key: cord-286968-ud1uerc8 authors: Nienhold, R.; Ciani, Y.; Koelzer, V. H.; Tzankov, A.; Haslbauer, J. D.; Menter, T.; Schwab, N.; Henkel, M.; Frank, A.; Zsikla, V.; Willi, N.; Kempf, W.; Hoyler, T.; Barbareschi, M.; Moch, H.; Tolnay, M.; Cathomas, G.; Demichelis, F.; Junt, T.; Mertz, K. D. title: Two distinct immunopathological profiles in lungs of lethal COVID-19 date: 2020-06-19 journal: nan DOI: 10.1101/2020.06.17.20133637 sha: doc_id: 286968 cord_uid: ud1uerc8 Immune responses in lungs of Coronavirus Disease 2019 (COVID-19) are poorly characterized. We conducted transcriptomic, histologic and cellular profiling of post mortem COVID-19 and normal lung tissues. Two distinct immunopathological reaction patterns were identified. One pattern showed high expression of interferon stimulated genes (ISGs) and cytokines, high viral loads and limited pulmonary damage, the other pattern showed severely damaged lungs, low ISGs, low viral loads and abundant immune infiltrates. Distinct patterns of pulmonary COVID-19 immune responses correlated to hospitalization time and may guide treatment and vaccination approaches. ISG low samples, and observed a higher frequency of CD8+PD1+ T-cells in the ISG low subgroup, potentially indicative of advanced disease (Extended Data Figure 3a,b) . Histological analysis of COVID-19 lung tissues revealed striking pulmonary damage exclusively in ISG low samples, with distinct peri-alveolar foci of infiltrating CD68+ macrophages and CD8+ T cells (Figure 1e) . Expression of ISGs was tightly correlated with pulmonary viral load (Figure 2a) , and immunohistochemical staining showed SARS-CoV-2 nucleocapsid protein mostly in pneumocytes of ISG high lungs (Figure 2b) . Since a cytokine storm has been proposed to cause adverse outcome of COVID-19 7 , and cytokines were highly expressed in bronchoalveolar lavages (BALs) of COVID-19 patients 8 , we investigated expression of a pro-inflammatory cytokine signature (TNF, IL6, IL1b, CCL2, IFNA17, IFNB1, CXCL9, CXCL10, CXCL11) in lung samples from lethal COVID-19. The proinflammatory gene signature was significantly enriched in the ISG high subset (Figure 2c) , but was not associated with alveolar hemorrhage (Figure 2d ). Within this cytokine signature, co-regulated subgroups (IL1B/IL6/TNF, IFNB1/IFNA17, CCL2/CXCL9/CXCL19/CXCL11) were identified ( Figure 2e ). Importantly, only the CXCL9/10/11 sub-signature was positively associated with alveolar hemorrhage (Figure 2f , Extended Data Figure 4 ). This is in line with observations that these chemokines compromise endothelial integrity via CXCR3 9 , and that CXCL10 is a key determinant of severe COVID-19 10 . Interestingly, basal levels of CXCL9 or CXCL10 are elevated in elderly, hypertensive and obese individuals, which were strongly represented in our autopsy cohort and are predisposed to severe COVID-19 11, 12 . Of note, our study could not take extrapulmonary cytokine sources or effects into account. Since none of the above pulmonary cytokine sub-signatures was positively associated with diffuse alveolar damage (DAD, Extended Data Figure 5) , we investigated which other local immune signature showed this association. We found a strong association of DAD with low expression of ISGs (Figure 2g) , and an activated CD8+ T cell signature (CD38, GZMA, GZMB, CCR5, Figure 2h ), yet not with pulmonary CD8+ T-cell infiltration (Figure 2i ). In addition, the activated CD8+ signature was inversely correlated to viral counts, particularly in ISG low cases (Figure 2j ). Therefore we speculate that activated CD8+ T cells are essential for virus elimination, similar to murine models of coronavirus infection 13 , yet it is possible that they contribute to pulmonary damage as well. Of note, ISG low samples also expressed elevated p53 and Ki67 (Figure 2k) , i.e. reactive markers of DAD which indicate lung remodeling 14 . Since the ISG low pattern showed lower viral counts, higher accumulation and activation of CD8+ T cells in tissues and accrual of pulmonary damage and remodeling, the ISG low phase may follow an earlier ISG high phase during the course of infection. This was supported by significantly 4 instead show low viral loads yet strong complement activation in lungs (Figure 2m ) and thus may potentially benefit from complement inhibition 16 . In addition, the ISG low pattern suggests that CD8+ T cells are involved in antiviral protection and should be considered for vaccination efforts. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Table 1a . Detailed autopsy findings for each patient were recently published, and the identifiers (with the prefix "C") for each COVID-19 patient are consistent with the description of this Swiss COVID-19 autopsy cohort 3 . In this study, we analysed formalin fixed and paraffin embedded (FFPE) lung tissue of distinct areas of the lungs of 16 of these COVID-19 patients. All 16 COVID-19 patients had positive nasopharyngeal swabs collected while alive. In all COVID-19 patients, diagnosis was confirmed by detection of SARS-CoV-2 in postmortal lung tissues. 5/16 patients were additionally tested by postmortal nasopharyngeal swabs which were positive for SARS-CoV-2 in all 5 cases. As a control cohort, we selected 6 autopsies performed between January 2019 and March 2020 at the Institute of Pathology Liestal ("normal" patients N1 -N6). These control patients died of other, non-infectious causes and had a similar age, gender and cardiovascular risk profile. Patients with infections were excluded from this control cohort. Another control cohort consisted of 4 autopsies of patients suffering from various infections mainly with bacteria affecting the lung (patients with lung pathology, P1 -P4). Details for both control cohorts are listed in Extended Data (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Quantification of SARS-CoV-2 in FFPE tissue samples The OIRRA is a targeted gene expression assay designed for the Ion™ next-generation sequencing (NGS) platform. This gene expression assay was originally designed to interrogate the tumor microenvironment to enable mechanistic studies and identification of predictive biomarkers for immunotherapy in cancer. The assay is optimized to measure the expression of genes involved in immune cell interactions and signaling, including genes expressed at low levels and involved in inflammatory signaling. The 398 genes covered by this assay are listed in Extended Data Table 2 . The NGS libraries were prepared as recommended by the supplier. In brief, 30ng of total RNA were (which was not certified by peer review) 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 June 19, 2020. Immunohistochemical analyses for CD3, CD4, CD8, CD15, CD20, CD68, CD123, CD163, PD-1, MPO, p53, Ki67, C3d and C5b-9 were performed on all lung tissue blocks used in this study. Antibodies, staining protocols and conditions are detailed in Extended Data Table 4 . Qualitative and semiquantitative assessment of histopathological lung damage and neutrophilic infiltration Hematoxylin and eosin (H&E) and Elastica van Gieson (EvG) stained sections of all lung tissues used in this study were independently evaluated by two experienced and board certified pathologists (VZ and KDM) (Extended Data Table 5 ). Both pathologists evaluated the presence of diffuse alveolar damage (DAD), and if present, its stage, intra-alveolar edema and hemorrhage. In addition, both All rights reserved. No reuse allowed without permission. (which was not certified by peer review) 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 June 19, 2020. . https://doi.org/10.1101/2020.06.17.20133637 doi: medRxiv preprint pathologists evaluated the severity of histopathological changes in COVID-19 lungs (1 = mild / discrete alterations, 2 = moderate, 3 = severe changes) based on resemblance between normal and pathologically altered lung tissues. Parameters that were taken into account included reduction of alveolar air-filled spaces, typical histologic features of DAD with hyaline membrane formation, infiltration of lymphocytes, monocytes and neutrophils into interstitial and alveolar spaces, type 2 pneumocyte hyperplasia, desquamation of pneumocytes, histologic features of organizing pneumonia including intra-alveolar fibrin deposition and fibrosis (acute fibrinous and organizing pneumonia, AFOP) 17, 18 For cell-level analysis, color deconvolution for DAB, AP and hematoxylin channels was performed and nuclear segmentation was optimized using cell-morphometric parameters. Marker-positive cells in stromal and epithelial regions were quantified. For CD3, CD4, CD8, CD20, CD68, CD123, CD163 and PD1, staining detection was optimized for the cytoplasmic / membranous compartment and marker expression was measured on a continuous scale at single cell resolution. For assessment of CD8/PD1 double stains, color deconvolution was optimized for separation of DAB (PD1) and AP (CD8) staining products. Internal controls (non-immune cells) and external controls (tonsil) were used to calibrate the detection limits and cross-validated by visual review. For each tissue sample, the total area of lung tissue in mm 2 , the absolute number of marker-positive cells, cell morphometric parameters and staining intensity were recorded. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) 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 June 19, 2020. Expression of gene signatures was calculated as median of log2(cpm + 1) of selected genes. Biological processes enrichment was performed using the enrichGO function of the package clusterProfiler 20 setting all the genes included in the assay as universe. All the analyses and graphical representations were performed using the R statistical environment software 21 and the following packages: ggplot2 22 , circlize 23 , ComplexHeatmap 24 , ggfortify 25 , reshape2 26 and factoextra 27 . Correlation between transcripts and viral counts was performed using Pearson's correlation. Association between continuous and categorical data were tested using Wilcoxon rank sum test. Box-plots elements indicate the median (center line), upper and lower quartiles (box limits) and show all the data points. Whiskers extend to the most extreme value included in 1.5x interquartile range. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) 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 June 19, 2020. (which was not certified by peer review) 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 June 19, 2020. (which was not certified by peer review) 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 June 19, 2020. . The datasets generated and analysed during this study can be accessed in GEO (GSE151764) and are available from the corresponding author upon request. Competing interests VHK has served as an invited speaker on behalf of Indica Labs. TH and TJ are employees of Novartis. The other authors declare no competing interests. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Patients were suffering from other infections of the lung (bacterial or viral pneumonia). Detailed analysis of individual pathogens is shown in Extended Data Figure 1 . All rights reserved. No reuse allowed without permission. (which was not certified by peer review) 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 June 19, 2020. . https://doi.org/10.1101/2020.06.17.20133637 doi: medRxiv preprint Extended Data Table 2. OIRRA gene list ABCF1 CCL5 CD40LG CTAG2 FASLG HIF1A IFIT1 IL3RA ADGRE5 CCNB2 CD44 CTLA4 FCER1G HLA-A IFIT2 IL4 ADORA2A CCR1 CD47 CTSS FCGR1A HLA-B IFIT3 IL6 AIF1 CCR2 CD48 CX3CL1 FCGR2B HLA-C IFITM1 IL7 AKT1 CCR4 CD52 CX3CR1 FCGR3A HLA-DMA IFITM2 IL7R ALOX15B CCR5 CD53 CX3CR1 FCGR3B HLA-DMB IFNA17 IRF1 ARG1 CCR6 CD6 CX3CR1 FCRLA HLA-DOA IFNB1 IRF4 AXL CCR7 CD63 CX3CR1 FOXM1 HLA-DOB IFNG IRF9 B3GAT1 CD14 CD68 CXCL1 FOXO1 HLA-DPA1 IGF1R IRS1 BAGE CD160 CD69 CXCL10 FOXP3 HLA-DPB1 IGSF6 ISG15 BATF CD163 CD70 CXCL11 FUT4 HLA-DQA1 IKZF1 ISG20 BCL2 CD19 CD74 CXCL13 FYB HLA-DQA2 IKZF2 ITGA1 BCL2L11 CD1C CD79A CXCL8 G6PD HLA-DQB2 IKZF3 ITGAE BCL6 CD1D CD79B CXCL9 GADD45GIP1 HLA-DRA IKZF4 ITGAL BRCA1 CD2 CD80 CXCR2 GAGE1 HLA-DRB1 IL10 ITGAM BRCA2 CD209 CD83 CXCR3 GAGE10 HLA-E IL10RA ITGAX BST2 CD22 CD86 CXCR4 GAGE12J HLA-F IL12A ITGB1 BTLA CD226 CD8A CXCR5 GAGE13 HLA-F-AS1 IL12B ITGB2 BUB1 CD244 CD8B CXCR6 GAGE2C HLA-G IL13 ITGB7 C10orf54 CD247 CDK1 CYBB GATA3 HMBS IL15 ITK C1QA CD27 CDKN2A DDX58 GBP1 ICAM1 IL17A JAML C1QB CD274 CDKN3 DGAT2 GNLY ICOS IL17F JCHAIN CA4 CD276 CEACAM1 DMBT1 GPR18 ICOSLG IL18 KIAA0101 CBLB CD28 CEACAM8 EBI3 GRAP2 ID2 IL1A KIR2DL1 CCL17 CD33 CIITA EFNA4 GUSB ID3 IL1B KIR2DL2 CCL18 CD37 CLEC4C EGFR GZMA IDO1 IL2 KIR2DL3 CCL2 CD38 CMKLR1 EGR2 GZMB IDO2 IL21 KLF2 CCL20 CD3D CORO1A EGR3 GZMH IFI27 IL22 KLRB1 CCL21 CD3E CRTAM EIF2AK2 GZMK IFI35 IL23A KLRD1 CCL22 CD3G CSF1R ENTPD1 HAVCR2 IFI44L IL2RA KLRF1 CCL3 CD4 CSF2RB EOMES HERC6 IFI6 IL2RB KLRG1 CCL4 CD40 CTAG1B FAS HGF IFIH1 IL2RG KLRK1 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) 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 June 19, 2020. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 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 June 19, 2020. (which was not certified by peer review) 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 June 19, 2020. At least two different tissue blocks from different areas of the lungs were evaluated for each case. 1 1 = slight to moderate changes; 2 = moderate changes; 3 = severe changes 2 1 = exudative; 2 = proliferating/organizing; 3 = fibrotic 3 1 = yes; 0 = no 4 1 = very few or few; 2 = moderate; 3 = numerous All rights reserved. No reuse allowed without permission. (which was not certified by peer review) 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 June 19, 2020. . https://doi.org/10.1101/2020.06.17.20133637 doi: medRxiv preprint Corona virus resource center Clinical and immunological features of severe and moderate coronavirus References 17 Time to consider histologic pattern of lung injury to treat critically ill patients with COVID-19 infection Pathological findings of COVID-19 associated with acute respiratory distress syndrome Fitting linear mixed-effects models using lme4 Hundreds of genes experienced convergent shifts in selective pressure in marine mammals R: A language and environment for statistical computing ggplot2: elegant graphics for data analysis circlize implements and enhances circular visualization in R Complex heatmaps reveal patterns and correlations in multidimensional genomic data ggfortify: Data visualization tools for statistical analysis results Reshaping data with the reshape package Package 'factoextra'. Extract and visualize the results of multivariate data analyses