Figures and data
Characteristics of cohorts from the NFV clinical trial (jRCT207120002311,12) and the University of Illinois5:
(A) Flowchart of cohorts from the NFV clinical trial and the University of Illinois along with the number of participants and inclusion criteria for our analysis are described. (B) Data collection schedule of viral load, blood test, and vital signs from participants in the NFV clinical trial is described. (C) and (D) show, for each participant (N=144 participants, 2191 samples), the timeline of sample collection and the captured SARS-CoV-2 viral RNA load for saliva RT-qPCR, respectively. The red and blue colors indicate samples for cohorts from the NFV clinical trial and the University of Illinois, respectively.
Clinical data of the overall cohort from the NFV clinical trial and in groups stratified by longitudinal virus dynamics
Stratification of individual SARS-CoV-2 viral dynamics in saliva:
(A) UMAP of stratified viral RNA load based on the extracted features from the reconstructed individual-level viral dynamics is shown. (B) The reconstructed individual viral RNA load is shown. Colors for individual-level viral dynamics correspond to the colors of the dots in the UMAP described in (A). (C) The time-course patterns of each group highlighted by the Partial Least-Squares Discriminant Analysis (PLS-DA). (D) Distributions between groups of each feature used for stratification of viral shedding patterns are shown. The p-values of ANOVA for the difference in each feature among stratified group are all less than 0.05. (E) Distributions of the number of individuals in each stratified group for the standard-of-care alone (left, n=97) and standard-of-care plus NFV administration (right, n=47) participants are shown. (F) Distributions of the number of individuals in each stratified group for Alpha variants (left, n=30), Delta variants (middle, n=13), and other variants (right, n=66) of SARS-CoV-2 are shown.
Correlation between clinical data and viral shedding patterns:
(A) P-values of ANOVA corrected by the FDR to compare clinical data among the three stratified groups are shown. Clinical data are listed in reverse order of p-values. (B) and (C) show ROC curves of random forest classifiers trained on predicting each group by using data for 39 clinical values and 8 daily symptoms, respectively. The corresponding AUC (area under curve) value of each ROC curve is shown on the top of each panel.
Correlation between micro-RNA data and viral shedding patterns:
(A) The strategy of micro-RNA data collection from saliva samples in the NFV clinical trial is described. We picked a total of 30 participants by choosing 10 participants from each group. We chose two samples (the nearest to estimated peak and the most distant but above the detection limit in the late phase) from each participant for quantifying micro-RNA. (B) P-values of Kruskal-Wallis ANOVA corrected by the FDR for each micro-RNA level are shown. Micro-RNA levels are listed by reverse order of p-values. Only the 24 micro-RNA levels with the lowest p-values are shown. (C) ROC curves of random forest classifiers trained on predicting each group by using levels of 92 micro-RNAs are shown. The corresponding AUC value of each ROC curve is presented on the top of each panel.
Reconstructed viral dynamics in saliva samples for individual participants:
The individual-level model fits to saliva RT-qPCR results using the target-celllimited model described in Eqs.(1-2), for the same cohorts described in Fig. 1, are shown. The closed dots and the solid curves indicate the measured data and the estimated viral dynamics, respectively. Individuals from the NFV clinical trial and the University of Illinois are shown in red and blue, respectively.
Correlation between mir-1846 level and the features of infection dynamics:
The correlation between the rank of mir-1846 and the rank of (A) the peak viral load, (B) the duration of viral shedding, (C) up-slope and (D) down-slope are shown, respectively. The Spearman’s correlation coefficients and p-values are presented in the top of each panel. The black solid line and the gray shaded area indicate results of the linear regression and their 95% confidence levels, respectively.
Pearson’s correlation coefficients between clinical data and features of viral dynamics.
Spearman’s correlation coefficients between micro-RNA data and features of viral dynamics.
Comparison of three model fits to viral load in saliva samples for individual participants:
Three different individual-level model fits to saliva RT-qPCR results using the target-cell-limited model and the immune effector model described in Eqs.(1-2) and Eqs.(3-6), respectively, are shown. The black closed dots and solid curves indicate the measured viral load and the expected viral dynamics using the target-cell-limited model, respectively (Expended Data Fig 1). The red and blue dashed curves indicate estimated viral dynamics using the immune effector model for all the 144 individuals described in Fig 1 and for the 54 individuals in the cohort from the University of Illinois, respectively. Namely, the blue dashed curves are the model fits presented in 1.
Daily symptom data for whole cohorts for each group
Features of reconstructed individual viral dynamics for each group
