(A) The bar graphs display the AIC of the four-parameter models in three runs. and clearance by controlling for comorbidities including heart, lung, kidney disease, hypertension (HTN), and diabetes and demographic info including age and body mass index (BMI). The axis represents the value (normalized coefficient of the group variable in the full model, and the axis denotes the ideals by Fst likelihood percentage test comparing the null LHW090-A7 model and full model). The null/full model represents the association between each individual measurement (response) and all collected clinical info with/without persistence and clearance group info (see Materials and Methods). The horizontal gray dashed collection denotes where the value equals 0.05, and the vertical gray dashed collection denotes a manually selected threshold (values?=?2). Download FIG?S4, TIF file, 1.5 MB. Copyright ? 2022 Wang et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license. FIG?S5. PLS-R regression model to associate the antibody profiles on day time 3 and continuous ideals of viral weight on day time 7. (A) The relationship between continuous ideals of viral weight on day time 7 and our defined persistence versus clearance phenotype. LHW090-A7 (****, LHW090-A7 The violin plots display the distributions of repeated regression R-square ideals using the actual data, and shuffled labels, illustrating the overall performance and robustness of the model. Black squares show the median accuracies with one standard deviation. (E) The correlation network demonstrates the cocorrelated features (small nodes) that are significantly correlated with the model-selected features (large nodes). Edge color corresponds to the correlation strength. Here, only the significant Spearman correlation coefficients larger than 0.6 after Benjamini-Hochberg multiple-testing correction are shown. Download FIG?S5, TIF file, 1.2 MB. Copyright ? 2022 Wang et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license. FIG?S6. Temporal development visualization of antibody features. Normalized antibody levels are shown over time per each measurement as days since sign onset with persistence (bottom) and clearance (top) organizations. Each dot represents an individual measurement of an individual participant, and the curves display smoothed nonparameter regression (LOESS) models. The color of the collection shows the antigen specificity. Download FIG?S6, TIF file, 1.6 MB. Copyright ? 2022 Wang et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license. FIG?S7. Temporal evolutionary curve of antibody features. For each antibody feature, the optimal model fitted by our four-parameter logistic regression model is definitely demonstrated for each group LHW090-A7 across each feature. Dots indicate individual patients, diamonds show the binned median, the curves show the optimal fitted models, and the colours show the organizations. The parameters demonstrated in the remaining corner are different for the displayed model and color-coded according to the group for which the parameter is definitely higher (refer to Fig.?5). (a) Initial levels at the time of symptom demonstration; (b) initial rise or conversion speed; (c) time to half-seroconversion; (d) the ultimate final plateau level. Download FIG?S7, TIF file, 1.5 MB. Copyright ? 2022 Wang et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license. FIG?S8. Four-parameter logistic regression model evaluation. The model overall performance was evaluated in three runs using randomly selected 85% sample units. (A) The pub graphs display the AIC of the four-parameter models in three runs. (B) The heatmaps display the AIC weighted-average parameter difference between individuals that cleared RNA (yellow) or encounter prolonged RNAemia (blue). (C) The Venn diagram depicts the shared features among the top 30 features across the unique experiments and three runs with partial datasets. Download FIG?S8, TIF file, 2.4 MB. Copyright ? 2022 Wang et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license. ABSTRACT Prolonged SARS-CoV-2 replication and systemic dissemination are linked to improved COVID-19 disease severity and mortality. However, the precise immune profiles that track with enhanced viral clearance, particularly from systemic RNAemia, remain incompletely defined..