PubAnnotation

Id	Subject	Object	Predicate	Lexical cue
T1	0-101	Sentence	denotes	Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications
T2	103-111	Sentence	denotes	Abstract
T3	112-218	Sentence	denotes	COVID-19 is currently a global pandemic, but human immune responses to the virus remain poorly understood.
T4	219-333	Sentence	denotes	We analyzed 125 COVID-19 patients, and compared recovered to healthy individuals using high dimensional cytometry.
T5	334-472	Sentence	denotes	Integrated analysis of ~200 immune and ~50 clinical features revealed activation of T cell and B cell subsets in a proportion of patients.
T6	473-621	Sentence	denotes	A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses reaching >30% of circulating B cells.
T7	622-708	Sentence	denotes	However, another subgroup had lymphocyte activation comparable to uninfected subjects.
T8	709-826	Sentence	denotes	Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change.
T9	827-940	Sentence	denotes	These analyses identified three “immunotypes” associated with poor clinical trajectories versus improving health.
T10	941-1038	Sentence	denotes	These immunotypes may have implications for the design of therapeutics and vaccines for COVID-19.
T11	1040-1136	Sentence	denotes	The COVID-19 pandemic has to date caused >7 million infections resulting in over 400,000 deaths.
T12	1137-1329	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	1330-1380	Sentence	denotes	The case fatality rate can be as high as ~10% (1).
T14	1381-1503	Sentence	denotes	Some severe COVID-19 patients display an acute respiratory distress syndrome (ARDS), reflecting severe respiratory damage.
T15	1504-1644	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	1645-1833	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	1834-2090	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	2091-2360	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	2361-2578	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	2579-2790	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	2791-3030	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	3031-3144	Sentence	denotes	Furthermore, how this activation should be viewed in the context of COVID-19 lymphopenia (18–20) remains unclear.
T23	3145-3264	Sentence	denotes	Most patients seroconvert within 7-14 days of infection and increased plasmablasts (PB) have been reported (16, 21–23).
T24	3265-3352	Sentence	denotes	However, the role of humoral responses in the pathogenesis of COVID-19 remains unclear.
T25	3353-3503	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	3504-3585	Sentence	denotes	IgA levels also can remain high and may correlate with disease severity (25, 27).
T27	3586-3688	Sentence	denotes	Furthermore, neutralizing antibodies can control SARS-CoV2 infection in vitro and in vivo (4, 28, 29).
T28	3689-3787	Sentence	denotes	Indeed, convalescent plasma containing neutralizing antibodies can improve clinical symptoms (30).
T29	3788-3987	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	3988-4180	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	4181-4308	Sentence	denotes	However, many studies describe small cohorts or even single patients, limiting a comprehensive interrogation of this diversity.
T32	4309-4488	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	4489-4744	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	4746-4845	Sentence	denotes	Acute SARS-CoV2 infection in humans results in broad changes in circulating immune cell populations
T35	4846-5067	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	5068-5152	Sentence	denotes	Blood was collected at enrollment (typically ~24-72 hours after admission; Fig. 1A).
T37	5153-5235	Sentence	denotes	Additional samples were obtained from patients who remained hospitalized on day 7.
T38	5236-5452	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	5453-5550	Sentence	denotes	Clinical metadata are available from the COVID-19 patients over the course of disease (table S1).
T40	5551-5754	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	5755-5874	Sentence	denotes	Fig. 1 Clinical characterization of patient cohorts, inflammatory markers, and quantification of major immune subsets.
T42	5875-6061	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	6062-6431	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	6432-6548	Sentence	denotes	Dark and light gray shaded regions represent clinical normal range and normal range based on study HD, respectively.
T45	6549-6799	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	6800-6926	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	6927-7137	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	7138-7235	Sentence	denotes	For COVID-19 patients, median BMI was 29 (range 16-78), and 68% were African American (table S2).
T49	7236-7337	Sentence	denotes	Comorbidities in COVID-19 patients were dominated by cardiovascular risk factors (83% of the cohort).
T50	7338-7442	Sentence	denotes	Nearly 20% of subjects suffered from chronic kidney disease and 18% had a previous thromboembolic event.
T51	7443-7612	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	7613-7720	Sentence	denotes	45% of the patients were treated with hydroxychloroquine (HCQ), 31% with steroids, and 29% with remdesivir.
T53	7721-7792	Sentence	denotes	Eighteen individuals died in the hospital or within a 30 day follow-up.
T54	7793-7907	Sentence	denotes	The majority of the patients were symptomatic at diagnosis and were enrolled ~9 days after initiation of symptoms.
T55	7908-8060	Sentence	denotes	Approximately 30% of patients required mechanical ventilation at presentation, with additional extracorporeal membrane oxygenation (ECMO) in four cases.
T56	8061-8185	Sentence	denotes	As has been reported for other COVID-19 patients (31), this COVID-19 cohort presented with a clinical inflammatory syndrome.
T57	8186-8391	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	8392-8469	Sentence	denotes	Similarly, troponin and NT-proBNP were increased in some patients (fig. S1B).
T59	8470-8654	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	8655-8791	Sentence	denotes	Although white blood cell counts (WBC) were mostly normal, individual leukocyte populations were altered in COVID-19 patients (Fig. 1B).
T61	8792-8906	Sentence	denotes	A subset of patients had high PMN counts (fig. S1B) as described previously (8, 32) and in a companion study (33).
T62	8907-9017	Sentence	denotes	Furthermore, approximately half of the COVID-19 patients were clinically lymphopenic (ALC <1 THO/ul, Fig. 1B).
T63	9018-9115	Sentence	denotes	In contrast, monocyte, eosinophil, and basophil counts were mostly normal (Fig. 1B and fig. S1B).
T64	9116-9240	Sentence	denotes	To examine potential associations between these clinical features, we performed correlation analysis (Fig. 1C and fig. S1C).
T65	9241-9474	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	9475-9607	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	9608-9850	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	9851-10037	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	10038-10243	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	10244-10297	Sentence	denotes	We first focused on the major lymphocyte populations.
T71	10298-10536	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	10537-10704	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	10705-10798	Sentence	denotes	This non-B, non-T cell population is also interrogated in more detail in the companion study.
T74	10799-11255	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	11256-11406	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	11407-11511	Sentence	denotes	We next asked if the changes in these lymphocyte populations were related to clinical metrics (Fig. 1H).
T77	11512-11664	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	11665-11839	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	11840-11994	Sentence	denotes	Thus, hospitalized COVID-19 patients present with a complex constellation of clinical features that may be associated with altered lymphocyte populations.
T80	11996-12080	Sentence	denotes	SARS-CoV2 infection is associated with CD8 T cell activation in a subset of patients
T81	12081-12228	Sentence	denotes	We next applied high-dimensional flow cytometric analysis to further investigate lymphocyte activation and differentiation during COVID-19 disease.
T82	12229-12489	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	12490-12603	Sentence	denotes	COVID-19 patients clearly segregated from RD and HD in PCA space, whereas RD and HD largely overlapped (Fig. 2A).
T84	12604-12679	Sentence	denotes	We investigated the immune features driving this COVID-19 immune signature.
T85	12680-12755	Sentence	denotes	Given their role in response to viral infection, we focused on CD8 T cells.
T86	12756-13105	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	13106-13226	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	13227-13329	Sentence	denotes	Furthermore, the frequency of CD39+ cells was increased in COVID-19 patients compared to HD (Fig. 2D).
T89	13330-13473	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	13474-13589	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	13590-13716	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	13717-13970	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	13971-14604	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	14605-14757	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	14758-14884	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	14885-15041	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	15042-15188	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	15189-15343	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	15344-15536	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	15537-15703	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	15704-15797	Sentence	denotes	However, the magnitude of the KI67+ or CD38+HLA-DR+ CD8 T cells varied widely in this cohort.
T102	15798-15902	Sentence	denotes	The frequency of KI67+ CD8 T cells correlated with the frequency of CD38+HLA-DR+ CD8 T cells (fig. S2D).
T103	15903-16148	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	16149-16414	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	16415-16574	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	16575-16800	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	16801-16907	Sentence	denotes	To gain more insights, we applied global high-dimensional mapping of the 27-parameter flow cytometry data.
T108	16908-17043	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	17044-17324	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	17325-17511	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	17512-17733	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	17734-17973	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	17974-18138	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	18139-18299	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	18300-18448	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	18450-18560	Sentence	denotes	SARS-CoV2 infection is associated with heterogeneous CD4 T cell responses and activation of CD4 T cell subsets
T117	18561-18728	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	18729-19063	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	19064-19184	Sentence	denotes	These analyses revealed a relative loss of naïve CD4 T cells compared to controls, but increased EM2 and EMRA (Fig. 3B).
T120	19185-19373	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	19374-19535	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	19536-19720	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	19721-19881	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	19882-19964	Sentence	denotes	Although some subjects had increased activation of EMRA, this was less pronounced.
T125	19965-20074	Sentence	denotes	In contrast, PD1 expression was increased in all other non-naïve populations compared to HD or RD (fig. S3C).
T126	20075-20205	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	20206-20343	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	20344-20454	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	20455-20686	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	20687-20921	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	20922-21118	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	21119-21267	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	21268-21565	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	21566-21673	Sentence	denotes	Fig. 3 CD4 T cell activation in a subset of COVID-19 patients associates with distinct CD4 T cell subsets.
T135	21674-21895	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	21896-22138	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	22139-22763	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	22764-22913	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	22914-23040	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	23041-23258	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	23259-23441	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	23442-23556	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	23557-23841	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	23842-23997	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	23998-24154	Sentence	denotes	Taken together, this multidimensional analysis revealed distinct populations of activated/proliferating CD4 T cells that were enriched in COVID-19 patients.
T146	24155-24413	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	24414-24669	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	24670-24834	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	24835-25008	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	25009-25067	Sentence	denotes	CXCL9, CCL2, and IL-1RA were also significantly increased.
T151	25068-25188	Sentence	denotes	In contrast, chemokines involved in the recruitment of eosinophils (eotaxin) or activated T cells (CCL5) were decreased.
T152	25189-25418	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	25419-25686	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	25687-25819	Sentence	denotes	Finally, we investigated whether CD8 T cells from COVID-19 subjects were capable of producing IFNɣ following polyclonal stimulation.
T155	25820-26041	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	26042-26199	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	26200-26371	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	26373-26491	Sentence	denotes	COVID-19 infection is associated with increased frequencies of plasmablasts and proliferation of memory B cell subsets
T159	26492-26552	Sentence	denotes	B cell subpopulations were also altered in COVID-19 disease.
T160	26553-26767	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	26768-26879	Sentence	denotes	Conversely, frequencies of CD27−IgD− B cells and CD27+CD38+ PB were often robustly increased (Fig. 4, A and B).
T162	26880-27017	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	27018-27171	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	27172-27303	Sentence	denotes	KI67 expression was markedly elevated in all B cell subpopulations in COVID-19 patients compared to either control group (Fig. 4C).
T165	27304-27421	Sentence	denotes	This observation suggests a role for an antigen-driven response to infection and/or lymphopenia-driven proliferation.
T166	27422-27516	Sentence	denotes	Higher KI67 in PB may reflect recent generation in the COVID-19 patients compared to HD or RD.
T167	27517-27610	Sentence	denotes	CXCR5 expression was also reduced on all major B cell subsets in COVID-19 patients (Fig. 4D).
T168	27611-27731	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	27732-27954	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	27955-28081	Sentence	denotes	These observations suggest that the B cell response phenotype of COVID-19 disease was not simply due to systemic inflammation.
T171	28082-28212	Sentence	denotes	Fig. 4 Deep profiling of COVID-19 patient B cell populations reveals robust plasmablast populations and other B cell alterations.
T172	28213-29490	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	29491-29831	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	29832-29970	Sentence	denotes	During acute viral infections or vaccination, PB responses are transiently detectable in the blood and correlate with cTfh responses (40).
T175	29971-30144	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	30145-30376	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	30377-30635	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	30636-30836	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	30837-30960	Sentence	denotes	The occasional lack of antibody did not appear to be related to immunosuppression in a small number of patients (fig. S5G).
T180	30961-31200	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	31201-31441	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	31442-31625	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	31626-31860	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	31861-31983	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	31984-32111	Sentence	denotes	Moreover, the robust PB response was apparent in the upper right section, highlighted by CD27, CD38, CD138, and KI67 (Fig. 4J).
T186	32112-32255	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	32256-32389	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	32390-32622	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	32623-32776	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	32777-33012	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	33013-33225	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	33226-33458	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	33459-33534	Sentence	denotes	EMD Groups 1 and 3 displayed distinct patterns across the FlowSOM clusters.
T194	33535-33686	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	33687-33910	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	33911-34147	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	34148-34368	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	34369-34474	Sentence	denotes	Whether all of these changes in the B cell compartment were due to direct antiviral responses is unclear.
T199	34475-34701	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	34703-34776	Sentence	denotes	Temporal changes in immune cell populations occur during COVID-19 disease
T201	34777-34868	Sentence	denotes	A key question for hospitalized COVID-19 patients is how immune responses change over time.
T202	34869-35080	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	35081-35297	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	35298-35496	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	35497-35590	Sentence	denotes	A similar temporal stability of CD4 T cell and B cell activation was also observed (Fig. 5A).
T206	35591-35673	Sentence	denotes	Fig. 5 Temporal relationships between immune responses and disease manifestation.
T207	35674-35861	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	35862-36133	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	36134-36239	Sentence	denotes	Significance determined by paired Wilcoxon test: p < 0.05, p < 0.01, p < 0.001, and **p < 0.0001.
T210	36240-36502	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	36503-36631	Sentence	denotes	Given this apparent stability between D0 and D7, we next investigated temporal changes in lymphocyte subpopulations of interest.
T212	36632-36942	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	36943-37122	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	37123-37293	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	37294-37473	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	37474-37669	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	37670-37760	Sentence	denotes	For KI67+ non-naïve CD8 T cells, there were no individuals in whom the response decreased.
T218	37761-37860	Sentence	denotes	Instead, this proliferative CD8 T cell response stayed stable (~70%) or increased (~30%; fig. S6A).
T219	37861-38041	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	38042-38124	Sentence	denotes	5C and 2E), suggesting a sustained CD8 T cell proliferative response to infection.
T221	38125-38316	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	38317-38717	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	38718-38833	Sentence	denotes	Approximately 42% of patients had sustained PB responses, at high levels (>10% of B cells) in many cases (Fig. 5F).
T224	38834-38995	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	38996-39187	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	39188-39380	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	39381-39427	Sentence	denotes	These analyses revealed distinct correlations.
T228	39428-39670	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	39671-39774	Sentence	denotes	Furthermore, decreases in CD4 and CD8 HLA-DR+CD38+ T cells positively correlated with APACHE III score.
T230	39775-39880	Sentence	denotes	However, stable HLA-DR+CD38+ CD4 T cell responses correlated with coagulation complications and ferritin.
T231	39881-39995	Sentence	denotes	Whereas decreasing activated cTfh over time was related to co-infection, the opposite pattern was observed for PB.
T232	39996-40277	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	40278-40381	Sentence	denotes	Finally, neither Remdesivir nor HCQ treatment correlated with any of these immune features in Fig. 5G).
T234	40382-40597	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	40598-40862	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	40863-41025	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	41026-41133	Sentence	denotes	Similar patterns were apparent for other T cell populations and these categorical clinical data (fig. S6F).
T238	41134-41269	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	41271-41400	Sentence	denotes	Identifying “immunotypes” and relationships between circulating B and T cell responses with disease severity in COVID-19 patients
T240	41401-41757	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	41758-41865	Sentence	denotes	We then asked how changes in T and B cell populations defined above on D0 were related to disease severity.
T242	41866-42018	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	42019-42214	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	42215-42375	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	42376-42496	Sentence	denotes	Fig. 6 High dimensional analysis of immune phenotypes with clinical data reveals distinct COVID-19 patient immunotypes.
T246	42497-42591	Sentence	denotes	(A) NIH ordinal scale for COVID-19 clinical severity. (B) Frequencies of major immune subsets.
T247	42592-43085	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	43086-43284	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	43285-43406	Sentence	denotes	Relative expression (according to heat scale) shown for both individual patients (points) and overall density (contours).
T250	43407-44084	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	44085-44151	Sentence	denotes	There were two challenges with extracting meaning from these data.
T252	44152-44278	Sentence	denotes	First, there was considerable inter-patient heterogeneity for each of these immune features related to disease severity score.
T253	44279-44436	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	44437-44559	Sentence	denotes	Thus, we next visualized major T and B cell subpopulation data as it related to clinical disease severity score (Fig. 6C).
T255	44560-44682	Sentence	denotes	Data were clustered based on immune features and then overlaid with the disease severity score over time for each patient.
T256	44683-44804	Sentence	denotes	This analysis revealed groups of patients with similar composite immune signatures of T and B cell populations (Fig. 6C).
T257	44805-44952	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	44953-45165	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	45166-45378	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	45379-45706	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	45707-45904	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	45905-46035	Sentence	denotes	An orthogonal vertical axis coordinate (“Component 2”) also existed that captured non-overlapping aspects of the immune landscape.
T263	46036-46158	Sentence	denotes	We next calculated the mean of Component 1 for each patient group, with COVID-19 patients separated by severity (Fig. 6E).
T264	46159-46273	Sentence	denotes	The contribution of Component 1 clearly increased in a stepwise manner with increasing disease severity (Fig. 6F).
T265	46274-46348	Sentence	denotes	Interestingly, RD were subtly positioned between HD and COVID-19 patients.
T266	46349-46515	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	46516-46628	Sentence	denotes	We next investigated how the UMAP Components were associated with individual immune features (tables S5 and S6).
T268	46629-46765	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	46766-46812	Sentence	denotes	PB also associated with Component 1 (Fig. 6G).
T270	46813-46901	Sentence	denotes	Other individual B cell features were differentially captured by UMAP Component 1 and 2.
T271	46902-47066	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	47067-47286	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	47287-47471	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	47472-47610	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	47611-47668	Sentence	denotes	We next took advantage of the FlowSOM clustering in Figs.
T276	47669-47820	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	47821-48039	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	48040-48277	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	48278-48545	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	48546-48668	Sentence	denotes	In addition, Component 1 was negatively correlated with CD4 T cell FlowSOM Clusters 2 and 3 that contained cTfh (Fig. 6H).
T281	48669-48872	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	48873-49041	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	49042-49159	Sentence	denotes	The most dynamic changes in Component 1 were associated with the largest increases in IgM antibody levels (fig. S9G).
T284	49160-49320	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	49321-49532	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	49533-49696	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	49697-49816	Sentence	denotes	Several antibody features also correlated with Component 1 consistent with some of the immune features discussed above.
T288	49817-50041	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	50042-50237	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	50238-50536	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	50537-50705	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	50706-51122	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	51123-51159	Sentence	denotes	However, the data presented in Figs.
T294	51160-51253	Sentence	denotes	1 to 5 also suggested a subset of patients with minimal activation of T and B cell responses.
T295	51254-51449	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	51450-51617	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	51618-51940	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	51941-52051	Sentence	denotes	These data further emphasize the different ways patients can present and possibly succumb to COVID-19 disease.
T299	52052-52161	Sentence	denotes	These patterns may be related to pre-existing conditions in combination with immune response characteristics.
T300	52162-52283	Sentence	denotes	It is likely that additional immune features, such as comprehensive serum cytokine measurements, will improve this model.
T301	52284-52517	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	52519-52529	Sentence	denotes	Discussion
T303	52530-52605	Sentence	denotes	The T and B cell response to SARS-CoV2 infection remains poorly understood.
T304	52606-52757	Sentence	denotes	Some studies suggest an overaggressive immune response leading to immunopathology (51) whereas others suggest T cell exhaustion or dysfunction (12–14).
T305	52758-52884	Sentence	denotes	Autopsies revealed high virus levels in the respiratory tract and other tissues (52), suggesting ineffective immune responses.
T306	52885-53003	Sentence	denotes	Nevertheless, non-hospitalized subjects who recovered from COVID-19 had evidence of virus-specific T cell memory (53).
T307	53004-53157	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	53158-53325	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	53326-53499	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	53500-53637	Sentence	denotes	Such knowledge would address the critical question of whether there is a common profile of immune dysfunction in critically ill patients.
T311	53638-53776	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	53777-53902	Sentence	denotes	To interrogate the immune response patterns of COVID-19 hospitalized patients, we studied a cohort of ~125 COVID-19 patients.
T313	53903-54223	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	54224-54274	Sentence	denotes	Using this approach, we made several key findings.
T315	54275-54387	Sentence	denotes	First, a defining feature of COVID-19 disease in hospitalized patients was heterogeneity of the immune response.
T316	54388-54607	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	54608-54782	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	54783-55351	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	55352-55510	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	55511-55701	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	55702-55814	Sentence	denotes	Thus, these immunotypes may reflect fundamental differences in the ways patients respond to SARS-CoV2 infection.
T322	55815-55886	Sentence	denotes	A second key observation from these studies was the robust PB response.
T323	55887-55993	Sentence	denotes	Some patients had PB frequencies rivaling those found in acute Ebola or Dengue infection (34, 42, 43, 55).
T324	55994-56094	Sentence	denotes	Furthermore, blood PB frequencies are typically correlated with blood activated cTfh responses (40).
T325	56095-56183	Sentence	denotes	However, in COVID-19 patients, this relationship between PB and activated cTfh was weak.
T326	56184-56478	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	56479-56678	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	56679-56803	Sentence	denotes	Most ICU patients made SARS-CoV2-specific antibodies, suggesting that at least part of the PB response was antigen-specific.
T329	56804-56944	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	56945-57076	Sentence	denotes	Future studies will be needed to address the antigen specificity, ontogeny, and role in pathogenesis for these robust PB responses.
T331	57077-57203	Sentence	denotes	A striking feature of some patients with strong T and B cell activation and proliferation was the durability of this response.
T332	57204-57294	Sentence	denotes	This T and B activation was interesting considering clinical lymphopenia in many patients.
T333	57295-57355	Sentence	denotes	This lymphopenia, however, was preferential for CD8 T cells.
T334	57356-57557	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	57558-57636	Sentence	denotes	Indeed CD95 was associated with activated T cell clusters in COVID-19 disease.
T336	57637-57847	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	57848-58012	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	58013-58264	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	58265-58381	Sentence	denotes	These ideas would fit with an overaggressive immune response and/or “cytokine storm” (2) in this subset of patients.
T340	58382-58568	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	58569-58738	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	58739-58927	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	58928-59094	Sentence	denotes	Using correlative analyses, we observed relationships between features of the different immunotypes, patient comorbidities, and clinical features of COVID-19 disease.
T344	59095-59320	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	59321-59476	Sentence	denotes	Moreover, this UMAP embedding approach allowed us to connect these integrated immune signatures back to specific clinically measurable features of disease.
T346	59477-59615	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	59616-60027	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	60028-60278	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	60279-60480	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	60481-60667	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	60668-60883	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	60884-61151	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	61152-61295	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	61296-61471	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	61473-61494	Sentence	denotes	Materials and methods
T356	61496-61544	Sentence	denotes	Patients, subjects, and clinical data collection
T357	61545-61731	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	61732-61835	Sentence	denotes	Healthy donors (HD) were adults with no prior diagnosis of or recent symptoms consistent with COVID-19.
T359	61836-61926	Sentence	denotes	Normal reference ranges for HDs were the UPenn clinical laboratory values shaded in green.
T360	61927-62097	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	62098-62262	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	62263-62312	Sentence	denotes	Peripheral blood was collected from all subjects.
T363	62313-62430	Sentence	denotes	For inpatients, clinical data were abstracted from the electronic medical record into standardized case report forms.
T364	62431-62596	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	62597-62776	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	62777-62869	Sentence	denotes	Clinical laboratory data were abstracted from the date closest to research blood collection.
T367	62870-62914	Sentence	denotes	HD and RD completed a survey about symptoms.
T368	62915-63024	Sentence	denotes	After enrollment, the clinical team determined three patients to be COVID-negative and/or PCR false positive.
T369	63025-63079	Sentence	denotes	Two of these patients were classified as Immunotype 3.
T370	63080-63163	Sentence	denotes	In keeping with inclusion criteria, these subjects were maintained in the analysis.
T371	63164-63282	Sentence	denotes	The statistical significance reported in Fig. 6K did not change when analysis was repeated without the three patients.
T372	63283-63456	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	63458-63475	Sentence	denotes	Sample processing
T374	63476-63550	Sentence	denotes	Peripheral blood was collected into sodium heparin tubes (BD, Cat#367874).
T375	63551-63618	Sentence	denotes	Tubes were spun (15 min, 3000 rpm, RT), plasma removed, and banked.
T376	63619-63809	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	63810-63998	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	63999-64078	Sentence	denotes	Samples were filtered with a 70 μm filter, counted, and aliquoted for staining.
T379	64080-64108	Sentence	denotes	Antibody panels and staining
T380	64109-64186	Sentence	denotes	Approximately 1-5×106 freshly isolated PBMCs were used per patient per stain.
T381	64187-64267	Sentence	denotes	See table S7 for buffer information and table S8 for antibody panel information.
T382	64268-64389	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	64390-64504	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	64505-64606	Sentence	denotes	Pellet was resuspended in 25 μl of chemokine receptor staining mix, and incubated at 37°C for 20 min.
T385	64607-64743	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	64744-64917	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	64918-65059	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	65060-65127	Sentence	denotes	PBMCs were stained with 50μl of intracellular mix overnight at 4°C.
T389	65128-65243	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	65244-65357	Sentence	denotes	Prior to acquisition, samples were diluted to 1% PFA and 10,000 counting beads added per sample (BD, Cat#335925).
T391	65358-65392	Sentence	denotes	Live/dead mix was prepared in PBS.
T392	65393-65531	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	65532-65577	Sentence	denotes	Intracellular mix was diluted in Perm Buffer.
T394	65579-65593	Sentence	denotes	Flow cytometry
T395	65594-65649	Sentence	denotes	Samples were acquired on a 5 laser BD FACS Symphony A5.
T396	65650-65757	Sentence	denotes	Standardized SPHERO rainbow beads (Spherotech, Cat#RFP-30-5A) were used to track and adjust PMTs over time.
T397	65758-65833	Sentence	denotes	UltraComp eBeads (ThermoFisher, Cat#01-2222-42) were used for compensation.
T398	65834-65888	Sentence	denotes	Up to 2 × 106 live PBMC were acquired per each sample.
T399	65890-65897	Sentence	denotes	Luminex
T400	65898-65994	Sentence	denotes	PBMCs from patients were thawed and rested overnight at 37°C in complete RPMI (cRPMI, table S7).
T401	65995-66109	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	66110-66195	Sentence	denotes	The next day, cells were collected and plated at 1 × 105/well in 100 μl in duplicate.
T403	66196-66309	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	66310-66440	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	66441-66563	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	66564-66711	Sentence	denotes	Luminex assay was run according to manufacturer’s instructions, using a custom human cytokine 31-plex panel (EMD Millipore Corporation, SPRCUS707).
T407	66712-66990	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	66991-67084	Sentence	denotes	Assay plates were measured using a Luminex FlexMAP 3D instrument (Thermofisher, Cat#APX1342).
T409	67085-67178	Sentence	denotes	Data acquisition and analysis were done using xPONENT software www.luminexcorp.com/xponent/).
T410	67179-67237	Sentence	denotes	Data quality was examined based on the following criteria:
T411	67238-67352	Sentence	denotes	The standard curve for each analyte has a 5P R2 value > 0.95 with or without minor fitting using xPONENT software.
T412	67353-67544	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	67545-67620	Sentence	denotes	No further tests were done on samples with results out of range low (<OOR).
T414	67621-67795	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	67797-67843	Sentence	denotes	Intracellular stain after CD3/CD28 stimulation
T416	67844-67957	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	67958-68068	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	68069-68181	Sentence	denotes	2μg/mL of anti-human CD28/CD49d was added to the wells containing plate-bound anti-CD3 (Clone L293, 347690, BD).
T419	68182-68326	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	68328-68376	Sentence	denotes	Longitudinal analysis D0-D7 and patient grouping
T421	68377-68664	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	68665-68857	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	68858-68972	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	68973-69052	Sentence	denotes	A fold change <0.5 was considered decreased, and >1.5 was considered increased.
T425	69053-69303	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	69304-69536	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	69538-69581	Sentence	denotes	Correlation plots and heatmap visualization
T428	69582-69696	Sentence	denotes	Pairwise correlations between variables were calculated and visualized as a correlogram using R function corrplot.
T429	69697-69885	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	69886-69981	Sentence	denotes	Heatmaps were created to visualize variable values using R function pheatmap or complexheatmap.
T431	69983-69993	Sentence	denotes	Statistics
T432	69994-70167	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	70168-70450	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	70451-70651	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	70652-70728	Sentence	denotes	Association between categorical variables was assessed by Fisher-exact test.
T436	70729-70930	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	70931-71045	Sentence	denotes	All tests were performed two-sided, using a nominal significance threshold of P < 0.05 unless otherwise specified.
T438	71046-71238	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	71239-71528	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	71529-71611	Sentence	denotes	Statistical analysis of flow cytometry data was performed using R package rstatix.
T441	71612-71703	Sentence	denotes	Other details, if any, for each experiment are provided within the relevant figure legends.
T442	71705-71758	Sentence	denotes	High dimensional data analysis of flow cytometry data
T443	71759-71836	Sentence	denotes	viSNE and FlowSOM analysis were performed on Cytobank (https://cytobank.org).
T444	71837-72066	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	72067-72266	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	72267-72443	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	72444-72517	Sentence	denotes	Resulting viSNE maps were fed into the FlowSOM clustering algorithm (59).
T448	72518-72643	Sentence	denotes	For each cell subset, a new self-organizing map (SOM) was generated using hierarchical consensus clustering on the tSNE axes.
T449	72644-72750	Sentence	denotes	For each SOM, 225 clusters and 10 or 15 metaclusters were identified for B cells and T cells respectively.
T450	72751-73011	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	73012-73089	Sentence	denotes	Resulting scores were hierarchically clustered using the hclust package in R.
T452	73091-73107	Sentence	denotes	Batch correction
T453	73108-73196	Sentence	denotes	During the sample acquisition period, the flow panel was changed to remove one antibody.
T454	73197-73328	Sentence	denotes	Batch correction was performed for samples acquired before and after this change to remove potential bias from downstream analysis.
T455	73329-73603	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	73604-73715	Sentence	denotes	After mean-centering, data were transformed back to the original fraction of parent scale by inverse transform.
T457	73716-73828	Sentence	denotes	This procedure was applied separately to all 553 flow features annotated in the main text and supplemental data.
T458	73829-73953	Sentence	denotes	Notably, this procedure avoids any batch-corrected feature values artificially falling outside of the original 0 to 1 range.
T459	73954-74107	Sentence	denotes	Following batch correction, neither UMAP Component 1 nor Component 2 had a statistically significant difference between panels by unpaired Wilcoxon test.
T460	74109-74190	Sentence	denotes	Visualizing variation of flow cytometric features across the UMAP embedding space
T461	74191-74334	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	74335-74721	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	74722-74934	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	74935-75186	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	75188-75214	Sentence	denotes	Definition of immunotype 3
T466	75215-75599	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.
T467	75601-75616	Sentence	denotes	Acknowledgments
T468	75617-75715	Sentence	denotes	The authors thank patients and blood donors, their families and surrogates, and medical personnel.
T469	75716-75727	Sentence	denotes	We thank L.
T470	75728-75765	Sentence	denotes	Bershaw for recruitment of HD and RD.
T471	75766-75777	Sentence	denotes	We thank S.
T472	75778-75827	Sentence	denotes	Ngiow for essential infrastructure support and C.
T473	75828-75904	Sentence	denotes	Ash for donation of computational equipment and design of schematic figures.
T474	75905-75983	Sentence	denotes	We thank the Wherry lab for discussions and critically reading the manuscript.
T475	75984-75992	Sentence	denotes	Funding:
T476	75993-76224	Sentence	denotes	This work was supported by the University of Pennsylvania Institute for Immunology Glick COVID-19 research award (MRB), NIH AI105343, AI082630, and the Allen Institute for Immunology (EJW) and NIH grants HL137006 and H137915 (NJM).
T477	76225-76271	Sentence	denotes	ACH was funded by grant CA230157 from the NIH.
T478	76272-76310	Sentence	denotes	DM and JG were funded by T32 CA009140.
T479	76311-76347	Sentence	denotes	ZC was funded by NIH grant CA234842.
T480	76348-76378	Sentence	denotes	DAO was funded by NHLBI StARR:
T481	76379-76392	Sentence	denotes	1R38HL143613.
T482	76393-76508	Sentence	denotes	NJM reports funding to her institution from Athersys, Inc., Biomarck, Inc., and the Marcus Foundation for Research.
T483	76509-76567	Sentence	denotes	JRG is a Cancer Research Institute-Mark Foundation Fellow.
T484	76568-76736	Sentence	denotes	JRG, JEW, CA, AH, and EJW are supported by the Parker Institute for Cancer Immunotherapy which supports the Cancer Immunology program at the University of Pennsylvania.
T485	76737-76782	Sentence	denotes	The authors declare no conflicts of interest.
T486	76783-76893	Sentence	denotes	Author contributions: DM, NJM, MJB, and EJW conceived the project; DM, JRG, AEB, and EJW designed experiments.
T487	76894-77070	Sentence	denotes	NM conceived the clinical cohort, obtained clinical samples and metadata from COVID-19 patients and provided clinical input; OK and JD provided clinical samples from HD and RD.
T488	77071-77137	Sentence	denotes	AEB and KD coordinated clinical sample procurement and processing.
T489	77138-77207	Sentence	denotes	DM, ARG, LKC, MBP, NH, JK, AP, FC, and SFL processed patient samples.
T490	77208-77335	Sentence	denotes	DM, ZC, and YJH stained and JEW acquired flow cytometry samples; JRG, AEB, and KN performed downstream flow cytometry analysis.
T491	77336-77373	Sentence	denotes	HR and SCC performed qRT-PCR of PBMC.
T492	77374-77420	Sentence	denotes	DM, SFL, and FC performed Luminex experiments.
T493	77421-77518	Sentence	denotes	ECG, EMA, MEW, SG, CPA, MJB, and SEH analyzed COVID-19 patient plasma and provided antibody data.
T494	77519-77653	Sentence	denotes	ACH and LAV provided additional clinical data; CA compiled and JRG, DO, and CA analyzed clinical metadata with input from ACH and LAV.
T495	77654-77778	Sentence	denotes	JRG, DAO, SM, and EJW designed data analysis and JRG, ARG, CA, DAO, and SM performed computational and statistical analyses.
T496	77779-77822	Sentence	denotes	DM, JRG, ARG, CA, and DAO compiled figures.
T497	77823-77886	Sentence	denotes	LKC, MBP, SA, ACH, LAV, NJM and MB provided intellectual input.
T498	77887-77972	Sentence	denotes	DM, AEB, ARG, JEW, and EJW wrote the manuscript; all authors reviewed the manuscript.
T499	77973-78130	Sentence	denotes	Competing interests: E.J.W. has consulting agreements with and/or is on the scientific advisory board for Merck, Roche, Pieris, Elstar, and Surface Oncology.
T500	78131-78195	Sentence	denotes	E.J.W. is a founder of Surface Oncology and Arsenal Biosciences.

T1

0-101

Sentence

denotes

Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications

T2

103-111

Sentence

denotes

Abstract

T3

112-218

Sentence

denotes

COVID-19 is currently a global pandemic, but human immune responses to the virus remain poorly understood.

T4

219-333

Sentence

denotes

We analyzed 125 COVID-19 patients, and compared recovered to healthy individuals using high dimensional cytometry.

T5

334-472

Sentence

denotes

Integrated analysis of ~200 immune and ~50 clinical features revealed activation of T cell and B cell subsets in a proportion of patients.

T6

473-621

Sentence

denotes

A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses reaching >30% of circulating B cells.

T7

622-708

Sentence

denotes

However, another subgroup had lymphocyte activation comparable to uninfected subjects.

T8

709-826

Sentence

denotes

Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change.

T9

827-940

Sentence

denotes

These analyses identified three “immunotypes” associated with poor clinical trajectories versus improving health.

T10

941-1038

Sentence

denotes

These immunotypes may have implications for the design of therapeutics and vaccines for COVID-19.

T11

1040-1136

Sentence

denotes

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

T12

1137-1329

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

1330-1380

Sentence

denotes

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

T14

1381-1503

Sentence

denotes

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

T15

1504-1644

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

1645-1833

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

1834-2090

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

2091-2360

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

2361-2578

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

2579-2790

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

2791-3030

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

3031-3144

Sentence

denotes

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

T23

3145-3264

Sentence

denotes

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

T24

3265-3352

Sentence

denotes

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

T25

3353-3503

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

3504-3585

Sentence

denotes

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

T27

3586-3688

Sentence

denotes

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

T28

3689-3787

Sentence

denotes

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

T29

3788-3987

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

3988-4180

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

4181-4308

Sentence

denotes

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

T32

4309-4488

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

4489-4744

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

4746-4845

Sentence

denotes

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

T35

4846-5067

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

5068-5152

Sentence

denotes

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

T37

5153-5235

Sentence

denotes

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

T38

5236-5452

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

5453-5550

Sentence

denotes

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

T40

5551-5754

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

5755-5874

Sentence

denotes

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

T42

5875-6061

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

6062-6431

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

6432-6548

Sentence

denotes

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

T45

6549-6799

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

6800-6926

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

6927-7137

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

7138-7235

Sentence

denotes

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

T49

7236-7337

Sentence

denotes

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

T50

7338-7442

Sentence

denotes

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

T51

7443-7612

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

7613-7720

Sentence

denotes

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

T53

7721-7792

Sentence

denotes

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

T54

7793-7907

Sentence

denotes

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

T55

7908-8060

Sentence

denotes

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

T56

8061-8185

Sentence

denotes

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

T57

8186-8391

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

8392-8469

Sentence

denotes

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

T59

8470-8654

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

8655-8791

Sentence

denotes

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

T61

8792-8906

Sentence

denotes

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

T62

8907-9017

Sentence

denotes

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

T63

9018-9115

Sentence

denotes

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

T64

9116-9240

Sentence

denotes

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

T65

9241-9474

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

9475-9607

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

9608-9850

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

9851-10037

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

10038-10243

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

10244-10297

Sentence

denotes

We first focused on the major lymphocyte populations.

T71

10298-10536

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

10537-10704

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

10705-10798

Sentence

denotes

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

T74

10799-11255

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

11256-11406

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

11407-11511

Sentence

denotes

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

T77

11512-11664

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

11665-11839

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

11840-11994

Sentence

denotes

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

T80

11996-12080

Sentence

denotes

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

T81

12081-12228

Sentence

denotes

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

T82

12229-12489

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

12490-12603

Sentence

denotes

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

T84

12604-12679

Sentence

denotes

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

T85

12680-12755

Sentence

denotes

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

T86

12756-13105

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

13106-13226

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

13227-13329

Sentence

denotes

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

T89

13330-13473

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

13474-13589

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

13590-13716

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

13717-13970

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

13971-14604

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

14605-14757

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

14758-14884

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

14885-15041

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

15042-15188

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

15189-15343

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

15344-15536

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

15537-15703

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

15704-15797

Sentence

denotes

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

T102

15798-15902

Sentence

denotes

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

T103

15903-16148

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

16149-16414

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

16415-16574

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

16575-16800

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

16801-16907

Sentence

denotes

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

T108

16908-17043

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

17044-17324

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

17325-17511

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

17512-17733

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

17734-17973

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

17974-18138

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

18139-18299

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

18300-18448

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

18450-18560

Sentence

denotes

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

T117

18561-18728

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

18729-19063

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

19064-19184

Sentence

denotes

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

T120

19185-19373

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

19374-19535

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

19536-19720

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

19721-19881

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

19882-19964

Sentence

denotes

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

T125

19965-20074

Sentence

denotes

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

T126

20075-20205

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

20206-20343

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

20344-20454

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

20455-20686

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

20687-20921

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

20922-21118

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

21119-21267

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

21268-21565

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

21566-21673

Sentence

denotes

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

T135

21674-21895

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

21896-22138

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

22139-22763

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

22764-22913

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

22914-23040

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

23041-23258

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

23259-23441

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

23442-23556

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

23557-23841

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

23842-23997

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

23998-24154

Sentence

denotes

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

T146

24155-24413

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

24414-24669

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

24670-24834

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

24835-25008

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

25009-25067

Sentence

denotes

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

T151

25068-25188

Sentence

denotes

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

T152

25189-25418

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

25419-25686

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

25687-25819

Sentence

denotes

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

T155

25820-26041

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

26042-26199

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

26200-26371

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

26373-26491

Sentence

denotes

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

T159

26492-26552

Sentence

denotes

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

T160

26553-26767

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

26768-26879

Sentence

denotes

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

T162

26880-27017

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

27018-27171

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

27172-27303

Sentence

denotes

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

T165

27304-27421

Sentence

denotes

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

T166

27422-27516

Sentence

denotes

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

T167

27517-27610

Sentence

denotes

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

T168

27611-27731

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

27732-27954

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

27955-28081

Sentence

denotes

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

T171

28082-28212

Sentence

denotes

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

T172

28213-29490

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

29491-29831

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

29832-29970

Sentence

denotes

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

T175

29971-30144

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

30145-30376

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

30377-30635

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

30636-30836

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

30837-30960

Sentence

denotes

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

T180

30961-31200

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

31201-31441

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

31442-31625

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

31626-31860

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

31861-31983

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

31984-32111

Sentence

denotes

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

T186

32112-32255

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

32256-32389

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

32390-32622

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

32623-32776

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

32777-33012

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

33013-33225

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

33226-33458

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

33459-33534

Sentence

denotes

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

T194

33535-33686

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

33687-33910

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

33911-34147

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

34148-34368

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

34369-34474

Sentence

denotes

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

T199

34475-34701

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

34703-34776

Sentence

denotes

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

T201

34777-34868

Sentence

denotes

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

T202

34869-35080

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

35081-35297

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

35298-35496

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

35497-35590

Sentence

denotes

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

T206

35591-35673

Sentence

denotes

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

T207

35674-35861

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

35862-36133

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

36134-36239

Sentence

denotes

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

T210

36240-36502

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

36503-36631

Sentence

denotes

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

T212

36632-36942

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

36943-37122

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

37123-37293

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

37294-37473

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

37474-37669

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

37670-37760

Sentence

denotes

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

T218

37761-37860

Sentence

denotes

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

T219

37861-38041

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

38042-38124

Sentence

denotes

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

T221

38125-38316

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

38317-38717

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

38718-38833

Sentence

denotes

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

T224

38834-38995

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

38996-39187

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

39188-39380

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

39381-39427

Sentence

denotes

These analyses revealed distinct correlations.

T228

39428-39670

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

39671-39774

Sentence

denotes

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

T230

39775-39880

Sentence

denotes

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

T231

39881-39995

Sentence

denotes

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

T232

39996-40277

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

40278-40381

Sentence

denotes

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

T234

40382-40597

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

40598-40862

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

40863-41025

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

41026-41133

Sentence

denotes

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

T238

41134-41269

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

41271-41400

Sentence

denotes

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

T240

41401-41757

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

41758-41865

Sentence

denotes

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

T242

41866-42018

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

42019-42214

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

42215-42375

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

42376-42496

Sentence

denotes

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

T246

42497-42591

Sentence

denotes

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

T247

42592-43085

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

43086-43284

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

43285-43406

Sentence

denotes

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

T250

43407-44084

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

44085-44151

Sentence

denotes

There were two challenges with extracting meaning from these data.

T252

44152-44278

Sentence

denotes

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

T253

44279-44436

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

44437-44559

Sentence

denotes

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

T255

44560-44682

Sentence

denotes

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

T256

44683-44804

Sentence

denotes

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

T257

44805-44952

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

44953-45165

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

45166-45378

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

45379-45706

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

45707-45904

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

45905-46035

Sentence

denotes

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

T263

46036-46158

Sentence

denotes

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

T264

46159-46273

Sentence

denotes

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

T265

46274-46348

Sentence

denotes

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

T266

46349-46515

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

46516-46628

Sentence

denotes

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

T268

46629-46765

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

46766-46812

Sentence

denotes

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

T270

46813-46901

Sentence

denotes

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

T271

46902-47066

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

47067-47286

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

47287-47471

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

47472-47610

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

47611-47668

Sentence

denotes

We next took advantage of the FlowSOM clustering in Figs.

T276

47669-47820

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

47821-48039

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

48040-48277

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

48278-48545

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

48546-48668

Sentence

denotes

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

T281

48669-48872

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

48873-49041

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

49042-49159

Sentence

denotes

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

T284

49160-49320

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

49321-49532

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

49533-49696

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

49697-49816

Sentence

denotes

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

T288

49817-50041

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

50042-50237

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

50238-50536

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

50537-50705

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

50706-51122

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

51123-51159

Sentence

denotes

However, the data presented in Figs.

T294

51160-51253

Sentence

denotes

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

T295

51254-51449

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

51450-51617

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

51618-51940

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

51941-52051

Sentence

denotes

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

T299

52052-52161

Sentence

denotes

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

T300

52162-52283

Sentence

denotes

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

T301

52284-52517

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

52519-52529

Sentence

denotes

Discussion

T303

52530-52605

Sentence

denotes

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

T304

52606-52757

Sentence

denotes

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

T305

52758-52884

Sentence

denotes

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

T306

52885-53003

Sentence

denotes

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

T307

53004-53157

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

53158-53325

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

53326-53499

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

53500-53637

Sentence

denotes

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

T311

53638-53776

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

53777-53902

Sentence

denotes

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

T313

53903-54223

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

54224-54274

Sentence

denotes

Using this approach, we made several key findings.

T315

54275-54387

Sentence

denotes

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

T316

54388-54607

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

54608-54782

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

54783-55351

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

55352-55510

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

55511-55701

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

55702-55814

Sentence

denotes

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

T322

55815-55886

Sentence

denotes

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

T323

55887-55993

Sentence

denotes

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

T324

55994-56094

Sentence

denotes

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

T325

56095-56183

Sentence

denotes

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

T326

56184-56478

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

56479-56678

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

56679-56803

Sentence

denotes

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

T329

56804-56944

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

56945-57076

Sentence

denotes

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

T331

57077-57203

Sentence

denotes

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

T332

57204-57294

Sentence

denotes

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

T333

57295-57355

Sentence

denotes

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

T334

57356-57557

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

57558-57636

Sentence

denotes

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

T336

57637-57847

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

57848-58012

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

58013-58264

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

58265-58381

Sentence

denotes

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

T340

58382-58568

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

58569-58738

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

58739-58927

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

58928-59094

Sentence

denotes

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

T344

59095-59320

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

59321-59476

Sentence

denotes

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

T346

59477-59615

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

59616-60027

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

60028-60278

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

60279-60480

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

60481-60667

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

60668-60883

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

60884-61151

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

61152-61295

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

61296-61471

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

61473-61494

Sentence

denotes

Materials and methods

T356

61496-61544

Sentence

denotes

Patients, subjects, and clinical data collection

T357

61545-61731

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

61732-61835

Sentence

denotes

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

T359

61836-61926

Sentence

denotes

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

T360

61927-62097

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

62098-62262

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

62263-62312

Sentence

denotes

Peripheral blood was collected from all subjects.

T363

62313-62430

Sentence

denotes

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

T364

62431-62596

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

62597-62776

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

62777-62869

Sentence

denotes

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

T367

62870-62914

Sentence

denotes

HD and RD completed a survey about symptoms.

T368

62915-63024

Sentence

denotes

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

T369

63025-63079

Sentence

denotes

Two of these patients were classified as Immunotype 3.

T370

63080-63163

Sentence

denotes

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

T371

63164-63282

Sentence

denotes

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

T372

63283-63456

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

63458-63475

Sentence

denotes

Sample processing

T374

63476-63550

Sentence

denotes

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

T375

63551-63618

Sentence

denotes

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

T376

63619-63809

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

63810-63998

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

63999-64078

Sentence

denotes

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

T379

64080-64108

Sentence

denotes

Antibody panels and staining

T380

64109-64186

Sentence

denotes

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

T381

64187-64267

Sentence

denotes

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

T382

64268-64389

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

64390-64504

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

64505-64606

Sentence

denotes

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

T385

64607-64743

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

64744-64917

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

64918-65059

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

65060-65127

Sentence

denotes

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

T389

65128-65243

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

65244-65357

Sentence

denotes

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

T391

65358-65392

Sentence

denotes

Live/dead mix was prepared in PBS.

T392

65393-65531

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

65532-65577

Sentence

denotes

Intracellular mix was diluted in Perm Buffer.

T394

65579-65593

Sentence

denotes

Flow cytometry

T395

65594-65649

Sentence

denotes

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

T396

65650-65757

Sentence

denotes

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

T397

65758-65833

Sentence

denotes

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

T398

65834-65888

Sentence

denotes

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

T399

65890-65897

Sentence

denotes

Luminex

T400

65898-65994

Sentence

denotes

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

T401

65995-66109

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

66110-66195

Sentence

denotes

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

T403

66196-66309

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

66310-66440

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

66441-66563

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

66564-66711

Sentence

denotes

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

T407

66712-66990

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

66991-67084

Sentence

denotes

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

T409

67085-67178

Sentence

denotes

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

T410

67179-67237

Sentence

denotes

Data quality was examined based on the following criteria:

T411

67238-67352

Sentence

denotes

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

T412

67353-67544

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

67545-67620

Sentence

denotes

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

T414

67621-67795

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

67797-67843

Sentence

denotes

Intracellular stain after CD3/CD28 stimulation

T416

67844-67957

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

67958-68068

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

68069-68181

Sentence

denotes

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

T419

68182-68326

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

68328-68376

Sentence

denotes

Longitudinal analysis D0-D7 and patient grouping

T421

68377-68664

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

68665-68857

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

68858-68972

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

68973-69052

Sentence

denotes

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

T425

69053-69303

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

69304-69536

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

69538-69581

Sentence

denotes

Correlation plots and heatmap visualization

T428

69582-69696

Sentence

denotes

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

T429

69697-69885

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

69886-69981

Sentence

denotes

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

T431

69983-69993

Sentence

denotes

Statistics

T432

69994-70167

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

70168-70450

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

70451-70651

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

70652-70728

Sentence

denotes

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

T436

70729-70930

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

70931-71045

Sentence

denotes

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

T438

71046-71238

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

71239-71528

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

71529-71611

Sentence

denotes

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

T441

71612-71703

Sentence

denotes

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

T442

71705-71758

Sentence

denotes

High dimensional data analysis of flow cytometry data

T443

71759-71836

Sentence

denotes

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

T444

71837-72066

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

72067-72266

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

72267-72443

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

72444-72517

Sentence

denotes

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

T448

72518-72643

Sentence

denotes

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

T449

72644-72750

Sentence

denotes

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

T450

72751-73011

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

73012-73089

Sentence

denotes

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

T452

73091-73107

Sentence

denotes

Batch correction

T453

73108-73196

Sentence

denotes

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

T454

73197-73328

Sentence

denotes

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

T455

73329-73603

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

73604-73715

Sentence

denotes

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

T457

73716-73828

Sentence

denotes

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

T458

73829-73953

Sentence

denotes

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

T459

73954-74107

Sentence

denotes

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

T460

74109-74190

Sentence

denotes

Visualizing variation of flow cytometric features across the UMAP embedding space

T461

74191-74334

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

74335-74721

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

74722-74934

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

74935-75186

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

75188-75214

Sentence

denotes

Definition of immunotype 3

T466

75215-75599

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.

T467

75601-75616

Sentence

denotes

Acknowledgments

T468

75617-75715

Sentence

denotes

The authors thank patients and blood donors, their families and surrogates, and medical personnel.

T469

75716-75727

Sentence

denotes

We thank L.

T470

75728-75765

Sentence

denotes

Bershaw for recruitment of HD and RD.

T471

75766-75777

Sentence

denotes

We thank S.

T472

75778-75827

Sentence

denotes

Ngiow for essential infrastructure support and C.

T473

75828-75904

Sentence

denotes

Ash for donation of computational equipment and design of schematic figures.

T474

75905-75983

Sentence

denotes

We thank the Wherry lab for discussions and critically reading the manuscript.

T475

75984-75992

Sentence

denotes

Funding:

T476

75993-76224

Sentence

denotes

This work was supported by the University of Pennsylvania Institute for Immunology Glick COVID-19 research award (MRB), NIH AI105343, AI082630, and the Allen Institute for Immunology (EJW) and NIH grants HL137006 and H137915 (NJM).

T477

76225-76271

Sentence

denotes

ACH was funded by grant CA230157 from the NIH.

T478

76272-76310

Sentence

denotes

DM and JG were funded by T32 CA009140.

T479

76311-76347

Sentence

denotes

ZC was funded by NIH grant CA234842.

T480

76348-76378

Sentence

denotes

DAO was funded by NHLBI StARR:

T481

76379-76392

Sentence

denotes

1R38HL143613.

T482

76393-76508

Sentence

denotes

NJM reports funding to her institution from Athersys, Inc., Biomarck, Inc., and the Marcus Foundation for Research.

T483

76509-76567

Sentence

denotes

JRG is a Cancer Research Institute-Mark Foundation Fellow.

T484

76568-76736

Sentence

denotes

JRG, JEW, CA, AH, and EJW are supported by the Parker Institute for Cancer Immunotherapy which supports the Cancer Immunology program at the University of Pennsylvania.

T485

76737-76782

Sentence

denotes

The authors declare no conflicts of interest.

T486

76783-76893

Sentence

denotes

Author contributions: DM, NJM, MJB, and EJW conceived the project; DM, JRG, AEB, and EJW designed experiments.

T487

76894-77070

Sentence

denotes

NM conceived the clinical cohort, obtained clinical samples and metadata from COVID-19 patients and provided clinical input; OK and JD provided clinical samples from HD and RD.

T488

77071-77137

Sentence

denotes

AEB and KD coordinated clinical sample procurement and processing.

T489

77138-77207

Sentence

denotes

DM, ARG, LKC, MBP, NH, JK, AP, FC, and SFL processed patient samples.

T490

77208-77335

Sentence

denotes

DM, ZC, and YJH stained and JEW acquired flow cytometry samples; JRG, AEB, and KN performed downstream flow cytometry analysis.

T491

77336-77373

Sentence

denotes

HR and SCC performed qRT-PCR of PBMC.

T492

77374-77420

Sentence

denotes

DM, SFL, and FC performed Luminex experiments.

T493

77421-77518

Sentence

denotes

ECG, EMA, MEW, SG, CPA, MJB, and SEH analyzed COVID-19 patient plasma and provided antibody data.

T494

77519-77653

Sentence

denotes

ACH and LAV provided additional clinical data; CA compiled and JRG, DO, and CA analyzed clinical metadata with input from ACH and LAV.

T495

77654-77778

Sentence

denotes

JRG, DAO, SM, and EJW designed data analysis and JRG, ARG, CA, DAO, and SM performed computational and statistical analyses.

T496

77779-77822

Sentence

denotes

DM, JRG, ARG, CA, and DAO compiled figures.

T497

77823-77886

Sentence

denotes

LKC, MBP, SA, ACH, LAV, NJM and MB provided intellectual input.

T498

77887-77972

Sentence

denotes

DM, AEB, ARG, JEW, and EJW wrote the manuscript; all authors reviewed the manuscript.

T499

77973-78130

Sentence

denotes

Competing interests: E.J.W. has consulting agreements with and/or is on the scientific advisory board for Merck, Roche, Pieris, Elstar, and Surface Oncology.

T500

78131-78195

Sentence

denotes

E.J.W. is a founder of Surface Oncology and Arsenal Biosciences.

T501

78196-78277

Sentence

denotes

E.J.W. has a patent licensing agreement on the PD-1 pathway with Roche/Genentech.

T502

78278-78440

Sentence

denotes

E.J.W. is an inventor on a patent (US Patent number 10,370,446) submitted by Emory University that covers the use of PD-1 blockade to treat infections and cancer.

T503

78441-78473

Sentence

denotes

Data and materials availability:

T504

78474-78652

Sentence

denotes

Flow Cytometry data collected in this study was deposited to the Human Pancreas Analysis Program (HPAP-RRID:SCR_016202) Database and Cytobank (61) (https://hpap.pmacs.upenn.edu).

T505

78653-78724

Sentence

denotes

B cell data (https://premium.cytobank.org/cytobank/experiments/308353).

T506

78725-78806

Sentence

denotes

Non Naive CD4 T cells (https://premium.cytobank.org/cytobank/experiments/308354).

T507

78807-78888

Sentence

denotes

Non Naive CD8 T cells (https://premium.cytobank.org/cytobank/experiments/308357).

T508

78889-79110

Sentence

denotes

This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

T509

79111-79194

Sentence

denotes

To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.

T510

79195-79396

Sentence

denotes

This license does not apply to figures/photos/artwork or other content included in the article that is credited to a third party; obtain authorization from the rights holder before using such material.

T511

79398-79429

Sentence

denotes

The UPenn COVID Processing Unit

T512

79430-79451

Sentence

denotes

Zahidul Alam, Mary M.

T513

79452-79471

Sentence

denotes

Addison, Katelyn T.

T514

79472-79503

Sentence

denotes

Byrne, Aditi Chandra, Hélène C.

T515

79504-79542

Sentence

denotes

Descamps, Yaroslav Kaminskiy, Jacob T.

T516

79543-79577

Sentence

denotes

Hamilton, Julia Han Noll, Dalia K.

T517

79578-79610

Sentence

denotes

Omran, Eric Perkey, Elizabeth M.

T518

79611-79644

Sentence

denotes

Prager, Dana Pueschl, Jennifer B.

T519

79645-79658

Sentence

denotes

Shah, Jake S.

T520

79659-79676

Sentence

denotes

Shilan, Ashley N.

T521

79677-79687

Sentence

denotes

Vanderbeck

T522

79688-79789

Sentence

denotes

All affiliated with the University of Pennsylvania Perelman School of Medicine Philadelphia, PA, USA.

T523

79791-79814

Sentence

denotes

Supplementary Materials

T524

79815-79874

Sentence

denotes

science.sciencemag.org/cgi/content/full/science.abc8511/DC1

T525

79875-79880

Sentence

denotes

Figs.

T526

79881-79890

Sentence

denotes

S1 to S11

T527

79891-79905

Sentence

denotes

Table S1 to S8

PMC:7402624 JSON TXT 18 Projects

Annnotations TAB TSV DIC JSON TextAE

PMC:7402624 JSONTXT 18 Projects

Annnotations TAB TSV DIC JSON TextAE

PMC:7402624 JSON TXT 18 Projects