Lipid profile changes in patients with COVID-19 referred to medical centers in Kermanshah, Iran; a case-control study

G Protein Subunit Beta 3 (GNB3) Variant Is Associated with Biochemical Changes in Brazilian Patients with Hypertension

BACKGROUND

Central Illustration : G Protein Subunit Beta 3 (GNB3) Variant Is Associated with Biochemical Changes in Brazilian Patients with Hypertension.

BACKGROUND

Genes and their variants associated with environmental factors contribute to the development of the hypertensive phenotype. The G protein beta 3 subunit gene (GNB3) is involved in the intracellular signaling process, and its variants have been related to susceptibility to arterial hypertension.

OBJECTIVE

To determine the association of the GNB3 variant (rs5443:C>T) with arterial hypertension, biochemical parameters, age, and obesity in hypertensive and normotensive individuals from Ouro Preto, Minas Gerais, Brazil.

METHOD

The identification of variants was performed by real-time PCR, using the TaqMan® system, in 310 samples (155 hypertensive and 155 normotensive). Biochemical analyses (renal function, lipid profile and glycemia) were performed from the serum using UV/Vis spectrophotometry and ion-selective electrode. A multiple logistic regression model was used to identify factors associated with arterial hypertension. The analysis of continuous variables with normal distribution was performed using the unpaired Student's t test; non-normal data were analyzed using Mann-Whitney. P < 0.05 was considered significant.

RESULTS

The rs5443:C>T variant was not associated with arterial hypertension in the evaluated population (p = 0.88). Regarding biochemical measures, the T allele was associated with high levels of triglycerides, glucose and uric acid in hypertensive individuals (p < 0.05).

CONCLUSION

These results show the importance of genetic diagnosis to prevent the causes and consequences of diseases and imply that the GNB3 rs5443:C>T variant may be associated with changes in the biochemical profile in hypertensive individuals.

Mixed storm in SARS-CoV-2 infection: A narrative review and new term in the Covid-19 era

Coronavirus disease 2019 (Covid-19) is caused by a novel severe acute respiratory syndrome coronavirus virus type 2 (SARS-CoV-2) leading to the global pandemic worldwide. Systemic complications in Covid-19 are mainly related to the direct SARS-CoV-2 cytopathic effects, associated hyperinflammation, hypercytokinemia, and the development of cytokine storm (CS). As well, Covid-19 complications are developed due to the propagation of oxidative and thrombotic events which may progress to a severe state called oxidative storm and thrombotic storm (TS), respectively. In addition, inflammatory and lipid storms are also developed in Covid-19 due to the activation of inflammatory cells and the release of bioactive lipids correspondingly. Therefore, the present narrative review aimed to elucidate the interrelated relationship between different storm types in Covid-19 and the development of the mixed storm (MS). In conclusion, SARS-CoV-2 infection induces various storm types including CS, inflammatory storm, lipid storm, TS and oxidative storm. These storms are not developing alone since there is a close relationship between them. Therefore, the MS seems to be more appropriate to be related to severe Covid-19 than CS, since it develops in Covid-19 due to the intricate interface between reactive oxygen species, proinflammatory cytokines, complement activation, coagulation disorders, and activated inflammatory signaling pathway.

Plasma lipid profile: a predictive marker of disease severity among COVID-19 patients—an opportunity for low-income countries

Objective

This study aimed to assess the correlation between body mass index (BMI) and plasma lipid profile levels in mild and severe COVID-19 patients.

Method

This was a prospective, observational, cohort study, conducted in a medical referral center specializing in management of COVID-19 cases. Patients were divided into two groups according to infection severity (mild and severe). Blood samples were obtained from all patients who tested positive to a PCR test for measuring biochemical and inflammatory markers such as lactate dehydrogenase, ferritin, C-reactive protein, and d-dimer, as well as lipid profile, including total cholesterol, triacylglycerols, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), which were analyzed and compared between the two groups. Pearson’s correlation was used to assess the correlation between BMI and plasma lipid profile among mild and severe cases.

Results

The levels of plasma triacylglycerols, d-dimer, lactate dehydrogenase, ferritin, and C-reactive protein with severe infection were significantly different between patients with mild and severe COVID-19 symptoms (p = 0.036, 0.03, 0.001, 0.014, and 0.006, respectively). A positive correlation between BMI and triglyceride levels was observed only in the severe infection group. However, HDL-C was negatively correlated with BMI.

Conclusion

A routine lipid profile test might help as a marker of inflammation and risk stratification in patients with COVID-19. Especially in middle- or low-income countries, the test can rapidly help clinicians to delineate prognostic measures and hence management and treatment plans for this disease as the levels of the lipid profile were correlated with the patients’ BMI and infection severity.