LitCovid-sentences  

PMC:7402624 / 41271-52517 JSONTXT 11 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T239 0-129 Sentence denotes Identifying “immunotypes” and relationships between circulating B and T cell responses with disease severity in COVID-19 patients
T240 130-486 Sentence denotes To further investigate the relationship between immune responses and COVID-19 disease trajectory, we stratified the COVID-19 patients (n = 125) into eight different categories according to the NIH Ordinal Severity Scale ranging from COVID 1 (death) and COVID 2 (requiring maximal clinical intervention) to COVID 8 (at home with no required care) (Fig. 6A).
T241 487-594 Sentence denotes We then asked how changes in T and B cell populations defined above on D0 were related to disease severity.
T242 595-747 Sentence denotes More severe disease was associated with lower frequencies of CD8 and CD4 T cells, with a greater effect on CD8 T cells in less severe disease (Fig. 6B).
T243 748-943 Sentence denotes Taking all patients together, there were no statistically significant changes in the major T cell and B cell subsets related to disease severity though some trends were present (fig. S7, A to C).
T244 944-1104 Sentence denotes In contrast, HLA-DR+CD38+ CD8 T cells as well as both KI67+ and HLA-DR+CD38+ CD4 T cells were increased in patients with more severe disease (fig. S7, D and E).
T245 1105-1225 Sentence denotes Fig. 6 High dimensional analysis of immune phenotypes with clinical data reveals distinct COVID-19 patient immunotypes.
T246 1226-1320 Sentence denotes (A) NIH ordinal scale for COVID-19 clinical severity. (B) Frequencies of major immune subsets.
T247 1321-1814 Sentence denotes Significance determined by unpaired Wilcoxon test with BH correction: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. (C) Heatmap of indicated immune parameters by row; donor type, disease severity, and mortality indicated across top. (D) UMAP projection of aggregated flow cytometry data. (E) Transformed UMAP projection; density contours drawn separately for healthy donor (HD), recovered donor (RD), and COVID-19 subjects (see Methods). (F) Bars represent mean of UMAP Component 1.
T248 1815-2013 Sentence denotes Dots represent individual subjects; bars shaded by subject group and/or severity score. (G) Density contour plots indicating variation of specified immune features across UMAP Component coordinates.
T249 2014-2135 Sentence denotes Relative expression (according to heat scale) shown for both individual patients (points) and overall density (contours).
T250 2136-2813 Sentence denotes Spearman’s Rank Correlation coefficient (ρ) and p-value for each feature vs. Component 1 (C1) and Component 2 (C2) shown. (H) (Left) Spearman correlation between UMAP Components 1 and 2 and FlowSOM clusters. (Right) Select FlowSOM clusters and their protein expression. (I) Spearman correlation between UMAP Components 1 and 2 and clinical metadata. (J) Heatmap of immune parameters used to define Immunotype 3 indicated by row; disease severity and mortality indicated across top. (K) (Left) Transformed UMAP projection; patient status for Immunotype 3 indicated by color. (Right) Spearman correlation between Immunotype 3 and disease severity, mortality, and UMAP Components.
T251 2814-2880 Sentence denotes There were two challenges with extracting meaning from these data.
T252 2881-3007 Sentence denotes First, there was considerable inter-patient heterogeneity for each of these immune features related to disease severity score.
T253 3008-3165 Sentence denotes Second, these binary comparisons (e.g., one immune subset versus one clinical feature) vastly underutilized the high dimensional information in this dataset.
T254 3166-3288 Sentence denotes Thus, we next visualized major T and B cell subpopulation data as it related to clinical disease severity score (Fig. 6C).
T255 3289-3411 Sentence denotes Data were clustered based on immune features and then overlaid with the disease severity score over time for each patient.
T256 3412-3533 Sentence denotes This analysis revealed groups of patients with similar composite immune signatures of T and B cell populations (Fig. 6C).
T257 3534-3681 Sentence denotes When individual CD8 T cell, CD4 T cell, or B cell populations were examined, a similar concept of patient subgroups emerged (fig. S7, F, G, and H).
T258 3682-3894 Sentence denotes These data suggested the idea of “immunotypes” of COVID-19 patients based on integrated responses of T and B cells, though some individual cell types and/or phenotypes separated patients more clearly than others.
T259 3895-4107 Sentence denotes These approaches provided insight into potential immune phenotypes associated with patients with severe disease, but suffered from the use of a small number of manually selected T or B cell subsets or phenotypes.
T260 4108-4435 Sentence denotes We therefore next employed Uniform Manifold Approximation and Projection (UMAP) to distill the ~200 flow cytometry features (see tables S5 and S6) representing the immune landscape of COVID-19 disease in two dimensional space, creating compact meta features (or Components) that could then be correlated with clinical outcomes.
T261 4436-4633 Sentence denotes This analysis revealed a clear trajectory from HD to COVID-19 patients (Fig. 6D), which we centered and aligned with the horizontal axis (“Component 1”) to facilitate downstream analysis (Fig. 6E).
T262 4634-4764 Sentence denotes An orthogonal vertical axis coordinate (“Component 2”) also existed that captured non-overlapping aspects of the immune landscape.
T263 4765-4887 Sentence denotes We next calculated the mean of Component 1 for each patient group, with COVID-19 patients separated by severity (Fig. 6E).
T264 4888-5002 Sentence denotes The contribution of Component 1 clearly increased in a stepwise manner with increasing disease severity (Fig. 6F).
T265 5003-5077 Sentence denotes Interestingly, RD were subtly positioned between HD and COVID-19 patients.
T266 5078-5244 Sentence denotes Component 1 remained an independent predictor of disease severity (P = 5.5 × 10−5) even after adjusting for the confounding demographic factors of age, sex, and race.
T267 5245-5357 Sentence denotes We next investigated how the UMAP Components were associated with individual immune features (tables S5 and S6).
T268 5358-5494 Sentence denotes UMAP Component 1 captured immune features, including the relative loss of CD4 and CD8 T cells and increase in nonB:nonT cells (Fig. 6G).
T269 5495-5541 Sentence denotes PB also associated with Component 1 (Fig. 6G).
T270 5542-5630 Sentence denotes Other individual B cell features were differentially captured by UMAP Component 1 and 2.
T271 5631-5795 Sentence denotes Component 1 contained a signal for T-bet+ PB populations (table S5) whereas Component 2 was enriched for T-bet+ memory B cells and CD138+ PB populations (table S6).
T272 5796-6015 Sentence denotes Activated HLA-DR+CD38+ and KI67+ CD4 and CD8 T cells had contributions to both Component 1 and Component 2, with these features residing in the upper right corner of the UMAP plot (Fig. 6, G and H, and fig. S8, A to D).
T273 6016-6200 Sentence denotes In contrast, T-bet+ non-naïve CD8 T cells were strongly associated with Component 2 whereas T-bet+ non-naïve CD4 T cells were also linked to Component 1 (Fig. 6G and tables S5 and S6).
T274 6201-6339 Sentence denotes Eomes+ CD8 or CD4 T cells were both associated with Component 2 and negatively associated with Component 1 (Fig. 6G and tables S5 and S6).
T275 6340-6397 Sentence denotes We next took advantage of the FlowSOM clustering in Figs.
T276 6398-6549 Sentence denotes 2 to 4 that identified individual immune cell types most perturbed in COVID-19 patients and linked these FlowSOM clusters to UMAP Components (Fig. 6H).
T277 6550-6768 Sentence denotes For non-naïve CD8 T cells, FlowSOM Cluster 11 that contained T-bet+CX3CR1+ but non-proliferating effector-like cells was positively correlated with UMAP Component 2 and negatively correlated with Component 1 (Fig. 6H).
T278 6769-7006 Sentence denotes In contrast, FlowSOM Cluster 14 contained activated, proliferating PD-1+CD39+ cells that might reflect either recently generated effector or possibly exhausted CD8 T cells (50) and was strongly associated with UMAP Component 1 (Fig. 6H).
T279 7007-7274 Sentence denotes For CD4 T cells, FlowSOM Cluster 14, containing activated, proliferating CD4 T cells, was captured by both UMAP Components, whereas a second activated CD4 T cell population that also expressed CD95 (FlowSOM Cluster 13) was only captured by UMAP Component 1 (Fig. 6H).
T280 7275-7397 Sentence denotes In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H).
T281 7398-7601 Sentence denotes Finally, for B cells, the FlowSOM Cluster of T-bet+CD138+ PB (Cluster 5) was positively correlated with Component 1 whereas the Tbet-CD138+ Cluster 3 was negatively correlated with Component 1 (Fig. 6H).
T282 7602-7770 Sentence denotes Locations in the UMAP immune landscape were dynamic, changing from D0 to D7 for both Component 1 and Component 2 consistent with the data in Fig. 5 and fig. S9, A to F.
T283 7771-7888 Sentence denotes The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G).
T284 7889-8049 Sentence denotes Given the association of the UMAP Component 1 with disease severity, we next examined the connections between UMAP Components with individual clinical features.
T285 8050-8261 Sentence denotes UMAP Component 1 correlated with several clinical measurements of inflammation (e.g., ferritin, hsCRP, IL-6), co-infection, organ failure (APACHE III), and acute kidney disease and renal insufficiency (Fig. 6I).
T286 8262-8425 Sentence denotes It was interesting, however, that, although D-dimer was elevated, this feature did not correlate with UMAP Component 1, but coagulation complication did (Fig. 6I).
T287 8426-8545 Sentence denotes Several antibody features also correlated with Component 1 consistent with some of the immune features discussed above.
T288 8546-8770 Sentence denotes In contrast, Component 2 lacked positive correlation to many of these clinical features of disease and rather was negatively correlated only to eosinophil count, NSAID use, and subsequent treatment with Remdesivir (Fig. 6I).
T289 8771-8966 Sentence denotes UMAP Component 1, but not Component 2, also correlated with mortality, although there were clearly patients with high Component 2, but low Component 1 who succumbed to COVID-19 disease (Fig. 6E).
T290 8967-9265 Sentence denotes These data indicate that the immune features captured by UMAP Component 1 have a strong relationship to many features of disease severity, whereas other features of immune dynamics during COVID-19 disease captured by UMAP Component 2 have a distinct relationship with clinical disease presentation.
T291 9266-9434 Sentence denotes More positive values in UMAP Components 1 or 2 captured mainly signals of change or differences in individual immune features in COVID-19 disease compared to HD and RD.
T292 9435-9851 Sentence denotes UMAP Component 1 captured an immunotype (Immunotype 1) that was characterized by effector or highly activated CD4 T cells, low cTfh, some CD8 TEMRA-like activation, possibly hyperactivated CD8 T cells, and Tbet+ PB, whereas Component 2 or Immunotype 2 captured Tbetbright effector-like CD8 T cells, lacked some of the robust CD4 T cell activation but has some features of proliferating B cells (Fig. 6G and fig. S8).
T293 9852-9888 Sentence denotes However, the data presented in Figs.
T294 9889-9982 Sentence denotes 1 to 5 also suggested a subset of patients with minimal activation of T and B cell responses.
T295 9983-10178 Sentence denotes To investigate this immune signature, we identified 20 patients who had responses more similar to HD and RD for five activated/responding B and T cell populations (Fig. 6J, middle, and fig. S10).
T296 10179-10346 Sentence denotes If the UMAP Components 1 and 2 captured two distinct “immunotypes” of patient responses to SARS-CoV2 infection, this group of 20 patients represent a third immunotype.
T297 10347-10669 Sentence denotes Immunotype 3 was negatively associated with UMAP Components 1 and 2 and negatively associated with disease severity, suggesting that a less robust immune response during COVID-19 was associated with less severe pathology (Fig. 6K and fig. S10), despite the fact that these patients were hospitalized with COVID-19 disease.
T298 10670-10780 Sentence denotes These data further emphasize the different ways patients can present and possibly succumb to COVID-19 disease.
T299 10781-10890 Sentence denotes These patterns may be related to pre-existing conditions in combination with immune response characteristics.
T300 10891-11012 Sentence denotes It is likely that additional immune features, such as comprehensive serum cytokine measurements, will improve this model.
T301 11013-11246 Sentence denotes Nevertheless, the current computational approach integrating deep immune profiling with disease severity trajectory and other clinical information revealed distinct patient immunotypes linked to distinct clinical outcomes (fig. S11).