ABSTRACT
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
ABSTRACT
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. CV and anthropometric risk profile OR of COVID-19 severity for a 7-SNP GRS
ABSTRACT
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. (Figure Presented).
ABSTRACT
PURPOSE: To analyze the associations between cholecalciferol or calcifediol supplementation, serum 25-hydroxyvitamin D (25OHD) levels and COVID-19 outcomes in a large population. METHODS: All individuals ≥ 18 years old living in Barcelona-Central Catalonia (n = 4.6 million) supplemented with cholecalciferol or calcifediol from April 2019 to February 2020 were compared with propensity score-matched untreated controls. Outcome variables were SARS-CoV2 infection, severe COVID-19 and COVID-19 mortality occuring during the first wave of the pandemic. Demographical data, comorbidities, serum 25OHD levels and concomitant pharmacological treatments were collected as covariates. Associations between cholecalciferol or calcifediol use and outcome variables were analyzed using multivariate Cox proportional regression. RESULTS: Cholecalciferol supplementation (n = 108,343) was associated with slight protection from SARS-CoV2 infection (n = 4352 [4.0%] vs 9142/216,686 [4.2%] in controls; HR 0.95 [CI 95% 0.91-0.98], p = 0.004). Patients on cholecalciferol treatment achieving 25OHD levels ≥ 30 ng/ml had lower risk of SARS-CoV2 infection, lower risk of severe COVID-19 and lower COVID-19 mortality than unsupplemented 25OHD-deficient patients (56/9474 [0.6%] vs 96/7616 [1.3%]; HR 0.66 [CI 95% 0.46-0.93], p = 0.018). Calcifediol use (n = 134,703) was not associated with reduced risk of SARS-CoV2 infection or mortality in the whole cohort. However, patients on calcifediol treatment achieving serum 25OHD levels ≥ 30 ng/ml also had lower risk of SARS-CoV2 infection, lower risk of severe COVID-19, and lower COVID-19 mortality compared to 25OHD-deficient patients not receiving vitamin D supplements (88/16276 [0.5%] vs 96/7616 [1.3%]; HR 0.56 [CI 95% 0.42-0.76], p < 0.001). CONCLUSIONS: In this large, population-based study, we observed that patients supplemented with cholecalciferol or calcifediol achieving serum 25OHD levels ≥ 30 ng/ml were associated with better COVID-19 outcomes.