Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism

Abstract

Background: Long-COVID is characterized by prolonged, diffuse symptoms months after acute COVID-19. Accurate diagnosis and targeted therapies for Long-COVID are lacking. We investigated vascular transformation biomarkers in Long-COVID patients.

Methods: A case-control study utilizing Long-COVID patients, one to six months (median 98.5 days) post-infection, with multiplex immunoassay measurement of sixteen blood biomarkers of vascular transformation, including ANG-1, P-SEL, MMP-1, VE-Cad, Syn-1, Endoglin, PECAM-1, VEGF-A, ICAM-1, VLA-4, E-SEL, thrombomodulin, VEGF-R2, VEGF-R3, VCAM-1 and VEGF-D.

Results: Fourteen vasculature transformation blood biomarkers were significantly elevated in Long-COVID outpatients, versus acutely ill COVID-19 inpatients and healthy controls subjects (P < 0.05). A unique two biomarker profile consisting of ANG-1/P-SEL was developed with machine learning, providing a classification accuracy for Long-COVID status of 96%. Individually, ANG-1 and P-SEL had excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, P < 0.0001; validated in a secondary cohort). Specific to Long-COVID, ANG-1 levels were associated with female sex and a lack of disease interventions at follow-up (P < 0.05).

Conclusions: Long-COVID patients suffer prolonged, diffuse symptoms and poorer health. Vascular transformation blood biomarkers were significantly elevated in Long-COVID, with angiogenesis markers (ANG-1/P-SEL) providing classification accuracy of 96%. Vascular transformation blood biomarkers hold potential for diagnostics, and modulators of angiogenesis may have therapeutic efficacy.

Keywords: Angiogenesis; Biomarkers; Long-COVID; Machine learning; Vascular transformation.

Fig. 1

Identification of important vascular transformation blood biomarkers in Long-COVID outpatients. A List generated with a Random Forest indicating the relative importance of fourteen blood biomarkers for classifying subjects between cohorts. The leading two biomarkers were ANG-1 and P-SEL. B Subjects plotted in two-dimensions, following t-SNE dimensionality reduction of all fourteen significant biomarkers, shows separation cluster of Long-COVID outpatients with some mixing with acutely ill COVID-19 inpatients and healthy control subjects. C Subjects plotted in two-dimensions, following t-SNE dimensionality reduction of two selected biomarkers, ANG-1 and P-SEL, showed distinct separation and clustering of Long-COVID outpatients from acutely ill COVID-19 inpatients and healthy control subjects

Fig. 2

Similar biomarker profiles and plasma concentrations relative to days after acute infection. A A heatmap demonstrated the pairwise Euclidian Distance between cohort’s biomarker profiles with respect to ANG-1 and P-SEL. Lower distances between patients indicate similar biomarker profiles while larger distances indicate large differences between profiles (distance was pseudocolored on the bar scale). The biomarker profile of Long-COVID outpatients is distinctively different from all other cohorts. The heatmap color scale was capped at 0.5 to restrict interpretation bias from Long-COVID outliers (max value 1.2) and allow for more visible details. B A plot demonstrated ANG-1 concentration versus time after acute infection. A cut-off value, adopted from previous ROC analyses on multiplex data, and a best fit polynomial regression line were calculated. C A plot demonstrated P-SEL concentration versus time after acute infection. A cut-off value, adopted from previous ROC analyses on multiplex data, and a best fit polynomial regression line were calculated

Fig. 3

Box plots and receiver operating characteristic (ROC) curves for leading biomarkers, ANG-1 and P-SEL. A A boxplot demonstrating significantly elevated blood ANG-1 concentrations in Long-COVID outpatients (****P < 0.0001). B ROC curves demonstrating the excellent Long-COVID classification potential of blood ANG-1 versus healthy control subjects (AUC = 1.00, P < 0.0001) and acutely ill COVID-19 inpatients (AUC = 1.00, P < 0.0001). ROC curve for Long-COVID versus healthy control (green) hidden by ROC curve for Long-COVID versus acutely ill COVID-19 patients. C A boxplot demonstrating significantly elevated blood P-SEL concentrations in Long-COVID outpatients (****P < 0.0001; ***P < 0.001). D ROC curves demonstrating the excellent Long-COVID classification potential of blood P-SEL versus healthy control subjects (AUC = 1.00, P < 0.0001) and acutely ill COVID-19 inpatients (AUC = 1.00, P < 0.0001). ROC curve for Long-COVID versus healthy control (green) hidden by ROC curve for Long-COVID versus acutely ill COVID-19 patients

Fig. 4

Violin plots demonstrating ANG-1 distribution in Long-COVID patients relative to sex and interventions at follow-up. A A violin plot demonstrating significantly elevated concentration of blood ANG-1 in Long-COVID female outpatients (*P < 0.05). B A violin plot demonstrating significantly elevated concentration of blood ANG-1 in Long-COVID outpatients that had no interventions at follow-up (*P < 0.05). Given the limited number of patients within this subgroup, the data was not corrected for multiple comparisons and should be considered exploratory