Single-cell Atlas Analysis Of Lethal COVID-19 At Different Stages Of Inflammation And Retrospective Analysis Of Mortality Factors

Objective:To explore the immunopathological features of death patients with COVID-19 at different stages of inflammation by mining the single cell sequencing data of autopsy lung tissue based on single cell sequencing technology.And through retrospective analysis of the collected clinical data of COVID-19 patients to explore the risk factors affecting the death of patients.Methods:Lung scRNA-seq data were obtained from GEO database GSE171524 dataset.The samples were grouped according to the clustering analysis results of the expression values of genes related to inflammatory factors,and the differences in cell composition of each group were analyzed.The main cell clusters and cell subclusters were determined by UMAP analysis and annotation.The scores of immune-related pathway gene set and Hallmarker gene set signaling pathways in all cells were calculated by ssGSEA analysis to obtain the pathways with significant differences.The cell interactions of each group were analyzed to reveal the cellular interactions of the main cell clusters of each group,and to locate the receptor-ligand interactions of cell subclusters.Meanwhile,clinical case data of COVID-19 patients admitted to the Department of Infection and the Department of Respiratory and Critical Care Medicine in the First Affiliated Hospital of Soochow University from December 07,2022 to January 31,2023 were collected.Patients were divided into death group and survival group according to whether they survived,and independent risk factors associated with death of COVID-19 patients were analyzed.The receiver operating characteristic(ROC)curve was used to evaluate its predictive power for the prognosis of COVID-19 patients.Results:After batch removal,normalization,integration and screening,21 samples were obtained from 27 lung scRNA-seq data sets in the GSE171524 dataset,which could be divided into normal group,early group and late group.Type Ⅱ alveolar epithelial cells and Type Ⅰ alveolar epithelial cells were the highest in the normal group.The proportion of macrophages in the early group was the highest.The proportion of fibroblasts in the late group was the highest.ssGSEA analysis showed significant differences in antigen-presenting co-stimulation,chemokine receptors,immune checkpoints,HLA,pro-inflammatory factors,MHCI,Para-inflammation,T-cell co-stimulation,and type Ⅱ interferon responses among the three groups.In addition,the Wnt/β-catenin signaling pathway was significantly different among all three groups in 11 out of 19 main cell clusters and significantly different among all three groups in 15 out of 41 cell subclusters.Kaplan-Meier survival analysis showed that there was a significant difference in OS between high-score and low-score groups(P=0.031)in Wnt/β-catenin signaling pathway target gene MMP7 positive cells.Higher Wnt/β-catenin signaling pathway ssGSEA score was associated with shorter OS and worse prognosis.Endothelial cells and epithelial cells interacted obviously in the normal group.The proportion of immune cell interaction increased in the early group.However,the late component fibrocytes and smooth muscle cells interacted obviously.There were also significant differences in receptor-ligand interactions between the early and late groups.In the retrospective analysis of clinical data,50 patients who died were selected as the death group,and 50 patients from 185 surviving patients were selected as the control by random sampling method.Univariate analysis showed that there were significant differences in age,male patients,existing chronic history,first clinical manifestations of Chest tightness and wheezing,WBC,LY,NE,RBC,HGB,PLT,BUN,CR,ALB,LDH,CRP,PCT,IL-6,IL-10,APTT,antiprothrombin Ⅲ activity,FDP,D-dimerization,PSI score,SOFA score,CURB-65 score,cHIS score,NLR and PLR(P<0.05)between the two groups.Binary multivariate Logistic regression analysis showed that IL-6 level,PSI score and SOFA score were independent risk factors for death of COVID-19 patients(P<0.05),and the area under the curve(AUC)of the three factors for predicting death risk of COVID-19 patients respectively were 0.793,0.917 and 0.985.Conclusion:The results of single cell analysis indicate that the significant changes in cell composition in each group may be the main cause of inflammation disorder and death in patients with COVID-19.Immune dysfunction plays a significant role in the early group of patients.For high-risk patients,early administration of anti-inflammatory therapy and cytokines inhibitors may help improve the prognosis of patients.The Wnt/β-catenin signaling pathway plays a key role in the immunopathology of lethal COVID-19,and may be involved in suppressing immune response at an early stage,and may be involved in the progression of pulmonary fibrosis in the late stage.Cell interaction analysis showed that in the early stage of inflammation,the role of vascular leakage and anti-fibrosis may be enhanced,while in the late stage,endothelial dysfunction,thrombosis and other pathological changes are further aggravated.Retrospective analysis of clinical data showed that IL-6 level,PSI score and SOFA score were independent risk factors for lethal COVID-19,and SOFA score had the best predictive efficacy.