Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space (preprint)

ABSTRACT Computational tools for integrative analyses of diverse single-cell experiments are facing formidable new challenges including dramatic increases in data scale, sample heterogeneity, and the need to informatively cross-reference new data with foundational datasets. Here, we present SCALEX, a deep-learning method that integrates single-cell data by projecting cells into a batch-invariant, common cell-embedding space in a truly online manner ( i.e. , without retraining the model). SCALEX substantially outperforms online iNMF and other state-of-the-art non-online integration methods on benchmark single-cell datasets of diverse modalities, (e.g., scRNA-seq, scATAC-seq), especially for datasets with partial overlaps, accurately aligning similar cell populations while retaining true biological differences. We showcase SCALEX’s advantages by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19 patients, each assembled from diverse data sources and growing with every new data. The online data integration capacity and superior performance makes SCALEX particularly appropriate for large-scale single-cell applications to build-upon previously hard-won scientific insights.

Construction of continuously expandable single-cell atlases through integration of heterogeneous datasets in a generalized cell-embedding space (preprint)

Single-cell RNA-seq and ATAC-seq analyses have been widely applied to decipher cell-type and regulation complexities. However, experimental conditions often confound biological variations when comparing data from different samples. For integrative single-cell data analysis, we have developed SCALEX, a deep generative framework that maps cells into a generalized, batch-invariant cell-embedding space. We demonstrate that SCALEX accurately and efficiently integrates heterogenous single-cell data using multiple benchmarks. It outperforms competing methods, especially for datasets with partial overlaps, accurately aligning similar cell populations while r,etaining true biological differences. We demonstrate the advantages of SCALEX by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19, which were assembled from multiple data sources and can keep growing through the inclusion of new incoming data. Analyses based on these atlases revealed the complex cellular landscapes of human and mouse tissues and identified multiple peripheral immune subtypes associated with COVID-19 disease severity.

CD127 imprints functional heterogeneity to diversify monocyte responses in human inflammatory diseases (preprint)

Studies on human monocytes historically focused on characterization of bulk responses, whereas functional heterogeneity is largely unknown. Here, we identified an inducible population of CD127-expressing human monocytes under inflammatory conditions and named the subset M127. M127 is nearly absent in healthy individuals yet abundantly present in patients with infectious and inflammatory conditions such as COVID-19 and rheumatoid arthritis. Multiple genomic and functional approaches revealed unique gene signatures of M127 and unified anti-inflammatory properties imposed by the CD127-STAT5 axis. M127 expansion correlated with mild COVID-19 disease outcomes. Thereby, we phenotypically and molecularly characterized a human monocyte subset marked by CD127 that retained anti-inflammatory properties within the pro-inflammatory environments, uncovering remarkable functional diversity among monocytes and signifying M127 as a potential therapeutic target for human inflammatory disorders.

Clinical Efficacy of Convalescent Plasma Therapy on Treating COVID-19 Patients: Evidence from Matched Study and a Meta-Analysis (preprint)

Background: COVID-19 has infected tens of millions of people worldwide since its pandemic. CPT is one of the promising treatment methods and is favored by more and more researchers. However, the clinical efficacy and safety of CPT in COVID-19 remains unclear.Methods: We performed a matched control study by PSM analysis (including 163 cases with CPT and 163 controls with the standard treatment) and meta-analysis (including 498 cases and 557 controls) estimate the clinical efficacy and security of CPT and COVID-19, which will help inform clinical management of COVID-19 infection.Results: We found that days of hospital stay in case with CPT groups were significantly higher than matched control group (P< 0.0001). A significant reduction in mortality (OR= 0.496, 95%CI= 0.342-0.719, P< 0.0001) was found in the CPT group compared with the standard treatment group, and a true positive result was also found in sequential analysis. In terms of adverse events, sequential analysis found a false positive, although meta-analysis found a significant increase in the incidence of adverse events in patients treated with CPT compared to the control group. No differences between the two groups in terms of length of stay, improvement of clinical symptoms, and discharge were found.Conclusions: This study is the first to systematically review and meta-analysis the efficacy and safety of CPT in patients with COVID-19 in the largest sample size. Our results showed that CPT could significantly reduce the mortality rate of COVID-19 patients, and there was no significant increase in the incidence of adverse events. These data provide evidence favoring the efficacy and safety of CPT as a therapeutic agent in COVID-19 patients and provide comprehensive reference for COVID-19 treatment.Funding Statement: This work was supported by Scientific Research Project of Jiangsu Commission of Health (H2019065), Key Foundation of Wuhan Huoshenshan Hospital (2020[18]), Key Research & Development Program of Jiangsu Province (BE2018713), Medical Innovation Project of Logistics Service (18JS005).Declaration of Interests: The authors declare no conflicts of interest with this work.Ethics Approval Statement: The authors were approved by the ethics committee of Huoshenshan hospital, and were conducted in accordance with the tenets of the Declaration of Helsinki and its amendments. All participants provided written informed consent for the collection of samples and their subsequent analysis.

Aspergillus But Not Candida: Fatal Fungus Infection in COVID-19 Critical Patients (preprint)

Objectives: Earlier researches suggested patients should be routinely screened for bacteria and fungi infection after COVID-19 being confirmed. Here, we enrolled 236 patients with COVID-19 to analyze the clinical characteristics, fungal strains, mortality, and laboratory data of different groups.Design: Single center retrospective studyPatients: A total of 236 COVID-19 patients from Huoshenshan Hospital were included in this study, consisting of 14(6%) died cases, 222(94%) discharged cases.Results: The result revealed that 5 mortality in positive group were all related to aspergillus infection while candida infection rarely caused death. Aspergillus was most common in non-survivors while candida was most common in survivors. In terms of interleukin-6 (IL6), viral loads, nucleic acid clearance time, etc, fungal serologically positive group had a higher level than negative group.Conclusions: Non-survivors of Covid-19 with fungal infection were almost associated with aspergillus infection. Aspergillus infection, instead of candida infection might be fatal for critical ill patients with COVID-19. There is great significance to carry out routine screening for fungal infection especially for critical patients to enable early treatment to be implemented.Funding Statement: This study was financially supported by grants Key Foundation of Wuhan Huoshenshan Hospital (2020[18]), Key Research& Development Program of Jiangsu Province (BE2018713), Medical Innovation Project of Logistics Service (18JS005).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: This study was approved by the Medical Ethical Committee of Wuhan Huoshenshan Hospital (No. HSSLL011). Written informed consent was obtained from each patient.