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Systemic inflammation may induce cardiac injury in COVID-19 patients including children and adolescents without underlying cardiovascular diseases: A systematic review.

ABSTRACT: Coronavirus disease 2019(COVID-19) is an ongoing global pandemic with a daily increasing number of affected individuals and a relatively high mortality rate. COVID-19 patients that develop cardiac injury are at increased risk of a worse clinical course with higher rates of mortality. Increasing amounts of evidence suggest that a system-wide inflammatory response and a cytokine storm mediated type syndrome plays a crucial role in disease progression. This systematic review investigates the possible role of hyperinflammation in inducing cardiac injury as one of the severe complications of COVID-19. A systematic literature search was performed using PubMed, Embase and Scopus databases to identify relevant clinical studies that investigated cardiovascular injury manifestations and reported inflammatory and cardiac biomarkers in COVID-19 patients. Only 29 studies met our inclusion criteria and the majority of these studies demonstrated significantly elevated inflammatory and cardiac blood markers. It was evident that underlying cardiovascular diseases may increase the risk of developing cardiac injury. However, many COVID-19 patients included in this review, developed different types of cardiac injury without having any underlying cardiovascular diseases. Furthermore, many of these patients were either children or adolescents. Therefore, age and comorbidities may not always be the two main risk factors that dictate the severity and outcome of COVID-19. Further investigations are required to understand the underlying mechanisms of pathogenicity as an urgent requirement to develop the appropriate treatment and prevention strategies. These strategies may specifically target hyperinflammation as a suspected driving factor for some of the severe complications of COVID-19.

SUBMITTER: Saed Aldien A

PROVIDER: S-EPMC8046745 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSeveral studies have investigated the value of the systemic immune-inflammation index (SII) for predicting cardiovascular disease (CVD), but the results were inconsistent. Therefore, a meta-analysis and systematic review were conducted to assess the correlation between SII and risk of CVD.Materials and methodsTwo investigators systematically searched PubMed, Embase, Web of Science, Cochrane library, and CINAHL databases to identify all studies that examined the association between SII levels and CVD. The risk estimates of CVD for people with high SII compared to those with low SII levels and the weighted mean difference (WMD) between the CVD and control groups were pooled using fixed- or random-effects models based on the heterogeneity test. We used the Newcastle-Ottawa Scale to assess the risk of bias in eligible studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was applied to rate the certainty of evidence.ResultsA total of 13 studies with 152,996 participants were included for analysis. The overall pooled results showed that higher SII was significantly associated with an increased risk of CVD (HR = 1.39, 95%CI: 1.20-1.61, P < 0.001). This increased risk could be observed in almost all CVD subtypes, including ischemic stroke (HR = 1.31, 95%CI: 1.06-1.63, P = 0.013), hemorrhagic stroke (HR = 1.22, 95%CI: 1.10-1.37, P < 0.001), myocardial infarction (HR = 1.11, 95%CI: 1.01-1.23, P = 0.027), and peripheral arterial disease (HR = 1.51, 95%CI: 1.18-1.93, P = 0.001). There were no significant but still similar trends in venous thrombosis (HR = 4.65, 95%CI: 0.66-32.71, P = 0.122), cerebral small vessel disease (HR = 1.09, 95%CI: 0.95-1.25, P = 0.233), and acute coronary syndrome (HR = 1.08, 95%CI: 0.96-1.22, P = 0.200). Furthermore, the pooled results showed that SII levels at the onset of CVD were significantly higher than that in the general population (WMD = 355.2, 95%CI: 234.8-475.6, P < 0.001), which was consistent across different CVD subtypes. The GRADE assessment suggested that the quality of current evidence from observational studies was low or very low.ConclusionThis study indicated that SII may be a potential biomarker for CVD development and elevated SII is associated with an increased risk of CVD. However, the quality of evidence is generally low. Additional well-designed studies are necessary to determine the optimal cutoff value and to characterize the benefited population.

Project description:PurposeSystemic inflammation is potentially associated with ocular diseases such as late age-related macular degeneration (AMD). Using the serum concentration of high-sensitive C-reactive protein (hs-CRP) as surrogate of systemic inflammation, we examined potential associations between the serum hs-CRP concentration and the presence and degree of eye diseases.MethodsThe population-based Beijing Eye Study included 3468 Chinese individuals. The study participants underwent a standardized interview and a detailed ophthalmic examination. The serum concentration of hs-CRP was determined.ResultsOut of 3468 participants, 2452 (70.7%) individuals (mean age:63.4±9.4 year; range:50-91 years) had hs-CRP measurements (mean:1.96±4.07mg/L). In multivariate analysis, higher serum concentration of hs-CRP was significantly (regression coefficient r: 0.21) associated with a higher level of diabetic retinopathy (P = 0.007; standardized regression coefficient beta:0.06; non-standardized regression coefficient B:1.35; 95% confidence interval (CI):0.37,2.22) and polypoidal choroidal vasculopathy (P = 0.002;beta:0.06;B:6.22;95%CI:2.24,10.2) after adjusting for higher serum concentration of high-density lipoproteins (P<0.001;beta:-0.12;B:-1.31;95%CI:-1.77,-0.85), higher body mass index (P = 0.01;beta:0.06;B:0.06;95%CI:0.01, 0.11), lower level of education (P = 0.04;beta:-0.06;B:-0.22;95%CI:-0.42,-0.02), lower cognitive function score (P = 0.01;beta:-0.07;B:-0.08;95%CI:-0.13,-0.02). If the presences of other ocular diseases were added to the model, the presence of glaucoma (P = 0.99), open-angle glaucoma (P = 0.80), angle-closure glaucoma (P = 0.67), pseudoexfoliation (P = 0.18), nuclear cataract (P = 0.30), cortical cataract (P = 0.15), subcapsular cataract (P = 0.59), retinal vein occlusions (P = 0.33), central serous choroidopathy (P = 0.44), early stage of age-related macular degeneration (AMD) (P = 0.46), intermediate stage of AMD (P = 0.20) and late stage of AMD (P = 0.91) including geographic atrophy (P = 0.60) or neovascular AMD (P = 0.68) were not significantly associated with the serum concentration of hs-CRP.ConclusionsIn Chinese aged 50+ years, higher serum concentration of hs-CRP was significantly associated with a higher level of diabetic retinopathy and higher frequency of polypoidal choroidal vasculopathy. Other major ocular disorders, namely glaucoma including open-angle glaucoma and angle-closure glaucoma, pseudoexfoliation, nuclear, cortical or subcapsular cataract, retinal vein occlusions, central serous choroidopathy, early, intermediate or late stage of AMD including geographic atrophy, were not significantly associated with hs-CRP serum concentrations. It suggests that these diseases, in contrast to diabetic retinopathy and polypoidal choroidal vasculopathy, were not associated with a major systemic inflammatory component.

Project description:ObjectiveDuring cardiovascular disease progression, molecular systems of myocardium (e.g., a proteome) undergo diverse and distinct changes. Dynamic, temporally-regulated alterations of individual molecules underlie the collective response of the heart to pathological drivers and the ultimate development of pathogenesis. Advances in high-throughput omics technologies have enabled cost-effective, temporal profiling of targeted systems in animal models of human diseases. However, computational analysis of temporal patterns from omics data remains challenging. In particular, bioinformatic pipelines involving unsupervised statistical approaches to support cardiovascular investigations are lacking, which hinders one's ability to extract biomedical insights from these complex datasets.Approach and resultsWe developed a non-parametric data analysis platform to resolve computational challenges unique to temporal omics datasets. Our platform consists of three modules. Module I preprocesses the temporal data using either cubic splines or principal component analysis (PCA), and it simultaneously accomplishes the tasks on missing data imputation and denoising. Module II performs an unsupervised classification by K-means or hierarchical clustering. Module III evaluates and identifies biological entities (e.g., molecular events) that exhibit strong associations to specific temporal patterns. The jackstraw method for cluster membership has been applied to estimate p-values and posterior inclusion probabilities (PIPs), both of which guided feature selection. To demonstrate the utility of the analysis platform, we employed a temporal proteomics dataset that captured the proteome-wide dynamics of oxidative stress induced post-translational modifications (O-PTMs) in mouse hearts undergoing isoproterenol (ISO)-induced hypertrophy.ConclusionWe have created a platform, CV.Signature.TCP, to identify distinct temporal clusters in omics datasets. We presented a cardiovascular use case to demonstrate its utility in unveiling biological insights underlying O-PTM regulations in cardiac remodeling. This platform is implemented in an open source R package (https://github.com/UCLA-BD2K/CV.Signature.TCP).

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Systemic inflammation may induce cardiac injury in COVID-19 patients including children and adolescents without underlying cardiovascular diseases: A systematic review.

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