Dataset Information

A network meta-analysis of association between cardiometabolic risk factors and COVID-19 outcome severity.

ABSTRACT:

Background

Cardiometabolic comorbidities have been associated with a higher risk of COVID-19 severity and mortality, but more investigations are needed to determine which comorbidity is more detrimental.

Methods

Embase, Emcare, and MEDLINE were searched systematically for prospective and retrospective studies assessing the associations of cardiometabolic risk factors and COVID-19 outcomes of hospitalization, severity, and mortality among COVID-19-diagnosed patients. Literature search was performed from first publication to May 19, 2021. Study quality was assessed by the Newcastle-Ottawa Scale.

Results

From the literature search, 301 studies suggested that all included cardiometabolic risk factors were associated with a higher risk of COVID-19 hospitalization, severity, and mortality, except that overweight was associated with a decreased risk of mortality (relative risk [RR] 0.88; 95% CI, 0.80-0.98). Patients with diabetes (RR 1.46; 95% CI, 1.45-1.47) were most likely to be hospitalized; patients with heart failure had the highest risk for severe COVID-19 outcomes (RR 1.89; 95% CI, 1.71-2.09); while patients with stroke were most susceptible to overall mortality (RR 1.99; 95% CI, 1.90-2.08). In the network meta-analysis, cerebrovascular disease had the highest impact (RR 1.69; 95% CI, 1.65-1.73) on COVID-19 outcomes compared to other cardiometabolic risk factors. For different combinations of risk factors, cardiovascular disease and diabetes combined (RR 6.98; 95% CI, 5.28-9.22) was more detrimental than others.

Conclusions

Considering the high prevalence of cardiometabolic comorbidities and risk of all severe outcomes, patients with cardiometabolic comorbidities should be prioritized in vaccination and treatment development of COVID-19.

SUBMITTER: Li AB

PROVIDER: S-EPMC10667650 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Publications

A network meta-analysis of association between cardiometabolic risk factors and COVID-19 outcome severity.

Li Alina Binbin AB Yang Bo B Li Yufei Y Huynh Rachel R Shim Samuel S Lo Kenneth K Li Jie J Zullo Andrew A Wu Wen-Chih WC Liu Simin S

Journal of diabetes 20230830 11

<h4>Background</h4>Cardiometabolic comorbidities have been associated with a higher risk of COVID-19 severity and mortality, but more investigations are needed to determine which comorbidity is more detrimental.<h4>Methods</h4>Embase, Emcare, and MEDLINE were searched systematically for prospective and retrospective studies assessing the associations of cardiometabolic risk factors and COVID-19 outcomes of hospitalization, severity, and mortality among COVID-19-diagnosed patients. Literature sea ...[more]

PMID: 37649300

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Project description:AimsCoronavirus disease 2019 (COVID-19) can lead to multiorgan damage. MicroRNAs (miRNAs) in blood reflect cell activation and tissue injury. We aimed to determine the association of circulating miRNAs with COVID-19 severity and 28 day intensive care unit (ICU) mortality.Methods and resultsWe performed RNA-Seq in plasma of healthy controls (n = 11), non-severe (n = 18), and severe (n = 18) COVID-19 patients and selected 14 miRNAs according to cell- and tissue origin for measurement by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in a separate cohort of mild (n = 6), moderate (n = 39), and severe (n = 16) patients. Candidates were then measured by RT-qPCR in longitudinal samples of ICU COVID-19 patients (n = 240 samples from n = 65 patients). A total of 60 miRNAs, including platelet-, endothelial-, hepatocyte-, and cardiomyocyte-derived miRNAs, were differentially expressed depending on severity, with increased miR-133a and reduced miR-122 also being associated with 28 day mortality. We leveraged mass spectrometry-based proteomics data for corresponding protein trajectories. Myocyte-derived (myomiR) miR-133a was inversely associated with neutrophil counts and positively with proteins related to neutrophil degranulation, such as myeloperoxidase. In contrast, levels of hepatocyte-derived miR-122 correlated to liver parameters and to liver-derived positive (inverse association) and negative acute phase proteins (positive association). Finally, we compared miRNAs to established markers of COVID-19 severity and outcome, i.e. SARS-CoV-2 RNAemia, age, BMI, D-dimer, and troponin. Whilst RNAemia, age and troponin were better predictors of mortality, miR-133a and miR-122 showed superior classification performance for severity. In binary and triplet combinations, miRNAs improved classification performance of established markers for severity and mortality.ConclusionCirculating miRNAs of different tissue origin, including several known cardiometabolic biomarkers, rise with COVID-19 severity. MyomiR miR-133a and liver-derived miR-122 also relate to 28 day mortality. MiR-133a reflects inflammation-induced myocyte damage, whilst miR-122 reflects the hepatic acute phase response.

Project description:BackgroundEpidemiological 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 findingsWe 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.ConclusionsIn 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.

Dataset Information

A network meta-analysis of association between cardiometabolic risk factors and COVID-19 outcome severity.

Background

Methods

Results

Conclusions

Publications

A network meta-analysis of association between cardiometabolic risk factors and COVID-19 outcome severity.

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