figure 1. A PRISMA flow diagram summarizing the study selection process.

PRISMA indicates Preferred Reporting Items for Systematic Reviews and Meta‐Analyses.

Comprehensive literature searches were conducted in PubMed, Web of Science, and Google Scholar. Searches and screening were performed between October and December 2025, and records identified up to December 2025 were eligible for inclusion. The search strategy combined MI‐related terms (“myocardial infarction,” “acute myocardial infarction,” “myocardial infarct*,” AMI, STEMI, and NSTEMI) with broad ncRNA terms (eg, “microRNAs,” microRNA*, miRNA*, “RNA, long noncoding,” lncRNA*, “long noncoding rna*,” “long non‐coding rna*,” “RNA, circular,” circRNA*, “circular rna*,” “transfer RNA‐derived small RNA*,” “tRNA‐derived small RNA*,” tsRNA*, “noncoding rna*,” “non‐coding rna*,” and ncRNA*) and treatment/context terms capturing acute management and secondary prevention (eg, “percutaneous coronary intervention,” PCI, “primary PCI,” angioplast*, stent*, “thrombolytic therapy,” thrombolys*, fibrinolys*, reperfus*, “drug therapy,” treat*, therap*, antiplatelet, clopidogrel, prasugrel, ticagrelor, aspirin, and statin*), alongside prognostic and response‐related terms (predict*, prognos*, “treatment outcome,” outcome*, and respon*). Searches were limited to English‐language publications, with no restriction on publication year, and only records with full‐text articles available for assessment were considered eligible.

All records were imported into Covidence where possible, and duplicates were removed before screening. Title/abstract screening and full‐text assessment were performed independently by 2 reviewers (Ł.W. and M.B.) at each stage. Disagreements were resolved by discussion; if consensus could not be reached, a third reviewer (R.M.) adjudicated. Formal interreviewer agreement statistics were not calculated.

Eligible studies comprised original human research (prospective or retrospective cohorts, nested case–control studies, and other longitudinal observational designs) in which an ncRNA (miRNA, lncRNA, circRNA, or tRNA‐derived small RNA [tsRNA]) measured in a human biospecimen was evaluated as a biomarker for post‐MI prognostic phenotypes, clinical outcomes, or prespecified treatment‐response end points. We excluded case reports/series and narrative reviews/editorials; animal‐only or in vitro–only studies without a linked human outcome analysis; studies not specific to MI (eg, peripheral artery disease cohorts, stable coronary disease/elective stenting without index MI); studies focused purely on diagnostic discrimination (acute MI [AMI] versus controls) without subsequent outcome or treatment‐response assessment; studies lacking a clinically interpretable follow‐up end point after MI (eg, cross‐sectional expression profiling without longitudinal outcomes); studies limited to genetic predisposition or polymorphisms (eg, miRNA single‐nucleotide polymorphism pharmacogenetics) rather than circulating/cellular ncRNA expression as a prognostic biomarker; and studies reporting only correlations with risk scores (eg, TIMI [Thrombolysis in Myocardial Infarction]/GRACE [Global Registry of Acute Coronary Events]) without subsequent event follow‐up.

Data were charted using a standardized extraction form that captured study design, population and MI phenotype, treatment context, outcomes and follow‐up, biospecimen type and sampling time, RNA measurement platform and normalization, effect estimates/model performance, key findings relevant to prognostication, and study limitations. The full study‐level extraction table is provided as Table S1, whereas the main article presents a condensed evidence hierarchy to improve readability and clinical interpretability.

Given substantial heterogeneity in study populations, sampling windows, ncRNA classes, and outcome definitions, findings were synthesized qualitatively; no quantitative meta‐analysis was performed. Consistent with the objectives of a scoping review, we did not apply a formal risk‐of‐bias tool across studies, because the included literature was methodologically heterogeneous and the primary aim was evidence mapping rather than pooled effect estimation. Instead, key methodological features relevant to interpretability and reproducibility were charted for each study, including cohort size, biospecimen and sampling window, assay platform, normalization strategy, follow‐up duration, end point definition, and the presence or absence of validation.

RESULTS

Table S1 provides the full study‐level extraction of the included studies, including population/context, end point definitions, biospecimen type, comparator groups, sample size, analytical platform, normalization strategy, effect estimates/model performance, key findings, and reported limitations. Across 46 included human studies, most investigations were observational (prospective/retrospective cohort or nested case–control), with a smaller number of randomized or treatment‐comparison contexts. ³⁰ , ³¹ , ³² , ³³ , ³⁴ , ³⁵ , ³⁶ , ³⁷ , ³⁸ , ³⁹ , ⁴⁰ , ⁴¹ , ⁴² , ⁴³ , ⁴⁴ , ⁴⁵ , ⁴⁶ , ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ , ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁰ , ⁶¹ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁵ , ⁶⁶ , ⁶⁷ , ⁶⁸ , ⁶⁹ , ⁷⁰ , ⁷¹ , ⁷² , ⁷³ , ⁷⁴ Sample sizes varied widely, from small mechanistic clinical cohorts (n=25) to large prospective data sets (up to n=932), with follow‐up windows spanning short‐term outcomes (eg, 30 days) to longer‐term end points reaching 5 to 6 years. ³⁸ , ⁴⁰ , ⁴¹ , ⁷¹ Most studies were conducted in acute populations with MI undergoing contemporary invasive management, frequently focusing on STEMI treated with primary PCI, although mixed STEMI/NSTEMI ³¹ or broader ACS/chest‐pain cohorts were also represented. ⁷³ End points were heterogeneous and included (1) clinical events, such as MACE composites, cardiovascular death, all‐cause mortality, HF hospitalization, and ischemic complications (including stent thrombosis and stroke), (2) imaging‐derived phenotypes of myocardial injury and remodeling (cardiovascular magnetic resonance [CMR]–based infarct size, microvascular obstruction, salvage index, and longitudinal left ventricular [LV] volumes/function), and (3) periprocedural reperfusion injury metrics, particularly no‐reflow definitions based on TIMI and myocardial blush/angiographic criteria. ³⁰ , ³¹ , ³² , ³³ , ³⁴ , ³⁵ , ³⁶ , ³⁷ , ³⁸ , ³⁹ , ⁴⁰ , ⁴¹ , ⁴² , ⁴³ , ⁴⁴ , ⁴⁵ , ⁴⁶ , ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ , ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁰ , ⁶¹ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁵ , ⁶⁶ , ⁶⁷ , ⁶⁸ , ⁶⁹ , ⁷⁰ , ⁷¹ , ⁷² , ⁷³ , ⁷⁴

Biospecimens, Sampling Approaches, and Analytical Platforms

Circulating biofluids dominated the evidence base: plasma‐based analyses were most common, followed by serum, with a minority using cellular fractions/whole blood (including platelet‐poor plasma, peripheral blood cells, and whole‐blood lysates). ³⁰ , ³¹ , ³² , ³³ , ³⁴ , ³⁵ , ³⁶ , ³⁷ , ³⁸ , ³⁹ , ⁴⁰ , ⁴¹ , ⁴² , ⁴³ , ⁴⁴ , ⁴⁵ , ⁴⁶ , ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ , ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁰ , ⁶¹ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁵ , ⁶⁶ , ⁶⁷ , ⁶⁸ , ⁶⁹ , ⁷⁰ , ⁷¹ , ⁷² , ⁷³ Only Gidlöf et al quantified ncRNAs not only in plasma but also in urine samples. ⁴¹ Many studies relied on single‐time point sampling, whereas a smaller subset explicitly examined serial kinetics across early reperfusion or later recovery phases. ³³ , ⁵² , ⁵⁶ In addition, sampling strategies varied markedly, ranging from arterial catheter/sheath blood obtained at the time of PCI (including prereperfusion and early serial postreperfusion draws) to peripheral venous samples collected later during hospitalization and at follow‐up weeks to months after MI. Quantitative reverse transcription–polymerase chain reaction was the predominant measurement platform, whereas a smaller set used broader discovery profiling (eg, small RNA sequencing, transcriptome‐wide screening, or microarray approaches) with subsequent candidate prioritization or validation. ³⁴ , ³⁹ , ⁵⁶ , ⁶⁸ , ⁷¹

Normalization strategies varied substantially and included frequent reliance on U6 and/or relative‐expression 2^−ΔΔCt approaches, alongside spike‐in controls and, less commonly, empirically selected stable reference miRNAs (NormFinder/geNorm) and more extensive preanalytic quality control. ³⁰ , ³⁴ , ⁴⁵ , ⁴⁶ , ⁵⁶ This methodological diversity was repeatedly highlighted in study‐level limitations (eg, single‐center recruitment, limited external validation, small event counts, and variable sampling windows), underscoring constraints on reproducibility and generalizability across the included literature.

ncRNA Classes and Candidates Evaluated

miRNAs were the primary ncRNA class studied, with fewer investigations of lncRNAs, ³¹ , ⁴³ , ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵³ , ⁶⁴ , ⁶⁵ , ⁷⁰ circRNAs, ⁴⁴ , ⁵⁹ and tsRNAs/tRNA‐derived fragment (tRFs) ⁷⁴ and only occasional multiclass models integrating ncRNA layers or pairing ncRNAs with established clinical biomarkers (eg, troponin/NT‐proBNP or other laboratory/imaging markers). ³³ , ³⁴ , ³⁵ , ³⁷ , ⁴¹ , ⁴⁷ , ⁶² Frequently recurring miRNA candidates included miR‐1, miR‐133a, miR‐223‐3p, miR‐21/miR‐21‐5p, miR‐150, and myocardial‐enriched miRNAs related to injury biology (eg, miR‐208b and miR‐499‐5p), reflecting a strong focus on cardiomyocyte damage signatures and inflammatory/platelet‐related pathways.^* Among lncRNAs, LIPCAR and MALAT1 were repeatedly evaluated in post‐MI remodeling and adverse‐event contexts. ⁴³ , ⁴⁸ , ⁴⁹ , ⁶⁵ , ⁷⁰ One eligible study evaluated peripheral‐blood tsRNA profiles in patients with STEMI with reduced–ejection fraction HF after AMI who had undergone complete revascularization and received sacubitril/valsartan for at least 6 months. ⁷⁴ In this study, patients were classified according to LV ejection fraction response after treatment, comparing sacubitril/valsartan resistance with no sacubitril/valsartan resistance. ⁷⁴

Figure 2 summarizes representative biomarkers for which the reported expression pattern could be linked to an adverse or favorable post‐MI phenotype.

Figure 2. Directional summary of representative ncRNA biomarkers and their associated post‐MI outcomes.

The figure summarizes representative directional associations between ncRNA expression patterns and post‐MI prognostic or treatment‐response phenotypes reported in the included human studies. Upward arrows indicate higher expression associated with the indicated outcome, whereas downward arrows indicate lower expression associated with the indicated outcome. Red boxes denote adverse phenotypes, including no reflow/microvascular injury, adverse LV remodeling or dysfunction, MACEs, mortality, or treatment resistance. Green boxes denote favorable phenotypes, including more favorable structural recovery or better treatment response. Gray boxes indicate dynamic or time‐dependent associations that should not be interpreted as a single static high/low relationship. Dashed outlines indicate emerging or limited evidence. circRNA indicates circular RNA; lncRNA, long noncoding RNA; LV, left ventricular; LVEF, LV ejection fraction; LVR, LV remodeling; MACE, major adverse cardiovascular event; MI, myocardial infarction; miRNA, microRNA; ncRNA, noncoding RNA; NSVR, no sacubitril/valsartan resistance; PCI, percutaneous coronary intervention; tRF, tRNA‐derived fragment; and tsRNA, tRNA‐derived small RNA.

ncRNAs Associated With Clinical Events and Survival

A substantial subset of studies linked circulating ncRNAs to MACE‐type composites and mortality across varying horizons.^† Effect sizes and performance metrics ranged from modest incremental discrimination to stronger single‐marker associations in selected cohorts, often with cut‐point stratification and multivariable modeling (logistic/Cox) of clinical end points.^‡ For example, miR‐145 measured during the early post‐MI course was reported as an independent predictor of 1‐year adverse outcomes (including composite clinical events and cardiac death), with high hazard ratios and moderate receiver operating characteristic performance. ³⁶ In PCI populations, whole‐blood miRNA signals (eg, miR‐223‐3p and the miR‐126‐3p/miR‐223‐3p ratio) were associated with recurrent ischemic end points over 30 days and 1 year, with reported improvements in model discrimination compared with clinical variables alone. ⁴⁶

Several studies also emphasized the additive value of combining ncRNAs with clinical biomarkers or other molecular measures. ³⁵ , ⁴⁵ , ⁵⁰ , ⁵² , ⁵⁴ , ⁵⁶ , ⁷¹ Notably, multimarker approaches included plasma mitochondrial DNA combined with specific miRNAs for 6‐month MACE risk stratification, systematic miRNA panels paired with troponin for predicting CMR‐derived injury phenotypes, and sequencing‐derived miRNA candidates associated with longer‐term survival. ⁴⁰ , ⁵⁶ , ⁶⁸ In larger‐scale discovery‐to‐validation workflows, systematic profiling identified reproducible miRNA candidates (eg, miR‐26a‐5p, miR‐21‐5p, and miR‐191‐5p) that differed between event and nonevent groups over a 2‐year MACE horizon, with reported incremental discrimination beyond clinical models. ⁷¹ Additional cohorts examined post‐PCI dynamics (eg, exosomal miR‐186‐5p changes) and linked higher post‐PCI levels or smaller decreases to subsequent MACE accumulation. ⁵⁷

ncRNAs Associated With LV Remodeling, Ventricular Dysfunction, and Imaging Phenotypes

Imaging‐based remodeling and LV dysfunction end points were commonly operationalized using CMR or echocardiography‐derived changes in LV volumes, infarct size, and systolic function across 4 to 12 months (and in some studies up to 2 years).^§ Several studies reported that adding ncRNAs to clinical models improved discrimination for adverse remodeling or LV dysfunction, although findings were not universally consistent across candidate sets. ³⁵ , ⁴⁸ , ⁵¹ , ⁵⁵ , ⁶⁵ For example, admission plasma miR‐1254 was associated with more favorable remodeling at 6 months in a CMR phenotyping cohort after STEMI, remaining significant in multivariable models that incorporated clinical parameters and established biomarkers. ³⁵ In other cohorts with STEMI, circulating ncRNAs (eg, miR‐146a and miR‐21 measured around day 5) were associated with 1‐year remodeling risk and showed moderate‐to‐high areas under the curve for discriminating remodeling phenotypes. ⁵¹ However, Maries et al reported that admission plasma miR‐101, miR‐150, and miR‐21 were not significantly different between patients with versus without 12‐month LV remodeling, suggesting that these candidates may be sensitive to sampling timing and cohort‐specific factors. ⁵⁵

Beyond miRNAs, lncRNAs and circRNAs were also linked to remodeling‐related outcomes. ⁴⁸ , ⁵⁹ , ⁶⁵ LIPCAR demonstrated time‐dependent associations with post‐MI remodeling (downregulated early and higher at later time points among remodelers), with multivariable modeling suggesting independent predictive value at 12 months. ⁴⁸ MICRA (a circRNA) contributed to echocardiography‐based risk stratification of LV function at 4 months in multivariable ordinal regression with internal validation, supporting potential incremental prognostic utility. ⁵⁹

ncRNAs Related to Reperfusion Injury and No Reflow

Multiple studies evaluated ncRNAs as biomarkers of impaired myocardial reperfusion, microvascular obstruction (MVO), or angiographic no reflow after PCI. ³³ , ⁴⁷ , ⁵⁸ , ⁶² , ⁷⁰ , ⁷² Definitions were typically anchored to TIMI flow/angiographic criteria (with or without myocardial blush) and, in some cases, invasive microvascular indexes or CMR evidence of MVO. ³³ , ⁴⁷ , ⁵⁸ , ⁷⁰ , ⁷² Reported discrimination for no reflow ranged from moderate to high depending on the marker and cohort, including models incorporating lncRNA–miRNA axes (eg, lncRNA TUG1/miR‐30e/natriuretic peptide B) and single‐miRNA candidates, such as miR‐30e or miR‐660‐5p. ⁴⁷ , ⁶² , ⁷²

ncRNAs Evaluated as Candidate Response‐to‐Therapy Biomarkers

Only a small subset of studies explicitly operationalized treatment response as a biomarker‐targeted outcome (rather than using standard clinical end points under treatment). ³² , ⁵³ , ⁶¹ , ⁷⁴ These included contexts such as symptom/clinical efficacy measures after therapeutic interventions and antifibrotic biomarker response under mineralocorticoid receptor antagonism, with mixed results on whether baseline ncRNA profiles identified responders. ³² , ⁵³ , ⁶¹ , ⁷⁴ For example, lncRNA BANCR was evaluated alongside clinical response to antiplatelet strategies in AMI, with reported diagnostic/prognostic performance for therapeutic effect in a single study. ⁵³ In contrast, in an eplerenone‐treated cohort with systolic dysfunction post‐MI, baseline fibrosis‐linked miRNAs did not robustly identify patients with greater antifibrotic response, and treatment‐by‐miRNA interactions were not consistently demonstrated. ⁶¹ A tsRNA/tRF study extended this response‐to‐therapy theme to sacubitril/valsartan‐treated post‐AMI HF. Su et al compared sacubitril/valsartan resistance and no sacubitril/valsartan resistance after at least 6 months of treatment and identified 3 validated tRFs with discriminatory performance for treatment‐response heterogeneity: tRF‐59:76‐Tyr‐GTA‐2‐M3 (area under the curve, 0.875), tRF‐60:76‐Val‐AAC‐1‐M5 (area under the curve, 0.847), and tRF‐1:29‐Gly‐GCC‐1 (area under the curve, 0.819). ⁷⁴ Bioinformatic analyses and human umbilical vein endothelial cell transfection experiments further suggested that tRF‐60:76‐Val‐AAC‐1‐M5 may influence sacubitril/valsartan response through TNFRSF10B and BCL2L1 within lipid/atherosclerosis‐related signaling. ⁷⁴ However, because samples were collected after treatment and the cohort was small and single center, these findings are best interpreted as exploratory evidence of response‐associated molecular heterogeneity rather than as validated baseline prediction of therapeutic benefit.

Overall, the included literature shows broad exploration of ncRNA candidates across diverse end points and biospecimen types, but with substantial heterogeneity in end point definitions, sampling windows, platforms, normalization, and validation strategies, as reflected in recurring study‐level limitations and variability of reported effect sizes. ³⁰ , ³¹ , ³² , ³³ , ³⁴ , ³⁵ , ³⁶ , ³⁷ , ³⁸ , ³⁹ , ⁴⁰ , ⁴¹ , ⁴² , ⁴³ , ⁴⁴ , ⁴⁵ , ⁴⁶ , ⁴⁷ , ⁴⁸ , ⁴⁹ , ⁵⁰ , ⁵¹ , ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ , ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁰ , ⁶¹ , ⁶² , ⁶³ , ⁶⁴ , ⁶⁵ , ⁶⁶ , ⁶⁷ , ⁶⁸ , ⁶⁹ , ⁷⁰ , ⁷¹ , ⁷² , ⁷³ , ⁷⁴

DISCUSSION

A central signal from our mapping is an inconsistency between what many studies measure and what they aim to predict. The literature shows broad exploration of ncRNAs, predominantly miRNAs, as post‐MI prognostic biomarkers, but also reveals why translation remains limited: end point heterogeneity, phase‐mismatched sampling, and analytically consequential variability in normalization and peri‐PCI confounding likely underlie inconsistent replication. Current evidence is considerably stronger for prognostic enrichment across reperfusion‐related phenotypes, remodeling, and adverse cardiovascular outcomes than for true response‐to‐therapy biomarker use, which remains supported by only a small subset of studies. The most compelling translational pathway is likely standardized, phase aligned, multicenter validation of ncRNAs for post‐MI risk stratification, alongside future trial‐embedded studies designed specifically to test predictive and pharmacodynamic biomarker roles.

The field has largely leaned on cardiomyocyte‐enriched circulating miRNAs that increase rapidly with necrosis (classically miR‐1/133a/208/499) because they are analytically accessible and have shown strong diagnostic associations in acute MI across multiple studies and meta‐analyses. ⁷⁵ , ⁷⁶ However, diagnostic strength does not guarantee prognostic utility, particularly for end points such as LV remodeling, HF, or long‐horizon MACEs that are shaped by reperfusion success, microvascular injury, inflammation, repair, and comorbidity‐modified trajectories. ⁷⁷ , ⁷⁸ This framing helps interpret why some candidates appear informative in selected cohorts/time points while showing weak or null associations in others: they may primarily report acute myocyte injury burden rather than the downstream processes that determine late clinical course. hs‐cTn algorithms already provide excellent diagnostic discrimination; accordingly, evidence from clinical chest‐pain/NSTEMI pathways suggests that even when individual miRNAs associate with MI, miRNA panels may not add diagnostic accuracy beyond hs‐cTnT when kinetics and guideline‐recommended pathways are applied. ⁷⁹ In practice, these considerations suggest that the most plausible clinical application of ncRNAs lies less in improving MI diagnosis and more in post‐MI risk stratification and treatment‐response assessment, where residual risk remains substantial and prognostic refinement could be clinically actionable.

A second, strongly explanatory theme is timing. After infarction, inflammatory and reparative programs evolve over days to weeks; thus, a biomarker sampled prereperfusion, immediately post‐PCI, on day 5, or months later is interrogating different pathophysiology. ⁷⁷ Many of the heterogeneous findings in remodeling and MACE studies are therefore consistent with a basic expectation: early injury‐phase signals should track infarct severity and reperfusion injury, whereas later signals may better index repair/fibrosis pathways that govern remodeling and HF transition. ⁷⁷ This reinforces a practical interpretation of the mixed remodeling literature: heterogeneity in sampling timing can generate seemingly conflicting results because identical ncRNA candidates may index acute injury at one time point and reparative/remodeling pathways at another.

This timing issue is especially important in primary PCI cohorts because procedure‐related confounding can directly distort measured ncRNA levels. Heparin exposure is common during angiography/PCI and can inhibit reverse transcription and polymerase chain reaction amplification, potentially biasing quantitative polymerase chain reaction–based miRNA estimates unless explicitly mitigated (eg, heparinase‐based deheparinization or inhibition controls). ⁸⁰ , ⁸¹ Thus, between‐study differences in whether samples were obtained from arterial sheaths/catheters during PCI versus peripheral venipuncture later, and whether heparin interference was addressed, offer a valid methodological mechanism for nonreplication. More broadly, reliance on convenient but unstable normalizers likely contributes to variability: multiple studies in inflammatory and clinical contexts demonstrate that U6 can be unsuitable for circulating miRNA normalization because of low abundance and condition‐dependent instability. ⁸² , ⁸³ In the highly inflammatory and hemodynamically unstable post‐MI setting, normalization strategy is a key determinant of effect estimates and can substantially shape whether a candidate appears prognostically informative.

The apparent breadth of the literature should also be interpreted in relation to the biological breadth of the post‐MI syndrome. Reperfusion injury, no reflow/MVO, LV remodeling, recurrent ischemic events, HF transition, mortality, and pharmacologic response are related but nonequivalent phenotypes. Therefore, discordant ncRNA directions across studies do not necessarily indicate contradiction; in many cases, they reflect differences in sampling phase, biospecimen, end point definition, and the biological process being captured. This is why a phenotype‐specific synthesis is more informative than a single pooled narrative across all ncRNAs and outcomes.

Evidence Strength and Candidate Prioritization

As summarized in the Table1, qualitative prioritization of the mapped candidates suggests that no single ncRNA currently meets the evidentiary threshold for clinical implementation after MI. Nevertheless, some candidates emerge as more credible starting points for further development than others. We considered signals stronger when they were supported by larger or prospective cohorts, clinically meaningful end points, multivariable or incremental modeling, internal validation or discovery‐to‐validation workflows, biologically plausible sampling time points, and acceptable analytical handling. Conversely, candidates were considered weaker when they were derived from small single‐center data sets, unadjusted analyses, single posttreatment measurements, unstable normalization strategies, and inconsistent end point definitions, or lacked any validation.

Table 1.

Qualitative Evidence Hierarchy for Representative ncRNA Candidates After Myocardial Infarction

End point domain	Candidate(s)/model	Evidence profile	Incremental value/validation signal	Main limitations affecting clinical readiness	Qualitative evidence category	Clinical‐development interpretation
Clinical events/recurrent ischemic outcomes	Whole‐blood miR‐223‐3p; miR‐126‐3p/miR‐223‐3p ratio 46	Evaluated in a relatively large PCI‐treated cohort with AMI with clinically relevant ischemic end points at 30 d and 1 y. Associations were tested in adjusted models, and discrimination was compared across candidate markers.	Adjusted associations with recurrent ischemic end points were reported; the ratio provided model‐discrimination information, although it was not externally validated.	Whole‐blood/cellular matrix limits direct comparability with plasma/serum studies; end point rates were relatively low; external validation and standardized assay implementation are lacking.	Stronger candidate for external validation	One of the more credible event‐related signals, but best interpreted as a candidate for independent validation rather than a clinically deployable biomarker.
Clinical events/MACEs	Sequencing‐derived miRNA candidates/panel: miR‐26a‐5p, miR‐21‐5p, miR‐191‐5p 71	Identified through broader miRNA profiling with a discovery‐to‐validation structure and evaluated for 2‐y MACEs.	Reported incremental discrimination beyond clinical models, supporting potential value as part of a multimarker approach.	Requires independent external validation, harmonized assay translation from sequencing to targeted platforms, and assessment of calibration and clinical decision utility.	Stronger candidate for external validation	More promising as a panel‐based risk‐enrichment strategy than as isolated single‐miRNA biomarkers; individual components should not be interpreted as uniformly robust across end point domains.
Clinical events/MACEs and cardiac death	miR‐145 36	Single‐center cohort with STEMI; miR‐145 measured during the early post‐MI course and associated with 1‐y MACEs/cardiac death in adjusted analyses.	Multivariable prognostic association and ROC performance were reported.	Single‐center design, selected population with STEMI, limited analytical standardization, and no external validation; unclear incremental value beyond contemporary biomarker/imaging models.	Promising single‐cohort signal	Biologically and clinically interesting, but replication and comparison against standard post‐MI risk models are required.
Clinical events/MACE dynamics	Exosomal miR‐186‐5p dynamics 57	Serial/dynamic post‐PCI exosomal miRNA signal associated with subsequent MACEs.	Dynamic change pattern may capture postintervention recovery biology rather than a static baseline risk signal.	Interpretation depends on serial sampling design; limited replication; clinical thresholds and external validation are lacking.	Promising dynamic signal	Potentially useful for monitoring/recovery phenotyping, but not yet a validated baseline prognostic biomarker.
LV remodeling/LV dysfunction	MICRA 59	circRNA candidate linked to LV function after MI using echocardiography‐based risk stratification.	Multivariable modeling and internal validation were reported.	External validation is lacking; assay standardization and reproducibility across platforms are required; clinical added value over LVEF/CMR markers remains uncertain.	Stronger candidate for external validation	One of the more mature non‐miRNA candidates for LV dysfunction risk stratification, but not clinically ready.
LV remodeling/structural recovery	LIPCAR 48, 49	lncRNA candidate repeatedly evaluated in post‐MI remodeling/adverse‐event contexts; showed time‐dependent behavior after MI.	Multivariable modeling suggested independent predictive value for remodeling/survival‐related phenotypes.	Dynamic early‐vs‐late expression complicates a single‐threshold interpretation; sampling time must be standardized; external validation remains necessary.	Promising but time‐dependent candidate	Best developed as a phase‐specific remodeling biomarker rather than a universal static predictor.
LV remodeling/CMR‐defined remodeling	miR‐1254 35	Evaluated against CMR‐defined remodeling after STEMI, with association persisting in multivariable models.	Imaging‐linked end point and adjustment for clinical parameters strengthen biological and clinical interpretability.	Single‐cohort signal; replication, external validation, and comparison with established CMR/protein biomarkers are needed.	Promising imaging‐linked signal	A credible remodeling candidate, but currently hypothesis generating until independently replicated.
LV remodeling/remodeling‐risk miRNAs	miR‐146a, miR‐21, miR‐320a, miR‐1 39 , 51 , 54 , 55	Multiple miRNAs evaluated across remodeling or LV function studies, often with moderate‐to‐high reported discrimination in selected cohorts.	Some studies reported multivariable associations or ROC performance for remodeling phenotypes.	Direction and performance vary across cohorts, sampling windows, and end point definitions; miR‐21 in particular has inconsistent findings across remodeling studies.	Unstable/timing‐sensitive evidence	These markers may be biologically informative, but require phase‐aligned sampling and harmonized end point definitions before prioritization.
Reperfusion injury/no reflow/MVO	miR‐30e; miR‐660‐5p; TUG1/miR‐30e/NPPB axis; MALAT1 47 , 62 , 70 , 72	Phenotype‐specific candidates linked to no reflow/MVO after primary PCI. End points are proximal to reperfusion and mechanistically coherent with microvascular injury.	Several studies reported discrimination for no reflow, and some used multivariable models or combined‐marker approaches.	Mostly single‐center cohorts; heterogeneous no‐reflow definitions; angiographic and CMR end points are not interchangeable; limited external validation.	Moderate phenotype‐specific evidence	Suitable for focused validation in standardized no‐reflow/MVO cohorts rather than broad post‐MI prognosis.
Treatment‐response/antiplatelet‐treatment context	BANCR 53	Evaluated alongside therapeutic effect and 6‐mo MACEs in patients with AMI treated with antiplatelet strategies.	Reported diagnostic/prognostic performance for therapeutic effect and MACEs.	Single study; limited adjustment; no external validation; end point combines symptom/ECG response and clinical outcomes.	Exploratory treatment‐response signal	Hypothesis generating only; should not be interpreted as a validated response predictor.
Treatment‐response/antifibrotic response	Fibrosis‐linked miRNAs, including miR‐133a, in eplerenone‐treated post‐MI systolic dysfunction 61	Evaluated in a treatment‐comparison context with collagen‐biomarker response end points.	Baseline miRNAs did not robustly identify greater antifibrotic response; no consistent treatment‐by‐miRNA interaction was shown.	Indirect fibrosis end points; subgroup context; limited evidence for predictive enrichment.	Weak/negative response‐prediction evidence	Useful as a cautionary example that biological plausibility does not necessarily translate into treatment‐response prediction.
Treatment‐response/sacubitril/valsartan heterogeneity	tsRNA/tRF candidates: tRF‐59:76‐Tyr‐GTA‐2‐M3, tRF‐60:76‐Val‐AAC‐1‐M5, tRF‐1:29‐Gly‐GCC‐1 74	Small post‐AMI HF study comparing SVR vs NSVR after ≥6 mo sacubitril/valsartan; RNA‐seq discovery followed by within‐study qRT‐PCR confirmation; ROC AUCs suggested discrimination of SVR, but no external validation or baseline prediction was performed.	ROC AUCs suggested discrimination of SVR; HUVEC experiments and target prediction suggested possible mechanistic links through TNFRSF10B/BCL2L1 and lipid/atherosclerosis signaling.	Small single‐center cohort; selected Han Chinese population; posttreatment sampling rather than baseline prediction; no external validation; limited adjustment for clinical/pharmacodynamic confounders.	Exploratory emerging‐class evidence	Important for expanding the ncRNA landscape to tsRNAs/tRFs, but requires prospective baseline/serial validation before clinical interpretation.
Injury‐linked diagnostic miRNAs with prognostic associations	miR‐1, miR‐133a, miR‐208/208a, miR‐499 37 , 41 , 42 , 54 , 58 , 63 , 75 , 76	Repeatedly studied cardiomyocyte‐enriched miRNAs strongly linked to acute myocyte injury and infarct biology.	Some studies associated these miRNAs with infarct size, LVEF, mortality, or adverse outcomes.	Prognostic value may be confounded by infarct size and acute necrosis; incremental value beyond hs‐cTn, NT‐proBNP, and CMR injury markers, and clinical variables remains uncertain.	Weak as stand‐alone prognostic candidates	Strong biological/diagnostic signals, but lower priority as independent prognostic biomarkers unless shown to add value beyond established injury markers.

Evidence categories are qualitative and intended to support interpretation rather than provide a formal risk‐of‐bias grade or meta‐analytic ranking. “Stronger candidate for external validation” denotes relative maturity within the mapped evidence base and does not imply clinical readiness or guideline‐level validation. Across all categories, external validation, calibration, decision‐curve analysis, and direct comparison against established post‐MI clinical, imaging, and protein‐biomarker models were uncommon. “Promising single‐cohort signal” denotes candidates with biologically plausible and clinically interpretable associations that require independent replication. “Moderate phenotype‐specific evidence” denotes signals supported within a coherent end point domain but limited by single‐center design, end point heterogeneity, or lack of external validation. “Exploratory” denotes findings supported mainly by small, single‐study, posttreatment, or minimally adjusted data sets. Across all categories, external validation, calibration, decision‐curve analysis, and direct comparison against established post‐MI clinical, imaging, and protein‐biomarker models were uncommon. AMI indicates acute MI; AUC, area under the curve; circRNA, circular RNA; CMR, cardiovascular magnetic resonance; HF, heart failure; hs‐cTn, high‐sensitivity cardiac troponin; HUVEC, human umbilical vein endothelial cell; lncRNA, long noncoding RNA; LV, left ventricular; LVEF, LV ejection fraction; MACE, major adverse cardiovascular event; MI, myocardial infarction; miRNA, microRNA; MVO, microvascular obstruction; ncRNA, noncoding RNA; NPPB, natriuretic peptide B; NSVR, no sacubitril/valsartan resistance; NT‐proBNP, N‐terminal pro–B‐type natriuretic peptide; PCI, percutaneous coronary intervention; qRT‐PCR, quantitative reverse transcription–polymerase chain reaction; RNA‐seq, RNA sequencing; ROC, receiver operating characteristic; STEMI, ST‐segment–elevation myocardial infarction; SVR, sacubitril/valsartan resistance; tRF, tRNA‐derived fragment; and tsRNA, tRNA‐derived small RNA.

On this basis, the strongest evidence is not for an individual universal ncRNA biomarker, but for phenotype‐specific candidates or panels. For recurrent ischemic and clinical event prediction, whole‐blood miR‐223‐3p and the miR‐126‐3p/miR‐223‐3p ratio are among the more credible event‐related signals because they were evaluated in a relatively large PCI‐treated cohort with AMI, were linked to clinically relevant ischemic end points, and retained predictive value in adjusted analyses. ⁴⁶ Similarly, sequencing‐derived miRNA candidates, such as miR‐26a‐5p, miR‐21‐5p, and miR‐191‐5p, are promising because they were identified in a discovery‐to‐validation workflow and showed incremental discrimination beyond clinical models. ⁷¹ These findings support the concept that multimarker miRNA models may be more clinically useful than single ncRNAs, particularly for heterogeneous outcomes, such as MACEs.

For structural recovery and remodeling, the most promising candidates are those evaluated against imaging‐based phenotypes rather than loosely defined clinical composites. LIPCAR and MICRA are notable among non‐miRNA candidates because they were linked to remodeling or LV function in models incorporating clinical variables, and MICRA underwent internal validation. ⁴⁸ , ⁵⁹ However, even these candidates remain below a clinical‐grade evidence threshold: LIPCAR shows a time‐dependent pattern that complicates single‐threshold interpretation, and MICRA requires external validation and assay standardization before it can be considered robust. ⁴⁸ , ⁵⁹ Among miRNAs, miR‐1254 is a credible remodeling‐related signal because it was associated with CMR‐defined remodeling in multivariable analyses, but it remains a single‐cohort candidate requiring replication. ³⁵

For reperfusion‐related injury and no‐reflow/MVO, miR‐30e, miR‐660‐5p, TUG1, and MALAT1 are biologically plausible and clinically coherent because they map to a proximal post‐PCI phenotype closely linked to microvascular injury. ⁴⁷ , ⁶² , ⁷⁰ , ⁷² This end point proximity reduces some long‐term confounding compared with late MACE prediction. However, the evidence remains only moderately strong because most studies were single center, used heterogeneous angiographic or imaging definitions, and generally lacked external validation. Therefore, these markers are best viewed as candidates for phenotype‐specific validation rather than as broadly applicable prognostic biomarkers.

Treatment‐response biomarkers occupied the least mature evidence tier. BANCR, fibrosis‐linked miRNAs in the eplerenone context, and the newly added tsRNA/tRF candidates for sacubitril/valsartan response are hypothesis generating rather than clinically robust response predictors. ⁵³ , ⁶¹ , ⁷⁴ The tsRNA/tRF study is nevertheless important because it broadens the post‐MI ncRNA landscape beyond the more extensively studied miRNA, lncRNA, and circRNA classes. tsRNAs are generated by cleavage of precursor or mature tRNAs and may be induced by cellular stressors relevant to MI biology, including hypoxia, oxidative stress, inflammation, and metabolic dysregulation. This makes them biologically plausible candidates in settings where the phenotype reflects not only acute myocyte injury but also downstream repair, ventricular remodeling, and treatment‐response heterogeneity. However, the currently eligible human post‐MI evidence is limited to 1 small single‐center study of patients with HF after AMI treated with sacubitril/valsartan, in which selected tRFs were associated with sacubitril/valsartan resistance rather than tested as baseline predictors of therapeutic benefit. ⁷⁴ Thus, tsRNAs/tRFs should be considered an emerging ncRNA class for prospective baseline and serial sampling studies, not validated treatment‐guiding biomarkers.

The weakest or most unstable candidates are those whose apparent prognostic value is likely driven by acute injury burden, timing effects, or limited study design. Cardiomyocyte‐enriched miRNAs, such as miR‐1, miR‐133a, miR‐208, and miR‐499, are well supported as injury‐linked or diagnostic signals, but their value as stand‐alone prognostic biomarkers is less convincing because they may primarily reflect infarct size or acute myocyte necrosis rather than later remodeling, HF transition, or recurrent events. ³⁷ , ⁴¹ , ⁴² , ⁵⁴ , ⁵⁸ , ⁶³ , ⁷⁵ , ⁷⁶ Similarly, miR‐21 and related remodeling candidates have shown inconsistent results across sampling windows and cohorts, making them vulnerable to phase‐mismatched interpretation. ⁴⁰ , ⁵¹ , ⁵⁵ , ⁶⁹ These candidates should therefore be prioritized only when future studies can demonstrate incremental prognostic value beyond established clinical, imaging, and protein‐biomarker models.

Incremental Value Beyond Established Prognostic Standards

A key translational question is whether ncRNAs add clinically meaningful prognostic information beyond established post‐MI risk markers rather than merely correlate with adverse phenotypes. Across the included studies, this question was addressed inconsistently. Several investigations adjusted ncRNA associations for clinical variables or reported improved discrimination after adding ncRNAs to clinical models, but the comparator models were heterogeneous and often did not include the full range of established post‐MI prognostic tools, such as LV ejection fraction, infarct size or MVO by CMR, hs‐cTn, NT‐proBNP, inflammatory markers, renal function, and validated clinical risk scores. ³⁵ , ⁴⁶ , ⁴⁸ , ⁵⁹ , ⁷¹ Consequently, statistically significant ncRNA associations should not automatically be interpreted as clinically useful incremental biomarkers. The strongest translational signals were those in which ncRNAs improved prediction beyond clinical models or were evaluated alongside imaging or protein biomarkers, including miR‐1254 in CMR‐defined remodeling, MICRA for LV function, whole‐blood miR‐223‐3p and the miR‐126‐3p/miR‐223‐3p ratio for ischemic outcomes, and discovery‐to‐validation miRNA panels for MACEs. ³⁵ , ⁴⁶ , ⁵⁹ , ⁷¹ Even for these candidates, however, external validation was uncommon, calibration and decision‐curve analyses were generally absent, and direct head‐to‐head comparisons against established biomarkers were limited. Therefore, the present evidence supports ncRNAs as promising adjunctive markers for selected phenotypes, but not yet as reproducible replacements for established clinical, imaging, or protein‐based prognostic models. Future studies should prespecify clinically relevant base models and report whether ncRNAs improve discrimination, calibration, reclassification, and decision utility beyond standard post‐MI predictors.

The relatively strong interest in no‐reflow/MVO phenotypes in the mapped literature is biologically and clinically coherent. No reflow reflects MVO despite epicardial patency and is associated with worse outcomes; it is multifactorial, involving distal embolization, endothelial dysfunction, inflammation, edema, and microvascular spasm. ⁸⁴ , ⁸⁵ From a biomarker‐development standpoint, these end points offer 2 advantages: they are proximal to the acute phase (reducing long‐term confounding), and they are mechanistically linked to inflammatory–microvascular injury pathways that could plausibly release or modulate ncRNA patterns. ⁸⁴ , ⁸⁵ Nevertheless, end point ascertainment heterogeneity (angiographic TIMI/MBG [Myocardial Blush Grade] definitions versus CMR‐defined microvascular obstruction) can itself create nonequivalent “no‐reflow” groups and complicate comparisons across studies. A practical implication is that future ncRNA work in this domain should preferentially align with standardized, high‐resolution phenotyping (eg, CMR) and explicitly report the mapping between angiographic and imaging end points.

A notable translational opportunity, directly relevant to “treatment response,” is the increasing availability of mechanistically targeted therapies that modulate post‐MI inflammation and remodeling, creating settings where ncRNAs could function as pharmacodynamic markers or response predictors. In secondary prevention after MI, anti‐inflammatory biologic therapy with canakinumab (anti–interleukin‐1β) reduced recurrent cardiovascular events in a large randomized trial, supporting inflammation as a modifiable driver of outcomes. ⁸⁶ In acute STEMI, interleukin‐6 receptor inhibition with tocilizumab has been tested in randomized designs with imaging‐based injury/salvage outcomes, showing improved myocardial salvage index and signals consistent with modulation of acute inflammatory injury. ⁸⁷ These examples matter for ncRNA interpretation: if inflammation‐modifying antibodies change injury/salvage or event rates, they should also be expected to alter circulating ncRNA profiles. The field is increasingly extending from observational biomarker research toward ncRNA‐directed therapeutics, providing a more causality‐informed framework for prioritizing candidates. Inhibition of miR‐132 has progressed from preclinical development to human evaluation and is now being tested in post‐MI reduced–LV ejection fraction settings (HF‐REVERT), explicitly aiming to prevent or reverse adverse remodeling. ⁸⁸ , ⁸⁹ , ⁹⁰ This trajectory is conceptually important for the prognostic biomarker literature: candidates anchored in pathways with therapeutic tractability and mechanistic evidence may have a clearer translational route than purely correlative signals. At the same time, this necessitates more stringent evidentiary standards for biomarker claims: if ncRNAs are to guide therapy, studies must demonstrate robust incremental predictive performance, reproducibility across centers, and clinically useful risk thresholds rather than only statistical association.

Limitations

This scoping review has limitations that may affect completeness and interpretation. First, ncRNA prognostic studies often use heterogeneous terminology for “treatment response” and post‐MI end points, and relevant articles may not be readily discoverable via title/abstract indexing; despite comprehensive searching, some eligible studies may have been missed because they were indexed under different end point labels or framed ncRNAs as exploratory secondary analyses. Second, limiting inclusion to English‐language reports and available full texts can introduce selection bias and may underrepresent regional literature or conference‐only findings. Third, because we mapped a highly heterogeneous evidence base, we did not undertake quantitative pooling; consequently, our synthesis emphasizes patterns, methodological variability, and evidence gaps rather than summary effect sizes. Finally, extraction depended on the detail reported in primary studies; incomplete reporting of preanalytics (eg, anticoagulation/heparin handling or processing delays) and normalization/quality control limits the precision with which methodological drivers of heterogeneity can be adjudicated.

Future Directions

Several design shifts would make the next generation of post‐MI ncRNA studies more decisive and more clinically relevant. (1) Phase‐aligned sampling: explicitly anchor sampling to symptom onset and reperfusion, with serial early draws where mechanistic hypotheses concern reperfusion injury/no reflow, and later draws where hypotheses concern repair/fibrosis and remodeling. (2) Preanalytical standardization in PCI cohorts, including explicit mitigation of heparin‐associated inhibition when relevant and transparent reporting of handling/processing variables. (3) Normalization rigor: avoid default U6 normalization in circulating matrices and justify reference strategies empirically for the acute MI context. (4) Trial‐embedded biomarker programs in settings with biologic or ncRNA‐targeted interventions (eg, anticytokine antibodies; anti‐miR therapeutics), enabling robust assessment of pharmacodynamic tracking and predictive enrichment. (5) Outcome harmonization using standardized no‐reflow/MVO definitions and preferably imaging‐based phenotyping to minimize outcome misclassification.

CONCLUSIONS

The mapped literature shows broad exploration of ncRNAs, predominantly miRNAs with more limited evidence for lncRNAs, circRNAs, and emerging tsRNAs/tRFs, as prognostic biomarkers after MI, but also reveals why translation remains limited: end point heterogeneity, phase‐mismatched sampling, and analytically consequential variability in normalization and peri‐PCI confounding likely underlie inconsistent replication. External literature suggests that miRNAs are well supported as injury‐linked diagnostic signals, yet their incremental diagnostic value over hs‐cTn pathways may be limited, strengthening the approach to focus on prognostic enrichment and treatment response. The most compelling translational pathway is likely standardized, phase‐aligned, multicenter validation, increasingly integrated with mechanistic therapies (anti‐inflammatory antibodies) and emerging ncRNA‐targeted interventions (eg, miR‐132 inhibition), where ncRNAs can be evaluated not only as associations but as clinically actionable tools.

Sources of Funding

None.

Disclosures

None.

Supporting information

Table S1