An Interplay between Oxidative Stress (Lactate Dehydrogenase) and Inflammation (Anisocytosis) Mediates COVID-19 Severity Defined by Routine Clinical Markers.

Viral infections activate the innate immune response and the secretion of inflammatory cytokines. They also alter oxidative stress markers, which potentially can have an involvement in the pathogenesis of the disease. The aim of this research was to study the role of the oxidative stress process assessed through lactate dehydrogenase (LDH) on the severity of COVID-19 measured by oxygen saturation (SaO2) and the putative interaction with inflammation. The investigation enrolled 1808 patients (mean age of 68 and 60% male) with COVID-19 from the HM Hospitals database. To explore interactions, a regression model and mediation analyses were performed. The patients with lower SaO2 presented lymphopenia and higher values of neutrophils-to-lymphocytes ratio and on the anisocytosis coefficient. The regression model showed an interaction between LDH and anisocytosis, suggesting that high levels of LDH (>544 U/L) and an anisocytosis coefficient higher than 10% can impact SaO2 in COVID-19 patients. Moreover, analysis revealed that LDH mediated 41% (p value = 0.001) of the effect of anisocytosis on SaO2 in this cohort. This investigation revealed that the oxidative stress marker LDH and the interaction with anisocytosis have an important role in the severity of COVID-19 infection and should be considered for the management and treatment of the oxidative phenomena concerning this within a precision medicine strategy.

Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases.

The liver is a key organ involved in a wide range of functions, whose damage can lead to chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide, becoming a social and economic burden for most countries. Among the different factors that can cause CLD, alcohol abuse, viruses, drug treatments, and unhealthy dietary patterns top the list. These conditions prompt and perpetuate an inflammatory environment and oxidative stress imbalance that favor the development of hepatic fibrogenesis. High stages of fibrosis can eventually lead to cirrhosis or hepatocellular carcinoma (HCC). Despite the advances achieved in this field, new approaches are needed for the prevention, diagnosis, treatment, and prognosis of CLD. In this context, the scientific com-munity is using machine learning (ML) algorithms to integrate and process vast amounts of data with unprecedented performance. ML techniques allow the integration of anthropometric, genetic, clinical, biochemical, dietary, lifestyle and omics data, giving new insights to tackle CLD and bringing personalized medicine a step closer. This review summarizes the investigations where ML techniques have been applied to study new approaches that could be used in inflammatory-related, hepatitis viruses-induced, and coronavirus disease 2019-induced liver damage and enlighten the factors involved in CLD development.

Potential protective effect against SARS-CoV-2 infection by APOE rs7412 polymorphism.

The pandemic burden caused by the SARS-CoV-2 coronavirus constitutes a global public health emergency. Increasing understanding about predisposing factors to infection and severity is now a priority. Genetic, metabolic, and environmental factors can play a crucial role in the course and clinical outcome of COVID-19. We aimed to investigate the putative relationship between genetic factors associated to obesity, metabolism and lifestyle, and the presence and severity of SARS-CoV-2 infection. A total of 249 volunteers (178 women and 71 men, with mean and ± SD age of 49 ± 11 years) characterized for dietary, lifestyle habits and anthropometry, were studied for presence and severity of COVID-19 infection, and genotyped for 26 genetic variants related to obesity, lipid profile, inflammation, and biorhythm patterns. A statistically significant association was found concerning a protective effect of APOE rs7412 against SARS-CoV-2 infection (p = 0.039; OR 0.216; CI 0.084, 0.557) after correction for multiple comparisons. This protective effect was also ascribed to the APOɛ2 allele (p = 0.001; OR 0.207; CI 0.0796, 0.538). The genetic variant rs7412 resulting in ApoE2, genetic determinant of lipid and lipoprotein levels, could play a significant role protecting against SARS-CoV-2 infection.

Exploring Host Genetic Polymorphisms Involved in SARS-CoV Infection Outcomes: Implications for Personalized Medicine in COVID-19.

OBJECTIVE: To systematically explore genetic polymorphisms associated with the clinical outcomes in SARS-CoV infection in humans. METHODS: This comprehensive literature search comprised available English papers published in PubMed/Medline and SCOPUS databases following the PRISMA-P guidelines and PICO/AXIS criteria. RESULTS: Twenty-nine polymorphisms located in 21 genes were identified as associated with SARS-CoV susceptibility/resistance, disease severity, and clinical outcomes predominantly in Asian populations. Thus, genes implicated in key pathophysiological processes such as the mechanisms related to the entry of the virus into the cell and the antiviral immune/inflammatory responses were identified. CONCLUSIONS: Although caution must be taken, the results of this systematic review suggest that multiple genetic polymorphisms are associated with SARS-CoV infection features by affecting virus pathogenesis and host immune response, which could have important applications for the study and understanding of genetics in SARS-CoV-2/COVID-19 and for personalized translational clinical practice depending on the population studied and associated environments.