PMC:7402624 / 4746-11994 JSON TXT

Annnotations TAB JSON ListView MergeView

LitCovid-PD-FMA-UBERON

LitCovid-PD-UBERON

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T2","span":{"begin":322,"end":327},"obj":"Body_part"},{"id":"T3","span":{"begin":490,"end":495},"obj":"Body_part"},{"id":"T4","span":{"begin":2637,"end":2643},"obj":"Body_part"},{"id":"T5","span":{"begin":3924,"end":3929},"obj":"Body_part"},{"id":"T6","span":{"begin":5386,"end":5391},"obj":"Body_part"}],"attributes":[{"id":"A2","pred":"uberon_id","subj":"T2","obj":"http://purl.obolibrary.org/obo/UBERON_0000178"},{"id":"A3","pred":"uberon_id","subj":"T3","obj":"http://purl.obolibrary.org/obo/UBERON_0000178"},{"id":"A4","pred":"uberon_id","subj":"T4","obj":"http://purl.obolibrary.org/obo/UBERON_0002113"},{"id":"A5","pred":"uberon_id","subj":"T5","obj":"http://purl.obolibrary.org/obo/UBERON_0000178"},{"id":"A6","pred":"uberon_id","subj":"T6","obj":"http://purl.obolibrary.org/obo/UBERON_0000178"}],"text":"Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations\nWe conducted an observational study of hospitalized patients with COVID-19 at the University of Pennsylvania (UPenn IRB 808542) that included 149 hospitalized adults with confirmed SARS-CoV2 infection (COVID-19 patients). Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A). Additional samples were obtained from patients who remained hospitalized on day 7. Blood was also collected from non-hospitalized patients who had recovered from documented SARS-CoV2 infection (Recovered Donors (RD); n = 46), as well as from healthy donors (HD; n = 70) (UPenn IRB 834263) (Fig. 1A). Clinical metadata are available from the COVID-19 patients over the course of disease (table S1). Of the total patients and donors, flow cytometry data from PBMCs was collected from COVID-19 patients (n = 125), RDs (n = 36), and HDs (n = 60) along with clinical metadata (Fig. 1A and tables S2 to S4).\nFig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.\n(A) Overview of patient cohorts in study, including healthy donors (HD), recovered donors (RD), and COVID-19 patients. (B) Quantification of key clinical parameters in COVID-19 patients. Each dot is a COVID-19 patient; Healthy donor range indicated in green. (C) Spearman correlation and hierarchical clustering of indicated features for COVID-19 patients. (D) Representative flow cytometry plots and (E) frequencies of major immune subsets. (F) Ratio of CD4:CD8 T cells. (G) Spearman correlation of CD4:CD8 ratio and clinical lymphocyte count per patient. Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively. Vertical dashed line indicates clinical threshold for lymphopenia. (H) Spearman correlations of indicated subsets with various clinical features. (E and F) Each dot represents an individual healthy donor (green), RD (blue), or COVID-19 patient (red). Significance determined by unpaired Wilcoxon test with BH correction: *p \u003c 0.05, **p \u003c 0.01, ***p \u003c 0.001, and ****p \u003c 0.0001. COVID-19 patients had a median age of 60 and were significantly older than HD and RD (median age of 41 and 29 respectively), though the age distributions for all three cohorts overlapped (Fig. 1A and fig. S1A). For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2). Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort). Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event. A subset of patients (18%) were immunosuppressed, and 7% and 6% of patients were known to have a diagnosis of cancer or a pre-existing pulmonary condition, respectively. 45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir. Eighteen individuals died in the hospital or within a 30 day follow-up. The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms. Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.\nAs has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome. C reactive protein (CRP) was elevated in over 90% of subjects and LDH and D-dimer were increased in the vast majority, whereas ferritin was above normal in ~75% of COVID-19 patients (Fig. 1B and fig. S1B). Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B). In a subset of patients where it was measured, IL-6 levels were normal in 5 patients, moderately elevated in 5 patients (6-20 pg/ml), and high in 31 patients (21-738 pg/ml) (fig. S1B). Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B). A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33). Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC \u003c1 THO/ul, Fig. 1B). In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).\nTo examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C). This analysis revealed correlations between different COVID-19 disease severity metrics, as well as clinical features or interventions associated with more severe disease (e.g., D-dimer, vasoactive medication) (Fig. 1C and fig. S1C). WBC and PMN also correlated with metrics of disease severity (e.g., APACHE III), as well as with IL-6 levels (Fig. 1C and fig. S1C). Other relationships were also apparent, including correlations between age or mortality and metrics of disease severity and many other correlations between clinical measures of disease, inflammation, and co-morbidities (Fig. 1C and fig. S1C). Thus, COVID-19 patients presented with varied pre-existing comorbidities, complex clinical phenotypes, evidence of inflammation in many patients, and clinically altered leukocyte counts.\nTo begin to interrogate immune responses to acute SARS-CoV2 infection, we compared peripheral blood mononuclear cells (PBMC) of COVID-19 patients, RD, and HD subjects using high dimensional flow cytometry. We first focused on the major lymphocyte populations. B cell and CD3+ T cell frequencies were decreased in COVID-19 patients compared to HD or RD subjects, reflecting clinical lymphopenia, whereas the relative frequency of non-B and non-T cells was correspondingly elevated (Fig. 1, D and E). Although a numerical expansion of a non-B, non-T cell type is possible, loss of lymphocytes likely results in an increase in the relative frequency of this population. This non-B, non-T cell population is also interrogated in more detail in the companion study. Examining only CD3 T cells revealed preferential loss of CD8 T cells compared to CD4 T cells (Fig. 1, F and G, and fig. S1D); this pattern was reflected in absolute numbers estimated from the clinical data, where both CD4 and CD8 T cell counts in COVID-19 patients were lower than the clinical reference range, though the effect was more prominent for CD8 T cells (49/61 subjects below normal) than for CD4 T cells (38/61 subjects below normal) (fig. S1E). These findings are consistent with previous reports of lymphopenia during COVID-19 disease (17–20) but highlight a preferential impact on CD8 T cells.\nWe next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H). Lower WBC counts were associated preferentially with lower frequencies of CD4 and CD8 T cells and increased non-T non-B, but not with B cells (Fig. 1H). These lower T cell counts were associated with clinical markers of inflammation including ferritin, D-dimer, and hsCRP (Fig. 1H), whereas altered B cell frequencies were not. Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations."}

LitCovid-PubTator

LitCovid-PD-MONDO

LitCovid-PD-CLO

LitCovid-PD-CHEBI

LitCovid-PD-GO-BP

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T25","span":{"begin":5048,"end":5060},"obj":"http://purl.obolibrary.org/obo/GO_0006954"},{"id":"T26","span":{"begin":5220,"end":5232},"obj":"http://purl.obolibrary.org/obo/GO_0006954"},{"id":"T27","span":{"begin":5316,"end":5332},"obj":"http://purl.obolibrary.org/obo/GO_0006955"},{"id":"T28","span":{"begin":6986,"end":6998},"obj":"http://purl.obolibrary.org/obo/GO_0006954"}],"text":"Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations\nWe conducted an observational study of hospitalized patients with COVID-19 at the University of Pennsylvania (UPenn IRB 808542) that included 149 hospitalized adults with confirmed SARS-CoV2 infection (COVID-19 patients). Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A). Additional samples were obtained from patients who remained hospitalized on day 7. Blood was also collected from non-hospitalized patients who had recovered from documented SARS-CoV2 infection (Recovered Donors (RD); n = 46), as well as from healthy donors (HD; n = 70) (UPenn IRB 834263) (Fig. 1A). Clinical metadata are available from the COVID-19 patients over the course of disease (table S1). Of the total patients and donors, flow cytometry data from PBMCs was collected from COVID-19 patients (n = 125), RDs (n = 36), and HDs (n = 60) along with clinical metadata (Fig. 1A and tables S2 to S4).\nFig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.\n(A) Overview of patient cohorts in study, including healthy donors (HD), recovered donors (RD), and COVID-19 patients. (B) Quantification of key clinical parameters in COVID-19 patients. Each dot is a COVID-19 patient; Healthy donor range indicated in green. (C) Spearman correlation and hierarchical clustering of indicated features for COVID-19 patients. (D) Representative flow cytometry plots and (E) frequencies of major immune subsets. (F) Ratio of CD4:CD8 T cells. (G) Spearman correlation of CD4:CD8 ratio and clinical lymphocyte count per patient. Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively. Vertical dashed line indicates clinical threshold for lymphopenia. (H) Spearman correlations of indicated subsets with various clinical features. (E and F) Each dot represents an individual healthy donor (green), RD (blue), or COVID-19 patient (red). Significance determined by unpaired Wilcoxon test with BH correction: *p \u003c 0.05, **p \u003c 0.01, ***p \u003c 0.001, and ****p \u003c 0.0001. COVID-19 patients had a median age of 60 and were significantly older than HD and RD (median age of 41 and 29 respectively), though the age distributions for all three cohorts overlapped (Fig. 1A and fig. S1A). For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2). Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort). Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event. A subset of patients (18%) were immunosuppressed, and 7% and 6% of patients were known to have a diagnosis of cancer or a pre-existing pulmonary condition, respectively. 45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir. Eighteen individuals died in the hospital or within a 30 day follow-up. The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms. Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.\nAs has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome. C reactive protein (CRP) was elevated in over 90% of subjects and LDH and D-dimer were increased in the vast majority, whereas ferritin was above normal in ~75% of COVID-19 patients (Fig. 1B and fig. S1B). Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B). In a subset of patients where it was measured, IL-6 levels were normal in 5 patients, moderately elevated in 5 patients (6-20 pg/ml), and high in 31 patients (21-738 pg/ml) (fig. S1B). Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B). A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33). Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC \u003c1 THO/ul, Fig. 1B). In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).\nTo examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C). This analysis revealed correlations between different COVID-19 disease severity metrics, as well as clinical features or interventions associated with more severe disease (e.g., D-dimer, vasoactive medication) (Fig. 1C and fig. S1C). WBC and PMN also correlated with metrics of disease severity (e.g., APACHE III), as well as with IL-6 levels (Fig. 1C and fig. S1C). Other relationships were also apparent, including correlations between age or mortality and metrics of disease severity and many other correlations between clinical measures of disease, inflammation, and co-morbidities (Fig. 1C and fig. S1C). Thus, COVID-19 patients presented with varied pre-existing comorbidities, complex clinical phenotypes, evidence of inflammation in many patients, and clinically altered leukocyte counts.\nTo begin to interrogate immune responses to acute SARS-CoV2 infection, we compared peripheral blood mononuclear cells (PBMC) of COVID-19 patients, RD, and HD subjects using high dimensional flow cytometry. We first focused on the major lymphocyte populations. B cell and CD3+ T cell frequencies were decreased in COVID-19 patients compared to HD or RD subjects, reflecting clinical lymphopenia, whereas the relative frequency of non-B and non-T cells was correspondingly elevated (Fig. 1, D and E). Although a numerical expansion of a non-B, non-T cell type is possible, loss of lymphocytes likely results in an increase in the relative frequency of this population. This non-B, non-T cell population is also interrogated in more detail in the companion study. Examining only CD3 T cells revealed preferential loss of CD8 T cells compared to CD4 T cells (Fig. 1, F and G, and fig. S1D); this pattern was reflected in absolute numbers estimated from the clinical data, where both CD4 and CD8 T cell counts in COVID-19 patients were lower than the clinical reference range, though the effect was more prominent for CD8 T cells (49/61 subjects below normal) than for CD4 T cells (38/61 subjects below normal) (fig. S1E). These findings are consistent with previous reports of lymphopenia during COVID-19 disease (17–20) but highlight a preferential impact on CD8 T cells.\nWe next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H). Lower WBC counts were associated preferentially with lower frequencies of CD4 and CD8 T cells and increased non-T non-B, but not with B cells (Fig. 1H). These lower T cell counts were associated with clinical markers of inflammation including ferritin, D-dimer, and hsCRP (Fig. 1H), whereas altered B cell frequencies were not. Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations."}

LitCovid-PD-HP

{"project":"LitCovid-PD-HP","denotations":[{"id":"T3","span":{"begin":1857,"end":1868},"obj":"Phenotype"},{"id":"T4","span":{"begin":2629,"end":2651},"obj":"Phenotype"},{"id":"T5","span":{"begin":2675,"end":2695},"obj":"Phenotype"},{"id":"T6","span":{"begin":2807,"end":2813},"obj":"Phenotype"},{"id":"T7","span":{"begin":5674,"end":5685},"obj":"Phenotype"},{"id":"T8","span":{"begin":6565,"end":6576},"obj":"Phenotype"}],"attributes":[{"id":"A3","pred":"hp_id","subj":"T3","obj":"http://purl.obolibrary.org/obo/HP_0001888"},{"id":"A4","pred":"hp_id","subj":"T4","obj":"http://purl.obolibrary.org/obo/HP_0012622"},{"id":"A5","pred":"hp_id","subj":"T5","obj":"http://purl.obolibrary.org/obo/HP_0001907"},{"id":"A6","pred":"hp_id","subj":"T6","obj":"http://purl.obolibrary.org/obo/HP_0002664"},{"id":"A7","pred":"hp_id","subj":"T7","obj":"http://purl.obolibrary.org/obo/HP_0001888"},{"id":"A8","pred":"hp_id","subj":"T8","obj":"http://purl.obolibrary.org/obo/HP_0001888"}],"text":"Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations\nWe conducted an observational study of hospitalized patients with COVID-19 at the University of Pennsylvania (UPenn IRB 808542) that included 149 hospitalized adults with confirmed SARS-CoV2 infection (COVID-19 patients). Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A). Additional samples were obtained from patients who remained hospitalized on day 7. Blood was also collected from non-hospitalized patients who had recovered from documented SARS-CoV2 infection (Recovered Donors (RD); n = 46), as well as from healthy donors (HD; n = 70) (UPenn IRB 834263) (Fig. 1A). Clinical metadata are available from the COVID-19 patients over the course of disease (table S1). Of the total patients and donors, flow cytometry data from PBMCs was collected from COVID-19 patients (n = 125), RDs (n = 36), and HDs (n = 60) along with clinical metadata (Fig. 1A and tables S2 to S4).\nFig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.\n(A) Overview of patient cohorts in study, including healthy donors (HD), recovered donors (RD), and COVID-19 patients. (B) Quantification of key clinical parameters in COVID-19 patients. Each dot is a COVID-19 patient; Healthy donor range indicated in green. (C) Spearman correlation and hierarchical clustering of indicated features for COVID-19 patients. (D) Representative flow cytometry plots and (E) frequencies of major immune subsets. (F) Ratio of CD4:CD8 T cells. (G) Spearman correlation of CD4:CD8 ratio and clinical lymphocyte count per patient. Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively. Vertical dashed line indicates clinical threshold for lymphopenia. (H) Spearman correlations of indicated subsets with various clinical features. (E and F) Each dot represents an individual healthy donor (green), RD (blue), or COVID-19 patient (red). Significance determined by unpaired Wilcoxon test with BH correction: *p \u003c 0.05, **p \u003c 0.01, ***p \u003c 0.001, and ****p \u003c 0.0001. COVID-19 patients had a median age of 60 and were significantly older than HD and RD (median age of 41 and 29 respectively), though the age distributions for all three cohorts overlapped (Fig. 1A and fig. S1A). For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2). Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort). Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event. A subset of patients (18%) were immunosuppressed, and 7% and 6% of patients were known to have a diagnosis of cancer or a pre-existing pulmonary condition, respectively. 45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir. Eighteen individuals died in the hospital or within a 30 day follow-up. The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms. Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.\nAs has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome. C reactive protein (CRP) was elevated in over 90% of subjects and LDH and D-dimer were increased in the vast majority, whereas ferritin was above normal in ~75% of COVID-19 patients (Fig. 1B and fig. S1B). Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B). In a subset of patients where it was measured, IL-6 levels were normal in 5 patients, moderately elevated in 5 patients (6-20 pg/ml), and high in 31 patients (21-738 pg/ml) (fig. S1B). Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B). A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33). Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC \u003c1 THO/ul, Fig. 1B). In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).\nTo examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C). This analysis revealed correlations between different COVID-19 disease severity metrics, as well as clinical features or interventions associated with more severe disease (e.g., D-dimer, vasoactive medication) (Fig. 1C and fig. S1C). WBC and PMN also correlated with metrics of disease severity (e.g., APACHE III), as well as with IL-6 levels (Fig. 1C and fig. S1C). Other relationships were also apparent, including correlations between age or mortality and metrics of disease severity and many other correlations between clinical measures of disease, inflammation, and co-morbidities (Fig. 1C and fig. S1C). Thus, COVID-19 patients presented with varied pre-existing comorbidities, complex clinical phenotypes, evidence of inflammation in many patients, and clinically altered leukocyte counts.\nTo begin to interrogate immune responses to acute SARS-CoV2 infection, we compared peripheral blood mononuclear cells (PBMC) of COVID-19 patients, RD, and HD subjects using high dimensional flow cytometry. We first focused on the major lymphocyte populations. B cell and CD3+ T cell frequencies were decreased in COVID-19 patients compared to HD or RD subjects, reflecting clinical lymphopenia, whereas the relative frequency of non-B and non-T cells was correspondingly elevated (Fig. 1, D and E). Although a numerical expansion of a non-B, non-T cell type is possible, loss of lymphocytes likely results in an increase in the relative frequency of this population. This non-B, non-T cell population is also interrogated in more detail in the companion study. Examining only CD3 T cells revealed preferential loss of CD8 T cells compared to CD4 T cells (Fig. 1, F and G, and fig. S1D); this pattern was reflected in absolute numbers estimated from the clinical data, where both CD4 and CD8 T cell counts in COVID-19 patients were lower than the clinical reference range, though the effect was more prominent for CD8 T cells (49/61 subjects below normal) than for CD4 T cells (38/61 subjects below normal) (fig. S1E). These findings are consistent with previous reports of lymphopenia during COVID-19 disease (17–20) but highlight a preferential impact on CD8 T cells.\nWe next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H). Lower WBC counts were associated preferentially with lower frequencies of CD4 and CD8 T cells and increased non-T non-B, but not with B cells (Fig. 1H). These lower T cell counts were associated with clinical markers of inflammation including ferritin, D-dimer, and hsCRP (Fig. 1H), whereas altered B cell frequencies were not. Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations."}

LitCovid-sentences

2_test

{"project":"2_test","denotations":[{"id":"32669297-32346093-135105194","span":{"begin":3365,"end":3367},"obj":"32346093"},{"id":"32669297-32161940-135105195","span":{"begin":4123,"end":4124},"obj":"32161940"},{"id":"32669297-32242950-135105196","span":{"begin":4126,"end":4128},"obj":"32242950"},{"id":"32669297-32217835-135105197","span":{"begin":6602,"end":6604},"obj":"32217835"},{"id":"32669297-32376308-135105197","span":{"begin":6602,"end":6604},"obj":"32376308"},{"id":"32669297-32296069-135105197","span":{"begin":6602,"end":6604},"obj":"32296069"},{"id":"32669297-31986264-135105197","span":{"begin":6602,"end":6604},"obj":"31986264"}],"text":"Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations\nWe conducted an observational study of hospitalized patients with COVID-19 at the University of Pennsylvania (UPenn IRB 808542) that included 149 hospitalized adults with confirmed SARS-CoV2 infection (COVID-19 patients). Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A). Additional samples were obtained from patients who remained hospitalized on day 7. Blood was also collected from non-hospitalized patients who had recovered from documented SARS-CoV2 infection (Recovered Donors (RD); n = 46), as well as from healthy donors (HD; n = 70) (UPenn IRB 834263) (Fig. 1A). Clinical metadata are available from the COVID-19 patients over the course of disease (table S1). Of the total patients and donors, flow cytometry data from PBMCs was collected from COVID-19 patients (n = 125), RDs (n = 36), and HDs (n = 60) along with clinical metadata (Fig. 1A and tables S2 to S4).\nFig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.\n(A) Overview of patient cohorts in study, including healthy donors (HD), recovered donors (RD), and COVID-19 patients. (B) Quantification of key clinical parameters in COVID-19 patients. Each dot is a COVID-19 patient; Healthy donor range indicated in green. (C) Spearman correlation and hierarchical clustering of indicated features for COVID-19 patients. (D) Representative flow cytometry plots and (E) frequencies of major immune subsets. (F) Ratio of CD4:CD8 T cells. (G) Spearman correlation of CD4:CD8 ratio and clinical lymphocyte count per patient. Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively. Vertical dashed line indicates clinical threshold for lymphopenia. (H) Spearman correlations of indicated subsets with various clinical features. (E and F) Each dot represents an individual healthy donor (green), RD (blue), or COVID-19 patient (red). Significance determined by unpaired Wilcoxon test with BH correction: *p \u003c 0.05, **p \u003c 0.01, ***p \u003c 0.001, and ****p \u003c 0.0001. COVID-19 patients had a median age of 60 and were significantly older than HD and RD (median age of 41 and 29 respectively), though the age distributions for all three cohorts overlapped (Fig. 1A and fig. S1A). For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2). Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort). Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event. A subset of patients (18%) were immunosuppressed, and 7% and 6% of patients were known to have a diagnosis of cancer or a pre-existing pulmonary condition, respectively. 45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir. Eighteen individuals died in the hospital or within a 30 day follow-up. The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms. Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.\nAs has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome. C reactive protein (CRP) was elevated in over 90% of subjects and LDH and D-dimer were increased in the vast majority, whereas ferritin was above normal in ~75% of COVID-19 patients (Fig. 1B and fig. S1B). Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B). In a subset of patients where it was measured, IL-6 levels were normal in 5 patients, moderately elevated in 5 patients (6-20 pg/ml), and high in 31 patients (21-738 pg/ml) (fig. S1B). Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B). A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33). Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC \u003c1 THO/ul, Fig. 1B). In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).\nTo examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C). This analysis revealed correlations between different COVID-19 disease severity metrics, as well as clinical features or interventions associated with more severe disease (e.g., D-dimer, vasoactive medication) (Fig. 1C and fig. S1C). WBC and PMN also correlated with metrics of disease severity (e.g., APACHE III), as well as with IL-6 levels (Fig. 1C and fig. S1C). Other relationships were also apparent, including correlations between age or mortality and metrics of disease severity and many other correlations between clinical measures of disease, inflammation, and co-morbidities (Fig. 1C and fig. S1C). Thus, COVID-19 patients presented with varied pre-existing comorbidities, complex clinical phenotypes, evidence of inflammation in many patients, and clinically altered leukocyte counts.\nTo begin to interrogate immune responses to acute SARS-CoV2 infection, we compared peripheral blood mononuclear cells (PBMC) of COVID-19 patients, RD, and HD subjects using high dimensional flow cytometry. We first focused on the major lymphocyte populations. B cell and CD3+ T cell frequencies were decreased in COVID-19 patients compared to HD or RD subjects, reflecting clinical lymphopenia, whereas the relative frequency of non-B and non-T cells was correspondingly elevated (Fig. 1, D and E). Although a numerical expansion of a non-B, non-T cell type is possible, loss of lymphocytes likely results in an increase in the relative frequency of this population. This non-B, non-T cell population is also interrogated in more detail in the companion study. Examining only CD3 T cells revealed preferential loss of CD8 T cells compared to CD4 T cells (Fig. 1, F and G, and fig. S1D); this pattern was reflected in absolute numbers estimated from the clinical data, where both CD4 and CD8 T cell counts in COVID-19 patients were lower than the clinical reference range, though the effect was more prominent for CD8 T cells (49/61 subjects below normal) than for CD4 T cells (38/61 subjects below normal) (fig. S1E). These findings are consistent with previous reports of lymphopenia during COVID-19 disease (17–20) but highlight a preferential impact on CD8 T cells.\nWe next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H). Lower WBC counts were associated preferentially with lower frequencies of CD4 and CD8 T cells and increased non-T non-B, but not with B cells (Fig. 1H). These lower T cell counts were associated with clinical markers of inflammation including ferritin, D-dimer, and hsCRP (Fig. 1H), whereas altered B cell frequencies were not. Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations."}

PMC:7402624 / 4746-11994 JSONTXT

Annnotations TAB JSON ListView MergeView

PMC:7402624 / 4746-11994 JSON TXT