Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction.

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 CD56dim 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.

Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes.

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.

Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data.

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.

Association of epicardial adipose tissue with different stages of coronary artery disease: A cross-sectional UK Biobank cardiovascular magnetic resonance imaging substudy.

Objective: Increased epicardial adipose tissue (EAT) has been identified as a risk factor for the development of coronary artery disease (CAD). However, the exact role of EAT in the development of CAD is unclear. This study aims to compare EAT volumes between healthy controls and individuals with stable CAD and a history of myocardial infarction (MI). Furthermore, associations between clinical and biochemical parameters with EAT volumes are examined. Methods: This retrospective cross-sectional study included 171 participants from the United Kingdom Biobank (56 healthy controls; 60 stable CAD; 55 post MI), whom were balanced for age, sex and body mass index (BMI). EAT volumes were quantified on end-diastolic cardiac magnetic resonance (CMR) imaging short-axis slices along the left and right ventricle and indexed for body surface area (iEAT) and iEAT volumes were compared between groups. Results: iEAT volumes were comparable between control, CAD and MI cases (median [IQR]: 66.1[54.4-77.0] vs. 70.9[55.8-85.5] vs. 67.6[58.6-82.3] mL/m2, respectively (p > 0.005 for all). Increased HDL-cholesterol was associated with decreased iEAT volume (ß = -14.8, CI = -24.6 to -4.97, p = 0.003) and suggestive associations (P-value < 0.05 and ≥ 0.005) were observed between iEAT and triglycerides (ß = 3.26, CI = 0.42 to 6.09, p = 0.02), Apo-lipoprotein A (ß = -16.3, CI = -30.3 to -2.24, p = 0.02) and LDL-cholesterol (ß = 3.99, CI = -7.15 to -0.84, p = 0.01). Conclusions: No significant differences in iEAT volumes were observed between patients with CAD, MI and healthy controls. Our results indicate the importance of correcting for confounding by CVD risk factors, including circulating lipid levels, when studying the relationship between EAT volume and CAD. Further mechanistic studies on causal pathways and the role of EAT composition are warranted.

Translational insights from single-cell technologies across the cardiovascular disease continuum.

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.

Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility.

Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.

Sex differences in leukocyte profile in ST-elevation myocardial infarction patients.

BACKGROUND: Whether sex differences exist in the inflammatory response after ST-elevation myocardial infarction (STEMI) remains to be elucidated. We studied leukocyte profiles and their prognostic value in men and women presenting with STEMI. METHODS: From a total of 552 consecutive STEMI patients, blood samples were collected at hospital admission. Linear regression was used to assess the relationship between leukocyte profiles and enzymatic infarct size. Cox regression was used to assess the association between leukocyte profiles and one-year mortality. RESULTS: Women presented with higher lymphocyte counts (2.3·109 cells/L (IQR 1.6-3.1) vs. 1.8·109 cells/L (IQR 1.4-2.5), p = 3.00 ∙ 10-4) and percentages (21.1% (IQR 14.4-28.1) vs. 17.1% (IQR 12.3-24.3), p = 0.004). Lymphocyte to monocyte ratio (LMR) was also higher in women (3.25 (IQR 2.56-4.5) vs. 2.68 (IQR 2.08-3.59), p = 7.28 ∙ 10-7). Higher LMR was associated with lower peak CK-MB (ß = -0.27 (95% CI: -0.50, -0.03), p = 0.026), lower peak troponin T (ß = -0.45 (95% CI: -0.77, -0.13), p = 0.006) and lower one-year mortality risk (HR 0.35 (95% CI: 0.13, 0.96), p = 0.042). CONCLUSION: At admission for STEMI, women present with higher lymphocyte count and LMR. Higher LMR is associated with smaller infarct size and decreased one-year mortality risk and could be used as a biomarker to predict outcome.

Leukocyte profiles across the cardiovascular disease continuum: A population-based cohort study.

INTRODUCTION: Inflammation plays a pivotal role across all stadia of the cardiovascular disease (CVD) continuum, i.e. non-obstructive coronary artery disease (CAD), myocardial infarction (MI), and ischemic heart failure (iHF). However, inflammation across CVD continuum has not been studied yet within one population. Therefore, we mapped leukocyte profiles across the continuum within the UK Biobank. METHODS: The UK Biobank cohort study includes >500,000 participants aged 40 to 70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. A total of 333,218 individuals with available laboratory measurements at baseline were included in this study. These consisted of controls and individuals who had progression of CVD during follow-up (i.e. who developed CAD, MI, or iHF during follow-up). We investigated whether leukocytes and subtypes of leukocytes at baseline differed among the CVD continuum. Furthermore, we studied the possible interactions between sex and CVD on leukocytes. RESULTS: Of 333,218 individuals, 325,054 (97.5%) individuals were categorized as controls, and 8164 (2.5%) individuals had progression of CVD during follow-up. Of those 8164 individuals, 4552 (1.4%) developed CAD during follow-up, 2839 (0.9%) MI, and 773 (0.2%) in iHF. Compared to controls, mean leukocyte levels at baseline increased across the CVD continuum from 6.8·109 cells/L (SD 1.7·109 cells/L) to 7.7·109 cells/L (SD 1.9·109 cells/L) (Ptrend = 2.19·10-132) in individuals who developed iHF. This increase mainly depended on an increase in neutrophils. Furthermore, controls with leukocyte levels in the highest quartile at baseline had a 1.44 higher chance of being diagnosed with CAD during follow-up compared with individuals with leukocyte levels in lower quartiles (OR 1.44, 95% CI 1.34-1.56 P = 9.63·10-21). A similar increased change was observed for neutrophils, lymphocytes, monocytes, and eosinophils. There was a significant interaction between sex and CVD continuum on lymphocytes (P = 8.49·10-5). CONCLUSION: Overall leukocyte count increased across the CVD continuum, which mainly depended on the increase in neutrophil count. High leukocytes in individuals not having CAD at baseline were predictive for the development of CAD during follow-up. Women had a greater increase of lymphocytes across the CVD continuum compared to men. Understanding which cells are key players in which stadium, could serve as a starting point for the identification of new potential therapeutic targets in CVD.