Genetic effects on gene expression are often cell type-specific and obscured in bulk analyses. To resolve this context-dependent regulation, we performed a federated cis-eQTL meta-analysis across 12 PBMC datasets (2,032 individuals, 2.5 million cells). Across six immune cell types, we identified cis-eQTLs for 6,592 genes and fine-mapped 14,985 independent loci. Notably, the 42% of eQTLs that were undetected in a bulk eQTL study on 43,301 whole blood samples also showed stronger enrichment for disease GWAS loci. We further identified three genome-wide significant and 65 suggestive loci affecting the abundance of (rare) immune cell types and validated these using previously reported hematological GWAS and bulk-derived trans-eQTLs. Integrating single-cell cis-eQTLs with bulk trans-eQTLs enabled us to anchor 6,382 trans-eGenes (37.2% novel) to upstream regulators and reconstruct directed gene regulatory relationships. For example, a hemorrhoidal disease-associated variant showed a CD4+ T cell-specific cis-eQTL on BACH1 that colocalized with 45 immune and metabolic trans-eGenes. These results demonstrate the power of single-cell QTL meta-analysis in interpreting complex trait genetics.

Background: Assessment of health-related quality of life (HRQoL) in patients with cardiovascular disease (CVD) is impaired by limitations of current patient-reported outcome measures (PROMs). We developed the first cardiovascular disease (CVD) specific electronic PROM for which health items were derived by a fully patientcentered method. This paper reports on the measurement of HRQoL in CVD patients by a novel developed electronic patient-centred PROM based on a preference-based measurement model. Methods and results: In an earlier patient-based study nine health items were selected as most important to CVD patients. These items were assessed in the novel preference-based PROM of this study. CVD patients registered with a Dutch patient organization were asked to rate their health state. We compared HRQoL between subgroups of age, gender and CVD. A total of 554 patients participated in this study. The patient reported health items "worry", "self-reliance" and "sexuality" had the highest impact on HRQoL of CVD patients. Median HRQoL was better for men compared to woman (-17.04, IQR: 31.47 to -3.91 vs. -25.22; IQR: 42.06 to -9.53, p = 0.003). Best and worst HRQoL were observed in patients with an unknown or other CVD disease (-15.61, IQR: 28.52 to -3.91) followed by individuals with coronary artery disease (-16.99, IQR: 38.08 - 0.00) and heart failure (-24.27, IQR: 42.64 to -12.98). Conclusions: This novel patient-centred, preference-based, CVD-specific PROM accurately measures HRQoL by taking individual health preferences into account and tackling limitations of current PROMs. This PROM is therefore promising to evaluate interventions and optimize personalized therapies.

Immune checkpoints are understudied in cardiovascular disease. We investigated the TIM-3 pathway in human serum, peripheral blood mononuclear cells (PBMCs) and cardiac tissue following myocardial infarction (MI). First, TIM-3 ligands in serum, galectin-9 and HMGB-1, were associated with cardiac remodelling 4 months post-MI (n = 357). Next, post-hoc single-cell RNA-sequencing of PBMCs from MI patients (n = 38) and controls (n = 38) revealed acute downregulation of TIM-3 in lymphocytes 24 h post-MI, which occurred after 8 weeks in myeloid cells. In the heart, single-nucleus RNA-sequencing and spatial transcriptomics of MI tissue demonstrated cardiomyocyte HMGB-1 upregulation which could communicate with myeloid TIM-3. Pro-inflammatory macrophages specifically showed significant TIM-3 expression and NLRP3 inflammasome activity. On the protein level, HMGB-1 was also upregulated in the infarcted heart and actively translocated throughout the cells. Finally, in vitro macrophage stimulation with HMGB-1 induced pro-inflammatory polarization (e.g. NLRP3 pathway activation), which was prevented by blocking TIM-3. Thus, TIM-3/HMGB-1 interaction presents as a target in cardiac inflammation following MI.

Aims The development and incidence of de-novo heart failure after ST-elevation myocardial infarction (STEMI) in the contemporary era of rapid reperfusion are largely unknown. We aimed to establish the incidence of post-STEMI heart failure, stratified by left ventricular ejection fraction (LVEF) and to find predictors for its occurrence. Furthermore, we investigated the course of left ventricular systolic and diastolic function after STEMI. Methods and results A total of 1172 all-comer STEMI patients from the CardioLines Biobank were included. Patients were predominantly male (74.5%) and 64 +/- 12 years of age. During a median follow-up of 3.7 years (2.0, 5.5) we found a total incidence of post-STEMI heart failure of 10.9%, of which 52.1% heart failure with reduced ejection fraction (HFrEF), 29.4% heart failure with mildly reduced ejection fraction and 18.5% heart failure with preserved ejection fraction (HFpEF). Independent predictors for the development of HFrEF were male sex (beta = 0.97, p = 0.009), lung crepitations (beta = 1.09, p = 0.001), potassium level (mmol/L, beta = 0.43, p = 0.012), neutrophil count (109/L, beta = 0.09, p = 0.001) and a reduced LVEF (beta = 1.91, p < 0.001) at baseline. Independent predictors for the development of HFpEF were female sex (beta = 0.99, p = 0.029), pre-existing kidney failure (beta = 1.95, p = 0.003) and greater left atrial volume index (beta = 0.04, p = 0.033) at baseline. Follow-up echocardiography (median follow-up 20 months) showed an improvement in LVEF (p < 0.001), whereas changes in diastolic function parameters showed both improvement and deterioration. Conclusion In the current era of early STEMI reperfusion, still one in 10 patients develops heart failure, with approximately half of the patients with a reduced and half with a mildly reduced or normal LVEF. Predictors for the development of HFrEF were different from HFpEF. [GRAPHICS] .

AIMS:Despite treatment advancements, cardiovascular disease remains a leading cause of death worldwide. Identifying new targets is crucial for enhancing preventive and therapeutic strategies. The gut microbiome has been associated with coronary artery disease (CAD), however our understanding of specific changes during CAD development remains limited. We aimed to investigate microbiome changes in participants without clinically manifest CAD with different cardiovascular risk levels and in patients with ST-elevation myocardial infarction (STEMI).METHODS AND RESULTS:In this cross-sectional study, we characterized the gut microbiome using metagenomics of 411 faecal samples from individuals with low (n = 130), intermediate (n = 130), and high (n = 125) cardiovascular risk based on the Framingham score, and STEMI patients (n = 26). We analysed diversity, and differential abundance of species and functional pathways while accounting for confounders including medication and technical covariates. Collinsella stercoris, Flavonifractor plautii, and Ruthenibacterium lactatiformans showed increased abundances with cardiovascular risk, while Streptococcus thermophilus was negatively associated. Differential abundance analysis revealed eight species and 49 predicted metabolic pathways that were differently abundant among the groups. In the gut microbiome of STEMI patients, there was a depletion of pathways linked to vitamin, lipid, and amino acid biosynthesis.CONCLUSION:We identified four microbial species showing a gradual trend in abundance from low-risk individuals to those with STEMI, and observed differential abundant species and pathways in STEMI patients compared to those without clinically manifest CAD. Further investigation is warranted to gain deeper understanding of their precise role in CAD progression and potential implications, with the ultimate goal of identifying novel therapeutic targets.

BACKGROUND: The immune system’s role in ST-segment–elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed. METHODS: For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6–8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells). RESULTS: Compared with controls, classical monocytes were increased and CD56 dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease–associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies. CONCLUSIONS: Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered a key pathogenic driver of these diseases, but the underlying immune states and their clinical implications remain poorly understood. Multiomic factor analysis (MOFA) allows unsupervised data exploration across multiple data types, identifying major axes of variation and associating these with underlying molecular processes. We hypothesized that applying MOFA to multiomic data obtained from blood might uncover hidden sources of variance and provide pathophysiological insights linked to clinical needs. Here we compile a longitudinal multiomic dataset of the systemic immune landscape in both ACS and CCS (n = 62 patients in total, n = 15 women and n = 47 men) and validate this in an external cohort (n = 55 patients in total, n = 11 women and n = 44 men). MOFA reveals multicellular immune signatures characterized by distinct monocyte, natural killer and T cell substates and immune-communication pathways that explain a large proportion of inter-patient variance. We also identify specific factors that reflect disease state or associate with treatment outcome in ACS as measured using left ventricular ejection fraction. Hence, this study provides proof-of-concept evidence for the ability of MOFA to uncover multicellular immune programs in cardiovascular disease, opening new directions for mechanistic, biomarker and therapeutic studies. Multiomic factor analysis of blood multiomic data, including single-cell transcriptomics, for individuals with either acute or chronic coronary syndrome identifies immune cell signatures that correlate with treatment outcomes.

Galectin-3 and Suppression of tumorigenicity-2 (ST2) are known markers of cardiac fibrosis. We investigated the prognostic value of fibrotic markers for the development of diastolic dysfunction and long-term outcome in patients suffering an ST-elevated myocardial infarction (STEMI). We analyzed 236 patients from the GIPS-III cohort with available echocardiographic studies and plasma measurements at hospitalization and after 4 months follow-up. Adjusted logistic mixed effects modelling revealed no association between the occurrence of diastolic dysfunction over time with abnormal plasma levels of galectin-3 and ST2. We observed no differences regarding survival outcome at follow-up of 5 years between patients with normal versus abnormal values in both galectin-3 (P = 0.75), and ST2 (P = 0.85). In conclusion, galectin-3 and sST2 were not associated with the development of diastolic dysfunction in non-diabetic patients that presented with a STEMI.

Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered to be a key pathogenic driver, but immune states in humans and their clinical implications remain poorly understood. We hypothesized that Multi-Omic blood analysis combined with Multi-Omic Factor Analysis (MOFA) might uncover hidden sources of variance providing pathophysiological insights linked to clinical needs. Here, we compile a single cell longitudinal dataset of the circulating immune states in ACS & CCS (13x10 3 clinical & Multi-Omic variables, n=117 subjects, n=838 analyzed samples) from two independent cohorts. Using MOFA, we identify multilayered factors, characterized by distinct classical monocyte and CD4 + & CD8 + T cell states that explain a large proportion of inter-patient variance. Three factors either reflect disease course or predict outcome in coronary syndromes. The diagnostic performance of these factors reaches beyond established biomarkers highlighting the potential use of MOFA as a novel tool for multilayered patient risk stratification.

Fetuin-A acts as both an inhibitor of calcification and insulin signaling. Previous studies reported conflicting results on the association between fetuin-A and cardiometabolic diseases. We aim to provide further insights into the association between genetically predicted levels of fetuin-A and cardiometabolic diseases using a Mendelian randomization strategy. Genetic variants associated with fetuin-A and their effect sizes were obtained from previous genetic studies. A series of two-sample Mendelian randomization analyses in 412,444 unrelated individuals from the UK Biobank did not show evidence for an association of genetically predicted fetuin-A with any stroke, ischemic stroke, or myocardial infarction. We do find that increased levels of genetically predicted fetuin-A are associated with increased risk of type 2 diabetes (OR = 1.21, 95%CI 1.13-1.30, P = < 0.01). Furthermore, genetically predicted fetuin-A increases the risk of coronary artery disease in individuals with type 2 diabetes, but we did not find evidence for an association between genetically predicted fetuin-A and coronary artery disease in those without type 2 diabetes (P for interaction = 0.03). One SD increase in genetically predicted fetuin-A decreases risk of myocardial infarction in women, but we do not find evidence for an association between genetically predicted fetuin-A and myocardial infarction in men (P for interaction = < 0.01). Genetically predicted fetuin-A is associated with type 2 diabetes. Furthermore, type 2 diabetes status modifies the association of genetically predicted fetuin-A with coronary artery disease, indicating that fetuin-A increases risk in individuals with type 2 diabetes. Finally, higher genetically predicted fetuin-A reduces the risk of myocardial infarction in women, but we do not find evidence for an association between genetically predicted fetuin-A and myocardial infarction in men.

Background Adverse systolic remodeling after ST-elevation myocardial infarction (STEMI) is associated with poor clinical outcomes. However, little is known about diastolic remodeling. The purpose of this study was to identify the factors leading to diastolic remodeling. Methods Echocardiography was performed during hospitalization and at 4 months follow-up in 267 non-diabetic STEMI patients from the GIPS-III trial. As parameters of diastolic remodeling we used (1.) the E/e′ at 4 months adjusted for the E/e′ at hospitalization and (2.) the change in E/e′ between hospitalization and 4 months. Multivariable regression models correcting for age and sex were constructed to identify possible association of clinical and angiographic variables as well as biomarkers with diastolic remodeling. Results Older age, female gender, hypertension, multi vessel disease, higher glucose and higher peak CK were independent predictors of higher E/e′ at 4 months in a multivariable model (R 2 :0.20). After adjustment for E/e′ during hospitalization only female gender, multivessel disease and higher glucose remained predictors of E/e′ at four months (R 2 :0.40). Lower myocardial blush grade, AST and NT-proBNP were independent predictors of a higher increase of E/e′ between hospitalization and at 4 months in a multivariable model (R 2 :0.08). Conclusions Our data supports the hypothesis that female gender, multivessel coronary artery disease, and microvascular damage are important predictors of adverse diastolic remodeling after STEMI. In addition, our data suggests that older age and hypertension prior to STEMI may have contributed to worse pre-existing diastolic function. Trial registration : NIH, NCT01217307. Prospectively registered on October 8th 2010, https://clinicaltrials.gov/ct2/show/NCT01217307 .

BACKGROUND:Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals. RESULTS:We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases. CONCLUSION:Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms.

Iron deficiency has been extensively researched and is associated with adverse outcomes in heart failure. However, to our knowledge, the temporal evolution of iron status has not been previously investigated in patients with acute coronary syndrome (ACS). Therefore, we aimed to explore the temporal pattern of repeatedly measured iron, ferritin, transferrin, and transferrin saturation (TSAT) in relation to prognosis post-ACS. BIOMArCS (BIOMarker study to identify the Acute risk of a Coronary Syndrome) is a prospective, multicenter, observational cohort study conducted in The Netherlands between 2008 and 2015. A total of 844 patients with post-ACS were enrolled and underwent high-frequency (median 17) blood sampling during 1 year follow-up. Biomarkers of iron status were measured batchwise in a central laboratory. We analyzed 3 patient subsets, including the casecohort (n = 187). The primary endpoint (PE) was a composite of cardiovascular mortality and repeat nonfatal ACS, including unstable angina pectoris requiring revascularization. The association between iron status and the PE was analyzed using multivariable joint models. Mean age was 63 years; 78% were men, and >50% had iron deficiency at first sample in the case-cohort. After adjustment for a broad range of clinical variables, 1 SD decrease in log-iron was associated with a 2.2-fold greater risk of the PE (hazard ratio 2.19, 95% confidence interval 1.34 to 3.54, p = 0.002). Similarly, 1 SD decrease in log-TSAT was associated with a 78% increased risk of the PE (hazard ratio 1.78, 95% confidence interval 1.17 to 2.65, p = 0.006). Ferritin and transferrin were not associated with the PE. Repeated measurements of iron and TSAT predict risk of adverse outcomes in patients with post-ACS during 1 year follow-up. (C) 2022 The Authors. Published by Elsevier Inc.

Cardiovascular disease is the leading cause of death worldwide. The societal health burden it represents can be reduced by taking preventive measures and developing more effective therapies. Reaching these goals, however, requires a better understanding of the pathophysiological processes leading to and occurring in the diseased heart. In the last 5 years, several biological advances applying single-cell technologies have enabled researchers to study cardiovascular diseases with unprecedented resolution. This has produced many new insights into how specific cell types change their gene expression level, activation status and potential cellular interactions with the development of cardiovascular disease, but a comprehensive overview of the clinical implications of these findings is lacking. In this review, we summarize and discuss these recent advances and the promise of single-cell technologies from a translational perspective across the cardiovascular disease continuum, covering both animal and human studies, and explore the future directions of the field.

BACKGROUND AND AIMS:Leukocytosis, the expansion of white blood cells, is associated with increased cardiovascular risk. Studies in animal models have shown that high-density lipoprotein cholesterol (HDL-c) suppresses leukocytosis by mediating cholesterol efflux from hematopoietic stem and progenitor cells. HDL-c showed a moderate negative association with leukocyte numbers in the UK Biobank and Multi-Ethnic Study of Atherosclerosis. Cholesterol efflux capacity of HDL (HDL-CEC) or HDL particle (HDL-P) number has been proposed as improved inverse predictor of CVD compared to plasma HDL-c. In the LifeLines DEEP (LLD) cohort (n = 962), a sub-cohort representing the prospective population-based LL cohort from the North of The Netherlands, we tested the hypothesis that HDL-CEC and HDL-P were associated with lower leukocyte counts. METHODS:We carried out multivariable regression and causal mediation analyses (CMA) to test associations between HDL-c, HDL-CEC, or HDL-P and leukocyte counts. We measured HDL-CEC in THP-1 macrophages and HDL-P and composition using nuclear magnetic resonance. RESULTS:HDL-c associated negatively with leukocyte counts, as did extra-large and large HDL-P, while HDL-CEC showed no association. Each one-standard deviation (SD) increase in extra-large HDL-P was associated with 3.0% and 4.8% lower leukocytes and neutrophils, respectively (q < 0.001). In contrast, plasma concentration of small HDL-P associated positively with leukocyte and neutrophil counts, as did small HDL-P triglycerides (TG) and total plasma TG. CMA showed that the association between S-HDL-P and leukocytes was mediated by S-HDL-TG. CONCLUSIONS:The association between HDL-P and leukocyte counts in the general population is dependent on HDL-P size and composition, but not HDL-CEC.

SGLT2 inhibitors (SGLT2i) block renal glucose reabsorption. Due to the unexpected beneficial observations in type 2 diabetic patients potentially related to increased natriuresis, SGLT2i are also studied for heart failure treatment. This study aimed to identify genetic variants mimicking SGLT2i to further our understanding of the potential underlying biological mechanisms. Using the UK Biobank resource, we identified 264 SNPs located in the SLC5A2 gene or within 25kb of the 5′ and 3′ flanking regions, of which 91 had minor allele frequencies >1%. Twenty-seven SNPs were associated with glycated hemoglobin (HbA1c) after Bonferroni correction in participants without diabetes, while none of the SNPs were associated with sodium excretion. We investigated whether these variants had a directionally consistent effect on sodium excretion, HbA1c levels, and SLC5A2 expression. None of the variants met these criteria. Likewise, we identified no common missense variants, and although four SNPs could be defined as 5′ or 3′ prime untranslated region variants of which rs45612043 was predicted to be deleterious, these SNPs were not annotated to SLC5A2. In conclusion, no genetic variant was found mimicking SGLT2i based on their location near SLC5A2 and their association with sodium excretion or HbA1c and SLC5A2 expression or function.

Introduction: Increased levels of the inflammatory cytokine interleukin 6 (IL-6) after percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction (STEMI) are associated with larger infarct size and decreased cardiac function. Early treatment with the IL-6 receptor inhibitor tocilizumab in STEMI patients resulted in less myocardial damage, especially in patients treated >3 hours after symptom onset. However, the specific window of opportunity for IL-6 inhibition in STEMI patients remains to be investigated. Therefore, we studied IL-6 levels in STEMI patients varying in ischemic time (i.e. time from symptom onset to PCI), and its association with infarct size. Methods: In 369 STEMI patients IL-6 levels were measured at 24 hours post-PCI. Patients were categorized according to ischemic time (<2 hours, 2-3 hours, 3-4 hours, 4-5 hours, >5 hours). At 4 months, infarct size was assessed by magnetic resonance imaging. IL-6 levels were log transformed for statistical analysis. Results: IL-6 levels at 24 hours post-PCI increased from 9.2 ng/ml (IQR 5.2-16.7 ng/ml) in patients with symptom onset <2 hours to 13.2 ng/ml (IQR 9.0-20.2 ng/ml) in patients with symptom onset between 4-5 hours (P trend =0.036), stabilizing in patients with symptom onset >5 hours ( Figure 1A ). Higher IL-6 levels at 24 hours post-PCI were associated with larger infarct size in patients with symptom onset <4 hours (<2 hours: β 1.9, 95% CI 0.6-3.1, P=0.004; 2-3 hours: β 1.9, 95% CI 0.3-3.4, P=0.019; 3-4 hours: β 3.0, 95% CI 1.6-4.5, P<0.001) ( Figure 1B ). Conclusions: IL-6 levels at 24 hours post-PCI are related to ischemic time. Moreover, higher IL-6 levels are associated with larger infarct size in patients with ischemic time shorter than 4 hours, suggesting a time dependent role of IL-6. This suggests that the window of opportunity for IL-6 inhibition in STEMI patients is within 4 hours of symptom onset. Randomized controlled trials are necessary to further establish this relationship.

The gut metabolite trimethylamine N-oxide (TMAO) at admission has a prognostic value in ST-elevation myocardial infarction (STEMI) patients. However, its sequential changes and relationship with long-term infarct-related outcomes after primary percutaneous coronary intervention (PCI) remain elusive. We delineated the temporal course of TMAO and its relationship with infarct size and left ventricular ejection fraction (LVEF) post-PCI, adjusting for the estimated glomerular filtration rate (eGFR). We measured TMAO levels at admission, 24 h and 4 months post-PCI in 379 STEMI patients. Infarct size and LVEF were determined by cardiac magnetic resonance 4 months after PCI. TMAO levels decreased from admission (4.13 ± 4.37 μM) to 24 h (3.41 ± 5.84 μM, p = 0.001) and increased from 24 h to 4 months (3.70 ± 3.86 μM, p = 0.026). Higher TMAO values at 24 h were correlated to smaller infarct sizes (rho = −0.16, p = 0.024). Larger declines between admission and 4 months suggestively correlated with smaller infarct size, and larger TMAO increases between 24 h and 4 months were associated with larger infarct size (rho = −0.19, p = 0.008 and rho = −0.18, p = 0.019, respectively). Upon eGFR stratification using 90 mL/min/1.73 m2 as a cut-off, significant associations between TMAO and infarct size were only noted in subjects with impaired renal function. In conclusion, TMAO levels in post-PCI STEMI patients are prone to fluctuations, and these fluctuations could be prognostic for infarct size, particularly in patients with impaired renal function.