Severe COVID linked to RAAS and hyperlipidemia associated metabolic syndrome conditions
A recent study posted to the medRxiv* preprint server investigated the association of renin-angiotensin-aldosterone system (RAAS)-mediated hypertension (HT) with coronavirus disease 2019 (COVID-19).To get more news about Robotics as a Service, you can visit glprobotics.com official website.
Various studies have reported the role of angiotensin-converting enzyme-2 (ACE-2) receptors as the point of entry for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This information makes the ACE-2 receptors a critical focus in the assessment of RAAS-mediated hypertension and COVID-19 severity.
In the present study, researchers explored the physiology of risk factors related to the impact of COVID-19 on RAAS-targeted HT drugs and the interactions of hyperlipidemia (HL) with other risk factors associated with severe COVID-19.
The team collected data from electronic health records obtained from emergency and clinical health services and insurance records. The extracted records were classified into different sets based on several measures.
Out of the 1,000,000 randomly selected samples, approximately 997,140 were eligible for the study. However, the final study cohort included 269,536 COVID-19 patients plus an equal number of individuals who were not diagnosed with COVID-19, totaling 539,523 participants.
The team evaluated the impact of the RAAS hypertension pathway on manifestations of severe COVID-19 by analyzing the interaction of HT with RAAS drugs, including ACE inhibitors and angiotensin receptor blockers (ARBs), and comparing these interactions with non-RAAS medications like beta-blockers and calcium channel blockers.
Redescription-based topological data analysis (RTDA) was performed using phenotypic combinations that could distinguish underlying biological processes and related pathways. The team applied computation homology to determine topological loops found among the pathways. The collections of deformed simplices found in these loops represented connected redescriptions. Such redescriptions were organized into homology groups to obtain more information about the complex disease processes. The team also applied persistent homology analysis to examine homology groups. The representative cycles were subsequently used to characterize relevant redescriptions as markers for homological cycles.
The team performed cumulant-based network analysis (CuNA) and extracted data on associations between RAAS drugs, COVID-19 manifestations, age, gender, and susceptibility to COVID-19 infection and severity. Homological cycles were selected to highlight inclusions that involved severe COVID-19 and three types of HT drugs, viz. ACE inhibitors, beta-blockers, and ARBs.
The study findings showed that the RAAS complex played an important role in the exacerbation of chronic kidney disease in severe COVID-19 patients. The team also noted a trend that indicated that RAAS drugs suppressed the correlation of hypertension with severe COVID-19 more significantly than non-RAAS drugs. Furthermore, the researchers believe that this study highlighted the potential of topological data analysis in developing epidemiological studies that can efficiently target specific relationships to reveal novel connections that traditional analyses cannot fathom.