Search

BackgroundPost-COVID conditions (PCC) are common and have significant morbidity. Risk factors for PCC include advancing age, female sex, obesity, and diabetes mellitus. Little is known about early treatment, inflammation, and PCC.MethodsAmong 883 individuals with confirmed SARS-CoV-2 infection participating in a randomized trial of CCP vs. control plasma with available biospecimens and symptom data, the association between early COVID treatment, cytokine levels and PCC was evaluated. Cytokine and chemokine levels were assessed at baseline, day 14 and day 90 using a multiplexed sandwich immuosassay (Mesoscale Discovery). Presence of any self-reported PCC symptoms was assessed at day 90. Associations between COVID treatment, cytokine levels and PCC were examined using multivariate logistic regression models.ResultsOne-third of the 882 participants had day 90 PCC symptoms, with fatigue (14.5%) and loss of smell (14.5%) being most common. Cytokine levels decreased from baseline to day 90. In a multivariable analysis including diabetes, body mass index, race, and vaccine status, female sex (adjusted odds ratio[AOR]=2.70[1.93-3.81]), older age (AOR=1.32[1.17-1.50]), and elevated baseline levels of IL-6 (AOR=1.59[1.02-2.47]) were associated with development of PCC. There was a trend for decreased PCC in those with early CCP treatment (<5 days after symptom onset) compared to late CCP treatment.ConclusionIncreased IL-6 levels were associated with the development of PCC and there was a trend for decreased PCC with early CCP treatment in this predominately unvaccinated population. Future treatment studies should evaluate the effect of early treatment and anti-IL-6 therapies on PCC development.SummaryIncreased IL-6 levels were associated with the development of Post-COVID Conditions (PCC) and there was a trend for decreased PCC with early COVID convalescent plasma treatment in this predominately unvaccinated population.

Supplementary Material 1

Additional file 1: Supplementary Figures and Tables. Figure S1. (Related to Figure 1). Design of the study comparison between study participants. Figure S2. (Related to Figure 1). (A) Ridgeline plots of the unthresholded expressions of all the 40 surface markers for each main cell types. (B) Age projection (below and above median) onto CM, INT, NCM, CD4+ T cells and CD8+ T cell UMAPs. Figure S3. (Related to Figure 5). Dotplots of DEG for disease types for subsets. Table S1. Reagents. Table S2. The cell viability of each frozen PBMC tube. Table S3. List of 40 titrated oligonucleotide-tagged monoclonal antibodies. Table S4. List of selected genes included in the custom panel. Table S5. Threshold values of each antibody. Table S6. Antibodies not used for cell clustering. Table S7. Number of Cells in each of the clusters. Table S8. Significantly differentially expressed genes for each cell type (A-E). Table S9. Number of Cells for each participant. Table S10. Non-negative Spearman correlation between antibody and gene in each cell type.