The Activin/FLRG Pathway Associates with Poor COVID-19 Outcomes in Hospitalized Patients

Abstract

A subset of hospitalized COVID-19 patients, particularly the aged and those with comorbidities, develop the most severe form of the disease, characterized by acute respiratory disease syndrome (ARDS), coincident with experiencing a "cytokine storm." Here, we demonstrate that cytokines which activate the NF-κB pathway can induce activin A. Patients with elevated activin A, activin B, and FLRG at hospital admission were associated with the most severe outcomes of COVID-19, including the requirement for mechanical ventilation, and all-cause mortality. A prior study showed that activin A could decrease viral load, which indicated there might be a risk to giving COVID-19 patients an inhibitor of activin. To evaluate this, the role for activin A was examined in a hamster model of SARS-CoV-2 infection, via blockade of activin A signaling. The hamster model demonstrated that use of an anti-activin A antibody did not worsen the disease and there was no evidence for increase in lung viral load and pathology. The study indicates blockade of activin signaling may be beneficial in treating COVID-19 patients experiencing ARDS.

Keywords: ARDS; COVID-19; FLRG; FSTL3; SARS-Cov-2; activin A; activin B; acute respiratory disease syndrome.

FIG 1

Activin A, activin B, FLRG, and PAI-1 levels versus disease severity in COVID-19 patients prior to dosing and in non-COVID-19 controls. Activin A (A), activin B (B), FLRG (C), and PAI-1 (D) for control subjects, severe COVID-19 patients, and critical COVID-19 patients. Number of patients tested in each group (n) is indicated under each respective plot. Median values for each group are shown above each respective plot. Significant follow-up Dunn pairwise comparisons are shown above each plot; ***, P < 0.001, ****, P < 0.0001.

FIG 2

Activin A, activin B, and FLRG levels associate with mortality outcomes and supplemental oxygenation requirements at baseline. (A to D) Activin A (A), activin B (B), FLRG (C), and PAI-1 (D) at baseline between COVID-19 patients who survived and died during the study. (E to H) Activin A (E), activin B (F), FLRG (G), and PAI-1 (H) at baseline between COVID-19 patients requiring various levels of supplemental oxygen. Number of patients tested in each group (n) is indicated under each respective plot. Median values for each group are shown above each respective plot. Significant follow-up Dunn pairwise comparisons are shown above each plot; *, P < 0.05, **, P < 0.01, ***, P < 0.001, ****, P < 0.0001.

FIG 3

Cumulative incidence curves for all-cause mortality and 1-point clinical score improvement. All biomarkers (activin A, activin B, FLRG, and PAI-1) were median split to form high and low groups. The low biomarker group is shown in green, and the high biomarker group is shown in blue. (A to D) Cumulative incidence rate of all-cause mortality is plotted over time through study day 60. (E to H) Cumulative incidence rate of 1-point clinical score improvement is plotted over time through study day 30. Number of subjects remaining at risk for each event are shown below each plot at 5-day or 10-day intervals starting at study enrollment.

FIG 4

Both IL-1α and TNF-α can stimulate activin A production in bronchial/tracheal SMCs, lung fibroblasts and pulmonary artery SMCs, which can be rescued by dexamethasone. Activin A production was measured in conditioned medium by enzyme-linked immunosorbent assay (ELISA). Bronchial/tracheal smooth muscle (BTSMC) cells, normal human lung fibroblasts (NHLF), and pulmonary artery smooth muscle cells (PASMC) were serum starved overnight and then treated with 10 ng/ml IL-1 α or TNF-α for 5 days in the presence or absence of 100 μM dexamethasone, 100 nM anti-activin A antibody REGN2477 or isotype control REGN1945. Conditioned medium was diluted at 1:10 for ELISA. The experiment was repeated twice, with a consistent result.

FIG 5

Role of IKK, p38 and JNK in activin A induction in response to cytokine treatment. Bronchial/tracheal smooth muscle cells (SMC) (top) pulmonary artery SMC (bottom) were treated for 24 h with 100 ng/ml of TNF-α or IL-1α in combination with pharmacological inhibitors for IKK (3 μM withaferin A), p38 (0.3 μM SB203580) and JNK (30 μM SP600125). A combination of IKK and p38 inhibitors (same concentrations), a combination of IKK and JNK inhibitors (same concentrations) and a combination of p38 and JNK inhibitors (same concentrations) was also used. DMSO was used as a negative control for inhibitor treatments. Treatment with sterile water only (Mock) was used as an additional control. Activin A levels were quantified in conditioned media by ELISA. n = 3 for each treatment. Significant Bonferroni-corrected pairwise comparisons with DMSO within each treatment condition are labeled. *, P < 0.05, **, P < 0.01, ***, P < 0.001, ****, P < 0.0001.

FIG 6

Efficacy of the anti-activin A antibody alone, REGEN-COV antibody cocktail alone, and the combination of the anti-activin antibody and REGEN-COV cocktail in the golden Syrian hamster model of SARS-CoV-2. (A) Study design overview and the antibody administration schedule. SARS-CoV-2 challenge was administered to groups 1 to 4 on day 0 (n = 10 per group). Group 5 received PBS and served as a healthy control (n = 6). (B) Daily body weight changes; (C) lung inflammation grading scores; (D) survival curves. In panel B, data are mean ± standard error of mean (SER). The y axis represents percent body weight change from the baseline, 2 days (day -2) prior to SARS-CoV-2 challenge. x axis represents days prior and postchallenge. Black asterisks indicate mean body weight differences between groups 1 (black line) and 4 (green line). Red asterisk indicates mean body weight difference between Groups 2 (red line) and 4 (green line). In panel C, the y axis represents semiquantitative scores for lung inflammation. Data are mean ± standard deviation from the mean (SD). Asterisks indicate difference between SARS-CoV-2 challenged groups. In panel D, the y axis represents percentage of surviving hamsters. x axis represents days following SARS-CoV-2 challenge. Statistical analyses were conducted with a one-way ANOVA followed by Tuckey’s multiple-comparison tests. SARS-COV-2 challenged groups were compared. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

FIG 7

Efficacy of the anti-activin antibody A in the golden Syrian hamster model of SARS-CoV-2. (A) Study design overview and the antibody administration schedule. SARS-CoV-2 challenge was administered to froupls 1 and 2 on day 0 (n = 10 per group). At this point, group 3 (n = 6) received PBS and served as a healthy control. (B) Daily body weight changes; (C) lung inflammation grading scores. In panel data are mean ± SER. The y axis represents percent body weight change from the baseline (day 0), recorded prior to SARS-CoV2 challenge. x axis represents days following SARS-CoV2 challenge. In panel B, comparisons among SARS-COV-2 challenged groups were done with a one-way ANOVA followed by Tuckey’s multiple-comparison tests and no differences were found. In panel C, the y axis represents semiquantitative scores for lung inflammation. *, P < 0.05 indicates difference between SARS-CoV-2 challenged groups derived from a one-way ANOVA followed by Tukey’s multiple-comparison tests. Data are mean ± SD.

FIG 8

Viral genomic RNA (gRNA) and subgenomic RNA (sgRNA) in lungs and nasal turbines on day 7 following SARS-COV-2 challenge. Comparisons between SARS-COV-2 challenged groups were done with a one-way ANOVA followed by Tuckey’s multiple-comparison tests and no differences were found. Two out of 6 nasal turbine samples from healthy controls were contaminated and tested positive for viral gRNA. y axes are set to log₁₀ scale and represent genomic equivalents (GE) per gram. Data are mean ± SER.

FIG 9

Moderate positive correlations observed between activin A, activin B, and FLRG in COVID-19 patients (A and B). Correlation matrices for COVID-19 patients prior to dosing (A) and control subjects (B). Spearman rho correlation coefficients are shown, *, P < 0.05, **, P < 0.01, ***, P < 0.001, ****, P < 0.0001. (C and D) Scatterplots of each biomarker comparison from COVID-19 patients prior to dosing (C) and control subjects (D). For visualization purposes all analytes were log₁₀ transformed.