PubAnnotation

Id	Subject	Object	Predicate	Lexical cue
T11	0-96	Sentence	denotes	The COVID-19 pandemic has to date caused >7 million infections resulting in over 400,000 deaths.
T12	97-289	Sentence	denotes	Following infection with SARS-CoV2, COVID-19 patients can experience mild or even asymptomatic disease, or can present with severe disease requiring hospitalization and mechanical ventilation.
T13	290-340	Sentence	denotes	The case fatality rate can be as high as ~10% (1).
T14	341-463	Sentence	denotes	Some severe COVID-19 patients display an acute respiratory distress syndrome (ARDS), reflecting severe respiratory damage.
T15	464-604	Sentence	denotes	In acute respiratory viral infections, pathology can be mediated by the virus directly, by an overaggressive immune response, or both (2–4).
T16	605-793	Sentence	denotes	However, in severe COVID-19 disease, the characteristics of, and role for the immune response, as well as how these responses relate to clinical disease features, remain poorly understood.
T17	794-1050	Sentence	denotes	SARS-CoV2 antigen-specific T cells have been identified in the central memory (CM), effector memory (EM), and CD45RA+ effector memory (EMRA) compartments (5) but the characteristics of these cells and their role in infection or pathogenesis remain unclear.
T18	1051-1320	Sentence	denotes	Recovered subjects more often have evidence of virus-specific CD4 T cell responses than virus-specific CD8 T cell responses, though pre-existing CD4 T cell responses to other coronaviruses also are found in a subset of subjects in the absence of SARS-CoV2 exposure (6).
T19	1321-1538	Sentence	denotes	Inflammatory responses have been reported, including increases in IL-6- or GM-CSF-producing CD4 T cells in the blood (7) or decreases in immunoregulatory subsets such as regulatory T cells (Treg) or ɣδ T cells (8–11).
T20	1539-1750	Sentence	denotes	T cell exhaustion (12, 13) or increased inhibitory receptor expression on peripheral T cells has also been reported (7, 14), though these inhibitory receptors are also increased following T cell activation (15).
T21	1751-1990	Sentence	denotes	Moreover, although there is evidence of T cell activation in COVID-19 patients (16), some studies have found decreases in polyfunctionality (12, 17) or cytotoxicity (12); however, these changes have not been observed in other studies (13).
T22	1991-2104	Sentence	denotes	Furthermore, how this activation should be viewed in the context of COVID-19 lymphopenia (18–20) remains unclear.
T23	2105-2224	Sentence	denotes	Most patients seroconvert within 7-14 days of infection and increased plasmablasts (PB) have been reported (16, 21–23).
T24	2225-2312	Sentence	denotes	However, the role of humoral responses in the pathogenesis of COVID-19 remains unclear.
T25	2313-2463	Sentence	denotes	Whereas IgG levels reportedly drop slightly ~8 weeks after symptom onset (24, 25), recovered patients maintain high Spike-specific IgG titers (6, 26).
T26	2464-2545	Sentence	denotes	IgA levels also can remain high and may correlate with disease severity (25, 27).
T27	2546-2648	Sentence	denotes	Furthermore, neutralizing antibodies can control SARS-CoV2 infection in vitro and in vivo (4, 28, 29).
T28	2649-2747	Sentence	denotes	Indeed, convalescent plasma containing neutralizing antibodies can improve clinical symptoms (30).
T29	2748-2947	Sentence	denotes	However, not all patients that recover from COVID-19 have detectable neutralizing antibodies (6, 26), suggesting a complex relationship between humoral and cellular response in COVID-19 pathogenesis.
T30	2948-3140	Sentence	denotes	Taken together, this previous work provokes questions about the potential diversity of immune responses to SARS-CoV2 and the relationship of this immune response diversity to clinical disease.
T31	3141-3268	Sentence	denotes	However, many studies describe small cohorts or even single patients, limiting a comprehensive interrogation of this diversity.
T32	3269-3448	Sentence	denotes	The relationship of different immune response features to clinical parameters, as well as the changes in immune responses and clinical disease over time, remain poorly understood.
T33	3449-3704	Sentence	denotes	Because potential therapeutics for COVID-19 patients include approaches to inhibit, activate, or otherwise modulate immune function, it is essential to define the immune response characteristics related to disease features in well-defined patient cohorts.
T34	3706-3805	Sentence	denotes	Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations
T35	3806-4027	Sentence	denotes	We 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).
T36	4028-4112	Sentence	denotes	Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A).
T37	4113-4195	Sentence	denotes	Additional samples were obtained from patients who remained hospitalized on day 7.
T38	4196-4412	Sentence	denotes	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).
T39	4413-4510	Sentence	denotes	Clinical metadata are available from the COVID-19 patients over the course of disease (table S1).
T40	4511-4714	Sentence	denotes	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).
T41	4715-4834	Sentence	denotes	Fig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.
T42	4835-5021	Sentence	denotes	(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.
T43	5022-5391	Sentence	denotes	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.
T44	5392-5508	Sentence	denotes	Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively.
T45	5509-5759	Sentence	denotes	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).
T46	5760-5886	Sentence	denotes	Significance determined by unpaired Wilcoxon test with BH correction: p < 0.05, p < 0.01, p < 0.001, and **p < 0.0001.
T47	5887-6097	Sentence	denotes	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).
T48	6098-6195	Sentence	denotes	For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2).
T49	6196-6297	Sentence	denotes	Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort).
T50	6298-6402	Sentence	denotes	Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event.
T51	6403-6572	Sentence	denotes	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.
T52	6573-6680	Sentence	denotes	45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir.
T53	6681-6752	Sentence	denotes	Eighteen individuals died in the hospital or within a 30 day follow-up.
T54	6753-6867	Sentence	denotes	The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms.
T55	6868-7020	Sentence	denotes	Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.
T56	7021-7145	Sentence	denotes	As has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome.
T57	7146-7351	Sentence	denotes	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).
T58	7352-7429	Sentence	denotes	Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B).
T59	7430-7614	Sentence	denotes	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).
T60	7615-7751	Sentence	denotes	Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B).
T61	7752-7866	Sentence	denotes	A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33).
T62	7867-7977	Sentence	denotes	Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC <1 THO/ul, Fig. 1B).
T63	7978-8075	Sentence	denotes	In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).
T64	8076-8200	Sentence	denotes	To examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C).
T65	8201-8434	Sentence	denotes	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).
T66	8435-8567	Sentence	denotes	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).
T67	8568-8810	Sentence	denotes	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).
T68	8811-8997	Sentence	denotes	Thus, COVID-19 patients presented with varied pre-existing comorbidities, complex clinical phenotypes, evidence of inflammation in many patients, and clinically altered leukocyte counts.
T69	8998-9203	Sentence	denotes	To 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.
T70	9204-9257	Sentence	denotes	We first focused on the major lymphocyte populations.
T71	9258-9496	Sentence	denotes	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).
T72	9497-9664	Sentence	denotes	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.
T73	9665-9758	Sentence	denotes	This non-B, non-T cell population is also interrogated in more detail in the companion study.
T74	9759-10215	Sentence	denotes	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).
T75	10216-10366	Sentence	denotes	These findings are consistent with previous reports of lymphopenia during COVID-19 disease (17–20) but highlight a preferential impact on CD8 T cells.
T76	10367-10471	Sentence	denotes	We next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H).
T77	10472-10624	Sentence	denotes	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).
T78	10625-10799	Sentence	denotes	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.
T79	10800-10954	Sentence	denotes	Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations.
T80	10956-11040	Sentence	denotes	SARS-CoV2 infection is associated with CD8 T cell activation in a subset of patients
T81	11041-11188	Sentence	denotes	We next applied high-dimensional flow cytometric analysis to further investigate lymphocyte activation and differentiation during COVID-19 disease.
T82	11189-11449	Sentence	denotes	We first used principal component analysis (PCA) to examine the general distribution of immune profiles from COVID-19 patients (n = 118), RD (n = 60), and HD (n = 36) using 193 immune parameters identified by high-dimensional flow cytometry (tables S5 and S6).
T83	11450-11563	Sentence	denotes	COVID-19 patients clearly segregated from RD and HD in PCA space, whereas RD and HD largely overlapped (Fig. 2A).
T84	11564-11639	Sentence	denotes	We investigated the immune features driving this COVID-19 immune signature.
T85	11640-11715	Sentence	denotes	Given their role in response to viral infection, we focused on CD8 T cells.
T86	11716-12065	Sentence	denotes	Six major CD8 T cell populations were examined using the combination of CD45RA, CD27, CCR7, and CD95 cell surface markers to define naïve (CD45RA+CD27+CCR7+CD95−), central memory (CD45RA−CD27+CCR7+ [CM]), effector memory (CD45RA−CD27+CCR7− [EM1], CD45RA−CD27−CCR7+ [EM2], CD45RA−CD27−CCR7− [EM3]), and EMRA (CD45RA+CD27−CCR7−) (Fig. 2B) CD8 T cells.
T87	12066-12186	Sentence	denotes	Among the CD8 T cell populations, there was an increase in the EM2 and EMRA populations and a decrease in EM1 (Fig. 2C).
T88	12187-12289	Sentence	denotes	Furthermore, the frequency of CD39+ cells was increased in COVID-19 patients compared to HD (Fig. 2D).
T89	12290-12433	Sentence	denotes	Although the frequency of PD-1+ cells was not different in the total CD8 population (Fig. 2D), it was increased for both CM and EM1 (fig. S2A).
T90	12434-12549	Sentence	denotes	Finally, all major CD8 T cell naive/memory populations in RD were comparable to HD (Fig. 2, C and D, and fig. S2A).
T91	12550-12676	Sentence	denotes	Fig. 2 CD8 T cell subset skewing and activation patterns in COVID-19 patients and potential links to T cell driven cytokines.
T92	12677-12930	Sentence	denotes	(A) Principle Component Analysis (PCA) of aggregated flow cytometry data. (B) Representative flow cytometry plots of the gating strategy for CD8 T cell subsets. (C) Frequencies of CD8 T cell subsets as indicated. (D) Frequencies of PD1+ and CD39+ cells.
T93	12931-13564	Sentence	denotes	Frequencies of (E) KI67+ and (F) HLA-DR+CD38+ cells and representative flow cytometry plots; green line at upper decile of HD. (G) (Top) Global viSNE projection of non-naïve CD8 T cells for all subjects pooled, non-naïve CD8 T cells from healthy donor (HD), recovered donor (RD), and COVID-19 patients concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (H) viSNE projection of non-naïve CD8 T cell clusters identified by FlowSOM clustering. (I) Mean fluorescence intensity (MFI) as indicated, column-scaled z-score. (J) Percentage of non-naive CD8 T cells from each cohort in each FlowSOM cluster.
T94	13565-13717	Sentence	denotes	Boxes represent IQR. (C, D, E, F, J) Each dot represents an individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 patient (red).
T95	13718-13844	Sentence	denotes	Significance determined by unpaired Wilcoxon test with BH correction: p < 0.05, p < 0.01, p < 0.001, and **p < 0.0001.
T96	13845-14001	Sentence	denotes	Most acute viral infections induce proliferation and activation of CD8 T cells detectable by increases in KI67 or co-expression of CD38 and HLA-DR (34, 35).
T97	14002-14148	Sentence	denotes	There was a significant increase in KI67+ and also HLA-DR+CD38+ non-naïve CD8 T cells in COVID-19 patients compared to HD or RD (Fig. 2, E and F).
T98	14149-14303	Sentence	denotes	In COVID-19 patients, KI67+ CD8 T cells were increased compared to HD and RD across all subsets of non-naïve CD8 T cells, including CM and EM1 (fig. S2B).
T99	14304-14496	Sentence	denotes	These data indicate broad T cell activation, potentially driven by bystander activation and/or homeostatic proliferation in addition to antigen-driven activation of virus-specific CD8 T cells.
T100	14497-14663	Sentence	denotes	This activation phenotype was confirmed by HLA-DR and CD38 co-expression that was significantly increased for all non-naïve CD8 T cell subsets (Fig. 2F and fig. S2C).
T101	14664-14757	Sentence	denotes	However, the magnitude of the KI67+ or CD38+HLA-DR+ CD8 T cells varied widely in this cohort.
T102	14758-14862	Sentence	denotes	The frequency of KI67+ CD8 T cells correlated with the frequency of CD38+HLA-DR+ CD8 T cells (fig. S2D).
T103	14863-15108	Sentence	denotes	However, the frequency of CD38+HLA-DR+, but not KI67+ CD8 T cells, was elevated in COVID-19 patients who had concomitant infection with another microbe but was not impacted by pre-existing immunosuppression or treatment with steroids (fig. S2E).
T104	15109-15374	Sentence	denotes	Moreover, these changes in CD8 T cell subsets in COVID-19 patients did not show clear correlations with individual metrics of clinical disease such as hsCRP or D-dimer (fig. S2E), although the frequency of KI67+ CD8 T cells associated with IL-6 and ferritin levels.
T105	15375-15534	Sentence	denotes	Although CD8 T cell activation was common, ~20% of patients had no increase in KI67+ or CD38+HLA-DR+ CD8 T cells above the level found in HD (Fig. 2, E and F).
T106	15535-15760	Sentence	denotes	Thus, although robust CD8 T cell activation was a clear characteristic of many hospitalized COVID-19 patients, a substantial fraction of patients had little evidence of CD8 T cell activation in the blood compared to controls.
T107	15761-15867	Sentence	denotes	To gain more insights, we applied global high-dimensional mapping of the 27-parameter flow cytometry data.
T108	15868-16003	Sentence	denotes	A tSNE representation of the data highlighted key regions of non-naïve CD8 T cells found preferentially in COVID-19 patients (Fig. 2G).
T109	16004-16284	Sentence	denotes	A major region of this tSNE map present in COVID-19 patients, but not HD or RD, were CD8 T cells that enriched for expression of CD38, HLA-DR, KI67, CD39, and PD1 (Fig. 2G), highlighting the co-expression of these activation markers with other features including CD95 (i.e., FAS).
T110	16285-16471	Sentence	denotes	Notably, although non-naïve CD8 T cells from RD were highly similar to those from HD, subtle differences existed, including in the lower region highlighted by T-bet and CX3CR1 (Fig. 2G).
T111	16472-16693	Sentence	denotes	To further define and quantify these differences between COVID-19 patients and controls, we performed FlowSOM clustering (Fig. 2H) and compared expression of fourteen CD8 T cell markers to identify each cluster (Fig. 2I).
T112	16694-16933	Sentence	denotes	This approach identified an increase in cells in several clusters including Clusters 1, 2, and 5 in COVID-19 patients, reflecting CD45RA+CD27−CCR7− TEMRA-like populations that expressed CX3CR1 and varying levels of T-bet (Fig. 2, I and J).
T113	16934-17098	Sentence	denotes	Clusters 12 and 14 contained CD27+HLA-DR+CD38+KI67+PD-1+ activated, proliferating cells and were more prevalent in COVID-19 disease (Fig. 2, I and J, and fig. S2F).
T114	17099-17259	Sentence	denotes	In contrast, the central Eomes+CD45RA−CD27+CCR7− EM1-like Cluster 6 and T-bethiCX3CR1+ Cluster 11 were decreased compared to HD (Fig. 2, I and J, and fig. S2F).
T115	17260-17408	Sentence	denotes	Thus, CD8 T cell responses in COVID-19 patients were characterized by populations of activated, proliferating CD8 T cells in a subgroup of patients.
T116	17410-17520	Sentence	denotes	SARS-CoV2 infection is associated with heterogeneous CD4 T cell responses and activation of CD4 T cell subsets
T117	17521-17688	Sentence	denotes	We next examined six well-defined CD4 T cell subsets as above for the CD8 T cells, including naïve, effector memory (EM1,2,3), central memory (CM), and EMRA (Fig. 3A).
T118	17689-18023	Sentence	denotes	Given the potential role of antibodies in the response to SARS-CoV2 (27, 29), we also analyzed circulating Tfh (CD45RA−PD1+CXCR5+ [cTfh] (36)) and activated circulating Tfh (CD38+ICOS+ [activated cTfh]), the latter of which may be more reflective of recent antigen encounter and emigration from the germinal center (37, 38) (Fig. 3A).
T119	18024-18144	Sentence	denotes	These analyses revealed a relative loss of naïve CD4 T cells compared to controls, but increased EM2 and EMRA (Fig. 3B).
T120	18145-18333	Sentence	denotes	The frequency of activated but not total cTfh was statistically increased in COVID-19 patients compared to HD, though this effect appeared to be driven by a subgroup of patients (Fig. 3B).
T121	18334-18495	Sentence	denotes	It is worth noting that activated cTfh frequencies were also higher in RD compared to HD (Fig. 3B), perhaps reflecting residual COVID-19 responses in that group.
T122	18496-18680	Sentence	denotes	Frequencies of KI67+ or CD38+HLA-DR+ non-naïve CD4 T cells were increased in COVID-19 patients (Fig. 3, C and E); however, this change was not equivalent across all CD4 T cell subsets.
T123	18681-18841	Sentence	denotes	The most substantial increases in both KI67+ and CD38+HLA-DR+ cells were found in the effector memory populations (EM, EM2, EM3) and in cTfh (fig. S3, A and B).
T124	18842-18924	Sentence	denotes	Although some subjects had increased activation of EMRA, this was less pronounced.
T125	18925-19034	Sentence	denotes	In contrast, PD1 expression was increased in all other non-naïve populations compared to HD or RD (fig. S3C).
T126	19035-19165	Sentence	denotes	Co-expression of CD38 and HLA-DR by non-naïve CD4 T cells correlated with the frequency of KI67+ non-naïve CD4 T cells (fig. S3D).
T127	19166-19303	Sentence	denotes	Moreover, the frequency of total non-naïve CD4 T cells that were CD38+HLA-DR+ correlated with the frequency of activated cTfh (fig. S3E).
T128	19304-19414	Sentence	denotes	In general, the activation of CD4 T cells was correlated with the activation of CD8 T cells (Fig. 3, D and F).
T129	19415-19646	Sentence	denotes	However, whereas ~2/3 of patients had KI67+ non-naïve CD4 or CD8 T cell frequencies above controls, ~1/3 of the COVID-19 patients had no increase in frequency of KI67+ CD4 or CD8 T cells above that observed in HD (Fig. 3, D and F).
T130	19647-19881	Sentence	denotes	Moreover, although most patients had similar proportions of activated CD4 T cells compared to CD8 T cells, there was a subgroup of patients that had disproportionate activation of CD4 T cells compared to CD8 T cells (Fig. 3, D and F).
T131	19882-20078	Sentence	denotes	KI67+ and CD38+HLA-DR+ non-naïve CD4 T cell frequencies correlated with ferritin and with APACHE III score (fig. S3F), suggesting a relationship between CD4 T cell activation and disease severity.
T132	20079-20227	Sentence	denotes	Immunosuppression did not impact CD4 T cell activation; however, early steroid administration was weakly associated with CD4 T cell KI67 (fig. S3F).
T133	20228-20525	Sentence	denotes	Together, these data highlight T cell activation in COVID-19 patients similar to what has been observed in other acute infections or vaccinations (37, 39, 40), but also identify patients with high, low, or essentially no T cell response based on KI67+ or CD38+HLA-DR+ compared to control subjects.
T134	20526-20633	Sentence	denotes	Fig. 3 CD4 T cell activation in a subset of COVID-19 patients associates with distinct CD4 T cell subsets.
T135	20634-20855	Sentence	denotes	(A) Representative flow cytometry plots of the gating strategy for CD4 T cell subsets. (B) Frequencies of CD4 T cell subsets as indicated. (C) Frequencies of KI67+ cells; green line at upper decile of healthy donors (HD).
T136	20856-21098	Sentence	denotes	Representative flow cytometry plots. (D) KI67+ cells from non-naïve CD4 T cells versus non-naïve CD8 T cells, Spearman correlation of COVID-19 patients. (E) Frequencies of HLA-DR+CD38+ cells; green line at upper decile of healthy donors (HD).
T137	21099-21723	Sentence	denotes	Representative flow cytometry plots. (F) HLA-DR+CD38+ cells from non-naïve CD4 versus non-naïve CD8 T cells, Spearman correlation of COVID-19 patients. (G) (Top) Global viSNE projection of non-naïve CD4 T cells for all subjects pooled, non-naïve CD4 T cells from HD, RD, and COVID-19 patients concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (H) viSNE projection of non-naïve CD4 T cell clusters identified by FlowSOM clustering. (I) Mean fluorescence intensity (MFI) as indicated, column-scaled z-score. (J) Percentage of non-naïve CD4 T cells from each cohort in each FlowSOM cluster.
T138	21724-21873	Sentence	denotes	Boxes represent IQR. (B, C, E, J) Each dot represents an individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 patient (red).
T139	21874-22000	Sentence	denotes	Significance determined by unpaired Wilcoxon test with BH correction: p < 0.05, p < 0.01, p < 0.001, and **p < 0.0001.
T140	22001-22218	Sentence	denotes	Projecting the global CD4 T cell differentiation patterns into the high-dimensional tSNE space again identified major alterations in the CD4 T cell response during COVID-19 infection compared to HDs and RDs (Fig. 3G).
T141	22219-22401	Sentence	denotes	In COVID-19 infection, there was a notable increase in density in tSNE regions that mapped to expression of CD38, HLA-DR, PD1, CD39, KI67, and CD95 (Fig. 3G), similar to CD8 T cells.
T142	22402-22516	Sentence	denotes	To gain more insight into these CD4 T cell changes, we again used a FlowSOM clustering approach (Fig. 3, H and I).
T143	22517-22801	Sentence	denotes	This analysis identified an increase in Clusters 13 and 14 in COVID-19 patients compared to HD and RD that represent populations expressing HLA-DR, CD38, PD1, KI67 and CD95, as well as Cluster 15 that contained Tbet+CX3CR1+ “effector-like” CD4 T cells (Fig. 3, I and J, and fig. S3G).
T144	22802-22957	Sentence	denotes	In contrast, this clustering approach identified reduction in CXCR5+ cTfh-like cells (Clusters 2, 3) in COVID-19 subjects compared to HD (Fig. 3, I and H).
T145	22958-23114	Sentence	denotes	Taken together, this multidimensional analysis revealed distinct populations of activated/proliferating CD4 T cells that were enriched in COVID-19 patients.
T146	23115-23373	Sentence	denotes	A key feature of COVID-19 disease is thought to be an inflammatory response that, at least in some patients, is linked to clinical disease manifestation (2, 4) and high levels of chemokines/cytokines, including IL-1RA, IL-6, IL-8, IL-10, and CXCL10 (11, 41).
T147	23374-23629	Sentence	denotes	To investigate the potential connection of inflammatory pathways to T cell responses, we performed 31-plex Luminex analysis on paired plasma and culture supernatants of anti-CD3/anti-CD28 stimulated PBMC from a subset of COVID-19 patients and HD controls.
T148	23630-23794	Sentence	denotes	Due to biosafety restrictions, only eight COVID-19 patient blood samples that were confirmed SARS-CoV2 RNA negative in the blood by PCR could be studied (fig. S4A).
T149	23795-23968	Sentence	denotes	Half of these COVID-19 patients had plasma CXCL10 concentrations that were ~15 fold higher than HD controls, whereas the remainder showed only a limited increase (fig. S4B).
T150	23969-24027	Sentence	denotes	CXCL9, CCL2, and IL-1RA were also significantly increased.
T151	24028-24148	Sentence	denotes	In contrast, chemokines involved in the recruitment of eosinophils (eotaxin) or activated T cells (CCL5) were decreased.
T152	24149-24378	Sentence	denotes	IL-6 was not elevated in this group of patients, in contrast to the subset of individuals tested clinically (fig. S1B), potentially because IL-6 was measured in the hospital setting often when systemic inflammation was suspected.
T153	24379-24646	Sentence	denotes	Following stimulation in vitro, PBMC from COVID-19 patients produced more CCL2, CXCL10, eotaxin, and IL-1RA than HD (fig. S4, C and D) and concentrations of CXCL10 and CCL2 correlated between the matched supernatant from stimulated PBMC and plasma samples (fig. S4E).
T154	24647-24779	Sentence	denotes	Finally, we investigated whether CD8 T cells from COVID-19 subjects were capable of producing IFNɣ following polyclonal stimulation.
T155	24780-25001	Sentence	denotes	Following ɑCD3+ɑCD28 stimulation, similar proportions of CD8 T cells from COVID-19 patients and HD controls produced IFNɣ, suggesting that PBMC from COVID-19 patients were responsive to TCR crosslinking (fig. S4, F to H).
T156	25002-25159	Sentence	denotes	The ability of T cells to produce IFNɣ following stimulation occurred in patients with increases in KI67 as well as patients with low KI67 (fig. S4, F to H).
T157	25160-25331	Sentence	denotes	Taken together, these data support the notion that a subgroup of COVID-19 patients has elevated systemic cytokines and chemokines, including myeloid recruiting chemokines.
T158	25333-25451	Sentence	denotes	COVID-19 infection is associated with increased frequencies of plasmablasts and proliferation of memory B cell subsets
T159	25452-25512	Sentence	denotes	B cell subpopulations were also altered in COVID-19 disease.
T160	25513-25727	Sentence	denotes	Whereas naïve B cell frequencies were similar in COVID-19 patients and RD or HD, the frequencies of class-switched (IgD−CD27+) and not-class-switched (IgD+CD27+) memory B cells were significantly reduced (Fig. 4A).
T161	25728-25839	Sentence	denotes	Conversely, frequencies of CD27−IgD− B cells and CD27+CD38+ PB were often robustly increased (Fig. 4, A and B).
T162	25840-25977	Sentence	denotes	In some cases, PB represented >30% of circulating B cells, similar to levels observed in acute Ebola or Dengue virus infections (42, 43).
T163	25978-26131	Sentence	denotes	However, these PB responses were only observed in ~2/3 of patients, with the remaining patients displaying PB frequencies similar to HD and RD (Fig. 4B).
T164	26132-26263	Sentence	denotes	KI67 expression was markedly elevated in all B cell subpopulations in COVID-19 patients compared to either control group (Fig. 4C).
T165	26264-26381	Sentence	denotes	This observation suggests a role for an antigen-driven response to infection and/or lymphopenia-driven proliferation.
T166	26382-26476	Sentence	denotes	Higher KI67 in PB may reflect recent generation in the COVID-19 patients compared to HD or RD.
T167	26477-26570	Sentence	denotes	CXCR5 expression was also reduced on all major B cell subsets in COVID-19 patients (Fig. 4D).
T168	26571-26691	Sentence	denotes	Loss of CXCR5 was not specific to B cells, however, as expression was also decreased on non-naïve CD4 T cells (Fig. 4E).
T169	26692-26914	Sentence	denotes	Changes in the B cell subsets were not associated with co-infection, immune suppression, or treatment with steroids or other clinical features, though a possible negative association of IL-6 and PB was revealed (fig. S5A).
T170	26915-27041	Sentence	denotes	These observations suggest that the B cell response phenotype of COVID-19 disease was not simply due to systemic inflammation.
T171	27042-27172	Sentence	denotes	Fig. 4 Deep profiling of COVID-19 patient B cell populations reveals robust plasmablast populations and other B cell alterations.
T172	27173-28450	Sentence	denotes	(A) Gating strategy and frequencies of non-PB B cell subsets. (B) Representative flow cytometry plots and frequencies of PB; green line at upper decile of HD. (C) Representative flow cytometry plots and frequencies of KI67+ B cells. (D) (Left) Representative histograms of CXCR5 expression and (right) CXCR5 GMFI of B cell subsets. (E) CXCR5 GMFI of non-naïve CD4 T cells and cTfh. (F) Spearman correlation between PB and activated cTfh. (G) Spearman correlation between PB and anti-SARS-CoV2 IgG. (H and I) Spearman correlation between activated cTfh and anti-SARS-CoV2 (H) IgM and (I) IgG. (J) (Top) Global viSNE projection of B cells for all subjects pooled, with B cell populations of each cohort concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (K) Hierarchical clustering of Earth Mover’s Distance (EMD) using Pearson correlation, calculated pairwise for B cell populations for all subjects; row-scaled z-score. (L) Percentage of cohort in each EMD group. (M) Global viSNE projection of B cells for all subjects pooled, with EMD groups 1-3 concatenated and overlaid. (N) B cell clusters identified by FlowSOM clustering. (O) MFI as indicated; column-scaled z-score. (P) Percentage of B cells from each cohort in each FlowSOM cluster.
T173	28451-28791	Sentence	denotes	Boxes represent IQR. (A to F, P) Dots represent individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 (red) subjects. (A to E, P) Significance determined by unpaired Wilcoxon test with BH correction: p < 0.05, p < 0.01, p < 0.001, and **p < 0.0001. (GtoI) Black horizontal line represents positive threshold.
T174	28792-28930	Sentence	denotes	During acute viral infections or vaccination, PB responses are transiently detectable in the blood and correlate with cTfh responses (40).
T175	28931-29104	Sentence	denotes	Comparing the frequency of PB to the frequency of total cTfh or activated cTfh, however, revealed a weak correlation only with activated cTfh (Fig. 4F and fig. S5, B and C).
T176	29105-29336	Sentence	denotes	Furthermore, some patients had robust activated cTfh responses but PB frequencies similar to controls, whereas other patients with robust PB responses had relatively low frequencies of activated cTfh (Fig. 4F and fig. S5, B and C).
T177	29337-29595	Sentence	denotes	However, there was also an association between PB frequency and CD38+HLA-DR+ or KI67+ CD4 T cells that might reflect a role for non-CXCR5+ CD4 T cell help (fig. S5D), but such a relationship did not exist for the equivalent CD8 T cell populations (fig. S5E).
T178	29596-29796	Sentence	denotes	Although ~70% of COVID-19 patients analyzed made antibodies against SARS-CoV2 spike protein (79/111 IgG; 77/115 IgM (44)), antibody levels did not correlate with PB frequencies (Fig. 4G and fig. S5F).
T179	29797-29920	Sentence	denotes	The occasional lack of antibody did not appear to be related to immunosuppression in a small number of patients (fig. S5G).
T180	29921-30160	Sentence	denotes	The lack of PB correlation with antibody suggests that a proportion of these large PB responses were: i) generated against SARS-CoV2 antigens other than the spike protein or ii) inflammation-driven and perhaps non-specific or low affinity.
T181	30161-30401	Sentence	denotes	Notably, anti-SARS-CoV2 IgG and IgM levels correlated with the activated, but not total, cTfh response, suggesting that at least a proportion of cTfh were providing SARS-CoV2-specific help to B cells (Fig. 4, H and I, and fig. S5, H and I).
T182	30402-30585	Sentence	denotes	Although defining the precise specificity of the robust PB populations will require future studies, these data suggest that at least some of the PB response is specific for SARS-CoV2.
T183	30586-30820	Sentence	denotes	Projecting the flow cytometry data for B cells from HD, RD, and COVID-19 patients in tSNE space revealed a distinct picture of B cell populations in COVID-19 compared to controls, whereas RD and HD were similar (Fig. 4J and fig. S5J).
T184	30821-30943	Sentence	denotes	The COVID-19 patient B cell phenotype was dominated by loss of CXCR5 and IgD compared to B cells from HD and RD (Fig. 4J).
T185	30944-31071	Sentence	denotes	Moreover, the robust PB response was apparent in the upper right section, highlighted by CD27, CD38, CD138, and KI67 (Fig. 4J).
T186	31072-31215	Sentence	denotes	The expression of KI67 and CD95 in these CD27+CD38+CD138+ PB (Fig. 4J) could suggest recent generation and/or emigration from germinal centers.
T187	31216-31349	Sentence	denotes	We next asked whether there were different groups of COVID-19 patients (or HD and RD) with global differences in the B cell response.
T188	31350-31582	Sentence	denotes	We used Earth Movers Distance (EMD) (45) to calculate similarities between the probability distributions within the tSNE map (Fig. 4J) and clustered so that individuals with the most similar distributions grouped together (Fig. 4K).
T189	31583-31736	Sentence	denotes	The majority of COVID-19 patients fell into two distinct groups (EMD Groups 1 and 3, Fig. 4L), suggesting two major “immunotypes” of the B cell response.
T190	31737-31972	Sentence	denotes	The remainder of the COVID-19 patients (~25%) clustered with the majority of the HD and all of the RD controls, supporting the observation that some individuals had limited evidence of response to infection in their B cell compartment.
T191	31973-32185	Sentence	denotes	To identify the population differences between HD, RD and COVID-19 patients, we performed FlowSOM clustering on the tSNE map, and also overlaid each individual EMD group onto this same tSNE map (Fig. 4, M and N).
T192	32186-32418	Sentence	denotes	EMD Group 2 containing mostly HD and RD was enriched for naive B cells (IgD+CD27−, Cluster 10) and CXCR5+IgD−CD27+ switched memory (Cluster 2) and, indeed, Clusters 2 and 10 were statistically reduced in COVID-19 patients (Fig. 4P).
T193	32419-32494	Sentence	denotes	EMD Groups 1 and 3 displayed distinct patterns across the FlowSOM clusters.
T194	32495-32646	Sentence	denotes	B cells from individuals in EMD Group 1 were enriched for the FlowSOM Clusters 1, 5, and 6, all of which were increased in COVID-19 patients (Fig. 4P).
T195	32647-32870	Sentence	denotes	FlowSOM Clusters 1 and 6 captured T-bet+ memory B cells whereas FlowSOM Cluster 5 contained the CD27+CD38+CD138+KI67+ PB, all of which were enriched in COVID-19 patients compared to controls (Fig. 4, O and P, and fig. S5K).
T196	32871-33107	Sentence	denotes	In contrast, B cells from COVID-19 patients in EMD Group 3 also showed enrichment for the PB FlowSOM Cluster 5, though less prominent than for EMD Group 1, but the T-bet+ memory B cell Cluster 1 was substantially reduced in EMD Group 3.
T197	33108-33328	Sentence	denotes	Thus, B cell responses were evident in many hospitalized COVID-19 patients, most often characterized by elevated PB, decreases in memory B cell subsets, enrichment in a T-bet+ B cell subset, and loss of CXCR5 expression.
T198	33329-33434	Sentence	denotes	Whether all of these changes in the B cell compartment were due to direct antiviral responses is unclear.
T199	33435-33661	Sentence	denotes	Although there was heterogeneity in the B cell responses, COVID-19 patients fell into two distinct patterns containing activated B cell responses and a third group of patients with little evidence of an active B cell response.
T200	33663-33736	Sentence	denotes	Temporal changes in immune cell populations occur during COVID-19 disease
T201	33737-33828	Sentence	denotes	A key question for hospitalized COVID-19 patients is how immune responses change over time.
T202	33829-34040	Sentence	denotes	Thus, we used the global tSNE projections of overall CD8 T cell, CD4 T cell, and B cell differentiation states to interrogate temporal changes in these populations between D0 and D7 of hospitalization (Fig. 5A).
T203	34041-34257	Sentence	denotes	Combining data for all patients revealed considerable stability of the tSNE distributions between D0 and D7 in CD8 T cell, CD4 T cell, and B cell populations, particularly for key regions of interest discussed above.
T204	34258-34456	Sentence	denotes	For example, for CD8 T cells, the region of the tSNE map containing KI67+ and CD38+HLA-DR+ CD8 T cell populations that was enriched in COVID-19 patients at D0 (Fig. 2) was preserved at D7 (Fig. 5A).
T205	34457-34550	Sentence	denotes	A similar temporal stability of CD4 T cell and B cell activation was also observed (Fig. 5A).
T206	34551-34633	Sentence	denotes	Fig. 5 Temporal relationships between immune responses and disease manifestation.
T207	34634-34821	Sentence	denotes	(A) Global viSNE projection of non-naïve CD8 T cells, non-naïve CD4 T cells, and B cells for all subjects pooled, with cells from COVID-19 patients at D0 and D7 concatenated and overlaid.
T208	34822-35093	Sentence	denotes	Frequencies of (B) KI67+ and HLA-DR+CD38+ CD4 T cells, (C) KI67+ and HLA-DR+CD38+ CD8 T cells, or (D) PBs as indicated for healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 patients (red) with paired samples at D0 and D7 indicated by the connecting line.
T209	35094-35199	Sentence	denotes	Significance determined by paired Wilcoxon test: p < 0.05, p < 0.01, p < 0.001, and **p < 0.0001.
T210	35200-35462	Sentence	denotes	Longitudinal patterns (see Methods) of (E) HLA-DR+CD38+ CD4 T cells or (F) PBs in COVID-19 patients shown as frequency and representative flow cytometry plots. (G) Spearman correlations of clinical parameters with longitudinal fold changes in immune populations.
T211	35463-35591	Sentence	denotes	Given this apparent stability between D0 and D7, we next investigated temporal changes in lymphocyte subpopulations of interest.
T212	35592-35902	Sentence	denotes	Although there were no obvious temporal changes in major phenotypically defined CD4 and CD8 T cell or B cell subsets, including plasmablasts (Fig. 5D), the frequencies of HLA-DR+CD38+ and KI67+ non-naïve CD4 (Fig. 5B) and KI67+ non-naïve CD8 T cells were statistically increased at D7 compared to D0 (Fig. 5C).
T213	35903-36082	Sentence	denotes	However, in all cases, these temporal patterns were complex, with frequencies of subpopulations in individual patients appearing to increase, decrease, or stay the same over time.
T214	36083-36253	Sentence	denotes	To quantify these inter-patient changes, we used a previously described data set (46) to define the stability of populations of interest in healthy individuals over time.
T215	36254-36433	Sentence	denotes	We then used the range of this variation over time to identify COVID-19 patients with changes in immune cell subpopulations beyond that expected in healthy subjects (see methods).
T216	36434-36629	Sentence	denotes	Using this approach, ~50% of patients had an increase in HLA-DR+CD38+ non-naïve CD4 T cells over time, whereas in ~30% of patients, these cells were stable and, in ~20%, they decreased (Fig. 5E).
T217	36630-36720	Sentence	denotes	For KI67+ non-naïve CD8 T cells, there were no individuals in whom the response decreased.
T218	36721-36820	Sentence	denotes	Instead, this proliferative CD8 T cell response stayed stable (~70%) or increased (~30%; fig. S6A).
T219	36821-37001	Sentence	denotes	Notably, for patients in the stable category, the median frequency of KI67+ non-naïve CD8 T cells was ~10%, almost 5-fold higher than the ~1% detected for HD and RD subjects (Figs.
T220	37002-37084	Sentence	denotes	5C and 2E), suggesting a sustained CD8 T cell proliferative response to infection.
T221	37085-37276	Sentence	denotes	A similar pattern was observed for HLA-DR+CD38+ non-naïve CD8 (fig. S6B), where only ~10% of patients had a decrease in this population, whereas ~65% were stable and ~25% increased over time.
T222	37277-37677	Sentence	denotes	The high and even increasing activated or proliferating CD8 and CD4 T cell responses over ~1 week during acute viral infection contrasted with the sharp peak of KI67 in CD8 and CD4 T cells during acute viral infections, including smallpox vaccination with live vaccinia virus (47), live attenuated yellow fever vaccine YFV-17D (48), acute influenza virus infection (49), and acute HIV infection (35).
T223	37678-37793	Sentence	denotes	Approximately 42% of patients had sustained PB responses, at high levels (>10% of B cells) in many cases (Fig. 5F).
T224	37794-37955	Sentence	denotes	Thus, some patients displayed dynamic changes in T cell or B cell activation over 1 week in the hospital, but there were also other patients who remained stable.
T225	37956-38147	Sentence	denotes	In the latter case, some patients remained stable without clear activation of key immune populations whereas others had stable T and or B cell activation or numerical perturbation (fig. S6C).
T226	38148-38340	Sentence	denotes	We next asked whether these T and B cell dynamics related to clinical measures of COVID-19 disease, by correlating changes in immune features from D0 to D7 with clinical information (Fig. 5G).
T227	38341-38387	Sentence	denotes	These analyses revealed distinct correlations.
T228	38388-38630	Sentence	denotes	Decreases in all populations of responding CD4 and CD8 T cells (HLA-DR+CD38+, KI67+, or activated cTfh) between D0 and D7 were positively correlated with PMN and WBC counts, suggesting a relationship between T cell activation and lymphopenia.
T229	38631-38734	Sentence	denotes	Furthermore, decreases in CD4 and CD8 HLA-DR+CD38+ T cells positively correlated with APACHE III score.
T230	38735-38840	Sentence	denotes	However, stable HLA-DR+CD38+ CD4 T cell responses correlated with coagulation complications and ferritin.
T231	38841-38955	Sentence	denotes	Whereas decreasing activated cTfh over time was related to co-infection, the opposite pattern was observed for PB.
T232	38956-39237	Sentence	denotes	Increases in proliferating KI67+ CD4 and CD8 T cells over time were positively correlated to increasing anti-SARS-CoV2 antibody from day 0 to day 7, suggesting that some individuals might have been hospitalized during the expansion phase of the antiviral immune response (Fig. 5G).
T233	39238-39341	Sentence	denotes	Finally, neither Remdesivir nor HCQ treatment correlated with any of these immune features in Fig. 5G).
T234	39342-39557	Sentence	denotes	Examining categorical rather than continuous clinical data, 80% of patients with decreasing PB over time had hyperlipidemia, whereas only 20% of patients with increasing PB over time had this comorbidity (fig. S6D).
T235	39558-39822	Sentence	denotes	All patients who had decreasing CD38+HLA-DR+ CD8 T cells from day 0 to day 7 were treated with early vasoactive medication or inhaled nitric oxide whereas these treatments were less common for patients with stable or increasing CD38+HLA-DR+ CD8 T cells (fig. S6E).
T236	39823-39985	Sentence	denotes	In contrast, vasoactive medication, inhaled nitric oxide, and early steroid treatment were equally common in patients with increasing or decreasing PB (fig. S6D).
T237	39986-40093	Sentence	denotes	Similar patterns were apparent for other T cell populations and these categorical clinical data (fig. S6F).
T238	40094-40229	Sentence	denotes	Thus, the trajectory of change in the T and B cell response in COVID-19 patients was strongly connected to clinical metrics of disease.
T239	40231-40360	Sentence	denotes	Identifying “immunotypes” and relationships between circulating B and T cell responses with disease severity in COVID-19 patients
T240	40361-40717	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	40718-40825	Sentence	denotes	We then asked how changes in T and B cell populations defined above on D0 were related to disease severity.
T242	40826-40978	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	40979-41174	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	41175-41335	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	41336-41456	Sentence	denotes	Fig. 6 High dimensional analysis of immune phenotypes with clinical data reveals distinct COVID-19 patient immunotypes.
T246	41457-41551	Sentence	denotes	(A) NIH ordinal scale for COVID-19 clinical severity. (B) Frequencies of major immune subsets.
T247	41552-42045	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	42046-42244	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	42245-42366	Sentence	denotes	Relative expression (according to heat scale) shown for both individual patients (points) and overall density (contours).
T250	42367-43044	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	43045-43111	Sentence	denotes	There were two challenges with extracting meaning from these data.
T252	43112-43238	Sentence	denotes	First, there was considerable inter-patient heterogeneity for each of these immune features related to disease severity score.
T253	43239-43396	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	43397-43519	Sentence	denotes	Thus, we next visualized major T and B cell subpopulation data as it related to clinical disease severity score (Fig. 6C).
T255	43520-43642	Sentence	denotes	Data were clustered based on immune features and then overlaid with the disease severity score over time for each patient.
T256	43643-43764	Sentence	denotes	This analysis revealed groups of patients with similar composite immune signatures of T and B cell populations (Fig. 6C).
T257	43765-43912	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	43913-44125	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	44126-44338	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	44339-44666	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	44667-44864	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	44865-44995	Sentence	denotes	An orthogonal vertical axis coordinate (“Component 2”) also existed that captured non-overlapping aspects of the immune landscape.
T263	44996-45118	Sentence	denotes	We next calculated the mean of Component 1 for each patient group, with COVID-19 patients separated by severity (Fig. 6E).
T264	45119-45233	Sentence	denotes	The contribution of Component 1 clearly increased in a stepwise manner with increasing disease severity (Fig. 6F).
T265	45234-45308	Sentence	denotes	Interestingly, RD were subtly positioned between HD and COVID-19 patients.
T266	45309-45475	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	45476-45588	Sentence	denotes	We next investigated how the UMAP Components were associated with individual immune features (tables S5 and S6).
T268	45589-45725	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	45726-45772	Sentence	denotes	PB also associated with Component 1 (Fig. 6G).
T270	45773-45861	Sentence	denotes	Other individual B cell features were differentially captured by UMAP Component 1 and 2.
T271	45862-46026	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	46027-46246	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	46247-46431	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	46432-46570	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	46571-46628	Sentence	denotes	We next took advantage of the FlowSOM clustering in Figs.
T276	46629-46780	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	46781-46999	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	47000-47237	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	47238-47505	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	47506-47628	Sentence	denotes	In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H).
T281	47629-47832	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	47833-48001	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	48002-48119	Sentence	denotes	The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G).
T284	48120-48280	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	48281-48492	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	48493-48656	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	48657-48776	Sentence	denotes	Several antibody features also correlated with Component 1 consistent with some of the immune features discussed above.
T288	48777-49001	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	49002-49197	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	49198-49496	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	49497-49665	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	49666-50082	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	50083-50119	Sentence	denotes	However, the data presented in Figs.
T294	50120-50213	Sentence	denotes	1 to 5 also suggested a subset of patients with minimal activation of T and B cell responses.
T295	50214-50409	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	50410-50577	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	50578-50900	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	50901-51011	Sentence	denotes	These data further emphasize the different ways patients can present and possibly succumb to COVID-19 disease.
T299	51012-51121	Sentence	denotes	These patterns may be related to pre-existing conditions in combination with immune response characteristics.
T300	51122-51243	Sentence	denotes	It is likely that additional immune features, such as comprehensive serum cytokine measurements, will improve this model.
T301	51244-51477	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).
T302	51479-51489	Sentence	denotes	Discussion
T303	51490-51565	Sentence	denotes	The T and B cell response to SARS-CoV2 infection remains poorly understood.
T304	51566-51717	Sentence	denotes	Some studies suggest an overaggressive immune response leading to immunopathology (51) whereas others suggest T cell exhaustion or dysfunction (12–14).
T305	51718-51844	Sentence	denotes	Autopsies revealed high virus levels in the respiratory tract and other tissues (52), suggesting ineffective immune responses.
T306	51845-51963	Sentence	denotes	Nevertheless, non-hospitalized subjects who recovered from COVID-19 had evidence of virus-specific T cell memory (53).
T307	51964-52117	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	52118-52285	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	52286-52459	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	52460-52597	Sentence	denotes	Such knowledge would address the critical question of whether there is a common profile of immune dysfunction in critically ill patients.
T311	52598-52736	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	52737-52862	Sentence	denotes	To interrogate the immune response patterns of COVID-19 hospitalized patients, we studied a cohort of ~125 COVID-19 patients.
T313	52863-53183	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	53184-53234	Sentence	denotes	Using this approach, we made several key findings.
T315	53235-53347	Sentence	denotes	First, a defining feature of COVID-19 disease in hospitalized patients was heterogeneity of the immune response.
T316	53348-53567	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	53568-53742	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	53743-54311	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	54312-54470	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	54471-54661	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	54662-54774	Sentence	denotes	Thus, these immunotypes may reflect fundamental differences in the ways patients respond to SARS-CoV2 infection.
T322	54775-54846	Sentence	denotes	A second key observation from these studies was the robust PB response.
T323	54847-54953	Sentence	denotes	Some patients had PB frequencies rivaling those found in acute Ebola or Dengue infection (34, 42, 43, 55).
T324	54954-55054	Sentence	denotes	Furthermore, blood PB frequencies are typically correlated with blood activated cTfh responses (40).
T325	55055-55143	Sentence	denotes	However, in COVID-19 patients, this relationship between PB and activated cTfh was weak.
T326	55144-55438	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	55439-55638	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	55639-55763	Sentence	denotes	Most ICU patients made SARS-CoV2-specific antibodies, suggesting that at least part of the PB response was antigen-specific.
T329	55764-55904	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	55905-56036	Sentence	denotes	Future studies will be needed to address the antigen specificity, ontogeny, and role in pathogenesis for these robust PB responses.
T331	56037-56163	Sentence	denotes	A striking feature of some patients with strong T and B cell activation and proliferation was the durability of this response.
T332	56164-56254	Sentence	denotes	This T and B activation was interesting considering clinical lymphopenia in many patients.
T333	56255-56315	Sentence	denotes	This lymphopenia, however, was preferential for CD8 T cells.
T334	56316-56517	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	56518-56596	Sentence	denotes	Indeed CD95 was associated with activated T cell clusters in COVID-19 disease.
T336	56597-56807	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	56808-56972	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	56973-57224	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	57225-57341	Sentence	denotes	These ideas would fit with an overaggressive immune response and/or “cytokine storm” (2) in this subset of patients.
T340	57342-57528	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	57529-57698	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	57699-57887	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	57888-58054	Sentence	denotes	Using correlative analyses, we observed relationships between features of the different immunotypes, patient comorbidities, and clinical features of COVID-19 disease.
T344	58055-58280	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	58281-58436	Sentence	denotes	Moreover, this UMAP embedding approach allowed us to connect these integrated immune signatures back to specific clinically measurable features of disease.
T346	58437-58575	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	58576-58987	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	58988-59238	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	59239-59440	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	59441-59627	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	59628-59843	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	59844-60111	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	60112-60255	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	60256-60431	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.
T355	60433-60454	Sentence	denotes	Materials and methods
T356	60456-60504	Sentence	denotes	Patients, subjects, and clinical data collection
T357	60505-60691	Sentence	denotes	Patients admitted to the Hospital of the University of Pennsylvania with a positive SARS-CoV2 PCR test were screened and approached for informed consent within 3 days of hospitalization.
T358	60692-60795	Sentence	denotes	Healthy donors (HD) were adults with no prior diagnosis of or recent symptoms consistent with COVID-19.
T359	60796-60886	Sentence	denotes	Normal reference ranges for HDs were the UPenn clinical laboratory values shaded in green.
T360	60887-61057	Sentence	denotes	Recovered COVID-19 subjects (RD) were adults with a prior positive COVID-19 PCR test by self-report who met the definition of recovery by the Centers for Disease Control.
T361	61058-61222	Sentence	denotes	HD and RD were recruited initially by word of mouth and subsequently through a centralized University of Pennsylvania resource website for COVID-19-related studies.
T362	61223-61272	Sentence	denotes	Peripheral blood was collected from all subjects.
T363	61273-61390	Sentence	denotes	For inpatients, clinical data were abstracted from the electronic medical record into standardized case report forms.
T364	61391-61556	Sentence	denotes	ARDS was categorized in accordance with the Berlin definition reflecting each subject’s worst oxygenation level and with physician adjudication of chest radiographs.
T365	61557-61736	Sentence	denotes	APACHE III scoring was based on data collected in the first 24 hours of ICU admission or the first 24 hours of hospital admission for subjects admitted to general inpatient units.
T366	61737-61829	Sentence	denotes	Clinical laboratory data were abstracted from the date closest to research blood collection.
T367	61830-61874	Sentence	denotes	HD and RD completed a survey about symptoms.
T368	61875-61984	Sentence	denotes	After enrollment, the clinical team determined three patients to be COVID-negative and/or PCR false positive.
T369	61985-62039	Sentence	denotes	Two of these patients were classified as Immunotype 3.
T370	62040-62123	Sentence	denotes	In keeping with inclusion criteria, these subjects were maintained in the analysis.
T371	62124-62242	Sentence	denotes	The statistical significance reported in Fig. 6K did not change when analysis was repeated without the three patients.
T372	62243-62416	Sentence	denotes	All participants or their surrogates provided informed consent in accordance with protocols approved by the regional ethical research boards and the Declaration of Helsinki.
T373	62418-62435	Sentence	denotes	Sample processing
T374	62436-62510	Sentence	denotes	Peripheral blood was collected into sodium heparin tubes (BD, Cat#367874).
T375	62511-62578	Sentence	denotes	Tubes were spun (15 min, 3000 rpm, RT), plasma removed, and banked.
T376	62579-62769	Sentence	denotes	Remaining whole blood was diluted 1:1 with 1% RPMI (table S7) and layered into a SEPMATE tube (STEMCELL Technologies, Cat#85450) pre-loaded with lymphoprep (Alere Technologies, Cat#1114547).
T377	62770-62958	Sentence	denotes	SEPMATE tubes were spun (10 min, 1200xg, RT) and the PBMC layer collected, washed with 1% RPMI (10 min, 1600 rpm, RT) and treated with ACK lysis buffer (5 min, ThermoFisher, Cat#A1049201).
T378	62959-63038	Sentence	denotes	Samples were filtered with a 70 μm filter, counted, and aliquoted for staining.
T379	63040-63068	Sentence	denotes	Antibody panels and staining
T380	63069-63146	Sentence	denotes	Approximately 1-5×106 freshly isolated PBMCs were used per patient per stain.
T381	63147-63227	Sentence	denotes	See table S7 for buffer information and table S8 for antibody panel information.
T382	63228-63349	Sentence	denotes	PBMCs were stained with live/dead mix (100 μl, 10 min, RT), washed with FACS buffer, and spun down (1500 rpm, 5 min, RT).
T383	63350-63464	Sentence	denotes	PBMCs were incubated with 100 μl of Fc block (RT, 10 min) before a second wash (FACS buffer, 1500 rpm, 5 min, RT).
T384	63465-63566	Sentence	denotes	Pellet was resuspended in 25 μl of chemokine receptor staining mix, and incubated at 37°C for 20 min.
T385	63567-63703	Sentence	denotes	Following incubation, 25 μl of surface receptor staining mix was directly added and the PBMCs were incubated at RT for a further 45 min.
T386	63704-63877	Sentence	denotes	PBMCs were washed (FACS buffer, 1500 rpm, 5 min, RT) and stained with 50 μl of secondary antibody mix for 20 min at RT, then washed again (FACS buffer, 1500 rpm, 5 min, RT).
T387	63878-64019	Sentence	denotes	Samples were fixed and permeabilized by incubating in 100 μl of Fix/Perm buffer (RT, 30 min) and washed in Perm Buffer (1800 rpm, 5 min, RT).
T388	64020-64087	Sentence	denotes	PBMCs were stained with 50μl of intracellular mix overnight at 4°C.
T389	64088-64203	Sentence	denotes	The following morning, samples were washed (Perm Buffer, 1800 rpm, 5 min, RT) and further fixed in 50 μl of 4% PFA.
T390	64204-64317	Sentence	denotes	Prior to acquisition, samples were diluted to 1% PFA and 10,000 counting beads added per sample (BD, Cat#335925).
T391	64318-64352	Sentence	denotes	Live/dead mix was prepared in PBS.
T392	64353-64491	Sentence	denotes	For the surface receptor and chemokine staining mix, antibodies were diluted in FACS buffer with 50% BD Brilliant Buffer (BD, Cat#566349).
T393	64492-64537	Sentence	denotes	Intracellular mix was diluted in Perm Buffer.
T394	64539-64553	Sentence	denotes	Flow cytometry
T395	64554-64609	Sentence	denotes	Samples were acquired on a 5 laser BD FACS Symphony A5.
T396	64610-64717	Sentence	denotes	Standardized SPHERO rainbow beads (Spherotech, Cat#RFP-30-5A) were used to track and adjust PMTs over time.
T397	64718-64793	Sentence	denotes	UltraComp eBeads (ThermoFisher, Cat#01-2222-42) were used for compensation.
T398	64794-64848	Sentence	denotes	Up to 2 × 106 live PBMC were acquired per each sample.
T399	64850-64857	Sentence	denotes	Luminex
T400	64858-64954	Sentence	denotes	PBMCs from patients were thawed and rested overnight at 37°C in complete RPMI (cRPMI, table S7).
T401	64955-65069	Sentence	denotes	96-well flat bottom plates were coated with 1 μg/mL of anti-CD3 (UCHT1, #BE0231, BioXell) in PBS at 4°C overnight.
T402	65070-65155	Sentence	denotes	The next day, cells were collected and plated at 1 × 105/well in 100 μl in duplicate.
T403	65156-65269	Sentence	denotes	2 μg/mL of anti-human CD28/CD49d was added to the wells containing plate-bound anti-CD3 (Clone L293, 347690, BD).
T404	65270-65400	Sentence	denotes	PBMCs were stimulated or left unstimulated for 16 hours, spun down (1200 rpm, 10 min) and 85 μL/well of supernatant was collected.
T405	65401-65523	Sentence	denotes	Plasma from matched subjects was thawed on ice, spun (3000 rpm, 1 min) to remove debris, and 85 μl collected in duplicate.
T406	65524-65671	Sentence	denotes	Luminex assay was run according to manufacturer’s instructions, using a custom human cytokine 31-plex panel (EMD Millipore Corporation, SPRCUS707).
T407	65672-65950	Sentence	denotes	The panel included: EGF, FGF-2, Eotaxin, sIL-2Ra, G-CSF, GM-CSF, IFN-α2, IFN-γ, IL-10, IL-12P40, IL-12P70, IL-13, IL-15, IL-17A, IL-1Ra, HGF, IL-1β, CXCL9/MIG, IL-2, IL-4, IL-5, IL-6, IL-7, CXCL8/IL-8, CXCL10/IP-10, CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, RANTES, TNF-α, and VEGF.
T408	65951-66044	Sentence	denotes	Assay plates were measured using a Luminex FlexMAP 3D instrument (Thermofisher, Cat#APX1342).
T409	66045-66138	Sentence	denotes	Data acquisition and analysis were done using xPONENT software www.luminexcorp.com/xponent/).
T410	66139-66197	Sentence	denotes	Data quality was examined based on the following criteria:
T411	66198-66312	Sentence	denotes	The standard curve for each analyte has a 5P R2 value > 0.95 with or without minor fitting using xPONENT software.
T412	66313-66504	Sentence	denotes	To pass assay technical quality control, the results for two controls in the kit needed to be within the 95% of CI (confidence interval) provided by the vendor for >25 of the tested analytes.
T413	66505-66580	Sentence	denotes	No further tests were done on samples with results out of range low (<OOR).
T414	66581-66755	Sentence	denotes	Samples with results that were out of range high (>OOR) or greater than the standard curve maximum value (SC max) were not tested at higher dilutions without further request.
T415	66757-66803	Sentence	denotes	Intracellular stain after CD3/CD28 stimulation
T416	66804-66917	Sentence	denotes	96-well flat bottom plates were coated with 1μg/mL of anti-CD3 (UCHT1, #BE0231, BioXell) in PBS at 4°C overnight.
T417	66918-67028	Sentence	denotes	The next day, cells were collected and plated at 1 × 105/well in 100 μl with 1/1000 of GolgiPlug (BD #555029).
T418	67029-67141	Sentence	denotes	2μg/mL of anti-human CD28/CD49d was added to the wells containing plate-bound anti-CD3 (Clone L293, 347690, BD).
T419	67142-67286	Sentence	denotes	GolgiPlug-treated PBMCs were stimulated or left unstimulated for 16 hours, spun down (1200 rpm, 10 min) and were stained for intracellular IFNɣ.
T420	67288-67336	Sentence	denotes	Longitudinal analysis D0-D7 and patient grouping
T421	67337-67624	Sentence	denotes	To identify subjects where the frequency of specific immune cell populations increased, decreased or stayed stable over time (day 0 to day 7), where data was available we used a previously published dataset to establish a standard range of fold change over time in a healthy cohort (44).
T422	67625-67817	Sentence	denotes	A fold change greater than the mean fold change ± 2 standard deviations was considered an increase, less than this range was considered a decrease, and within this range was considered stable.
T423	67818-67932	Sentence	denotes	Where this data was not available, a fold change from day 0 to day 7 of between 0.5 and 1.5 was considered stable.
T424	67933-68012	Sentence	denotes	A fold change <0.5 was considered decreased, and >1.5 was considered increased.
T425	68013-68263	Sentence	denotes	In order to eliminate redundant tests and maximize statistical power, the pairwise statistical tests shown in Fig. 5G were performed using fold-change as a continuous metric, irrespective of the discrete up/stable/down classification described above.
T426	68264-68496	Sentence	denotes	Similarly, in fig. S9G, pairwise association tests between changes in UMAP Component coordinates and clinical data were performed using each difference value as a continuous metric, irrespective of the up/stable/down classification.
T427	68498-68541	Sentence	denotes	Correlation plots and heatmap visualization
T428	68542-68656	Sentence	denotes	Pairwise correlations between variables were calculated and visualized as a correlogram using R function corrplot.
T429	68657-68845	Sentence	denotes	Spearman's Rank Correlation coefficient (ρ) was indicated by square size and heat scale; significance indicated by: p < 0.05, p < 0.01, and **p < 0.001; black box indicates FDR < 0.05.
T430	68846-68941	Sentence	denotes	Heatmaps were created to visualize variable values using R function pheatmap or complexheatmap.
T431	68943-68953	Sentence	denotes	Statistics
T432	68954-69127	Sentence	denotes	Due to the heterogeneity of clinical and flow cytometric data, non-parametric tests of association were preferentially used throughout this study unless otherwise specified.
T433	69128-69410	Sentence	denotes	Correlation coefficients between ordered features (including discrete ordinal, continuous scale, or a mixture of the two) were quantified by the Spearman rank correlation coefficient and significance was assessed by the corresponding non-parametric methods (null hypothesis: ρ = 0).
T434	69411-69611	Sentence	denotes	Tests of association between mixed continuous versus non-ordered categorical variables were performed by unpaired Wilcoxon test (for n = 2 categories) or by Kruskal-Wallis test (for n > 2 categories).
T435	69612-69688	Sentence	denotes	Association between categorical variables was assessed by Fisher-exact test.
T436	69689-69890	Sentence	denotes	For association testing illustrated in heatmaps, categorical variables with more than 2 categories (e.g., ABO blood type) were transformed into binary dummy variables for each category versus the rest.
T437	69891-70005	Sentence	denotes	All tests were performed two-sided, using a nominal significance threshold of P < 0.05 unless otherwise specified.
T438	70006-70198	Sentence	denotes	When appropriate to adjust for multiple hypothesis testing, false discovery rate (FDR) correction was performed using the Benjamini-Hochberg procedure at the FDR < 0.05 significance threshold.
T439	70199-70488	Sentence	denotes	Joint statistical modeling to adjust for confounding of demographic factors (age, sex, and race) when testing for association of UMAP Components 1 and 2 with the NIH Ordinal Severity Scale was performed using ordinal logistic regression provided by the polr function of the R package MASS.
T440	70489-70571	Sentence	denotes	Statistical analysis of flow cytometry data was performed using R package rstatix.
T441	70572-70663	Sentence	denotes	Other details, if any, for each experiment are provided within the relevant figure legends.
T442	70665-70718	Sentence	denotes	High dimensional data analysis of flow cytometry data
T443	70719-70796	Sentence	denotes	viSNE and FlowSOM analysis were performed on Cytobank (https://cytobank.org).
T444	70797-71026	Sentence	denotes	B cells, non-naïve CD4 T cells, and non-naïve CD8 T cells were analyzed separately. viSNE analysis was performed using equal sampling of 1000 cells from each FCS file, with 5000 iterations, a perplexity of 30, and a theta of 0.5.
T445	71027-71226	Sentence	denotes	For B cells, the following markers were used to generate the viSNE maps: CD45RA, IgD, CXCR5, CD138, Eomes, TCF-1, CD38, CD95, CCR7, CD21, KI67, CD27, CX3CR1, CD39, T-bet, HLA-DR, CD16, CD19 and CD20.
T446	71227-71403	Sentence	denotes	For non-naïve CD4 and CD8 T cells, the following markers were used: CD45RA, PD1, CXCR5, TCF-1, CD38, CD95, Eomes, CCR7, KI67, CD16, CD27, CX3CR1, CD39, CD20, T-bet, and HLA-DR.
T447	71404-71477	Sentence	denotes	Resulting viSNE maps were fed into the FlowSOM clustering algorithm (59).
T448	71478-71603	Sentence	denotes	For each cell subset, a new self-organizing map (SOM) was generated using hierarchical consensus clustering on the tSNE axes.
T449	71604-71710	Sentence	denotes	For each SOM, 225 clusters and 10 or 15 metaclusters were identified for B cells and T cells respectively.
T450	71711-71971	Sentence	denotes	To group individuals based on B cell landscape, pairwise Earth Mover’s Distance (EMD) value was calculated on the B cell tSNE axes for all COVID-19 day 0 patients, healthy donors, and recovered donors using the emdist package in R as previously described (60).
T451	71972-72049	Sentence	denotes	Resulting scores were hierarchically clustered using the hclust package in R.
T452	72051-72067	Sentence	denotes	Batch correction
T453	72068-72156	Sentence	denotes	During the sample acquisition period, the flow panel was changed to remove one antibody.
T454	72157-72288	Sentence	denotes	Batch correction was performed for samples acquired before and after this change to remove potential bias from downstream analysis.
T455	72289-72563	Sentence	denotes	Because the primary flow features were expressed as a fraction of the parent population (falling in the 0-to-1 interval) a variance stabilizing transform (logit) was first applied to each data value, prior to re-centering the second panel to have the same mean as the first.
T456	72564-72675	Sentence	denotes	After mean-centering, data were transformed back to the original fraction of parent scale by inverse transform.
T457	72676-72788	Sentence	denotes	This procedure was applied separately to all 553 flow features annotated in the main text and supplemental data.
T458	72789-72913	Sentence	denotes	Notably, this procedure avoids any batch-corrected feature values artificially falling outside of the original 0 to 1 range.
T459	72914-73067	Sentence	denotes	Following batch correction, neither UMAP Component 1 nor Component 2 had a statistically significant difference between panels by unpaired Wilcoxon test.
T460	73069-73150	Sentence	denotes	Visualizing variation of flow cytometric features across the UMAP embedding space
T461	73151-73294	Sentence	denotes	A feature-weighted kernel density was computed across all COVID-19 patients, and was displayed as a contour plot (Fig. 6G and fig. S8, A to D).
T462	73295-73681	Sentence	denotes	Whereas traditional kernel density methods apply the same base kernel function to every point to visualize point density, here the base kernel function centered at each individual COVID-19 patient sample was instead weighted (multiplied) by the Z-transform (mean-centered and standard deviation-scaled) of the log-transformed input feature prior to computing the overall kernel density.
T463	73682-73894	Sentence	denotes	This weighting procedure facilitated visualization of the overall feature gradients (going from relatively low-to-high expression) across UMAP coordinates independent of the different range of each input feature.
T464	73895-74146	Sentence	denotes	A radially symmetric two-dimensional Gaussian was used as the base kernel function with a variance parameter equal to one-half, which was tuned to be sufficiently broad in order to smooth out local discontinuities and best visualize feature gradients.
T465	74148-74174	Sentence	denotes	Definition of immunotype 3
T466	74175-74559	Sentence	denotes	To define COVID-19 patients with low or absent immune responses, classified as immunotype 3, the intersection of the bottom 50% of 5 different flow parameters was used: PB as % of B cells, KI67+ as % of non-naïve CD4 T cells, KI67+ as % of non-naïve CD8 T cells, HLA-DR+CD38+ as % of non-naïve CD4 T cells, HLA-DR+CD38+ as % of non-naïve CD8 T cells—graphically displayed in fig. S10.

T11

0-96

Sentence

denotes

The COVID-19 pandemic has to date caused >7 million infections resulting in over 400,000 deaths.

T12

97-289

Sentence

denotes

Following infection with SARS-CoV2, COVID-19 patients can experience mild or even asymptomatic disease, or can present with severe disease requiring hospitalization and mechanical ventilation.

T13

290-340

Sentence

denotes

The case fatality rate can be as high as ~10% (1).

T14

341-463

Sentence

denotes

Some severe COVID-19 patients display an acute respiratory distress syndrome (ARDS), reflecting severe respiratory damage.

T15

464-604

Sentence

denotes

In acute respiratory viral infections, pathology can be mediated by the virus directly, by an overaggressive immune response, or both (2–4).

T16

605-793

Sentence

denotes

However, in severe COVID-19 disease, the characteristics of, and role for the immune response, as well as how these responses relate to clinical disease features, remain poorly understood.

T17

794-1050

Sentence

denotes

SARS-CoV2 antigen-specific T cells have been identified in the central memory (CM), effector memory (EM), and CD45RA+ effector memory (EMRA) compartments (5) but the characteristics of these cells and their role in infection or pathogenesis remain unclear.

T18

1051-1320

Sentence

denotes

Recovered subjects more often have evidence of virus-specific CD4 T cell responses than virus-specific CD8 T cell responses, though pre-existing CD4 T cell responses to other coronaviruses also are found in a subset of subjects in the absence of SARS-CoV2 exposure (6).

T19

1321-1538

Sentence

denotes

Inflammatory responses have been reported, including increases in IL-6- or GM-CSF-producing CD4 T cells in the blood (7) or decreases in immunoregulatory subsets such as regulatory T cells (Treg) or ɣδ T cells (8–11).

T20

1539-1750

Sentence

denotes

T cell exhaustion (12, 13) or increased inhibitory receptor expression on peripheral T cells has also been reported (7, 14), though these inhibitory receptors are also increased following T cell activation (15).

T21

1751-1990

Sentence

denotes

Moreover, although there is evidence of T cell activation in COVID-19 patients (16), some studies have found decreases in polyfunctionality (12, 17) or cytotoxicity (12); however, these changes have not been observed in other studies (13).

T22

1991-2104

Sentence

denotes

Furthermore, how this activation should be viewed in the context of COVID-19 lymphopenia (18–20) remains unclear.

T23

2105-2224

Sentence

denotes

Most patients seroconvert within 7-14 days of infection and increased plasmablasts (PB) have been reported (16, 21–23).

T24

2225-2312

Sentence

denotes

However, the role of humoral responses in the pathogenesis of COVID-19 remains unclear.

T25

2313-2463

Sentence

denotes

Whereas IgG levels reportedly drop slightly ~8 weeks after symptom onset (24, 25), recovered patients maintain high Spike-specific IgG titers (6, 26).

T26

2464-2545

Sentence

denotes

IgA levels also can remain high and may correlate with disease severity (25, 27).

T27

2546-2648

Sentence

denotes

Furthermore, neutralizing antibodies can control SARS-CoV2 infection in vitro and in vivo (4, 28, 29).

T28

2649-2747

Sentence

denotes

Indeed, convalescent plasma containing neutralizing antibodies can improve clinical symptoms (30).

T29

2748-2947

Sentence

denotes

However, not all patients that recover from COVID-19 have detectable neutralizing antibodies (6, 26), suggesting a complex relationship between humoral and cellular response in COVID-19 pathogenesis.

T30

2948-3140

Sentence

denotes

Taken together, this previous work provokes questions about the potential diversity of immune responses to SARS-CoV2 and the relationship of this immune response diversity to clinical disease.

T31

3141-3268

Sentence

denotes

However, many studies describe small cohorts or even single patients, limiting a comprehensive interrogation of this diversity.

T32

3269-3448

Sentence

denotes

The relationship of different immune response features to clinical parameters, as well as the changes in immune responses and clinical disease over time, remain poorly understood.

T33

3449-3704

Sentence

denotes

Because potential therapeutics for COVID-19 patients include approaches to inhibit, activate, or otherwise modulate immune function, it is essential to define the immune response characteristics related to disease features in well-defined patient cohorts.

T34

3706-3805

Sentence

denotes

Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations

T35

3806-4027

Sentence

denotes

We 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).

T36

4028-4112

Sentence

denotes

Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A).

T37

4113-4195

Sentence

denotes

Additional samples were obtained from patients who remained hospitalized on day 7.

T38

4196-4412

Sentence

denotes

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).

T39

4413-4510

Sentence

denotes

Clinical metadata are available from the COVID-19 patients over the course of disease (table S1).

T40

4511-4714

Sentence

denotes

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).

T41

4715-4834

Sentence

denotes

Fig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.

T42

4835-5021

Sentence

denotes

(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.

T43

5022-5391

Sentence

denotes

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.

T44

5392-5508

Sentence

denotes

Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively.

T45

5509-5759

Sentence

denotes

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).

T46

5760-5886

Sentence

denotes

Significance determined by unpaired Wilcoxon test with BH correction: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

T47

5887-6097

Sentence

denotes

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).

T48

6098-6195

Sentence

denotes

For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2).

T49

6196-6297

Sentence

denotes

Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort).

T50

6298-6402

Sentence

denotes

Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event.

T51

6403-6572

Sentence

denotes

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.

T52

6573-6680

Sentence

denotes

45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir.

T53

6681-6752

Sentence

denotes

Eighteen individuals died in the hospital or within a 30 day follow-up.

T54

6753-6867

Sentence

denotes

The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms.

T55

6868-7020

Sentence

denotes

Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.

T56

7021-7145

Sentence

denotes

As has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome.

T57

7146-7351

Sentence

denotes

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).

T58

7352-7429

Sentence

denotes

Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B).

T59

7430-7614

Sentence

denotes

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).

T60

7615-7751

Sentence

denotes

Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B).

T61

7752-7866

Sentence

denotes

A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33).

T62

7867-7977

Sentence

denotes

Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC <1 THO/ul, Fig. 1B).

T63

7978-8075

Sentence

denotes

In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).

T64

8076-8200

Sentence

denotes

To examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C).

T65

8201-8434

Sentence

denotes

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).

T66

8435-8567

Sentence

denotes

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).

T67

8568-8810

Sentence

denotes

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).

T68

8811-8997

Sentence

denotes

Thus, COVID-19 patients presented with varied pre-existing comorbidities, complex clinical phenotypes, evidence of inflammation in many patients, and clinically altered leukocyte counts.

T69

8998-9203

Sentence

denotes

To 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.

T70

9204-9257

Sentence

denotes

We first focused on the major lymphocyte populations.

T71

9258-9496

Sentence

denotes

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).

T72

9497-9664

Sentence

denotes

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.

T73

9665-9758

Sentence

denotes

This non-B, non-T cell population is also interrogated in more detail in the companion study.

T74

9759-10215

Sentence

denotes

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).

T75

10216-10366

Sentence

denotes

These findings are consistent with previous reports of lymphopenia during COVID-19 disease (17–20) but highlight a preferential impact on CD8 T cells.

T76

10367-10471

Sentence

denotes

We next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H).

T77

10472-10624

Sentence

denotes

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).

T78

10625-10799

Sentence

denotes

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.

T79

10800-10954

Sentence

denotes

Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations.

T80

10956-11040

Sentence

denotes

SARS-CoV2 infection is associated with CD8 T cell activation in a subset of patients

T81

11041-11188

Sentence

denotes

We next applied high-dimensional flow cytometric analysis to further investigate lymphocyte activation and differentiation during COVID-19 disease.

T82

11189-11449

Sentence

denotes

We first used principal component analysis (PCA) to examine the general distribution of immune profiles from COVID-19 patients (n = 118), RD (n = 60), and HD (n = 36) using 193 immune parameters identified by high-dimensional flow cytometry (tables S5 and S6).

T83

11450-11563

Sentence

denotes

COVID-19 patients clearly segregated from RD and HD in PCA space, whereas RD and HD largely overlapped (Fig. 2A).

T84

11564-11639

Sentence

denotes

We investigated the immune features driving this COVID-19 immune signature.

T85

11640-11715

Sentence

denotes

Given their role in response to viral infection, we focused on CD8 T cells.

T86

11716-12065

Sentence

denotes

Six major CD8 T cell populations were examined using the combination of CD45RA, CD27, CCR7, and CD95 cell surface markers to define naïve (CD45RA+CD27+CCR7+CD95−), central memory (CD45RA−CD27+CCR7+ [CM]), effector memory (CD45RA−CD27+CCR7− [EM1], CD45RA−CD27−CCR7+ [EM2], CD45RA−CD27−CCR7− [EM3]), and EMRA (CD45RA+CD27−CCR7−) (Fig. 2B) CD8 T cells.

T87

12066-12186

Sentence

denotes

Among the CD8 T cell populations, there was an increase in the EM2 and EMRA populations and a decrease in EM1 (Fig. 2C).

T88

12187-12289

Sentence

denotes

Furthermore, the frequency of CD39+ cells was increased in COVID-19 patients compared to HD (Fig. 2D).

T89

12290-12433

Sentence

denotes

Although the frequency of PD-1+ cells was not different in the total CD8 population (Fig. 2D), it was increased for both CM and EM1 (fig. S2A).

T90

12434-12549

Sentence

denotes

Finally, all major CD8 T cell naive/memory populations in RD were comparable to HD (Fig. 2, C and D, and fig. S2A).

T91

12550-12676

Sentence

denotes

Fig. 2 CD8 T cell subset skewing and activation patterns in COVID-19 patients and potential links to T cell driven cytokines.

T92

12677-12930

Sentence

denotes

(A) Principle Component Analysis (PCA) of aggregated flow cytometry data. (B) Representative flow cytometry plots of the gating strategy for CD8 T cell subsets. (C) Frequencies of CD8 T cell subsets as indicated. (D) Frequencies of PD1+ and CD39+ cells.

T93

12931-13564

Sentence

denotes

Frequencies of (E) KI67+ and (F) HLA-DR+CD38+ cells and representative flow cytometry plots; green line at upper decile of HD. (G) (Top) Global viSNE projection of non-naïve CD8 T cells for all subjects pooled, non-naïve CD8 T cells from healthy donor (HD), recovered donor (RD), and COVID-19 patients concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (H) viSNE projection of non-naïve CD8 T cell clusters identified by FlowSOM clustering. (I) Mean fluorescence intensity (MFI) as indicated, column-scaled z-score. (J) Percentage of non-naive CD8 T cells from each cohort in each FlowSOM cluster.

T94

13565-13717

Sentence

denotes

Boxes represent IQR. (C, D, E, F, J) Each dot represents an individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 patient (red).

T95

13718-13844

Sentence

denotes

Significance determined by unpaired Wilcoxon test with BH correction: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

T96

13845-14001

Sentence

denotes

Most acute viral infections induce proliferation and activation of CD8 T cells detectable by increases in KI67 or co-expression of CD38 and HLA-DR (34, 35).

T97

14002-14148

Sentence

denotes

There was a significant increase in KI67+ and also HLA-DR+CD38+ non-naïve CD8 T cells in COVID-19 patients compared to HD or RD (Fig. 2, E and F).

T98

14149-14303

Sentence

denotes

In COVID-19 patients, KI67+ CD8 T cells were increased compared to HD and RD across all subsets of non-naïve CD8 T cells, including CM and EM1 (fig. S2B).

T99

14304-14496

Sentence

denotes

These data indicate broad T cell activation, potentially driven by bystander activation and/or homeostatic proliferation in addition to antigen-driven activation of virus-specific CD8 T cells.

T100

14497-14663

Sentence

denotes

This activation phenotype was confirmed by HLA-DR and CD38 co-expression that was significantly increased for all non-naïve CD8 T cell subsets (Fig. 2F and fig. S2C).

T101

14664-14757

Sentence

denotes

However, the magnitude of the KI67+ or CD38+HLA-DR+ CD8 T cells varied widely in this cohort.

T102

14758-14862

Sentence

denotes

The frequency of KI67+ CD8 T cells correlated with the frequency of CD38+HLA-DR+ CD8 T cells (fig. S2D).

T103

14863-15108

Sentence

denotes

However, the frequency of CD38+HLA-DR+, but not KI67+ CD8 T cells, was elevated in COVID-19 patients who had concomitant infection with another microbe but was not impacted by pre-existing immunosuppression or treatment with steroids (fig. S2E).

T104

15109-15374

Sentence

denotes

Moreover, these changes in CD8 T cell subsets in COVID-19 patients did not show clear correlations with individual metrics of clinical disease such as hsCRP or D-dimer (fig. S2E), although the frequency of KI67+ CD8 T cells associated with IL-6 and ferritin levels.

T105

15375-15534

Sentence

denotes

Although CD8 T cell activation was common, ~20% of patients had no increase in KI67+ or CD38+HLA-DR+ CD8 T cells above the level found in HD (Fig. 2, E and F).

T106

15535-15760

Sentence

denotes

Thus, although robust CD8 T cell activation was a clear characteristic of many hospitalized COVID-19 patients, a substantial fraction of patients had little evidence of CD8 T cell activation in the blood compared to controls.

T107

15761-15867

Sentence

denotes

To gain more insights, we applied global high-dimensional mapping of the 27-parameter flow cytometry data.

T108

15868-16003

Sentence

denotes

A tSNE representation of the data highlighted key regions of non-naïve CD8 T cells found preferentially in COVID-19 patients (Fig. 2G).

T109

16004-16284

Sentence

denotes

A major region of this tSNE map present in COVID-19 patients, but not HD or RD, were CD8 T cells that enriched for expression of CD38, HLA-DR, KI67, CD39, and PD1 (Fig. 2G), highlighting the co-expression of these activation markers with other features including CD95 (i.e., FAS).

T110

16285-16471

Sentence

denotes

Notably, although non-naïve CD8 T cells from RD were highly similar to those from HD, subtle differences existed, including in the lower region highlighted by T-bet and CX3CR1 (Fig. 2G).

T111

16472-16693

Sentence

denotes

To further define and quantify these differences between COVID-19 patients and controls, we performed FlowSOM clustering (Fig. 2H) and compared expression of fourteen CD8 T cell markers to identify each cluster (Fig. 2I).

T112

16694-16933

Sentence

denotes

This approach identified an increase in cells in several clusters including Clusters 1, 2, and 5 in COVID-19 patients, reflecting CD45RA+CD27−CCR7− TEMRA-like populations that expressed CX3CR1 and varying levels of T-bet (Fig. 2, I and J).

T113

16934-17098

Sentence

denotes

Clusters 12 and 14 contained CD27+HLA-DR+CD38+KI67+PD-1+ activated, proliferating cells and were more prevalent in COVID-19 disease (Fig. 2, I and J, and fig. S2F).

T114

17099-17259

Sentence

denotes

In contrast, the central Eomes+CD45RA−CD27+CCR7− EM1-like Cluster 6 and T-bethiCX3CR1+ Cluster 11 were decreased compared to HD (Fig. 2, I and J, and fig. S2F).

T115

17260-17408

Sentence

denotes

Thus, CD8 T cell responses in COVID-19 patients were characterized by populations of activated, proliferating CD8 T cells in a subgroup of patients.

T116

17410-17520

Sentence

denotes

SARS-CoV2 infection is associated with heterogeneous CD4 T cell responses and activation of CD4 T cell subsets

T117

17521-17688

Sentence

denotes

We next examined six well-defined CD4 T cell subsets as above for the CD8 T cells, including naïve, effector memory (EM1,2,3), central memory (CM), and EMRA (Fig. 3A).

T118

17689-18023

Sentence

denotes

Given the potential role of antibodies in the response to SARS-CoV2 (27, 29), we also analyzed circulating Tfh (CD45RA−PD1+CXCR5+ [cTfh] (36)) and activated circulating Tfh (CD38+ICOS+ [activated cTfh]), the latter of which may be more reflective of recent antigen encounter and emigration from the germinal center (37, 38) (Fig. 3A).

T119

18024-18144

Sentence

denotes

These analyses revealed a relative loss of naïve CD4 T cells compared to controls, but increased EM2 and EMRA (Fig. 3B).

T120

18145-18333

Sentence

denotes

The frequency of activated but not total cTfh was statistically increased in COVID-19 patients compared to HD, though this effect appeared to be driven by a subgroup of patients (Fig. 3B).

T121

18334-18495

Sentence

denotes

It is worth noting that activated cTfh frequencies were also higher in RD compared to HD (Fig. 3B), perhaps reflecting residual COVID-19 responses in that group.

T122

18496-18680

Sentence

denotes

Frequencies of KI67+ or CD38+HLA-DR+ non-naïve CD4 T cells were increased in COVID-19 patients (Fig. 3, C and E); however, this change was not equivalent across all CD4 T cell subsets.

T123

18681-18841

Sentence

denotes

The most substantial increases in both KI67+ and CD38+HLA-DR+ cells were found in the effector memory populations (EM, EM2, EM3) and in cTfh (fig. S3, A and B).

T124

18842-18924

Sentence

denotes

Although some subjects had increased activation of EMRA, this was less pronounced.

T125

18925-19034

Sentence

denotes

In contrast, PD1 expression was increased in all other non-naïve populations compared to HD or RD (fig. S3C).

T126

19035-19165

Sentence

denotes

Co-expression of CD38 and HLA-DR by non-naïve CD4 T cells correlated with the frequency of KI67+ non-naïve CD4 T cells (fig. S3D).

T127

19166-19303

Sentence

denotes

Moreover, the frequency of total non-naïve CD4 T cells that were CD38+HLA-DR+ correlated with the frequency of activated cTfh (fig. S3E).

T128

19304-19414

Sentence

denotes

In general, the activation of CD4 T cells was correlated with the activation of CD8 T cells (Fig. 3, D and F).

T129

19415-19646

Sentence

denotes

However, whereas ~2/3 of patients had KI67+ non-naïve CD4 or CD8 T cell frequencies above controls, ~1/3 of the COVID-19 patients had no increase in frequency of KI67+ CD4 or CD8 T cells above that observed in HD (Fig. 3, D and F).

T130

19647-19881

Sentence

denotes

Moreover, although most patients had similar proportions of activated CD4 T cells compared to CD8 T cells, there was a subgroup of patients that had disproportionate activation of CD4 T cells compared to CD8 T cells (Fig. 3, D and F).

T131

19882-20078

Sentence

denotes

KI67+ and CD38+HLA-DR+ non-naïve CD4 T cell frequencies correlated with ferritin and with APACHE III score (fig. S3F), suggesting a relationship between CD4 T cell activation and disease severity.

T132

20079-20227

Sentence

denotes

Immunosuppression did not impact CD4 T cell activation; however, early steroid administration was weakly associated with CD4 T cell KI67 (fig. S3F).

T133

20228-20525

Sentence

denotes

Together, these data highlight T cell activation in COVID-19 patients similar to what has been observed in other acute infections or vaccinations (37, 39, 40), but also identify patients with high, low, or essentially no T cell response based on KI67+ or CD38+HLA-DR+ compared to control subjects.

T134

20526-20633

Sentence

denotes

Fig. 3 CD4 T cell activation in a subset of COVID-19 patients associates with distinct CD4 T cell subsets.

T135

20634-20855

Sentence

denotes

(A) Representative flow cytometry plots of the gating strategy for CD4 T cell subsets. (B) Frequencies of CD4 T cell subsets as indicated. (C) Frequencies of KI67+ cells; green line at upper decile of healthy donors (HD).

T136

20856-21098

Sentence

denotes

Representative flow cytometry plots. (D) KI67+ cells from non-naïve CD4 T cells versus non-naïve CD8 T cells, Spearman correlation of COVID-19 patients. (E) Frequencies of HLA-DR+CD38+ cells; green line at upper decile of healthy donors (HD).

T137

21099-21723

Sentence

denotes

Representative flow cytometry plots. (F) HLA-DR+CD38+ cells from non-naïve CD4 versus non-naïve CD8 T cells, Spearman correlation of COVID-19 patients. (G) (Top) Global viSNE projection of non-naïve CD4 T cells for all subjects pooled, non-naïve CD4 T cells from HD, RD, and COVID-19 patients concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (H) viSNE projection of non-naïve CD4 T cell clusters identified by FlowSOM clustering. (I) Mean fluorescence intensity (MFI) as indicated, column-scaled z-score. (J) Percentage of non-naïve CD4 T cells from each cohort in each FlowSOM cluster.

T138

21724-21873

Sentence

denotes

Boxes represent IQR. (B, C, E, J) Each dot represents an individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 patient (red).

T139

21874-22000

Sentence

denotes

Significance determined by unpaired Wilcoxon test with BH correction: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

T140

22001-22218

Sentence

denotes

Projecting the global CD4 T cell differentiation patterns into the high-dimensional tSNE space again identified major alterations in the CD4 T cell response during COVID-19 infection compared to HDs and RDs (Fig. 3G).

T141

22219-22401

Sentence

denotes

In COVID-19 infection, there was a notable increase in density in tSNE regions that mapped to expression of CD38, HLA-DR, PD1, CD39, KI67, and CD95 (Fig. 3G), similar to CD8 T cells.

T142

22402-22516

Sentence

denotes

To gain more insight into these CD4 T cell changes, we again used a FlowSOM clustering approach (Fig. 3, H and I).

T143

22517-22801

Sentence

denotes

This analysis identified an increase in Clusters 13 and 14 in COVID-19 patients compared to HD and RD that represent populations expressing HLA-DR, CD38, PD1, KI67 and CD95, as well as Cluster 15 that contained Tbet+CX3CR1+ “effector-like” CD4 T cells (Fig. 3, I and J, and fig. S3G).

T144

22802-22957

Sentence

denotes

In contrast, this clustering approach identified reduction in CXCR5+ cTfh-like cells (Clusters 2, 3) in COVID-19 subjects compared to HD (Fig. 3, I and H).

T145

22958-23114

Sentence

denotes

Taken together, this multidimensional analysis revealed distinct populations of activated/proliferating CD4 T cells that were enriched in COVID-19 patients.

T146

23115-23373

Sentence

denotes

A key feature of COVID-19 disease is thought to be an inflammatory response that, at least in some patients, is linked to clinical disease manifestation (2, 4) and high levels of chemokines/cytokines, including IL-1RA, IL-6, IL-8, IL-10, and CXCL10 (11, 41).

T147

23374-23629

Sentence

denotes

To investigate the potential connection of inflammatory pathways to T cell responses, we performed 31-plex Luminex analysis on paired plasma and culture supernatants of anti-CD3/anti-CD28 stimulated PBMC from a subset of COVID-19 patients and HD controls.

T148

23630-23794

Sentence

denotes

Due to biosafety restrictions, only eight COVID-19 patient blood samples that were confirmed SARS-CoV2 RNA negative in the blood by PCR could be studied (fig. S4A).

T149

23795-23968

Sentence

denotes

Half of these COVID-19 patients had plasma CXCL10 concentrations that were ~15 fold higher than HD controls, whereas the remainder showed only a limited increase (fig. S4B).

T150

23969-24027

Sentence

denotes

CXCL9, CCL2, and IL-1RA were also significantly increased.

T151

24028-24148

Sentence

denotes

In contrast, chemokines involved in the recruitment of eosinophils (eotaxin) or activated T cells (CCL5) were decreased.

T152

24149-24378

Sentence

denotes

IL-6 was not elevated in this group of patients, in contrast to the subset of individuals tested clinically (fig. S1B), potentially because IL-6 was measured in the hospital setting often when systemic inflammation was suspected.

T153

24379-24646

Sentence

denotes

Following stimulation in vitro, PBMC from COVID-19 patients produced more CCL2, CXCL10, eotaxin, and IL-1RA than HD (fig. S4, C and D) and concentrations of CXCL10 and CCL2 correlated between the matched supernatant from stimulated PBMC and plasma samples (fig. S4E).

T154

24647-24779

Sentence

denotes

Finally, we investigated whether CD8 T cells from COVID-19 subjects were capable of producing IFNɣ following polyclonal stimulation.

T155

24780-25001

Sentence

denotes

Following ɑCD3+ɑCD28 stimulation, similar proportions of CD8 T cells from COVID-19 patients and HD controls produced IFNɣ, suggesting that PBMC from COVID-19 patients were responsive to TCR crosslinking (fig. S4, F to H).

T156

25002-25159

Sentence

denotes

The ability of T cells to produce IFNɣ following stimulation occurred in patients with increases in KI67 as well as patients with low KI67 (fig. S4, F to H).

T157

25160-25331

Sentence

denotes

Taken together, these data support the notion that a subgroup of COVID-19 patients has elevated systemic cytokines and chemokines, including myeloid recruiting chemokines.

T158

25333-25451

Sentence

denotes

COVID-19 infection is associated with increased frequencies of plasmablasts and proliferation of memory B cell subsets

T159

25452-25512

Sentence

denotes

B cell subpopulations were also altered in COVID-19 disease.

T160

25513-25727

Sentence

denotes

Whereas naïve B cell frequencies were similar in COVID-19 patients and RD or HD, the frequencies of class-switched (IgD−CD27+) and not-class-switched (IgD+CD27+) memory B cells were significantly reduced (Fig. 4A).

T161

25728-25839

Sentence

denotes

Conversely, frequencies of CD27−IgD− B cells and CD27+CD38+ PB were often robustly increased (Fig. 4, A and B).

T162

25840-25977

Sentence

denotes

In some cases, PB represented >30% of circulating B cells, similar to levels observed in acute Ebola or Dengue virus infections (42, 43).

T163

25978-26131

Sentence

denotes

However, these PB responses were only observed in ~2/3 of patients, with the remaining patients displaying PB frequencies similar to HD and RD (Fig. 4B).

T164

26132-26263

Sentence

denotes

KI67 expression was markedly elevated in all B cell subpopulations in COVID-19 patients compared to either control group (Fig. 4C).

T165

26264-26381

Sentence

denotes

This observation suggests a role for an antigen-driven response to infection and/or lymphopenia-driven proliferation.

T166

26382-26476

Sentence

denotes

Higher KI67 in PB may reflect recent generation in the COVID-19 patients compared to HD or RD.

T167

26477-26570

Sentence

denotes

CXCR5 expression was also reduced on all major B cell subsets in COVID-19 patients (Fig. 4D).

T168

26571-26691

Sentence

denotes

Loss of CXCR5 was not specific to B cells, however, as expression was also decreased on non-naïve CD4 T cells (Fig. 4E).

T169

26692-26914

Sentence

denotes

Changes in the B cell subsets were not associated with co-infection, immune suppression, or treatment with steroids or other clinical features, though a possible negative association of IL-6 and PB was revealed (fig. S5A).

T170

26915-27041

Sentence

denotes

These observations suggest that the B cell response phenotype of COVID-19 disease was not simply due to systemic inflammation.

T171

27042-27172

Sentence

denotes

Fig. 4 Deep profiling of COVID-19 patient B cell populations reveals robust plasmablast populations and other B cell alterations.

T172

27173-28450

Sentence

denotes

(A) Gating strategy and frequencies of non-PB B cell subsets. (B) Representative flow cytometry plots and frequencies of PB; green line at upper decile of HD. (C) Representative flow cytometry plots and frequencies of KI67+ B cells. (D) (Left) Representative histograms of CXCR5 expression and (right) CXCR5 GMFI of B cell subsets. (E) CXCR5 GMFI of non-naïve CD4 T cells and cTfh. (F) Spearman correlation between PB and activated cTfh. (G) Spearman correlation between PB and anti-SARS-CoV2 IgG. (H and I) Spearman correlation between activated cTfh and anti-SARS-CoV2 (H) IgM and (I) IgG. (J) (Top) Global viSNE projection of B cells for all subjects pooled, with B cell populations of each cohort concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (K) Hierarchical clustering of Earth Mover’s Distance (EMD) using Pearson correlation, calculated pairwise for B cell populations for all subjects; row-scaled z-score. (L) Percentage of cohort in each EMD group. (M) Global viSNE projection of B cells for all subjects pooled, with EMD groups 1-3 concatenated and overlaid. (N) B cell clusters identified by FlowSOM clustering. (O) MFI as indicated; column-scaled z-score. (P) Percentage of B cells from each cohort in each FlowSOM cluster.

T173

28451-28791

Sentence

denotes

Boxes represent IQR. (A to F, P) Dots represent individual healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 (red) subjects. (A to E, P) Significance determined by unpaired Wilcoxon test with BH correction: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. (GtoI) Black horizontal line represents positive threshold.

T174

28792-28930

Sentence

denotes

During acute viral infections or vaccination, PB responses are transiently detectable in the blood and correlate with cTfh responses (40).

T175

28931-29104

Sentence

denotes

Comparing the frequency of PB to the frequency of total cTfh or activated cTfh, however, revealed a weak correlation only with activated cTfh (Fig. 4F and fig. S5, B and C).

T176

29105-29336

Sentence

denotes

Furthermore, some patients had robust activated cTfh responses but PB frequencies similar to controls, whereas other patients with robust PB responses had relatively low frequencies of activated cTfh (Fig. 4F and fig. S5, B and C).

T177

29337-29595

Sentence

denotes

However, there was also an association between PB frequency and CD38+HLA-DR+ or KI67+ CD4 T cells that might reflect a role for non-CXCR5+ CD4 T cell help (fig. S5D), but such a relationship did not exist for the equivalent CD8 T cell populations (fig. S5E).

T178

29596-29796

Sentence

denotes

Although ~70% of COVID-19 patients analyzed made antibodies against SARS-CoV2 spike protein (79/111 IgG; 77/115 IgM (44)), antibody levels did not correlate with PB frequencies (Fig. 4G and fig. S5F).

T179

29797-29920

Sentence

denotes

The occasional lack of antibody did not appear to be related to immunosuppression in a small number of patients (fig. S5G).

T180

29921-30160

Sentence

denotes

The lack of PB correlation with antibody suggests that a proportion of these large PB responses were: i) generated against SARS-CoV2 antigens other than the spike protein or ii) inflammation-driven and perhaps non-specific or low affinity.

T181

30161-30401

Sentence

denotes

Notably, anti-SARS-CoV2 IgG and IgM levels correlated with the activated, but not total, cTfh response, suggesting that at least a proportion of cTfh were providing SARS-CoV2-specific help to B cells (Fig. 4, H and I, and fig. S5, H and I).

T182

30402-30585

Sentence

denotes

Although defining the precise specificity of the robust PB populations will require future studies, these data suggest that at least some of the PB response is specific for SARS-CoV2.

T183

30586-30820

Sentence

denotes

Projecting the flow cytometry data for B cells from HD, RD, and COVID-19 patients in tSNE space revealed a distinct picture of B cell populations in COVID-19 compared to controls, whereas RD and HD were similar (Fig. 4J and fig. S5J).

T184

30821-30943

Sentence

denotes

The COVID-19 patient B cell phenotype was dominated by loss of CXCR5 and IgD compared to B cells from HD and RD (Fig. 4J).

T185

30944-31071

Sentence

denotes

Moreover, the robust PB response was apparent in the upper right section, highlighted by CD27, CD38, CD138, and KI67 (Fig. 4J).

T186

31072-31215

Sentence

denotes

The expression of KI67 and CD95 in these CD27+CD38+CD138+ PB (Fig. 4J) could suggest recent generation and/or emigration from germinal centers.

T187

31216-31349

Sentence

denotes

We next asked whether there were different groups of COVID-19 patients (or HD and RD) with global differences in the B cell response.

T188

31350-31582

Sentence

denotes

We used Earth Movers Distance (EMD) (45) to calculate similarities between the probability distributions within the tSNE map (Fig. 4J) and clustered so that individuals with the most similar distributions grouped together (Fig. 4K).

T189

31583-31736

Sentence

denotes

The majority of COVID-19 patients fell into two distinct groups (EMD Groups 1 and 3, Fig. 4L), suggesting two major “immunotypes” of the B cell response.

T190

31737-31972

Sentence

denotes

The remainder of the COVID-19 patients (~25%) clustered with the majority of the HD and all of the RD controls, supporting the observation that some individuals had limited evidence of response to infection in their B cell compartment.

T191

31973-32185

Sentence

denotes

To identify the population differences between HD, RD and COVID-19 patients, we performed FlowSOM clustering on the tSNE map, and also overlaid each individual EMD group onto this same tSNE map (Fig. 4, M and N).

T192

32186-32418

Sentence

denotes

EMD Group 2 containing mostly HD and RD was enriched for naive B cells (IgD+CD27−, Cluster 10) and CXCR5+IgD−CD27+ switched memory (Cluster 2) and, indeed, Clusters 2 and 10 were statistically reduced in COVID-19 patients (Fig. 4P).

T193

32419-32494

Sentence

denotes

EMD Groups 1 and 3 displayed distinct patterns across the FlowSOM clusters.

T194

32495-32646

Sentence

denotes

B cells from individuals in EMD Group 1 were enriched for the FlowSOM Clusters 1, 5, and 6, all of which were increased in COVID-19 patients (Fig. 4P).

T195

32647-32870

Sentence

denotes

FlowSOM Clusters 1 and 6 captured T-bet+ memory B cells whereas FlowSOM Cluster 5 contained the CD27+CD38+CD138+KI67+ PB, all of which were enriched in COVID-19 patients compared to controls (Fig. 4, O and P, and fig. S5K).

T196

32871-33107

Sentence

denotes

In contrast, B cells from COVID-19 patients in EMD Group 3 also showed enrichment for the PB FlowSOM Cluster 5, though less prominent than for EMD Group 1, but the T-bet+ memory B cell Cluster 1 was substantially reduced in EMD Group 3.

T197

33108-33328

Sentence

denotes

Thus, B cell responses were evident in many hospitalized COVID-19 patients, most often characterized by elevated PB, decreases in memory B cell subsets, enrichment in a T-bet+ B cell subset, and loss of CXCR5 expression.

T198

33329-33434

Sentence

denotes

Whether all of these changes in the B cell compartment were due to direct antiviral responses is unclear.

T199

33435-33661

Sentence

denotes

Although there was heterogeneity in the B cell responses, COVID-19 patients fell into two distinct patterns containing activated B cell responses and a third group of patients with little evidence of an active B cell response.

T200

33663-33736

Sentence

denotes

Temporal changes in immune cell populations occur during COVID-19 disease

T201

33737-33828

Sentence

denotes

A key question for hospitalized COVID-19 patients is how immune responses change over time.

T202

33829-34040

Sentence

denotes

Thus, we used the global tSNE projections of overall CD8 T cell, CD4 T cell, and B cell differentiation states to interrogate temporal changes in these populations between D0 and D7 of hospitalization (Fig. 5A).

T203

34041-34257

Sentence

denotes

Combining data for all patients revealed considerable stability of the tSNE distributions between D0 and D7 in CD8 T cell, CD4 T cell, and B cell populations, particularly for key regions of interest discussed above.

T204

34258-34456

Sentence

denotes

For example, for CD8 T cells, the region of the tSNE map containing KI67+ and CD38+HLA-DR+ CD8 T cell populations that was enriched in COVID-19 patients at D0 (Fig. 2) was preserved at D7 (Fig. 5A).

T205

34457-34550

Sentence

denotes

A similar temporal stability of CD4 T cell and B cell activation was also observed (Fig. 5A).

T206

34551-34633

Sentence

denotes

Fig. 5 Temporal relationships between immune responses and disease manifestation.

T207

34634-34821

Sentence

denotes

(A) Global viSNE projection of non-naïve CD8 T cells, non-naïve CD4 T cells, and B cells for all subjects pooled, with cells from COVID-19 patients at D0 and D7 concatenated and overlaid.

T208

34822-35093

Sentence

denotes

Frequencies of (B) KI67+ and HLA-DR+CD38+ CD4 T cells, (C) KI67+ and HLA-DR+CD38+ CD8 T cells, or (D) PBs as indicated for healthy donor (HD; green), recovered donor (RD; blue), or COVID-19 patients (red) with paired samples at D0 and D7 indicated by the connecting line.

T209

35094-35199

Sentence

denotes

Significance determined by paired Wilcoxon test: *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

T210

35200-35462

Sentence

denotes

Longitudinal patterns (see Methods) of (E) HLA-DR+CD38+ CD4 T cells or (F) PBs in COVID-19 patients shown as frequency and representative flow cytometry plots. (G) Spearman correlations of clinical parameters with longitudinal fold changes in immune populations.

T211

35463-35591

Sentence

denotes

Given this apparent stability between D0 and D7, we next investigated temporal changes in lymphocyte subpopulations of interest.

T212

35592-35902

Sentence

denotes

Although there were no obvious temporal changes in major phenotypically defined CD4 and CD8 T cell or B cell subsets, including plasmablasts (Fig. 5D), the frequencies of HLA-DR+CD38+ and KI67+ non-naïve CD4 (Fig. 5B) and KI67+ non-naïve CD8 T cells were statistically increased at D7 compared to D0 (Fig. 5C).

T213

35903-36082

Sentence

denotes

However, in all cases, these temporal patterns were complex, with frequencies of subpopulations in individual patients appearing to increase, decrease, or stay the same over time.

T214

36083-36253

Sentence

denotes

To quantify these inter-patient changes, we used a previously described data set (46) to define the stability of populations of interest in healthy individuals over time.

T215

36254-36433

Sentence

denotes

We then used the range of this variation over time to identify COVID-19 patients with changes in immune cell subpopulations beyond that expected in healthy subjects (see methods).

T216

36434-36629

Sentence

denotes

Using this approach, ~50% of patients had an increase in HLA-DR+CD38+ non-naïve CD4 T cells over time, whereas in ~30% of patients, these cells were stable and, in ~20%, they decreased (Fig. 5E).

T217

36630-36720

Sentence

denotes

For KI67+ non-naïve CD8 T cells, there were no individuals in whom the response decreased.

T218

36721-36820

Sentence

denotes

Instead, this proliferative CD8 T cell response stayed stable (~70%) or increased (~30%; fig. S6A).

T219

36821-37001

Sentence

denotes

Notably, for patients in the stable category, the median frequency of KI67+ non-naïve CD8 T cells was ~10%, almost 5-fold higher than the ~1% detected for HD and RD subjects (Figs.

T220

37002-37084

Sentence

denotes

5C and 2E), suggesting a sustained CD8 T cell proliferative response to infection.

T221

37085-37276

Sentence

denotes

A similar pattern was observed for HLA-DR+CD38+ non-naïve CD8 (fig. S6B), where only ~10% of patients had a decrease in this population, whereas ~65% were stable and ~25% increased over time.

T222

37277-37677

Sentence

denotes

The high and even increasing activated or proliferating CD8 and CD4 T cell responses over ~1 week during acute viral infection contrasted with the sharp peak of KI67 in CD8 and CD4 T cells during acute viral infections, including smallpox vaccination with live vaccinia virus (47), live attenuated yellow fever vaccine YFV-17D (48), acute influenza virus infection (49), and acute HIV infection (35).

T223

37678-37793

Sentence

denotes

Approximately 42% of patients had sustained PB responses, at high levels (>10% of B cells) in many cases (Fig. 5F).

T224

37794-37955

Sentence

denotes

Thus, some patients displayed dynamic changes in T cell or B cell activation over 1 week in the hospital, but there were also other patients who remained stable.

T225

37956-38147

Sentence

denotes

In the latter case, some patients remained stable without clear activation of key immune populations whereas others had stable T and or B cell activation or numerical perturbation (fig. S6C).

T226

38148-38340

Sentence

denotes

We next asked whether these T and B cell dynamics related to clinical measures of COVID-19 disease, by correlating changes in immune features from D0 to D7 with clinical information (Fig. 5G).

T227

38341-38387

Sentence

denotes

These analyses revealed distinct correlations.

T228

38388-38630

Sentence

denotes

Decreases in all populations of responding CD4 and CD8 T cells (HLA-DR+CD38+, KI67+, or activated cTfh) between D0 and D7 were positively correlated with PMN and WBC counts, suggesting a relationship between T cell activation and lymphopenia.

T229

38631-38734

Sentence

denotes

Furthermore, decreases in CD4 and CD8 HLA-DR+CD38+ T cells positively correlated with APACHE III score.

T230

38735-38840

Sentence

denotes

However, stable HLA-DR+CD38+ CD4 T cell responses correlated with coagulation complications and ferritin.

T231

38841-38955

Sentence

denotes

Whereas decreasing activated cTfh over time was related to co-infection, the opposite pattern was observed for PB.

T232

38956-39237

Sentence

denotes

Increases in proliferating KI67+ CD4 and CD8 T cells over time were positively correlated to increasing anti-SARS-CoV2 antibody from day 0 to day 7, suggesting that some individuals might have been hospitalized during the expansion phase of the antiviral immune response (Fig. 5G).

T233

39238-39341

Sentence

denotes

Finally, neither Remdesivir nor HCQ treatment correlated with any of these immune features in Fig. 5G).

T234

39342-39557

Sentence

denotes

Examining categorical rather than continuous clinical data, 80% of patients with decreasing PB over time had hyperlipidemia, whereas only 20% of patients with increasing PB over time had this comorbidity (fig. S6D).

T235

39558-39822

Sentence

denotes

All patients who had decreasing CD38+HLA-DR+ CD8 T cells from day 0 to day 7 were treated with early vasoactive medication or inhaled nitric oxide whereas these treatments were less common for patients with stable or increasing CD38+HLA-DR+ CD8 T cells (fig. S6E).

T236

39823-39985

Sentence

denotes

In contrast, vasoactive medication, inhaled nitric oxide, and early steroid treatment were equally common in patients with increasing or decreasing PB (fig. S6D).

T237

39986-40093

Sentence

denotes

Similar patterns were apparent for other T cell populations and these categorical clinical data (fig. S6F).

T238

40094-40229

Sentence

denotes

Thus, the trajectory of change in the T and B cell response in COVID-19 patients was strongly connected to clinical metrics of disease.

T239

40231-40360

Sentence

denotes

Identifying “immunotypes” and relationships between circulating B and T cell responses with disease severity in COVID-19 patients

T240

40361-40717

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

40718-40825

Sentence

denotes

We then asked how changes in T and B cell populations defined above on D0 were related to disease severity.

T242

40826-40978

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

40979-41174

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

41175-41335

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

41336-41456

Sentence

denotes

Fig. 6 High dimensional analysis of immune phenotypes with clinical data reveals distinct COVID-19 patient immunotypes.

T246

41457-41551

Sentence

denotes

(A) NIH ordinal scale for COVID-19 clinical severity. (B) Frequencies of major immune subsets.

T247

41552-42045

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

42046-42244

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

42245-42366

Sentence

denotes

Relative expression (according to heat scale) shown for both individual patients (points) and overall density (contours).

T250

42367-43044

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

43045-43111

Sentence

denotes

There were two challenges with extracting meaning from these data.

T252

43112-43238

Sentence

denotes

First, there was considerable inter-patient heterogeneity for each of these immune features related to disease severity score.

T253

43239-43396

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

43397-43519

Sentence

denotes

Thus, we next visualized major T and B cell subpopulation data as it related to clinical disease severity score (Fig. 6C).

T255

43520-43642

Sentence

denotes

Data were clustered based on immune features and then overlaid with the disease severity score over time for each patient.

T256

43643-43764

Sentence

denotes

This analysis revealed groups of patients with similar composite immune signatures of T and B cell populations (Fig. 6C).

T257

43765-43912

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

43913-44125

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

44126-44338

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

44339-44666

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

44667-44864

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

44865-44995

Sentence

denotes

An orthogonal vertical axis coordinate (“Component 2”) also existed that captured non-overlapping aspects of the immune landscape.

T263

44996-45118

Sentence

denotes

We next calculated the mean of Component 1 for each patient group, with COVID-19 patients separated by severity (Fig. 6E).

T264

45119-45233

Sentence

denotes

The contribution of Component 1 clearly increased in a stepwise manner with increasing disease severity (Fig. 6F).

T265

45234-45308

Sentence

denotes

Interestingly, RD were subtly positioned between HD and COVID-19 patients.

T266

45309-45475

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

45476-45588

Sentence

denotes

We next investigated how the UMAP Components were associated with individual immune features (tables S5 and S6).

T268

45589-45725

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

45726-45772

Sentence

denotes

PB also associated with Component 1 (Fig. 6G).

T270

45773-45861

Sentence

denotes

Other individual B cell features were differentially captured by UMAP Component 1 and 2.

T271

45862-46026

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

46027-46246

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

46247-46431

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

46432-46570

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

46571-46628

Sentence

denotes

We next took advantage of the FlowSOM clustering in Figs.

T276

46629-46780

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

46781-46999

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

47000-47237

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

47238-47505

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

47506-47628

Sentence

denotes

In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H).

T281

47629-47832

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

47833-48001

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

48002-48119

Sentence

denotes

The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G).

T284

48120-48280

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

48281-48492

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

48493-48656

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

48657-48776

Sentence

denotes

Several antibody features also correlated with Component 1 consistent with some of the immune features discussed above.

T288

48777-49001

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

49002-49197

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

49198-49496

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

49497-49665

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

49666-50082

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

50083-50119

Sentence

denotes

However, the data presented in Figs.

T294

50120-50213

Sentence

denotes

1 to 5 also suggested a subset of patients with minimal activation of T and B cell responses.

T295

50214-50409

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

50410-50577

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

50578-50900

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

50901-51011

Sentence

denotes

These data further emphasize the different ways patients can present and possibly succumb to COVID-19 disease.

T299

51012-51121

Sentence

denotes

These patterns may be related to pre-existing conditions in combination with immune response characteristics.

T300

51122-51243

Sentence

denotes

It is likely that additional immune features, such as comprehensive serum cytokine measurements, will improve this model.

T301

51244-51477

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).

T302

51479-51489

Sentence

denotes

Discussion

T303

51490-51565

Sentence

denotes

The T and B cell response to SARS-CoV2 infection remains poorly understood.

T304

51566-51717

Sentence

denotes

Some studies suggest an overaggressive immune response leading to immunopathology (51) whereas others suggest T cell exhaustion or dysfunction (12–14).

T305

51718-51844

Sentence

denotes

Autopsies revealed high virus levels in the respiratory tract and other tissues (52), suggesting ineffective immune responses.

T306

51845-51963

Sentence

denotes

Nevertheless, non-hospitalized subjects who recovered from COVID-19 had evidence of virus-specific T cell memory (53).

T307

51964-52117

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

52118-52285

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

52286-52459

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

52460-52597

Sentence

denotes

Such knowledge would address the critical question of whether there is a common profile of immune dysfunction in critically ill patients.

T311

52598-52736

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

52737-52862

Sentence

denotes

To interrogate the immune response patterns of COVID-19 hospitalized patients, we studied a cohort of ~125 COVID-19 patients.

T313

52863-53183

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

53184-53234

Sentence

denotes

Using this approach, we made several key findings.

T315

53235-53347

Sentence

denotes

First, a defining feature of COVID-19 disease in hospitalized patients was heterogeneity of the immune response.

T316

53348-53567

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

53568-53742

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

53743-54311

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

54312-54470

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

54471-54661

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

54662-54774

Sentence

denotes

Thus, these immunotypes may reflect fundamental differences in the ways patients respond to SARS-CoV2 infection.

T322

54775-54846

Sentence

denotes

A second key observation from these studies was the robust PB response.

T323

54847-54953

Sentence

denotes

Some patients had PB frequencies rivaling those found in acute Ebola or Dengue infection (34, 42, 43, 55).

T324

54954-55054

Sentence

denotes

Furthermore, blood PB frequencies are typically correlated with blood activated cTfh responses (40).

T325

55055-55143

Sentence

denotes

However, in COVID-19 patients, this relationship between PB and activated cTfh was weak.

T326

55144-55438

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

55439-55638

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

55639-55763

Sentence

denotes

Most ICU patients made SARS-CoV2-specific antibodies, suggesting that at least part of the PB response was antigen-specific.

T329

55764-55904

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

55905-56036

Sentence

denotes

Future studies will be needed to address the antigen specificity, ontogeny, and role in pathogenesis for these robust PB responses.

T331

56037-56163

Sentence

denotes

A striking feature of some patients with strong T and B cell activation and proliferation was the durability of this response.

T332

56164-56254

Sentence

denotes

This T and B activation was interesting considering clinical lymphopenia in many patients.

T333

56255-56315

Sentence

denotes

This lymphopenia, however, was preferential for CD8 T cells.

T334

56316-56517

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

56518-56596

Sentence

denotes

Indeed CD95 was associated with activated T cell clusters in COVID-19 disease.

T336

56597-56807

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

56808-56972

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

56973-57224

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

57225-57341

Sentence

denotes

These ideas would fit with an overaggressive immune response and/or “cytokine storm” (2) in this subset of patients.

T340

57342-57528

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

57529-57698

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

57699-57887

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

57888-58054

Sentence

denotes

Using correlative analyses, we observed relationships between features of the different immunotypes, patient comorbidities, and clinical features of COVID-19 disease.

T344

58055-58280

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

58281-58436

Sentence

denotes

Moreover, this UMAP embedding approach allowed us to connect these integrated immune signatures back to specific clinically measurable features of disease.

T346

58437-58575

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

58576-58987

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

58988-59238

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

59239-59440

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

59441-59627

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

59628-59843

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

59844-60111

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

60112-60255

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

60256-60431

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.

T355

60433-60454

Sentence

denotes

Materials and methods

T356

60456-60504

Sentence

denotes

Patients, subjects, and clinical data collection

T357

60505-60691

Sentence

denotes

Patients admitted to the Hospital of the University of Pennsylvania with a positive SARS-CoV2 PCR test were screened and approached for informed consent within 3 days of hospitalization.

T358

60692-60795

Sentence

denotes

Healthy donors (HD) were adults with no prior diagnosis of or recent symptoms consistent with COVID-19.

T359

60796-60886

Sentence

denotes

Normal reference ranges for HDs were the UPenn clinical laboratory values shaded in green.

T360

60887-61057

Sentence

denotes

Recovered COVID-19 subjects (RD) were adults with a prior positive COVID-19 PCR test by self-report who met the definition of recovery by the Centers for Disease Control.

T361

61058-61222

Sentence

denotes

HD and RD were recruited initially by word of mouth and subsequently through a centralized University of Pennsylvania resource website for COVID-19-related studies.

T362

61223-61272

Sentence

denotes

Peripheral blood was collected from all subjects.

T363

61273-61390

Sentence

denotes

For inpatients, clinical data were abstracted from the electronic medical record into standardized case report forms.

T364

61391-61556

Sentence

denotes

ARDS was categorized in accordance with the Berlin definition reflecting each subject’s worst oxygenation level and with physician adjudication of chest radiographs.

T365

61557-61736

Sentence

denotes

APACHE III scoring was based on data collected in the first 24 hours of ICU admission or the first 24 hours of hospital admission for subjects admitted to general inpatient units.

T366

61737-61829

Sentence

denotes

Clinical laboratory data were abstracted from the date closest to research blood collection.

T367

61830-61874

Sentence

denotes

HD and RD completed a survey about symptoms.

T368

61875-61984

Sentence

denotes

After enrollment, the clinical team determined three patients to be COVID-negative and/or PCR false positive.

T369

61985-62039

Sentence

denotes

Two of these patients were classified as Immunotype 3.

T370

62040-62123

Sentence

denotes

In keeping with inclusion criteria, these subjects were maintained in the analysis.

T371

62124-62242

Sentence

denotes

The statistical significance reported in Fig. 6K did not change when analysis was repeated without the three patients.

T372

62243-62416

Sentence

denotes

All participants or their surrogates provided informed consent in accordance with protocols approved by the regional ethical research boards and the Declaration of Helsinki.

T373

62418-62435

Sentence

denotes

Sample processing

T374

62436-62510

Sentence

denotes

Peripheral blood was collected into sodium heparin tubes (BD, Cat#367874).

T375

62511-62578

Sentence

denotes

Tubes were spun (15 min, 3000 rpm, RT), plasma removed, and banked.

T376

62579-62769

Sentence

denotes

Remaining whole blood was diluted 1:1 with 1% RPMI (table S7) and layered into a SEPMATE tube (STEMCELL Technologies, Cat#85450) pre-loaded with lymphoprep (Alere Technologies, Cat#1114547).

T377

62770-62958

Sentence

denotes

SEPMATE tubes were spun (10 min, 1200xg, RT) and the PBMC layer collected, washed with 1% RPMI (10 min, 1600 rpm, RT) and treated with ACK lysis buffer (5 min, ThermoFisher, Cat#A1049201).

T378

62959-63038

Sentence

denotes

Samples were filtered with a 70 μm filter, counted, and aliquoted for staining.

T379

63040-63068

Sentence

denotes

Antibody panels and staining

T380

63069-63146

Sentence

denotes

Approximately 1-5×106 freshly isolated PBMCs were used per patient per stain.

T381

63147-63227

Sentence

denotes

See table S7 for buffer information and table S8 for antibody panel information.

T382

63228-63349

Sentence

denotes

PBMCs were stained with live/dead mix (100 μl, 10 min, RT), washed with FACS buffer, and spun down (1500 rpm, 5 min, RT).

T383

63350-63464

Sentence

denotes

PBMCs were incubated with 100 μl of Fc block (RT, 10 min) before a second wash (FACS buffer, 1500 rpm, 5 min, RT).

T384

63465-63566

Sentence

denotes

Pellet was resuspended in 25 μl of chemokine receptor staining mix, and incubated at 37°C for 20 min.

T385

63567-63703

Sentence

denotes

Following incubation, 25 μl of surface receptor staining mix was directly added and the PBMCs were incubated at RT for a further 45 min.

T386

63704-63877

Sentence

denotes

PBMCs were washed (FACS buffer, 1500 rpm, 5 min, RT) and stained with 50 μl of secondary antibody mix for 20 min at RT, then washed again (FACS buffer, 1500 rpm, 5 min, RT).

T387

63878-64019

Sentence

denotes

Samples were fixed and permeabilized by incubating in 100 μl of Fix/Perm buffer (RT, 30 min) and washed in Perm Buffer (1800 rpm, 5 min, RT).

T388

64020-64087

Sentence

denotes

PBMCs were stained with 50μl of intracellular mix overnight at 4°C.

T389

64088-64203

Sentence

denotes

The following morning, samples were washed (Perm Buffer, 1800 rpm, 5 min, RT) and further fixed in 50 μl of 4% PFA.

T390

64204-64317

Sentence

denotes

Prior to acquisition, samples were diluted to 1% PFA and 10,000 counting beads added per sample (BD, Cat#335925).

T391

64318-64352

Sentence

denotes

Live/dead mix was prepared in PBS.

T392

64353-64491

Sentence

denotes

For the surface receptor and chemokine staining mix, antibodies were diluted in FACS buffer with 50% BD Brilliant Buffer (BD, Cat#566349).

T393

64492-64537

Sentence

denotes

Intracellular mix was diluted in Perm Buffer.

T394

64539-64553

Sentence

denotes

Flow cytometry

T395

64554-64609

Sentence

denotes

Samples were acquired on a 5 laser BD FACS Symphony A5.

T396

64610-64717

Sentence

denotes

Standardized SPHERO rainbow beads (Spherotech, Cat#RFP-30-5A) were used to track and adjust PMTs over time.

T397

64718-64793

Sentence

denotes

UltraComp eBeads (ThermoFisher, Cat#01-2222-42) were used for compensation.

T398

64794-64848

Sentence

denotes

Up to 2 × 106 live PBMC were acquired per each sample.

T399

64850-64857

Sentence

denotes

Luminex

T400

64858-64954

Sentence

denotes

PBMCs from patients were thawed and rested overnight at 37°C in complete RPMI (cRPMI, table S7).

T401

64955-65069

Sentence

denotes

96-well flat bottom plates were coated with 1 μg/mL of anti-CD3 (UCHT1, #BE0231, BioXell) in PBS at 4°C overnight.

T402

65070-65155

Sentence

denotes

The next day, cells were collected and plated at 1 × 105/well in 100 μl in duplicate.

T403

65156-65269

Sentence

denotes

2 μg/mL of anti-human CD28/CD49d was added to the wells containing plate-bound anti-CD3 (Clone L293, 347690, BD).

T404

65270-65400

Sentence

denotes

PBMCs were stimulated or left unstimulated for 16 hours, spun down (1200 rpm, 10 min) and 85 μL/well of supernatant was collected.

T405

65401-65523

Sentence

denotes

Plasma from matched subjects was thawed on ice, spun (3000 rpm, 1 min) to remove debris, and 85 μl collected in duplicate.

T406

65524-65671

Sentence

denotes

Luminex assay was run according to manufacturer’s instructions, using a custom human cytokine 31-plex panel (EMD Millipore Corporation, SPRCUS707).

T407

65672-65950

Sentence

denotes

The panel included: EGF, FGF-2, Eotaxin, sIL-2Ra, G-CSF, GM-CSF, IFN-α2, IFN-γ, IL-10, IL-12P40, IL-12P70, IL-13, IL-15, IL-17A, IL-1Ra, HGF, IL-1β, CXCL9/MIG, IL-2, IL-4, IL-5, IL-6, IL-7, CXCL8/IL-8, CXCL10/IP-10, CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, RANTES, TNF-α, and VEGF.

T408

65951-66044

Sentence

denotes

Assay plates were measured using a Luminex FlexMAP 3D instrument (Thermofisher, Cat#APX1342).

T409

66045-66138

Sentence

denotes

Data acquisition and analysis were done using xPONENT software www.luminexcorp.com/xponent/).

T410

66139-66197

Sentence

denotes

Data quality was examined based on the following criteria:

T411

66198-66312

Sentence

denotes

The standard curve for each analyte has a 5P R2 value > 0.95 with or without minor fitting using xPONENT software.

T412

66313-66504

Sentence

denotes

To pass assay technical quality control, the results for two controls in the kit needed to be within the 95% of CI (confidence interval) provided by the vendor for >25 of the tested analytes.

T413

66505-66580

Sentence

denotes

No further tests were done on samples with results out of range low (<OOR).

T414

66581-66755

Sentence

denotes

Samples with results that were out of range high (>OOR) or greater than the standard curve maximum value (SC max) were not tested at higher dilutions without further request.

T415

66757-66803

Sentence

denotes

Intracellular stain after CD3/CD28 stimulation

T416

66804-66917

Sentence

denotes

96-well flat bottom plates were coated with 1μg/mL of anti-CD3 (UCHT1, #BE0231, BioXell) in PBS at 4°C overnight.

T417

66918-67028

Sentence

denotes

The next day, cells were collected and plated at 1 × 105/well in 100 μl with 1/1000 of GolgiPlug (BD #555029).

T418

67029-67141

Sentence

denotes

2μg/mL of anti-human CD28/CD49d was added to the wells containing plate-bound anti-CD3 (Clone L293, 347690, BD).

T419

67142-67286

Sentence

denotes

GolgiPlug-treated PBMCs were stimulated or left unstimulated for 16 hours, spun down (1200 rpm, 10 min) and were stained for intracellular IFNɣ.

T420

67288-67336

Sentence

denotes

Longitudinal analysis D0-D7 and patient grouping

T421

67337-67624

Sentence

denotes

To identify subjects where the frequency of specific immune cell populations increased, decreased or stayed stable over time (day 0 to day 7), where data was available we used a previously published dataset to establish a standard range of fold change over time in a healthy cohort (44).

T422

67625-67817

Sentence

denotes

A fold change greater than the mean fold change ± 2 standard deviations was considered an increase, less than this range was considered a decrease, and within this range was considered stable.

T423

67818-67932

Sentence

denotes

Where this data was not available, a fold change from day 0 to day 7 of between 0.5 and 1.5 was considered stable.

T424

67933-68012

Sentence

denotes

A fold change <0.5 was considered decreased, and >1.5 was considered increased.

T425

68013-68263

Sentence

denotes

In order to eliminate redundant tests and maximize statistical power, the pairwise statistical tests shown in Fig. 5G were performed using fold-change as a continuous metric, irrespective of the discrete up/stable/down classification described above.

T426

68264-68496

Sentence

denotes

Similarly, in fig. S9G, pairwise association tests between changes in UMAP Component coordinates and clinical data were performed using each difference value as a continuous metric, irrespective of the up/stable/down classification.

T427

68498-68541

Sentence

denotes

Correlation plots and heatmap visualization

T428

68542-68656

Sentence

denotes

Pairwise correlations between variables were calculated and visualized as a correlogram using R function corrplot.

T429

68657-68845

Sentence

denotes

Spearman's Rank Correlation coefficient (ρ) was indicated by square size and heat scale; significance indicated by: *p < 0.05, **p < 0.01, and ***p < 0.001; black box indicates FDR < 0.05.

T430

68846-68941

Sentence

denotes

Heatmaps were created to visualize variable values using R function pheatmap or complexheatmap.

T431

68943-68953

Sentence

denotes

Statistics

T432

68954-69127

Sentence

denotes

Due to the heterogeneity of clinical and flow cytometric data, non-parametric tests of association were preferentially used throughout this study unless otherwise specified.

T433

69128-69410

Sentence

denotes

Correlation coefficients between ordered features (including discrete ordinal, continuous scale, or a mixture of the two) were quantified by the Spearman rank correlation coefficient and significance was assessed by the corresponding non-parametric methods (null hypothesis: ρ = 0).

T434

69411-69611

Sentence

denotes

Tests of association between mixed continuous versus non-ordered categorical variables were performed by unpaired Wilcoxon test (for n = 2 categories) or by Kruskal-Wallis test (for n > 2 categories).

T435

69612-69688

Sentence

denotes

Association between categorical variables was assessed by Fisher-exact test.

T436

69689-69890

Sentence

denotes

For association testing illustrated in heatmaps, categorical variables with more than 2 categories (e.g., ABO blood type) were transformed into binary dummy variables for each category versus the rest.

T437

69891-70005

Sentence

denotes

All tests were performed two-sided, using a nominal significance threshold of P < 0.05 unless otherwise specified.

T438

70006-70198

Sentence

denotes

When appropriate to adjust for multiple hypothesis testing, false discovery rate (FDR) correction was performed using the Benjamini-Hochberg procedure at the FDR < 0.05 significance threshold.

T439

70199-70488

Sentence

denotes

Joint statistical modeling to adjust for confounding of demographic factors (age, sex, and race) when testing for association of UMAP Components 1 and 2 with the NIH Ordinal Severity Scale was performed using ordinal logistic regression provided by the polr function of the R package MASS.

T440

70489-70571

Sentence

denotes

Statistical analysis of flow cytometry data was performed using R package rstatix.

T441

70572-70663

Sentence

denotes

Other details, if any, for each experiment are provided within the relevant figure legends.

T442

70665-70718

Sentence

denotes

High dimensional data analysis of flow cytometry data

T443

70719-70796

Sentence

denotes

viSNE and FlowSOM analysis were performed on Cytobank (https://cytobank.org).

T444

70797-71026

Sentence

denotes

B cells, non-naïve CD4 T cells, and non-naïve CD8 T cells were analyzed separately. viSNE analysis was performed using equal sampling of 1000 cells from each FCS file, with 5000 iterations, a perplexity of 30, and a theta of 0.5.

T445

71027-71226

Sentence

denotes

For B cells, the following markers were used to generate the viSNE maps: CD45RA, IgD, CXCR5, CD138, Eomes, TCF-1, CD38, CD95, CCR7, CD21, KI67, CD27, CX3CR1, CD39, T-bet, HLA-DR, CD16, CD19 and CD20.

T446

71227-71403

Sentence

denotes

For non-naïve CD4 and CD8 T cells, the following markers were used: CD45RA, PD1, CXCR5, TCF-1, CD38, CD95, Eomes, CCR7, KI67, CD16, CD27, CX3CR1, CD39, CD20, T-bet, and HLA-DR.

T447

71404-71477

Sentence

denotes

Resulting viSNE maps were fed into the FlowSOM clustering algorithm (59).

T448

71478-71603

Sentence

denotes

For each cell subset, a new self-organizing map (SOM) was generated using hierarchical consensus clustering on the tSNE axes.

T449

71604-71710

Sentence

denotes

For each SOM, 225 clusters and 10 or 15 metaclusters were identified for B cells and T cells respectively.

T450

71711-71971

Sentence

denotes

To group individuals based on B cell landscape, pairwise Earth Mover’s Distance (EMD) value was calculated on the B cell tSNE axes for all COVID-19 day 0 patients, healthy donors, and recovered donors using the emdist package in R as previously described (60).

T451

71972-72049

Sentence

denotes

Resulting scores were hierarchically clustered using the hclust package in R.

T452

72051-72067

Sentence

denotes

Batch correction

T453

72068-72156

Sentence

denotes

During the sample acquisition period, the flow panel was changed to remove one antibody.

T454

72157-72288

Sentence

denotes

Batch correction was performed for samples acquired before and after this change to remove potential bias from downstream analysis.

T455

72289-72563

Sentence

denotes

Because the primary flow features were expressed as a fraction of the parent population (falling in the 0-to-1 interval) a variance stabilizing transform (logit) was first applied to each data value, prior to re-centering the second panel to have the same mean as the first.

T456

72564-72675

Sentence

denotes

After mean-centering, data were transformed back to the original fraction of parent scale by inverse transform.

T457

72676-72788

Sentence

denotes

This procedure was applied separately to all 553 flow features annotated in the main text and supplemental data.

T458

72789-72913

Sentence

denotes

Notably, this procedure avoids any batch-corrected feature values artificially falling outside of the original 0 to 1 range.

T459

72914-73067

Sentence

denotes

Following batch correction, neither UMAP Component 1 nor Component 2 had a statistically significant difference between panels by unpaired Wilcoxon test.

T460

73069-73150

Sentence

denotes

Visualizing variation of flow cytometric features across the UMAP embedding space

T461

73151-73294

Sentence

denotes

A feature-weighted kernel density was computed across all COVID-19 patients, and was displayed as a contour plot (Fig. 6G and fig. S8, A to D).

T462

73295-73681

Sentence

denotes

Whereas traditional kernel density methods apply the same base kernel function to every point to visualize point density, here the base kernel function centered at each individual COVID-19 patient sample was instead weighted (multiplied) by the Z-transform (mean-centered and standard deviation-scaled) of the log-transformed input feature prior to computing the overall kernel density.

T463

73682-73894

Sentence

denotes

This weighting procedure facilitated visualization of the overall feature gradients (going from relatively low-to-high expression) across UMAP coordinates independent of the different range of each input feature.

T464

73895-74146

Sentence

denotes

A radially symmetric two-dimensional Gaussian was used as the base kernel function with a variance parameter equal to one-half, which was tuned to be sufficiently broad in order to smooth out local discontinuities and best visualize feature gradients.

T465

74148-74174

Sentence

denotes

Definition of immunotype 3

T466

74175-74559

Sentence

denotes

To define COVID-19 patients with low or absent immune responses, classified as immunotype 3, the intersection of the bottom 50% of 5 different flow parameters was used: PB as % of B cells, KI67+ as % of non-naïve CD4 T cells, KI67+ as % of non-naïve CD8 T cells, HLA-DR+CD38+ as % of non-naïve CD4 T cells, HLA-DR+CD38+ as % of non-naïve CD8 T cells—graphically displayed in fig. S10.

PMC:7402624 / 1040-75599 JSON TXT 12 Projects

Annnotations TAB TSV DIC JSON TextAE

PMC:7402624 / 1040-75599 JSONTXT 12 Projects

Annnotations TAB TSV DIC JSON TextAE

PMC:7402624 / 1040-75599 JSON TXT 12 Projects