Association of immune cell subsets with cardiac mechanics in the Multi-Ethnic Study of Atherosclerosis

Interpretable Machine Learning Models Using Peripheral Immune Cells to Predict 90-Day Readmission or Mortality in Acute Heart Failure Patients

BACKGROUND

Acute heart failure (AHF) carries a grave prognosis, marked by high readmission and mortality rates within 90 days post-discharge. This underscores the urgent need for enhanced care transitions, early monitoring, and precise interventions for at-risk individuals during this critical period.

OBJECTIVE

Our study aims to develop and validate an interpretable machine learning (ML) model that integrates peripheral immune cell data with conventional clinical markers. Our goal is to accurately predict 90-day readmission or mortality in patients AHF.

METHODS

In our study, we conducted a retrospective analysis on 1210 AHF patients, segregating them into training and external validation cohorts. Patients were categorized based on their 90-day outcomes post-discharge into groups of 'with readmission/mortality' and 'without readmission/mortality'. We developed various ML models using data from peripheral immune cells, traditional clinical indicators, or both, which were then internally validated. The feature importance of the most promising model was examined through the Shapley Additive Explanations (SHAP) method, culminating in external validation.

RESULTS

In our cohort of 1210 patients, 28.4% (344) faced readmission or mortality within 90 days post-discharge. Our study pinpointed 10 significant indicators-spanning peripheral immune cells and traditional clinical metrics-that predict these outcomes, with the support vector machine (SVM) model showing superior performance. SHAP analysis further distilled these predictors to five key determinants, including three clinical indicators and two immune cell types, essential for assessing 90-day readmission or mortality risks.

CONCLUSION

Our analysis identified the SVM model, which merges traditional clinical indicators and peripheral immune cells, as the most effective for predicting 90-day readmission or mortality in AHF patients. This innovative approach promises to refine risk assessment and enable more targeted interventions for at-risk individuals through continuous improvement.

Immune profiling of murine cardiac leukocytes identifies triggering receptor expressed on myeloid cells 2 as a novel mediator of hypertensive heart failure

AIMS

Heart failure with preserved ejection fraction (HFpEF) is characterized by diastolic dysfunction, microvascular dysfunction, and myocardial fibrosis with recent evidence implicating the immune system in orchestrating cardiac remodelling.

METHODS AND RESULTS

Here, we show the mouse model of deoxycorticosterone acetate (DOCA)-salt hypertension induces key elements of HFpEF, including diastolic dysfunction, exercise intolerance, and pulmonary congestion in the setting of preserved ejection fraction. A modified single-cell sequencing approach, cellular indexing of transcriptomes and epitopes by sequencing, of cardiac immune cells reveals an altered abundance and transcriptional signature in multiple cell types, most notably cardiac macrophages. The DOCA-salt model results in differential expression of several known and novel genes in cardiac macrophages, including up-regulation of Trem2, which has been recently implicated in obesity and atherosclerosis. The role of Trem2 in hypertensive heart failure, however, is unknown. We found that mice with genetic deletion of Trem2 exhibit increased cardiac hypertrophy, diastolic dysfunction, renal injury, and decreased cardiac capillary density after DOCA-salt treatment compared to wild-type controls. Moreover, Trem2-deficient macrophages have impaired expression of pro-angiogenic gene programmes and increased expression of pro-inflammatory cytokines. Furthermore, we found that plasma levels of soluble TREM2 are elevated in DOCA-salt treated mice and humans with heart failure.

CONCLUSIONS

Together, our data provide an atlas of immunological alterations that can lead to improved diagnostic and therapeutic strategies for HFpEF. We provide our dataset in an easy to explore and freely accessible web application making it a useful resource for the community. Finally, our results suggest a novel cardioprotective role for Trem2 in hypertensive heart failure.

Integrated bioinformatics and machine learning algorithms reveal the critical cellular senescence-associated genes and immune infiltration in heart failure due to ischemic cardiomyopathy

Heart failure (HF) is the final stage of many cardiovascular illnesses and the leading cause of death worldwide. At the same time, ischemic cardiomyopathy has replaced valvular heart disease and hypertension as the primary causes of heart failure. Cellular senescence in heart failure is currently receiving more attention. In this paper, we investigated the correlation between the immunological properties of myocardial tissue and the pathological mechanisms of cellular senescence during ischemic cardiomyopathy leading to heart failure (ICM-HF) using bioinformatics and machine learning methodologies. Our goals were to clarify the pathogenic causes of heart failure and find new treatment options. First, after obtaining GSE5406 from the Gene Expression Omnibus (GEO) database and doing limma analysis, differential genes (DEGs) among the ICM-HF and control groups were identified. We intersected these differential genes with cellular senescence-associated genes (CSAG) via the CellAge database to obtain 39 cellular senescence-associated DEGs (CSA-DEGs). Then, a functional enrichment analysis was performed to elucidate the precise biological processes by which the hub genes control cellular senescence and immunological pathways. Then, the respective key genes were identified by Random Forest (RF) method, LASSO (Least Absolute Shrinkage and Selection Operator) algorithms, and Cytoscape's MCODE plug-in. Three sets of key genes were taken to intersect to obtain three CSA-signature genes (including MYC, MAP2K1, and STAT3), and these three CSA-signature genes were validated in the test gene set (GSE57345), and Nomogram analysis was done. In addition, we assessed the relationship between these three CSA- signature genes and the immunological landscape of heart failure encompassing immunological infiltration expression profiles. This work implies that cellular senescence may have a crucial role in the pathogenesis of ICM-HF, which may be closely tied to its effect on the immune microenvironment. Exploring the molecular underpinnings of cellular senescence during ICM-HF is anticipated to yield significant advances in the disease's diagnosis and therapy.

Association of immune cell subsets with incident heart failure in two population-based cohorts

AIMS

Circulating inflammatory markers are associated with incident heart failure (HF), but prospective data on associations of immune cell subsets with incident HF are lacking. We determined the associations of immune cell subsets with incident HF as well as HF subtypes [with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF)].

METHODS AND RESULTS

Peripheral blood immune cell subsets were measured in adults from the Multi-Ethnic Study of Atherosclerosis (MESA) and Cardiovascular Health Study (CHS). Cox proportional hazard models adjusted for demographics, HF risk factors, and cytomegalovirus serostatus were used to evaluate the association of the immune cell subsets with incident HF. The average age of the MESA cohort at the time of immune cell measurements was 63.0 ± 10.4 years with 51% women, and in the CHS cohort, it was 79.6 ± 4.4 years with 62% women. In the meta-analysis of CHS and MESA, a higher proportion of CD4+ T helper (Th) 1 cells (per one standard deviation) was associated with a lower risk of incident HF [hazard ratio (HR) 0.91, (95% CI 0.83-0.99), P = 0.03]. Specifically, higher proportion of CD4+ Th1 cells was significantly associated with a lower risk of HFrEF [HR 0.73, (95% CI 0.62-0.85), <0.001] after correction for multiple testing. No association was observed with HFpEF. No other cell subsets were associated with incident HF.

CONCLUSIONS

We observed that higher proportions of CD4+ Th1 cells were associated with a lower risk of incident HFrEF in two distinct population-based cohorts, with similar effect sizes in both cohorts demonstrating replicability. Although unexpected, the consistency of this finding across cohorts merits further investigation.

Phenotypic Changes of Peripheral γδ T Cell and Its Subsets in Patients With Coronary Artery Disease

Coronary atherosclerotic heart disease (CAD) is a chronic inflammatory cardiovascular disease with high morbidity and mortality. Growing data indicate that many immune cells are involved in the development of atherosclerosis. However, the immunological roles of γδ T cells in the initiation and progression of CAD are not fully understood. Here, we used flow cytometry to determine phenotypical changes of γδ T cells and their subpopulations in peripheral blood samples collected from 37 CAD patients. The Pearson correlation coefficient was used to analyze the relationship between the clinical parameter (serum LDL-C level) and the changes of immunophenotypes of γδ T cells. Our results demonstrated that the frequencies and absolute numbers of total γδ T cells and Vδ2⁺ T cells were significantly decreased in CAD patients when compared to healthy individuals. However, the proportion of Vδ1⁺ T cells was much lower in CAD patients than that of healthy individuals. Most importantly, a significant alteration of the Vδ1/Vδ2 ratio was found in CAD patients. In addition, a series of surface markers that are associated with costimulatory signals (CD28, CD40L, CD80, CD86), activation levels (CD69, CD25, HLA-DR), activating NK cell receptors (NKp30, NKp46, NKG2D) and inhibitory receptors (PD-1, CTLA-4, PD-1, Tim-3) were determined and then analyzed in the total γδ T cells, Vδ2⁺T cells and Vδ2^-T cells of CAD patients and healthy individuals. The data demonstrated that immunological activities of total γδ T cells, Vδ2⁺T cells, and Vδ2^-T cells of CAD patients were much lower than those in healthy individuals. Moreover, we found that there were positive correlations between the serum LDL-C levels and frequencies of CD3⁺γδ⁺ T cells, CD69⁺Vδ2⁺T cells, NKG2D⁺Vδ2⁺T cells, and NKp46⁺Vδ2⁺T cells. By contrast, there was an inverse correlation between the levels of serum LDL-C and the frequencies of CD69⁺Vδ2^-T cells and NKp46⁺Vδ2^-T cells. Accordingly, these findings could help us to better understand the roles of γδ T cells in the CAD, and shed light on the development of novel diagnostic techniques and therapeutic strategies by targeting γδ T cells for CAD patients.