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 (β = -0.27 (95% CI: -0.50, -0.03), p = 0.026), lower peak troponin T (β = -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

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

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.& nbsp;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.& nbsp;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/m(2), respectively (p > 0.005 for all). Increased HDL-cholesterol was associated with decreased iEAT volume (8 =-14.8, CI =-24.6 to-4.97, p = 0.003) and suggestive associations (P-value = 0.005) were observed between iEAT and triglycerides (beta = 3.26, CI = 0.42 to 6.09, p = 0.02), Apo-lipoprotein A (beta =-16.3, CI =-30.3 to-2.24, p = 0.02) and LDL-cholesterol (beta = 3.99, CI =-7.15 to-0.84, p = 0.01).& nbsp;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

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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

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

Single-cell dissection of the immune response after acute myocardial infarction

Background: The role of the immune system in the context of acute myocardial infarction (MI), and its response to such event are poorly characterized, but is thought to be an important driver of myocardial remodeling, thromboinflammation, and exacerbation of atherosclerosis - triggering recurrent cardiovascular events. So far, anti-inflammatory approaches drugs have shown promising effects on the prevention of recurrent cardiovascular events or myocardial salvage after myocardial infarction. However, they broadly impair the immune system and some are associated with increased infectious side effects. Therefore, a more detailed understanding of the immune response to myocardial infarction is needed to tailor anti-inflammatory therapeutic approaches in MI patients. Methods: To gain such detailed longitudinal understanding of the immune response in ST-elevated myocardial infarction (STEMI) patients, we compared peripheral blood mononuclear cell (PBMCs) single-cell RNA-sequencing (scRNA-seq) expression and plasma protein profiles over time and in comparison to age- and sex-balanced controls in 38 STEMI patients at hospital admission, 24 hours (acute phase) and 6-8 weeks (chronic phase) after STEMI. Results: In total, 95,995 diseased and 33,878 control PBMCs were analyzed. Compared to controls, we observed a relative increase in the number of classical monocytes and a decrease in the number of CD56dim natural killer cells in STEMI patients at admission, and these differences persisted until 24 hours after STEMI. The monocytes also showed the largest gene expression changes in STEMI patients compared to controls, and in STEMI patients over time. These were associated with changes in the activity of toll-like receptors, IFN and IL-1 signaling. Subsequent differential cell-cell communication analysis suggested that these monocytes are mainly involved in the outgoing differential communication in the first 24h after a STEMI, whereas in the next 6-8 weeks they become mostly involved in the incoming differential communication. Finally, a targeted protein cardiovascular biomarker panel revealed 33 out of 92 plasma proteins to be changed during the acute and/or chronic phase after STEMI. Interestingly, the plasma levels of three of these proteins were found to be affected by genetic variation, disease status and time after STEMI. Indicating the importance of taking all these aspects into consideration when defining potential future therapies. Conclusions: Altogether, our analyses have revealed the immunological pathways that are disturbed upon MI, and in which cell type and during which stage of the disease. Additionally, we also provide insights in which patients are 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 after MI and provide further guidance for future therapeutic studies

Additional file 12 of Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data

Additional file 12: Table S17. Enrichment of co-eGenes for GWAS result