Classic and genetic cardiovascular risk burden and case-fatality from SARS-CoV-2 virus infection. The CARGENCORS study

Background

The disease presentation of the severe acute respiratory syndrome coronavirus 2 infection (COVID-19) ranges from asymptomatic to fatal. COVID-19 patients with pre-existing coronary artery disease (CAD) risk factors or overt cardiovascular disease more often develop severe COVID-19, which are also related to thrombotic, inflammatory, and to viral infectivity response. We hypothesised that despite some genetic predisposition, especially in COVID-19 severity, the main determinants of fatal complications in COVID-19 patients are related to comorbidity.

Purpose

To determine the role of genetics and cardiovascular comorbidity in mortality from COVID-19.

Methods

We conducted a retrospective cohort study including 3,120 patients with positive COVID-19 test from several hospitals and primary care between February 2020 and June 2021. Among them 1,096 required hospitalization, and 121 died within 3 months after symptom onset. Standard parametric and non-parametric methods, as required, were used to compare patient characteristics by vital status. Individual genotypes for 32 CAD, 14 thrombosis, 19 inflammation, and 11 viral infectivity single nucleotide variants (SNV), as well as, 2 COVID-19 SNVs already published were tested for association with mortality with Cochran-Armitage statistics and p-values corrected for multiple comparisons. The mutually-adjusted odds ratio (OR) and 95% confidence interval (95% CI) of fatal COVID-19 was analysed for SNVs significantly associated to case-fatality, with their adverse alleles count (0, 1 or 2), and for comorbidity factors with logistic regression adjusted for age and sex. The discrimination of the models was also estimated by the area under the curve (AUC).

Results

Fatal and non-fatal cases' characteristics are compared in Table 1. Fatal cases had a more adverse cardiovascular and anthropometric risk profile. After correcting for multiple testing by Benjamini-Hochberg method, we observed the inflammation-related rs6993770 SNV to be significantly associated with COVID-19 fatality (p-value = 0.04). The CAD-related rs9982601 and rs2505083 SNVs, and the thrombosis-related rs7853989 SNV were moderately associated with COVID-19 fatality (p-value ≤0.1). On Figure 1 we show the adjusted OR for rs6993770 (OR: 1.02; 95% CI 1.01–1.03 per risk allele) and that for clinical factors related to COVID-19 case-fatality. The AUC of the model was 0.85 (95% CI 0.81–0.88), which not improved that of a model with clinical risk factors alone (AUC: 0.84; 95% CI 0.81–0.87).

Conclusion

The rs6993770 inflammation (interleukin measurement trait)-related SNV was independently associated to case fatality; however the outcome was mainly driven by age, male sex, diabetes, and glomerular filtration rate.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): Carlos III Health Institute and the European Regional Development FundAgency for Management of University and Research GrantsCrue-CSIC-Santander FONDO SUPERA COVID-19

Coronary computed tomography angiography improves coronary risk prediction in general population

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Carlos III Health Institute and the European Regional Development FundAgency for Management of University and Research Grants

Introduction

In the next decades, it is expected an increasing incidence of acute coronary syndrome in the Spanish population. Identify high-risk patients could be the most cost-effective way to reduce its incidence and morbi-mortality burden. We studied the effect of adding coronary artery calcification (CAC) and the extent of atherosclerotic disease (SIS score) to classical cardiovascular (CV) risk factors in coronary risk prediction.

Methods

This was a prospective cohort study of 325 asymptomatic patients recruited between 2013-2017. Demographic characteristics and CV risk factors were obtained and all participants underwent a coronary computed tomography angiography exam in which CAC and SIS were determined. The cohort was followed-up (median= 4 years) for a composite endpoint that included CV death, myocardial infarction, coronary angiography and/or revascularization. Improvement in discrimination and in reclassification by the inclusion of CAC/SIS in the Framingham-REGICOR function were examined with the Sommer's D index and with the Net reclassification index (NRI) (categorical and continuous), respectively.

Results

Nine of the 251 individuals included in the study had an event in the follow-up. Of the included participants, 94 had a CAC = 0 and 85 a SIS = 0. These participants had no events. The addition of SIS or of SIS and CAC scores to the Framigham-REGICOR risk function increased significantly the discrimination capacity from 0.71 to 0.88 (Table 1). Reclassification measured by the continuous NRI also improved significantly from 69.5 to 112.4/115.5 when SIS or both scores were included (Table 2).

Conclusions

CAC and SIS scores were associated to 4-year CV event incidence, independently of coronary risk estimation. Discrimination and reclassification of the Framigham-REGICOR coronary function were significantly improved by both indexes, but SIS overrode the effect of CAC.

Cholesterol and hypertension treatment but not time-dependent covariates or competing risks improve coronary risk prediction: the REGICOR study

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Carlos III Health Institute Agency for Management of University and Research Grants

Background

Cardiovascular (CV) risk functions are the recommended tool to identify high-risk individuals. However, discrimination of CV risk functions is not optimal. While the effect of biomarkers in CV risk prediction has been extensively studied, there is no data of CV risk functions including time-dependent covariates, competing risks and treatments.

Aim

To examine the effect of including time-dependent covariates, competing risks and treatments in CV risk prediction.

Methods

Participants from the REGICOR population cohorts (North-Eastern Spain) aged 35-74 years without previous history of cardiovascular disease were included (n=8,470). Coronary and stroke events, and mortality due to other CV causes or to cancer were recorded during the follow-up (median=12.6 years). A multi-state Markov model was constructed to include competing risks and time-dependent classical risk factors and treatments (2 measurements). This model was compared to Cox models with the basal measurement of classical risk factors, treatments or competing risks. Models were cross-validated and compared by their discrimination (area under the ROC curve), calibration (Hosmer-Lemeshow test) and reclassification (categorical net reclassification index).

Results

Cancer mortality was the event with the highest cumulative incidence. In coronary event prediction, cholesterol and hypertension treatment addition to classical risk factors, improved significantly discrimination by 2% and reclassification by 7-9%. In stroke event prediction, inclusion of time-dependent covariates decreased significantly discrimination by 3-5%.

Conclusion

Coronary risk prediction improves when cholesterol and hypertension treatment are included in risk functions. Coronary/stroke prediction does not improve with 2 measurements of covariates or with competing risks.

Relationship of 5-year changes in inflammatory, metabolic and oxidative biomarkers with cardiovascular diseases incidence at 10-years

Funding Acknowledgements

Type of funding sources: Public Institution(s). Main funding source(s): Carlos III Health Institute and the European Regional Development Fund Government of Catalonia through the Agency for Management of University and Research Grants

Background

Early stratification of cardiovascular (CV) risk saves thousands of lives every year. There is a debate about the value of determining genetic or plasma biochemical biomarkers, related to atherosclerosis process, to improve the prediction of an incident CV disease. While, single measurements of some of these biomarkers have been associated with an increased risk of CV disease, the change of the levels of these biomarkers over time could also improve the prediction of CV events and drive the identification of new biological pathways and therapeutic targets.

Purpose

This study aimed to examine the relationship between 5-year change in the levels of biomarkers of inflammation (TNF-α, IL-10, IL-6, MCP-1, and CRP), glucidic metabolism (adiponectin, leptin, and insulin) and oxidation (GHS-Px), and the incidence of CV events at 10 years in a population without previous CV disease.

Methods

This was a cohort study nested in a large population cohort. Participants were randomly selected from the REGICOR cohort (North-Eastern Spain) recruited in 2005 (6.352 participants). Biomarkers were measured at baseline and in a re-examination in 2010. Participants were followed until 2020 for a composite CV disease endpoint including fatal and non-fatal first occurrence of coronary artery disease, stroke and peripheral artery disease. Baseline characteristics were compared between participants with and without CV events with standard parametric and non-parametric methods, as required. We used Cox regression to analyse the effect of the 5-year change of the biomarker levels on the occurrence of the composite endpoint adjusted for age, sex, baseline levels of each biomarker and classical CV risk factors.

Results

We included 419 individuals aged 35 to 74 years. Overall, 6.2% developed an incident CV disease within the 10-year follow-up. Characteristics of participants, who had or not a CV event, are compared in Table 1. Cases had a more adverse CV and anthropometric risk profile. Compared to individuals with sustained IL-6 and insulin levels, those with increased IL-6 or insulin after five years were at higher independent risk of CV disease at ten years. After adjusting for potential confounders, an increased IL-6 and insulin at the 5-year follow-up were independently associated with CV disease at 10-years (Table 2). Each rise of IL-6 or insulin in 1pg/mL or 10pg/mL, respectively, increased 32% (IL-6) and 2% (insulin) the risk of developing a CV event at 10-years.

Conclusions

Increasing IL-6 and insulin levels over five years indicates a higher risk of CV disease ten years thereafter, independently of classical risk factors.

Genetic risk score for risk stratification of patients positive for SARS-CoV-2 virus. The CARGENCORS study

Funding Acknowledgements

Type of funding sources: Other. Main funding source(s): Carlos III Health Institute and the European Regional Development Fund Government of Catalonia through the Agency for Management of University and Research Grants Crue-CSIC-Santander FONDO SUPERA COVID-19

Background

The disease presentation of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ranges from asymptomatic to fatal. COVID-19 patients with pre-existing coronary artery disease (CAD) risk factors or overt cardiovascular disease are at particular risk of severe disease. We hypothesised that a specific genetic risk score (GRS) based on single nucleotide polymorphisms (SNPs) allele count to score COVID-19 severity might include SNPs counts related to CAD incidence and to thrombosis, inflammation, and viral infectivity determinants involved in the severity of SARS-CoV-2. Such GRS could improve the early risk stratification of COVID-19 patients and optimize treatment strategies.

Purpose

To evaluate the capacity of a genetic risk score (GRS) with candidate genes to predict COVID-19 severity.

Methods

We conducted an age- and sex-matched case-control study with 1:2 ratio recruitment involving 2454 patients from Catalan hospitals and primary care. Cases were hospitalized severe (requiring at least oxygen treatment) or fatal COVID-19 patients; and controls were moderate-symptom and asymptomatic patients treated at home. Standard parametric and non-parametric methods, as required, were used to compare patient characteristics by severity. Individual genotypes for 33 CAD, 14 thrombosis, 22 inflammation, 15 viral infectivity SNPs and 2 COVID-19 SNPs already published were tested for association with severity with Cochran-Armitage statistics and p-values corrected for multiple comparisons. GRS was computed as the unweighted count of adverse alleles (0, 1 or 2). The odds ratio of severe COVID-19 was analysed for GRS (and its component SNPs) with logistic regression models adjusted for potential confounding factors. Area under the curve (AUC) improvement and net reclassification index (NRI) for GRS was estimated from a basic model including CAD and COVID-19 severity risk factors. Models’ performance was measured with the Akaike information criterion.

Results

SNPs identifications are not shown to prevent patent conflict. Cases and control characteristics are compared in Table 1. Cases had a more adverse cardiovascular and anthropometric risk profile. After correcting for multiple testing by Benjamini-Hochberg criteria, we observed 13 SNPs to be significantly associated with severity. After excluding the close SNPs in linkage disequilibrium, 7 were retained in the GRS model, which yielded the discrimination and reclassification characteristics described in Table 2.

Conclusion

A GRS with 7 SNPs related to CAD, thrombosis and inflammation significantly improves the severe COVID-19 risk assessment done with age, sex, comorbidity, and anthropometry alone.

Validity and trends of myocardial infarction incidence and case-fatality estimated from linked administrative databases

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): CIBERCV of cardiovascular diseases; CIBERESP.

OnBehalf

REGICOR investigators

Background

Although myocardial infarction (MI) severity trends are systematically measured with mortality rates, MI incidence trends and the precision of its estimation by linkage of anonymized electronic databases are relatively untested. We validated a linked-data method (LDM) to estimate a population MI incidence and case-fatality, and to analyse the 1990-2016 trends in North-Eastern Spain. 

Methods

LDM consisted of linking MI hospital discharges (n = 4,533,981) and mortality registry data (n = 40,676) for 2008-2016, selecting key MI diagnostic codes. The prospective REGICOR study, including all MI cases in Girona, 1990-2009, was used as the gold standard for validation purposes. Standardized MI cumulated incidence and 28-day case fatality for population aged 35-74 years was calculated, 1990-2016 trends were analysed by linear and joinpoint regression and annual percentage change (APC).

Results

LDM and REGICOR MI incidence and case-fatality estimates were similar for 2008-09 (Table). LDM MI incidence and case-fatality significantly decreased: APC 1990-2016 [95% CI]) was -1.8 [-2.6;-0.9] in women, and APC 2002-2016  -2.8 [-3.8;-1.8] in men; case-fatality APC 1990-2016 was -4.7% [-5.7;-3.8] in women and APC 1995-2005 -6.5%[-8.5;-4.5] in men. 

Conclusions

LDM in population aged 35-74 reliably estimated MI incidence and case-fatality. MI incidence and case-fatality significantly decreased after 1990.

Comparative analysis of REGICOR vs LDM REGICOR 2008-2009 LDM 2008-2009 Estimate 95% CI Estimate 95% CI P-Value Cumulated incidence Men 245.4 228.3; 262.5 239.7 222.5; 256.3 0.626 Women 61.1 52.6; 69.6 58.2 49.9; 66.4 0.626 Overall 28-day case-fatality Men 23.5% 19.7; 27.2 21.3% 17.8; 24.9 0.422 Women 19.3% 6.7; 31.9 17.7% 6.3; 29.1 0.855 In-hospital case-fatality Men 6.9% 4.8; 9.0 5.7% 3.8; 7.6 0.394 Women 5.0% 1.9; 8.2 3.7% 1.0; 6.5 0.540 Pre-hospital case-fatality Men 16.5% 11.8; 21.3 15.6% 11.2; 20.1 0.791 Women 14.2 % 6.6; 21.9 14.0% 6.3; 21.7 0.961 CI Confidence Interval

Standardized comparison of cardiovascular risk factors prevalence in Spanish women and men living with HIV and in the general population

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Spain’s Ministry of Science and Innovation (Madrid, Spain), co-financed with European Union European Regional Development Funds –ERDF- [CIBERCV CB16/11/00229]; the Health Department of the Generalitat de Catalunya (Barcelona, Spain) through the Agència de Gestió d’Ajuts Universitaris de Recerca de Catalunya (AGAUR) (Barcelona, Spain) [2017SGR222].

OnBehalf

DARIOS and VACH investigators

Background

People living with HIV (PLWH) have an increased risk of cardiovascular (CV) disease, likely due to a higher prevalence of CV risk factors. We compared age-standardized prevalence and management of CV risk factors in PLWH to that of general population in Spain.

Methods

Blood pressure, lipid, glucose and anthropometric profile were cross-sectionally compared along with treatment of hypertension, dyslipidemia, and diabetes in a general population cohort and a PLWH cohort. Prevalence rates were standardized by the direct method by 10-year age groups in European standard populations by gender. 

Results

We included 39,598 individuals aged 35 to 74 years: 28,360 from the general population cohort and 11,238 from the PLWH cohort. Compared to general population, PLWH had a higher concentration of triglycerides (>35mg/dL in women and >26mg/dL in men), and a higher prevalence of metabolic syndrome (>10% and >7.8%) and diabetes (>8.5% and >5.3%) (Table). The proportion of treated diabetes, dyslipidemia, and hypertension were up to 3-fold lower in both women and men living with HIV than in general population (Table).

Conclusions

Lipid, gluco-metabolic profiles were significantly worse in PLWH compared to general population. In addition, PLWH were less often treated for diagnosed diabetes, dyslipidemia, and hypertension.

CV risk factor standardized prevalence Cardiovascular risk factor WOMEN MEN General population People living with HIV p-Value General population People living with HIV p-Value N = 15,159 N = 2,171 N = 13,201 N = 9,067 Hypertension, % 27.4 (26.7 - 28.0) 24.8 (21.6 - 28.1) 0.136 29.0 (28.2 - 29.7) 22.9 (21.4 - 24.4) <0.001 Treated hypertension, % a 62.7 (60.7 - 64.7) 18.9 (13.5 - 24.4) <0.001 59.3 (57.5 - 61.1) 24.1 (21.0 - 27.1) <0.001 Triglycerides, mg/dL b 99 (99 - 100) 134 (134 - 148) <0.001 122 (121 - 122) 148 (148 - 164) <0.001 Total cholesterol, mg/dL 214 (213 - 215) 207 (199 - 215) 0.111 214 (213 - 216) 195 (191 - 198) <0.001 Treated dyslipidaemia, % c 14.0 (13.5 - 14.6) 7.80 (5.60 - 10.0) <0.001 15.1 (14.5 - 15.7) 7.8 (6.8 - 8.7) <0.001 Glucose, mg/dL 97 (96 - 97) 103 (98 - 107) 0.007 104 (103 - 105) 106 (104 - 109) 0.122 Diabetes, % 10.6 (10.1 - 11.1) 19.1 (16.0 - 22.1) <0.001 15.4 (14.8 - 16.0) 20.7 (19.2 - 22.2) <0.001 Treated diabetes, % d 34.4 (31.5 - 37.2) 12.8 (8.00 - 17.5) <0.001 40.0 (37.1 - 42.9) 16.6 (13.9 - 19.3) <0.001 Metabolic Syndrome, % 20.5 (19.8 - 21.1) 31.1 (25.8 - 36.4) <0.001 27.9 (27.1 - 28.7) 35.7 (33.1 - 38.2) <0.001 Values are expressed as mean (95% confidence interval). a Among patients with history of hypertension. b Mean (95% confidence interval) were obtained with log-transformed values. c Among all cohort participants. d Among patients with history of diabetes. HDL-c, high density lipoprotein cholesterol; LDL-c, low density lipoprotein cholesterol