key: cord-0755499-cfkf5ixz authors: Messing, M.; Sekhon, M. S.; Hughes, M. R.; Stukas, S.; Hoiland, R. L.; Cooper, J.; Ahmed, N.; Hamer, M.; Li, Y.; Shin, S. B.; Tung, L. W.; Wellington, C.; Sin, D. D.; Leslie, K. B.; McNagny, K. M. title: Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes date: 2022-02-01 journal: nan DOI: 10.1101/2022.01.31.22270208 sha: 693e0e446754fc8acf54c2aaf548d61e6b91d2a3 doc_id: 755499 cord_uid: cfkf5ixz The COVID-19 pandemic continues to challenge the capacities of hospital ICUs which currently lack the ability to identify prospectively those patients who may require extended management. In this study of 90 ICU COVID-19 patients, we used multiplexed cytokine evaluation and, on 42 of these patients (binned into Initial and Replication Cohorts), CyTOF-based deep immunophenotyping. This revealed blood prognostic biomarkers that, at time of ICU admission, prospectively distinguish, with 91% sensitivity and 91% specificity, patients who will subsequently die or have long ICU stays (> 6 days) from those who will have short-stays (< 6 days). This is achieved through a tiered evaluation of serum IL-10 and targeted immunophenotyping of monocyte subsets (specifically, CD11clow classical monocytes) through statistical approaches. We have distilled this down to a prognostic test that could prove useful in guiding clinical resource allocation, treatment regimens and assessment of new therapeutic interventions. challenging to predict but severe disease has been broadly linked to advanced age, obesity, 23 underlying comorbidities and secondary infections 5, 6, 7, 8, 9, 10 . Neither symptoms nor conventional 24 clinical measurements (serum C-reactive protein (CRP), blood D-dimers etc.) have sufficient 25 prognostic power and thus approved interventions for severe COVID-19 (including systemic 26 corticosteroids and tocilizumab) are administered broadly as clinicians lack the ability to identify 27 accurately patients at risk of long-term complications and death 11, 12, 13, 14, 15 . Immunologically, 28 "severe" patients have been reported to exhibit lymphopenia, neutrophilia, accumulation of lung 29 monocytes, emergency myelopoiesis, and substantial changes in serum cytokine and chemokine 30 profiles likely reflecting a cytokine storm as the result of a delayed, but exuberant, immune 31 response to infection 16, 17, 18, 19, 20, 21, 22, 23 . The latter has been of particular interest for the development 32 of prognostic tools but while some markers have proven useful in measuring the severity of active 33 COVID-19, to date, they have lacked the necessary statistical power to prospectively predict the 34 likelihood of incipient severe disease 24, 25, 26, 27, 28, 29, 30, 31 . For example, serum IL-6 (alone, or together 35 with other inflammatory markers) has most consistently been linked to severe active disease and, 36 by some groups, was shown to predict the need for subsequent mechanical ventilation as well as 37 survival 32,33,34,35,36, and other lineages) with active severe disease and poor outcomes 17, 19, 34, 40, 41, 42, 43, 44 . While these 49 global cellular profiling efforts provide important insights into the immune response to SARS-50 CoV-2 infection, they have yet to be translated into prognostic tools to assist with individualized 51 care. 52 53 Here we focused on the development of an immunological biomarker screen that, at ICU admission 54 for COVID-19, predicts length of ICU stay or death. Strikingly, we find that, at ICU admission, 55 measurements of serum IL-10 and simple monocyte subset surface signatures, specifically, 56 CD11c low classical monocytes, can predict with 91% sensitivity and 91% specificity patients who 57 will either die or have a longer stay in ICU. We offer these biomarkers as a model clinical 58 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint laboratory test with future potential in gaining insights into variable responses to SARS-CoV-2 59 infection. 60 61 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint To identify potential prognostic markers of COVID-19, we collected PBMCs from 8 Table 1 ) designed to detect broad shifts in levels of normal PBMC 70 lineages as well as their activation status, and the possible mobilization of tissue resident innate 71 immune cells and bone marrow progenitors into peripheral blood. Based on these data we 72 developed a refined, second-generation, 38-antibody CyTOF panel (Supplementary Table 1) , 73 which was used on PBMCs collected from a further 28 of the 90 ICU COVID-19 patients (the 74 "Replication Cohort"). Data from the Replication Cohort were used to validate observations from 75 the Initial Cohort on early alterations in immune responses that could effectively differentiate 76 patients likely to recover after a short ICU stay from those who would either die or have prolonged 77 stays in ICU. The ICU admission sera from all patients in the Cytokine Cohort (which includes all 78 patients in the Initial Cohort and the Replication Cohort) were analyzed for levels of four 79 cytokines: IL-1β, IL-6, IL-10 and TNFα (Fig. 1a, b) . 80 Clinical and demographic details of all patients and healthy controls are presented in Table 1 and 82 include age, sex, body mass index (BMI), requirement for ventilation during admission and ICU 83 admission levels of serum CRP, blood D-dimer levels, and white blood cell counts along with their 84 differentials . The average age of the ICU patients was 63.5 years with a 2-to-1 bias towards male 85 patients, consistent with previous patient demographic reports linking more severe COVID-19 86 with older male patients 45 . Table 1 also bins patients into two clinical outcome groups of "Short-87 Stay" and "Long-Stay/Died" based on the length of time in the ICU and survival: "Short-Stay" 88 patients are classified as those spending < 6 days in the ICU and were survivors, while "Long-89 Stay/Died" patients are defined as patients who spent 6 or more days in the ICU or died during 90 their stay in ICU. The choice of 6 days as the cut-off was based upon iterative empirical analyses 91 of immune data that divided, with greatest statistical significance (by p-value), patients into two 92 sub-groups with distinct clinical outcomes (Fig. 1a, c) . 93 94 Importantly, we found no significant differences between the two clinical outcome groups with 95 respect to mean age, BMI, blood clotting parameters (D-dimer levels) or serum CRP levels ( Fig. 96 1d, e). At admission, the mean total PMN counts were significantly increased in the Long-97 Stay/Died group compared to the healthy controls (p<0.0001) and compared to the Short-Stay 98 group (p=0.025) (Fig. 1f ). In our separate analyses of just the Initial Cohort and Replication 99 Cohorts, however, differences in PMN counts were not statistically significant and thus we did not 100 consider this measurement as a useful prognostic biomarker of clinical outcomes in the context of 101 smaller cohort numbers. PBMC counts were also not significantly changed between healthy 102 controls and patients or between our two clinical outcome groups (Fig. 1f) . Thus, while these 103 routine clinical tests follow a broad spectrum of parameters including inflammation, coagulopathy, 104 hypo-immunity and autoimmunity, none consistently proves prognostic in identifying patients 105 who would require an extended stay in ICU or die. Accordingly, we conducted more detailed 106 immunological examinations focused on a single, specific COVID-19-associated process, namely 107 inflammation. 108 109 Serum cytokine analyses as prognostic screens for predicting clinical outcome 110 We began by examining serum levels of IL-1β, IL-6, IL-10 and TNFα at ICU admission in all 111 serum samples from our Cytokine Cohort of 90 COVID-19 patients. Strikingly, we found that the 112 mean ICU admission levels of serum IL-10 (p = 0.004) and TNFα (p = 0.0005) were significantly 113 elevated in the Long-Stay/Died group relative to the Short-Stay group (Fig. 1g) and TNFα only showed a weak correlation with each other (Pearson correlation coefficient R 2 = 119 0.12) suggesting that each may represent a different aspect or chronology of the inflammatory 120 process. 121 122 Given the clear prognostic value of ICU admission levels of TNFα and IL-10, we also examined 123 the subsequent mean maximum serum cytokine levels in post admission samples from patients in 124 the Short-Stay and the Long-Stay/Died groups and found an even more significant difference 125 between the two groups for both serum TNFα (p < 0.0001) and serum IL-10 (p = 0.0009) (Fig. 126 1h). Intriguingly, many patients in the Long-Stay/Died group who demonstrated modest admission 127 levels of serum IL-10 and TNFα subsequently developed high levels during their stay in ICU, 128 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint further reinforcing the importance of these two cytokines as predictive measures of patient 129 outcomes and monitoring the trajectory of disease. 130 131 While admission levels of serum IL-6 were also significantly different between the two clinical 132 groups (p = 0.007) (Fig. 1i) , we excluded this cytokine from further analyses due to the potential 133 confounding effects of anti-IL-6 receptor antibody (tocilizumab) treatments, which has routinely 134 been administered to COVID-19 patients in British Columbia during ICU admission since 135 February 2021 and such treatments could complicate the interpretation of our results. Finally, there 136 were no significant differences between the two clinical outcome groups with respect to mean 137 serum IL-1β levels at ICU admission (p = 0.205) and thus this cytokine was also not analyzed 138 further (Fig. 1i) . In summary, we found that ICU admission levels of serum IL-10 and TNFα were 139 useful and statistically powerful prognostic markers for clinical outcomes in severe COVID-19. CyTOF panel on the Replication Cohort (Fig 1.) , we saw no differences between the Short-Stay 151 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint patients and Long-Stay/Died patients with respect to major peripheral blood immune populations. 152 The more-focussed and larger 38-marker CyTOF panel, used to analyze immune cell subsets in 153 the Replication Cohort, permitted clear identification of broad blood cell lineages (B, T, NK, and 154 myelomonocytic) as well as major subsets within each cell lineage leading to 41 distinct cell subset 155 clusters based on the variable expression of these cell-surface markers (Fig. 2a-c) . While these 156 analyses of the Replication Cohort samples and the Initial Cohort samples confirmed previous 157 reports 5,46 of general lymphopenia in COVID-19 patients relative to healthy controls with respect 158 to both total CD4 T cells and total CD8 T cells, these markers failed to discriminate between the 159 Short-Stay and Long-Stay/Died patient groups. Also consistent with previous reports, we observed 160 no significant differences in total B cells in COVID-19 patients compared to healthy controls or 161 between the two clinical outcome groups (Fig. 2d) . Although mean total NK cells, MAIT cells, γδ 162 T cells, DC2/3 and pDC were depleted in COVID-19 patients relative to healthy controls these, 163 too, failed to distinguish the Short-Stay group from the Long-Stay/Died group (Fig. 2e) . Finally, 164 while mean total monocytes and stem cell levels were significantly increased in COVID-19 165 patients relative to healthy controls they failed, individually, to distinguish the Short-Stay from the 166 Long-Stay/Died patient groups (Fig. 2f ). In summary, broad immune subset analyses were 167 insufficient to predict COVID-19 patient clinical outcomes with respect to the length of stay in 168 ICU and/or death in either the Initial Cohort or the Replication Cohort. We, therefore, performed 169 more detailed analyses of immune cell subsets within these broad cell categories to identify more 170 subtle potential differences between the two clinical outcome groups that could assist in the 171 prospective identification of Long-Stay/Died patients. 172 173 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint outcome 175 To reveal a larger diversity of specific immune cell subsets we performed more focused cluster 176 analyses on patient PBMC samples from the Initial Cohort and the Replication Cohort after pre-177 gating for selected major cellular subsets. To restrict the clustering to the myelomonocytic 178 compartment we performed gated analyses on GM-CSFR + (CD116 + ) CD19 -CD3cells (Fig. 3a ) 179 and restricted clustering to shared marker channels to enable direct comparison between the Initial 180 and the Replication cohorts. These analyses did not reveal subsets that separated Short-Stay from 181 Long-Stay/Died patients with respect to absolute cell counts. To focus more specifically on the 182 monocytic subsets as well as to simplify the cluster analyses, after pre-gating on CD116+ CD19-183 CD3-cells, we restricted the marker channels selected for clustering to a set of 7 markers useful 184 in defining monocytic subsets (CD45, CD14, CD16, CD11c, HLA-DR, CD123, CD56, see Figs. 185 3b,c). Interestingly, this strategy revealed a CD11c low classical monocytic subset (CD45 + CD116 + 186 CD3ε -CD11c low HLA-DR + CD14 + CD16 -/low CD123 -/low ) that, in both the Initial and the 187 Replication Cohorts, was consistently enriched in COVID-19 patients relative to healthy controls 188 (p = 0.001, Replication Cohort) and was preferentially enriched in the Long-Stay/Died group 189 relative to the Short-Stay group (p = 0.019, Replication Cohort) (Fig. 3d) . The prognostic value of 190 the CD11c low classical monocytic marker was restricted to this subset of classical monocytes in 191 both the Initial and Replication Cohorts and did not reflect underlying changes of total classical 192 monocytes which were unchanged in the two clinical outcome groups (Fig. 3e) . Moreover, for 193 both Initial and Replication Cohorts, total intermediate monocytes (CD14 + CD16 int ) and total non-194 classical monocytes (CD14 low CD16 + ), as well as observed subpopulations of these types of 195 monocytes, did not prove useful prognostically (Fig. 3f) . Focussing the analyses further on 196 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint classical monocytes, we found that a three-marker gating strategy was sufficient to identify the 197 CD11c low classical monocyte population identified by our multi-dimensional analyses (shown here 198 for one representative sample from each group in the Replication Cohort, where intensity is 199 proportional to relative frequency of cells) (Fig. 3g) . Thus, the prognostically useful biomarker of 200 CD11c low classical monocytes was detectable in two dimensions in both the Initial and the 201 Replication Cohorts using antibodies to a small set of cell-surface markers. Since deeper analyses of multiple cytokines and cell subsets at ICU admission revealed significant 215 differences between the Long-Stay/Died and Short-Stay groups, we sought to combine these 216 findings to generate a streamlined prognostic tool that could accurately predict whether a patient, 217 newly admitted to ICU, was likely to have a subsequent longer stay in ICU or die. Although both 218 serum TNFα and serum IL-10 were significantly elevated in Long-Stay/Died patients relative to 219 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. Short-Stay patients in the Cytokine Cohort, using Pearson analyses, the length of stay in ICU 220 correlated more significantly with serum IL-10 levels (R 2 = 0.48) and maximum IL-10 levels (R 2 221 = 0.54) than with serum levels of TNFα (R 2 = 0.14). Thus, we proceeded with serum IL-10, only, 222 as our cytokine-based pre-screen portion of a stepwise integrated prognostic tool. As the first step, 223 using a cut-off value of 15pg/ml for serum IL-10, data from the 90-sample Cytokine Cohort 224 demonstrated a 79% specificity and 55% sensitivity in predicting that a patient newly admitted to 225 ICU would have a longer stay in ICU or die (Fig. 4g) . This prognostic specificity of 79% is 226 somewhat comparable with that seen in the smaller subsets of the Cytokine Cohort, namely the 227 14-sample Initial Cohort (86%) and the 28-sample Replication Cohort (100%). Similarly, the 228 prognostic sensitivity of 55% in the Cytokine Cohort is somewhat comparable with that observed 229 in the Initial Cohort (86%) and the Replication Cohort (56%) (Figs. 4a-c,g). The variations in 230 estimates of prognostic sensitivity and specificity between cohorts (the Cytokine Cohort and its 231 two subsets of the Initial Cohort and Replication Cohort), however, likely demonstrate variations 232 that reflect the influences of random patient sampling and, very importantly, cohort size. These 233 results validate serum IL-10 levels as a pre-screen for patients likely to die or to experience a long 234 ICU stay. 235 We then explored the utility of combining serum IL-10 levels (with a cut-off value of 15pg/ml) 237 with the levels of CD11c low classical monocytes (with a cut-off value of 2.7x10 7 /ml) as a stepwise 238 integrated diagnostic tool. With this approach, 100% of the Long-Stay/Died patients were correctly 239 identified in the Initial Cohort and 88% of Long-Stay/Died patients were correctly identified in the 240 Replication Cohort, the latter with a specificity of 100% (Figs. 4d,e,g). These analyses of all 42 241 patients in the combined Initial and Replication Cohorts (n = 42) allowed us to predict with 91% 242 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. suggest that a simple screen of two biomarkers at the time of ICU admission allows for rapid 245 identification of those patients who are likely to die or require extended ICU care (Fig. 4h) The goal of the present study was to identify prognostic biomarkers that, at time of ICU admission, 250 could predict subsequent outcome of COVID-19. Such markers are in urgent need and, with further 251 testing and refinement, could serve to triage patients into specific groups for timely and appropriate 252 care while, at the same time, offer insights into the immune-mediated determinants of disease 253 response. Like many previous studies, we found that although severe COVID-19 is linked to broad 254 shifts in peripheral blood immune subsets (increased PMNs and T cell lymphopenia) and increased 255 blood inflammatory markers (CRP, D-dimer, etc.), none of these proved prognostic with respect 256 to subsequent length of ICU stay and/or death. Therefore, we used CyTOF-based PBMC 257 immunophenotyping and serum cytokine analyses on samples drawn at ICU admission to focus 258 our attention on more subtle shifts in inflammatory parameters with a view to identifying 259 prognostic biomarkers. Through iterative empirical analyses of these data, we identified two 260 groups of ICU patients who would subsequently have clinically distinguishable disease outcomes: 261 those who would be discharged from ICU within 6 days and those who would require a longer 262 ICU stay or die. We then used retrospective analyses to generate a simple set of biomarkers that 263 could easily be applied in the clinic to identify, at the time of ICU admission, those patients at 264 greater risk of death or lengthy stay in ICU. 265 266 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint also may explain why anti-IL-6 receptor therapy has shown only limited efficacy as a broad-290 spectrum therapeutic for severe COVID-19 and fails to reduce overall mortality 13, 47 . Similarly, 291 although corticosteroids have emerged as a standard-of-care for COVID-19 ICU patients and 292 undoubtedly provide improved recovery after infection, they are widely recognized as "double-293 edged swords": while they are effective at suppressing excessive inflammation, they also potently 294 suppress adaptive immune responses, potentially reducing viral clearance and increasing 295 susceptibility to secondary infections 12, 48 . With that backdrop, a benefit of the streamlined ICU 296 biomarker panel described here is that it provides a direct prognostic link to patient outcome and 297 may also serve as a biomarker panel for monitoring patient response to therapies. 298 299 In our study, deep immunophenotyping of the myeloid compartment in COVID-19 patients proved 300 pivotal in defining markers to predict patient outcomes. While we saw no significant early changes 301 in total monocyte numbers or total classical monocyte numbers or frequencies, a prognostically 302 useful monocytic subset was contained within these broader subsets which highlights the need for 303 a high-dimensional evaluation to identify subtle, but informative, changes in immune 304 subpopulations that might otherwise have been overlooked. After identification of such subtle 305 biomarkers using high-dimensional analytic technologies, simpler two-dimensional technologies 306 (using limited markers) can then be used to measure the biomarker clinically. It is noteworthy that 307 previous studies have linked both increased peripheral blood monocytes and increased numbers of 308 inflammatory macrophages in the lung to severity of COVID-19 49, 50, 51, 52 . Other studies reported 309 subtle, monocyte subset-specific changes in severe COVID-19, including dysfunctional pro-310 inflammatory cytokine production, reduction in HLA-DR transcripts, accumulation of HLA-DR low 311 monocytes and reduction of non-classical monocytes 16, 17, 34, 38, 42 . Further, CD11c low monocytic 312 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint enrichment has been described in severe COVID-19 17 . The data presented here confirm and extend 313 these observations in a manner that facilitates accurate prognostication. They also reveal CD11c low 314 classical monocytes as new target populations for more focused mechanistic studies in future 315 research. While the combination of these two biomarkers certainly provides prognostic 316 information on disease outcome in COVID-19, there is a possible parallel interpretation of the 317 results: since all patients received corticosteroids at the time of admission, the biomarkers 318 described here may actually be identifying those patients who are, in fact, more responsive to 319 corticosteroid therapy. We leave this intriguing possibility for future investigation. 320 Although not specifically addressed here, we believe that these prognostic biomarkers provide a 322 roadmap for future studies aimed at guiding and monitoring response to therapy. Such monitoring 323 is particularly important in the context of therapies that have the acknowledged potential of 324 exacerbating clinical disease if given in a temporally inappropriate manner in the COVID-19 cycle 325 of stimulation and progression to clearance and resolution. While we have focused here on the 326 utility of these markers at the time of ICU admission it is possible that these may prove even more 327 valuable as temporal monitoring tools for revealing disease trajectory on this continuum and 328 responses to therapeutic intervention. 329 330 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. technical assistance for patient sample processing and mass cytometry data collection and 411 processing. All authors contributed to editing the manuscript. 412 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; Fig. 1: Patient cohort selection, characteristics and cytokine analyses. a, Experimental design overview: peripheral blood was collected from COVID-19 patients within 48h of ICU admission; immune cells and serum were isolated and stored followed by immune cell subset and cytokine analyses and clinical data integration. b, patient cohorts overview. c, patient outcome groups based on length of stay in ICU. (d-e), Patient age, body mass index (BMI), Creactive protein (CRP) levels and D-dimer levels. f, Complete blood counts of patients and healthy controls. (g-i), Serum cytokine levels of IL-10, TNFa, maximum IL-10, maximum TNFa, IL-6 and IL-1b. *, p < 0.05; **, p < 0.01; ***, p < 0.001; ns, p ≥ 0.05 by two-tailed, two-sample unequal variance Student's t-Test. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint 3 7 28 40 27 15 14 24 6 12 2 19 4 21 22 43 39 8 20 17 10 37 34 16 30 36 26 23 35 18 42 32 33 38 13 11 29 31 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. SHORT-STAY a-c, Cytokine levels scatter plots of Initial (left), Replication (middle) and combined Cohorts (right) with dashed lines at cut-off value of 15pg/ml for serum IL-10. d-f, Cytokine and cellular levels scatter plots for Initial (left) Replication (middle) and combined cohorts (right) with dashed lines at cut-off values of 15pg/ml and 2.7 (x10 7 /ml) of serum IL-10 and CD11c low classical monocytes respectively. g, Sensitivity and specificity calculations for each screen and cohort. h, Prognostic patient screening chart based on serum IL-10 and CD11c low monocyte subset measurement. *, p < 0.05; **, p < 0.01; ***, p < 0.001; ns, p ≥ 0.05 by two-tailed, two-sample unequal variance Student's t-Test and R 2 by two-tailed Pearson correlation with 95% confidence interval. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted February 1, 2022. a, Representative gating of CD3 + cells. b, Initial Cohort UMAP projections of CD3 + gated cells (all samples combined; limited clustering channels) and mean marker expression heatmap. c, same as in b but for the Replication Cohort. d, Initial Cohort absolute counts of T cell subsets identified based on gated clustering. e, same as in d but for the Replication Cohort. *, p < 0.05; **, p < 0.01; ***, p < 0.001; ns, p ≥ 0.05 by two-tailed, two-sample unequal variance Student's t-Test. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted February 1, 2022. ; https://doi.org/10.1101/2022.01.31.22270208 doi: medRxiv preprint . 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