Racial and ethnic differences in pharmacotherapy to prevent coronary artery disease and thrombotic events.

Awareness of racial/ethnic disparities represents a key challenge for healthcare systems that attempt to provide effective healthcare and to reduce existing inequalities in the use of and adherence to guideline-recommended cardiovascular drugs to improve clinical outcomes for cardiovascular disease (CVD). In this review, we describe important racial/ethnic differences between and within ethnic groups in the prevalence, risk factors, haemostatic factors, anti-inflammatory and endothelial markers, recurrence, and outcomes of CVD. We discuss important differences in the selection, doses, and response [efficacy and adverse drug reactions (ADRs)] in ethnically diverse patients treated with antithrombotics or lipid-lowering drugs. Differences in drug response are mainly related to racial/ethnic differences in the frequency of polymorphisms in genes encoding drug-metabolizing enzymes (DMEs) and drug transporters. These polymorphisms markedly influence the pharmacokinetics, dose requirements, and safety of warfarin, clopidogrel, and statins. This review aims to support a better understanding of the genetic differences between and among populations to identify patients who may experience an ADR or a lack of drug response, thus optimizing therapy and improving outcomes. The greater the understanding of the differences in the genetic variants of DMEs and transporters that determine the differences in the exposure, efficacy, and safety of cardiovascular drugs between races/ethnicities, the greater the probability that personalized medicine will become a reality.

Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease.

DNA methylation commonly occurs at cytosine-phosphate-guanine sites (CpGs) that can serve as biomarkers for many diseases. We analyzed whole genome sequencing data to identify DNA methylation quantitative trait loci (mQTLs) in 4126 Framingham Heart Study participants. Our mQTL mapping identified 94,362,817 cis-mQTLvariant-CpG pairs (for 210,156 unique autosomal CpGs) at P < 1e-7 and 33,572,145 trans-mQTL variant-CpG pairs (for 213,606 unique autosomal CpGs) at P < 1e-14. Using cis-mQTL variants for 1258 CpGs associated with seven cardiovascular disease (CVD) risk factors, we found 104 unique CpGs that colocalized with at least one CVD trait. For example, cg11554650 (PPP1R18) colocalized with type 2 diabetes, and was driven by a single nucleotide polymorphism (rs2516396). We performed Mendelian randomization (MR) analysis and demonstrated 58 putatively causal relations of CVD risk factor-associated CpGs to one or more risk factors (e.g., cg05337441 [APOB] with LDL; MR P = 1.2e-99, and 17 causal associations with coronary artery disease (e.g. cg08129017 [SREBF1] with coronary artery disease; MR P = 5e-13). We also showed that three CpGs, e.g., cg14893161 (PM20D1), are putatively causally associated with COVID-19 severity. To assist in future analyses of the role of DNA methylation in disease pathogenesis, we have posted a comprehensive summary data set in the National Heart, Lung, and Blood Institute's BioData Catalyst.

Potential Genes Associated with COVID-19 and Comorbidity.

Hypertension, diabetes mellitus, and coronary artery disease are common comorbidities and dangerous factors for infection and serious COVID-19. Polymorphisms in genes associated with comorbidities may help observe susceptibility and disease severity variation. However, specific genetic factors and the extent to which they can explain variation in susceptibility of severity are unclear. Therefore, we evaluated candidate genes associated with COVID-19 and hypertension, diabetes mellitus, and coronary artery disease. In particular, we performed searches against OMIM, NCBI, and other databases, protein-protein interaction network construction, and GO and KEGG pathway enrichment analyses. Results showed that the associated overlapping genes were TLR4, NLRP3, MBL2, IL6, IL1RN, IL1B, CX3CR1, CCR5, AGT, ACE, and F2. GO and KEGG analyses yielded 302 GO terms (q < 0.05) and 29 signaling pathways (q < 0.05), respectively, mainly including coronavirus disease-COVID-19 and cytokine-cytokine receptor interaction. IL6 and AGT were central in the PPI, with 8 and 5 connections, respectively. In this study, we identified 11 genes associated with both COVID-19 and three comorbidities that may contribute to infection and disease severity. The key genes IL6 and AGT are involved in regulating immune response, cytokine activity, and viral infection. Therefore, RAAS inhibitors, AGT antisense nucleotides, cytokine inhibitors, vitamin D, fenofibrate, and vaccines regulating non-immune and immune factors could be potential strategies to prevent and cure COVID-19. The study provides a basis for further investigation of genes and pathways with predictive value for the risk of infection and prognosis and could help guide drug and vaccine development to improve treatment efficacy and the development of personalised treatments, especially for COVID-19 individuals with common comorbidities.

Relationship between adenosine A2a receptor polymorphism rs5751876 and fractional flow reserve during percutaneous coronary intervention.

Fractional flow reserve (FFR) assessed during adenosine-induced maximal hyperemia has emerged as a useful tool for the guidance of percutaneous coronary interventions (PCI). However, interindividual variability in the response to adenosine has been claimed as a major limitation to the use of adenosine for the measurement of FFR, carrying the risk of underestimating the severity of coronary stenoses, with potential negative prognostic consequences. Genetic variants of the adenosine receptor A2a (ADORA2A gene), located in the coronary circulation, have been involved in the modulation of the hyperemic response to adenosine. However, no study has so far evaluated the impact of the single nucleotide polymorphism rs5751876 of ADORA2A on the measurement of FFR in patients undergoing percutaneous coronary intervention that was, therefore, the aim of our study. We included patients undergoing coronary angiography and FFR assessment for intermediate (40-70%) coronary lesions. FFR measurement was performed by pressure-recording guidewire (Prime Wire, Volcano), after induction of hyperemia with intracoronary boli of adenosine (from 60 to 1440 µg, with dose doubling at each step). Restriction fragment length polymorphism (RFLP) analysis was performed to assess the presence of rs5751876 C>T polymorphism of ADORA2a receptor. We included 204 patients undergoing FFR measurement of 231 coronary lesions. A total of 134 patients carried the polymorphism (T allele), of whom 41 (30.6%) in homozygosis (T/T).Main clinical and angiographic features did not differ according to ADORA2A genotype. The rs5751876 C>T polymorphism did not affect mean FFR values (p = 0.91), the percentage of positive FFR (p = 0.54) and the duration of maximal hyperemia. However, the time to recovery to baseline FFR values was more prolonged among the T-allele carriers as compared to wild-type patients (p = 0.04). Based on these results, in patients with intermediate coronary stenoses undergoing FFR assessment with adenosine, the polymorphism rs5751876 of ADORA2A does not affect the peak hyperemic response to adenosine and the results of FFR. However, a more prolonged effect of adenosine was observed in T-carriers.

Assessing the genetic relationship between gastro-esophageal reflux disease and risk of COVID-19 infection.

Symptoms related with gastro-esophageal reflux disease (GERD) were previously shown to be linked with increased risk for the 2019 coronavirus disease (COVID-19). We aim to interrogate the possibility of a shared genetic basis between GERD and COVID-19 outcomes. Using published GWAS data for GERD (78 707 cases; 288 734 controls) and COVID-19 susceptibility (up to 32 494 cases; 1.5 million controls), we examined the genetic relationship between GERD and three COVID-19 outcomes: risk of developing severe COVID-19, COVID-19 hospitalization and overall COVID-19 risk. We estimated the genetic correlation between GERD and COVID-19 outcomes followed by Mendelian randomization (MR) analyses to assess genetic causality. Conditional analyses were conducted to examine whether known COVID-19 risk factors (obesity, smoking, type-II diabetes, coronary artery disease) can explain the relationship between GERD and COVID-19. We found small to moderate genetic correlations between GERD and COVID-19 outcomes (rg between 0.06 and 0.24). MR analyses revealed a OR of 1.15 (95% CI: 0.96-1.39) for severe COVID-19; 1.16 (1.01-1.34) for risk of COVID-19 hospitalization; 1.05 (0.97-1.13) for overall risk of COVID-19 per doubling of odds in developing GERD. The genetic correlation/associations between GERD and COVID-19 showed mild attenuation towards the null when obesity and smoking was adjusted for. Susceptibility for GERD and risk of COVID-19 hospitalization were genetically correlated, with MR findings supporting a potential causal role between the two. The genetic association between GERD and COVID-19 was partially attenuated when obesity is accounted for, consistent with obesity being a major risk factor for both diseases.

COVID-19 Severity Potentially Modulated by Cardiovascular-Disease-Associated Immune Dysregulation.

Patients with underlying cardiovascular conditions are particularly vulnerable to severe COVID-19. In this project, we aimed to characterize similarities in dysregulated immune pathways between COVID-19 patients and patients with cardiomyopathy, venous thromboembolism (VTE), or coronary artery disease (CAD). We hypothesized that these similarly dysregulated pathways may be critical to how cardiovascular diseases (CVDs) exacerbate COVID-19. To evaluate immune dysregulation in different diseases, we used four separate datasets, including RNA-sequencing data from human left ventricular cardiac muscle samples of patients with dilated or ischemic cardiomyopathy and healthy controls; RNA-sequencing data of whole blood samples from patients with single or recurrent event VTE and healthy controls; RNA-sequencing data of human peripheral blood mononuclear cells (PBMCs) from patients with and without obstructive CAD; and RNA-sequencing data of platelets from COVID-19 subjects and healthy controls. We found similar immune dysregulation profiles between patients with CVDs and COVID-19 patients. Interestingly, cardiomyopathy patients display the most similar immune landscape to COVID-19 patients. Additionally, COVID-19 patients experience greater upregulation of cytokine- and inflammasome-related genes than patients with CVDs. In all, patients with CVDs have a significant overlap of cytokine- and inflammasome-related gene expression profiles with that of COVID-19 patients, possibly explaining their greater vulnerability to severe COVID-19.

Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis.

BACKGROUND: Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses. METHODS AND FINDINGS: We selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10-8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10-5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10-5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null. CONCLUSIONS: In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.