Association of Low Levels of Soluble Low-Density Lipoprotein Receptor-Related Protein-1 and COVID-19 Outcomes During the First Wave of Pandemic.

Low-density lipoprotein receptor-related protein-1 (LRP1) is an endocytosis receptor that clears inflammatory proteins from circulation. LRP1 has anti-inflammatory effects that bind pro-inflammatory cytokines or ligands. LRP1 has a soluble form (sLRP1) which can be measured in serum. We report sLRP1 levels in hospitalized patients with COVID-19. The first objective of this study is to compare the sLRP1 levels between COVID-19 patients and healthy controls. The second objective is to examine the association between sLRP1 and the clinical outcome of COVID-19. All patients (20-80 years of age) were evaluated in a hospital using a positive PCR test for SARS­CoV­2 between April 1, 2020, and June 1, 2020. Controls (n=59) were selected from healthy subjects. sLRP1 levels were measured in patients from the emergency department (ED), inpatient service (IS), and the intensive care unit (ICU). The study included 180 cases. COVID-19 patients showed significantly lower sLRP1 levels compared to controls (1.43 (1.86) versus 2.27 (1.68) µg/mL, respectively, p<0.001). sLRP1 levels were 1.26 (1.81), 1.37 (1.65), and 1.74 (1.98) µg/mL in patients from ED, IS, and ICU, respectively (p=0.022). Patients who were admitted from ED displayed lower sLRP1 levels compared to those who were discharged (median sLRP1 levels were 0.86 versus 1.7 µg/mL, p=0.045). COVID-19 patients display significantly lower sLRP1 levels compared to the healthy controls. sLRP1 levels do not show any association with the clinical outcome of COVID-19. This study demonstrates that LRP1 displays a bidirectional course in COVID-19. A low sLRP1 level is a potential risk factor for susceptibility and hospital admission due to COVID-19. Further studies with larger sample sizes and longer follow-ups are needed to understand the long-term effects of novel biomarkers such as sLRP1 on the outcome of COVID-19.

Plasminogen activator inhibitor-1 levels as an indicator of severity and mortality for COVID-19

OBJECTIVE Coronavirus disease-19 (COVID-19) is a multisystemic disease that can cause severe illness and mortality by exacerbating symptoms such as thrombosis, fibrinolysis, and inflammation. Plasminogen activator inhibitor-1 (PAI-1) plays an important role in regulating fibrinolysis and may cause thrombotic events to develop. The goal of this study is to examine the relationship between PAI-1 levels and disease severity and mortality in relation to COVID-19. METHODS A total of 71 hospitalized patients were diagnosed with COVID-19 using real time-polymerase chain reaction tests. Each patient underwent chest computerized tomography (CT). Data from an additional 20 volunteers without COVID-19 were included in this single-center study. Each patient's PAI-1 data were collected at admission, and the CT severity score (CT-SS) was then calculated for each patient. RESULTS The patients were categorized into the control group (n=20), the survivor group (n=47), and the non-survivor group (n=24). In the non-survivor group, the mean age was 75.3±13.8, which is higher than in the survivor group (61.7±16.9) and in the control group (59.5±11.2), (p=0.001). When the PAI-1 levels were compared between each group, the non-survivor group showed the highest levels, followed by the survivor group and then the control group (p<0.001). Logistic regression analysis revealed that age, PAI-1, and disease severity independently predicted COVID-19 mortality rates. In this study, it was observed that PAI-1 levels with >10.2 ng/mL had 83% sensitivity and an 83% specificity rate when used to predict mortality after COVID-19. Then, patients were divided into severe (n=33) and non-severe (n=38) groups according to disease severity levels. The PAI-1 levels found were higher in the severe group (p<0.001) than in the non-severe group. In the regression analysis that followed, high sensitive troponin I and PAI-1 were found to indicate disease severity levels. The CT-SS was estimated as significantly higher in the non-survivor group compared to the survivor group (p<0.001). When comparing CT-SS between the severe group and the non-severe group, this was significantly higher in the severe group (p<0.001). In addition, a strong statistically significant positive correlation was found between CT-SS and PAI-1 levels (r: 0.838, p<0.001). CONCLUSION Anticipating poor clinical outcomes in relation to COVID-19 is crucial. This study showed that PAI-1 levels could independently predict disease severity and mortality rates for patients with COVID-19.