Pereira, Naveen L

ABSTRACT Ischemic events after contemporary percutaneous coronary intervention (PCI) are uncommon but carry high morbidity/mortality. Identifying patients at highest risk is critical to guide dual antiplatelet therapy (DAPT) intensity while minimizing bleeding. Current machine learning (ML) model‐developed risk scores do not incorporate pharmacogenetic data. To develop and externally validate ML models that integrate clinical, demographic, and CYP2C19 genetic information to predict 1‐year ischemic outcomes post‐PCI to refine clinical decision making. We analyzed 8317 patients from TAILOR‐PCI trial ( n = 4572) and the Precision PCI registry ( n = 3745). The outcome was a composite of cardiovascular death, myocardial infarction, stroke, and stent thrombosis at 1 year. Boruta feature selection identified 11 predictors. Multiple ML algorithms were trained in TAILOR‐PCI and validated in Precision PCI using cross‐validation and synthetic minority oversampling (SMOTE). Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The best external performance was achieved with a support vector machine (SVM, polynomial kernel) (AUC 0.667; sensitivity 0.871; specificity 0.282), while XGBoost provided a more balanced profile (AUC 0.619; sensitivity 0.442; specificity 0.688). Variable importance for the SVM polynomial model demonstrated that all 11 included Boruta feature selected predictors had relatively high importance (> 75). ML models trained on large clinical trial and real‐world registry datasets can help identify the small subset of patients at high ischemic risk after PCI. This distinction is of relevance because ischemic events are rare, and most patients may safely de‐escalate DAPT to reduce bleeding risk while maintaining ischemic protection through a multimodal approach to risk stratification. Trial Registration: TAILOR‐PCI URL: https://clinicaltrials.gov/ct2/show/NCT01742117

The 2025 American College of Cardiology/American Heart Association/American College of Emergency Physicians/National Association of Emergency Medical Services Physicians/Society for Cardiovascular Angiography & Interventions acute coronary syndrome guideline focuses on strategies to reduce bleeding risk with antiplatelet therapy yet lacks any recommendation related to CYP2C19 genotyping. The impact of CYP2C19 loss‐of‐function alleles on the effectiveness of clopidogrel is well documented, and although prasugrel and ticagrelor more effectively reduce the risk for atherothrombotic events compared with clopidogrel in patients with a CYP2C19 loss‐of‐function allele, clopidogrel reduces bleeding risk without an increase in atherothrombotic events compared with prasugrel or ticagrelor in those without a loss‐of‐function allele. Accordingly, an American Heart Association Scientific Statement supports CYP2C19 genetic testing before oral P2Y 12 inhibitors are prescribed. This commentary summarizes the evidence in support of CYP2C19 ‐guided P2Y 12 inhibitor selection in the context of other 2025 acute coronary syndrome guideline recommendations and urges future guidelines to incorporate recommendations for CYP2C19 genotyping, especially for those at high bleeding risk.

This study uncovers a previously unrecognized role for NAV3 in TGF-β1-driven cardiac fibroblast activation. We show that NAV3 facilitates profibrotic remodeling through noncanonical signaling and cell cycle arrest, independently of SMAD2/3. These findings position NAV3 as a novel regulator of fibroblast phenotype and a potential modulator of cardiac fibrosis.

Background. Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole genome transcriptomic profiling offers a systems-based, unbiased approach to elucidate the molecular mechanisms underlying ACR. However, noninvasive, longitudinal biomarker assessments capable of capturing the temporal dynamics of rejection biology remain scarce. Methods. RNA sequencing of peripheral blood from heart transplant recipients before, during, and after ACR was compared with nonrejection controls. Pathway analysis was conducted using differentially expressed genes (DEGs), and a machine learning approach was applied to assess gene-based prediction of ACR. Results. A total of 235 rejection-specific significant DEGs and 863 postrejection DEGs (false discovery rate < 0.05) were identified. During ACR, DEGs were enriched for T-cell activation/differentiation, apoptosis, and B-cell receptor signaling pathways. By combining the 2 sets of DEGs, a panel of 71 common genes was identified that reflected the significant, longitudinal transcriptomic dynamics of ACR. In an elastic net machine learning–based classifier, DYNLL1 and SERF2 were identified as ACR predictive genes, and achieved a cross-validated area under the receiver operating characteristic curve of 0.63. Conclusions. Peripheral blood transcriptomics identify dynamic temporal responses in ACR including T- and B-cell pathways with potential ACR predictive genes that warrant further investigation.

Abstract Background and Aims Truncating variants in the TTN gene (TTNtv) are the most common genetic cause of dilated cardiomyopathy (DCM) but also occur as incidental findings in the general population. This study investigated factors associated with the clinical manifestation of TTNtv. Methods An international multicentre retrospective observational study was performed in families with TTNtv-related DCM. Shared frailty models were used to estimate associations of variant characteristics with lifetime risk of DCM, and logistic regression to estimate odds ratios (ORs) for individual-level clinical risk factor profiles (cardiac conditions, cardiovascular comorbidities, lifestyle) and DCM. Results A total of 3158 subjects in 1043 families with TTNtv-related DCM were studied. TTNtv-positive subjects were 21-fold more likely to develop DCM [OR, 21.21; 95% confidence interval (CI), 14.80–30.39]. Disease onset was earlier in males, but was similar for TTNtv of different types and locations. The presence of clinical risk factors was associated with earlier DCM onset (OR, 3.41; 95% CI, 2.06–5.64), with a prior history of atrial fibrillation having a two-fold increased odds of DCM (OR, 2.05; 95% CI, 1.27–3.32). The prevalence of clinical risk factors increased with age; however, the strength of the DCM association was greatest for young-onset (&lt;30 years) disease (OR, 4.75; 95% CI, 2.35–9.60). Administration of beta-adrenergic receptor or renin-angiotensin system-blocking drugs prior to overt DCM was associated with 87% reduced odds of DCM (OR, .13; 95% CI, .08–.23). Conclusions Disease onset in TTNtv-associated familial DCM is dependent on individual patient context and is potentially modifiable by risk factor management and prophylactic therapeutic intervention.

ABSTRACT Aims Common genetic variants have been linked to an increased risk of non-ischaemic cardiomyopathy (NICM). The primary objective of this study was to evaluate the significance of these variants in a general population. Methods and results Thirteen NICM risk alleles, previously validated by meta-analyses of case-control genetic association studies, were used to determine genetic risk (GR) in a large, unselected cohort (n = 1897) of Olmsted County residents aged &gt;45 years. Clinical and echocardiographic data, with biomarkers, were correlated with this NICM-GR over a median of 16 years of follow-up (interquartile range [IQR] 15–17). There were no significant differences between the study population quartiles, based on NICM-GR, in terms of age (median 61.6 [IQR 53.6–70.4]), sex (48% male), and cardiovascular risk factors. A significant correlation was detected by specific linear-regression models between NICM-GR and left ventricular (LV) ejection-fraction (beta [standard error]: −2.68 [0.68], p &lt; 0.001), LV end-systolic-diameter (0.22 [0.06], p &lt; 0.001), and LV end-diastolic-diameter (0.14 [0.06], p = 0.01). During follow-up, 46 subjects developed NICM. Using a 3:1 matched-cohort of non-NICM versus NICM patients, linear-regression analysis found a significant correlation between NICM-GR and NICM development (odds ratio 2.27, 95% confidence interval 1.06–4.85, p = 0.03). There was no significant association between these variants and heart failure biomarkers (aldosterone, natriuretic peptides, ST2, galectin-3). Conclusions The NICM-GR correlates with LV function and dimension, and subsequent development of NICM in the general population. The lack of correlation of these variants with cardiovascular risk factors and the renin–angiotensin–aldosterone axis or natriuretic peptides suggest different biological mechanisms involved. These findings support the need to explore newer pathophysiologic pathways in the development of NICM.

Acute right ventricular failure (ARVF) is commonly seen in the intensive care unit and constitutes a significant clinical challenge, with associated high in-hospital mortality. Recently, the treatment of ARVF has significantly changed, with the progressive implementation of mechanical circulatory support devices that now represent important tools for clinicians in treating this condition. However, despite recent advancements, the optimal approach for ARVF remains elusive, and precise treatment algorithms and comprehensive management protocols are still lacking. In the present review, we explore the pathophysiology of ARVF, highlighting the different mechanisms that may lead to this clinical entity and emphasizing the left and right heart’s complex interplay. We analyze the different therapeutic options that are now available for short- and long-term management of ARVF, with a particular focus on the advantages and disadvantages of the mechanical circulatory support devices actually used. Furthermore, we propose future directions in the field and a possible flowchart for the treatment of this condition.

BACKGROUND: Dilated cardiomyopathy (DCM) is a major cause of heart failure and carries a high mortality rate. Myocardial recovery in DCM-related heart failure patients is highly variable, with some patients having little or no response to standard drug therapy. A genome-wide association study may agnostically identify biomarkers and provide novel insight into the biology of myocardial recovery in DCM. METHODS: A genome-wide association study for change in left ventricular ejection fraction was performed in 686 White subjects with recent-onset DCM who received standard pharmacotherapy. Genome-wide association study signals were subsequently functionally validated and studied in relevant cellular models to understand molecular mechanisms that may have contributed to the change in left ventricular ejection fraction. RESULTS: The genome-wide association study identified a highly suggestive locus that mapped to the 5′-flanking region of the CDCP1 (CUB [complement C1r/C1s, Uegf, and Bmp1] domain containing protein 1) gene (rs6773435; P =7.12×10 −7 ). The variant allele was associated with improved cardiac function and decreased CDCP1 transcription. CDCP1 expression was significantly upregulated in human cardiac fibroblasts (HCFs) in response to the PDGF (platelet-derived growth factor) signaling, and knockdown of CDCP1 significantly repressed HCF proliferation and decreased AKT (protein kinase B) phosphorylation. Transcriptomic profiling after CDCP1 knockdown in HCFs supported the conclusion that CDCP1 regulates HCF proliferation and mitosis. In addition, CDCP1 knockdown in HCFs resulted in significantly decreased expression of soluble ST2 (suppression of tumorigenicity-2), a prognostic biomarker for heart failure and inductor of cardiac fibrosis. CONCLUSIONS: CDCP1 may play an important role in myocardial recovery in recent-onset DCM and mediates its effect primarily by attenuating cardiac fibrosis.