LitCovid-sentences  

PMC:7402624 / 52519-61471 JSONTXT 11 Projects

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Id Subject Object Predicate Lexical cue
T302 0-10 Sentence denotes Discussion
T303 11-86 Sentence denotes The T and B cell response to SARS-CoV2 infection remains poorly understood.
T304 87-238 Sentence denotes Some studies suggest an overaggressive immune response leading to immunopathology (51) whereas others suggest T cell exhaustion or dysfunction (12–14).
T305 239-365 Sentence denotes Autopsies revealed high virus levels in the respiratory tract and other tissues (52), suggesting ineffective immune responses.
T306 366-484 Sentence denotes Nevertheless, non-hospitalized subjects who recovered from COVID-19 had evidence of virus-specific T cell memory (53).
T307 485-638 Sentence denotes SARS-CoV2-specific antibodies are also found in convalescent subjects and patients are currently being treated with convalescent plasma therapy (30, 54).
T308 639-806 Sentence denotes However, COVID-19 ICU patients have SARS-CoV2-specific antibodies (30), raising the question of why patients with these antibody responses are not controlling disease.
T309 807-980 Sentence denotes In general, these studies report on single patients or small cohorts and comprehensive deep immune profiling of a large number of COVID-19 hospitalized patients is limiting.
T310 981-1118 Sentence denotes Such knowledge would address the critical question of whether there is a common profile of immune dysfunction in critically ill patients.
T311 1119-1257 Sentence denotes Such data would also help guide testing of therapeutics to enhance, inhibit, or otherwise tailor the immune response in COVID-19 patients.
T312 1258-1383 Sentence denotes To interrogate the immune response patterns of COVID-19 hospitalized patients, we studied a cohort of ~125 COVID-19 patients.
T313 1384-1704 Sentence denotes We used high dimensional flow cytometry to perform deep immune profiling of individual B and T cell populations, with temporal analysis of immune changes during infection, and combined this profiling with extensive clinical data to understand the relationships between immune responses to SARS-CoV2 and disease severity.
T314 1705-1755 Sentence denotes Using this approach, we made several key findings.
T315 1756-1868 Sentence denotes First, a defining feature of COVID-19 disease in hospitalized patients was heterogeneity of the immune response.
T316 1869-2088 Sentence denotes Many COVID-19 patients displayed robust CD8 T cell and/or CD4 T cell activation and proliferation and PB responses, though a considerable subgroup of patients (~20%) had minimal detectable response compared to controls.
T317 2089-2263 Sentence denotes Furthermore, even within those patients who mounted detectable B and T cell responses during COVID-19 disease, the immune characteristics of this response were heterogeneous.
T318 2264-2832 Sentence denotes By deep immune profiling, we identified three immunotypes in hospitalized COVID-19 patients including: (1) patients with robust activation and proliferation of CD4 T cells, relative lack of cTfh, together with modest activation of TEMRA-like as well as highly activated or exhausted CD8 T cells and a signature of T-bet+ PB; (2) Tbetbright effector-like CD8 T cell responses, less robust CD4 T cell responses, and Ki67+ PB and memory B cells; and (3) an immunotype largely lacking detectable lymphocyte response to infection, suggesting a failure of immune activation.
T319 2833-2991 Sentence denotes UMAP embedding further resolved the T cell activation immunotype, suggesting a link between CD4 T cell activation, Immunotype 1, and increased severity score.
T320 2992-3182 Sentence denotes Although differences in age and race existed between the cohorts and could impact some immune variables, the major UMAP relationships were preserved even when correcting for these variables.
T321 3183-3295 Sentence denotes Thus, these immunotypes may reflect fundamental differences in the ways patients respond to SARS-CoV2 infection.
T322 3296-3367 Sentence denotes A second key observation from these studies was the robust PB response.
T323 3368-3474 Sentence denotes Some patients had PB frequencies rivaling those found in acute Ebola or Dengue infection (34, 42, 43, 55).
T324 3475-3575 Sentence denotes Furthermore, blood PB frequencies are typically correlated with blood activated cTfh responses (40).
T325 3576-3664 Sentence denotes However, in COVID-19 patients, this relationship between PB and activated cTfh was weak.
T326 3665-3959 Sentence denotes The lack of relationship between these two cell types in this disease could be due to T cell-independent B cell responses, lack of activated cTfh in peripheral blood at this time point, or lower CXCR5 expression observed across lymphocyte populations, making it more difficult to identify cTfh.
T327 3960-4159 Sentence denotes Indeed, activated (CD38+HLA-DR+) CD4 T cells could play a role in providing B cell help, perhaps as part of an extrafollicular response, but such a connection was also not robust in the current data.
T328 4160-4284 Sentence denotes Most ICU patients made SARS-CoV2-specific antibodies, suggesting that at least part of the PB response was antigen-specific.
T329 4285-4425 Sentence denotes Indeed, the cTfh response did correlate with antibodies suggesting that at least some of the humoral response is targeted against the virus.
T330 4426-4557 Sentence denotes Future studies will be needed to address the antigen specificity, ontogeny, and role in pathogenesis for these robust PB responses.
T331 4558-4684 Sentence denotes A striking feature of some patients with strong T and B cell activation and proliferation was the durability of this response.
T332 4685-4775 Sentence denotes This T and B activation was interesting considering clinical lymphopenia in many patients.
T333 4776-4836 Sentence denotes This lymphopenia, however, was preferential for CD8 T cells.
T334 4837-5038 Sentence denotes It may be notable that such focal lymphopenia preferentially affecting CD8 T cells is also a feature of acute Ebola infection of macaques and is associated with CD95 expression and severe disease (55).
T335 5039-5117 Sentence denotes Indeed CD95 was associated with activated T cell clusters in COVID-19 disease.
T336 5118-5328 Sentence denotes Nevertheless, the frequency of the KI67+ or CD38+HLA-DR+ CD8 and CD4 T cell responses in COVID-19 patients was similar in magnitude to other acute viral infections or live attenuated vaccines in humans (47–49).
T337 5329-5493 Sentence denotes However, during many acute viral infections, peak CD8 or CD4 T cell responses and the window of detectable PB in peripheral blood are relatively short (43, 56, 57).
T338 5494-5745 Sentence denotes The stability of CD8 and CD4 T cell activation and PB responses during COVID-19 disease suggests a prolonged period of peak immune responses at the time of hospitalization or perhaps a failure to appropriately down-regulate responses in some patients.
T339 5746-5862 Sentence denotes These ideas would fit with an overaggressive immune response and/or “cytokine storm” (2) in this subset of patients.
T340 5863-6049 Sentence denotes Indeed, in some patients, we found elevated serum cytokines and that stimulation of T cells in vitro provoked cytokines and chemokines capable of activating and recruiting myeloid cells.
T341 6050-6219 Sentence denotes A key question will be how to identify these patients for selected immune regulatory treatment while avoiding treating patients with already weak T and B cell responses.
T342 6220-6408 Sentence denotes An additional major finding was the ability to connect immune features not only to disease severity at the time of sampling but also to the trajectory of disease severity change over time.
T343 6409-6575 Sentence denotes Using correlative analyses, we observed relationships between features of the different immunotypes, patient comorbidities, and clinical features of COVID-19 disease.
T344 6576-6801 Sentence denotes By integrating ~200 immune features with extensive clinical data, disease severity scores, and temporal changes, we built an integrated computational model that connected patient immune response phenotype to disease severity.
T345 6802-6957 Sentence denotes Moreover, this UMAP embedding approach allowed us to connect these integrated immune signatures back to specific clinically measurable features of disease.
T346 6958-7096 Sentence denotes The integrated immune signatures captured by Components 1 and 2 in this UMAP model provided support for the notion of Immunotypes 1 and 2.
T347 7097-7508 Sentence denotes These analyses suggested that Immunotype 1, comprised of robust CD4 T cell activation, paucity of cTfh with proliferating effector/exhausted CD8 T cells and T-bet+ PB involvement, was connected to more severe disease whereas Immunotype 2, characterized by more traditional effector CD8 T cells subsets, less CD4 T cell activation and proliferating PB and memory B cells, was better captured by UMAP Component 2.
T348 7509-7759 Sentence denotes Immunotype 3, in which minimal lymphocyte activation response was observed, may represent ~20% of COVID-19 patients and is a potentially important scenario to consider as patients who may have failed to mount a robust antiviral T and B cell response.
T349 7760-7961 Sentence denotes This UMAP integrated modeling approach could be improved in the future with additional data on other immune cell types and/or comprehensive data for circulating inflammatory mediators for all patients.
T350 7962-8148 Sentence denotes Nevertheless, these findings provoke the idea of the tailoring clinical treatments or future immune-based clinical trials to patients whose immunotype suggests greater potential benefit.
T351 8149-8364 Sentence denotes Respiratory viral infections can cause pathology as a result of an immune response that is too weak and results in virus-induced pathology, or an immune response that is too strong and leads to immunopathology (58).
T352 8365-8632 Sentence denotes Our data suggest that the immune response of hospitalized COVID-19 patients may fall across this spectrum of immune response patterns, presenting as distinct immunotypes linked to clinical features, disease severity, and temporal changes in response and pathogenesis.
T353 8633-8776 Sentence denotes This study provides a compendium of immune response data and also an integrated framework as a “map” for connecting immune features to disease.
T354 8777-8952 Sentence denotes By localizing patients on an immune topology map built on this dataset, we can begin to infer which types of therapeutic interventions may be most useful in specific patients.