Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19.

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

Towards precision medicine: Omics approach for COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time.

Plasma cell-free RNA characteristics in COVID-19 patients.

The pathogenesis of COVID-19 is still elusive, which impedes disease progression prediction, differential diagnosis, and targeted therapy. Plasma cell-free RNAs (cfRNAs) carry unique information from human tissue and thus could point to resourceful solutions for pathogenesis and host-pathogen interactions. Here, we performed a comparative analysis of cfRNA profiles between COVID-19 patients and healthy donors using serial plasma. Analyses of the cfRNA landscape, potential gene regulatory mechanisms, dynamic changes in tRNA pools upon infection, and microbial communities were performed. A total of 380 cfRNA molecules were up-regulated in all COVID-19 patients, of which seven could serve as potential biomarkers (AUC > 0.85) with great sensitivity and specificity. Antiviral (NFKB1A, IFITM3, and IFI27) and neutrophil activation (S100A8, CD68, and CD63)-related genes exhibited decreased expression levels during treatment in COVID-19 patients, which is in accordance with the dynamically enhanced inflammatory response in COVID-19 patients. Noncoding RNAs, including some microRNAs (let 7 family) and long noncoding RNAs (GJA9-MYCBP) targeting interleukin (IL6/IL6R), were differentially expressed between COVID-19 patients and healthy donors, which accounts for the potential core mechanism of cytokine storm syndromes; the tRNA pools change significantly between the COVID-19 and healthy group, leading to the accumulation of SARS-CoV-2 biased codons, which facilitate SARS-CoV-2 replication. Finally, several pneumonia-related microorganisms were detected in the plasma of COVID-19 patients, raising the possibility of simultaneously monitoring immune response regulation and microbial communities using cfRNA analysis. This study fills the knowledge gap in the plasma cfRNA landscape of COVID-19 patients and offers insight into the potential mechanisms of cfRNAs to explain COVID-19 pathogenesis.

A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity.

The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further investigate the causality of traits on disease severity. Two causal traits, WBC counts and cholesterol levels, were identified based on MR study, and their functional genes are located at genes MHC complex and ApoE, respectively. Our gene-based analysis and GSEA revealed four interferon pathways, including type I interferon receptor binding and SARS coronavirus and innate immunity. We hope that our work will contribute to studying the genetic mechanisms of disease and serve as a useful reference for COVID-19 diagnosis and treatment.

Genomic epidemiology of SARS-CoV-2 in the UAE reveals novel virus mutation, patterns of co-infection and tissue specific host immune response.

To unravel the source of SARS-CoV-2 introduction and the pattern of its spreading and evolution in the United Arab Emirates, we conducted meta-transcriptome sequencing of 1067 nasopharyngeal swab samples collected between May 9th and Jun 29th, 2020 during the first peak of the local COVID-19 epidemic. We identified global clade distribution and eleven novel genetic variants that were almost absent in the rest of the world and that defined five subclades specific to the UAE viral population. Cross-settlement human-to-human transmission was related to the local business activity. Perhaps surprisingly, at least 5% of the population were co-infected by SARS-CoV-2 of multiple clades within the same host. We also discovered an enrichment of cytosine-to-uracil mutation among the viral population collected from the nasopharynx, that is different from the adenosine-to-inosine change previously reported in the bronchoalveolar lavage fluid samples and a previously unidentified upregulation of APOBEC4 expression in nasopharynx among infected patients, indicating the innate immune host response mediated by ADAR and APOBEC gene families could be tissue-specific. The genomic epidemiological and molecular biological knowledge reported here provides new insights for the SARS-CoV-2 evolution and transmission and points out future direction on host-pathogen interaction investigation.

Transcriptional Start Site Coverage Analysis in Plasma Cell-Free DNA Reveals Disease Severity and Tissue Specificity of COVID-19 Patients.

Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. A deep understanding of the variation of biological characteristics in severe COVID-19 patients is crucial for the detection of individuals at high risk of critical condition for the clinical management of the disease. Herein, by profiling the gene expression spectrum deduced from DNA coverage in regions surrounding transcriptional start site in plasma cell-free DNA (cfDNA) of COVID-19 patients, we deciphered the altered biological processes in the severe cases and demonstrated the feasibility of cfDNA in measuring the COVID-19 progression. The up- and downregulated genes in the plasma of severe patient were found to be closely related to the biological processes and functions affected by COVID-19 progression. More importantly, with the analysis of transcriptome data of blood cells and lung cells from control group and cases with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, we revealed that the upregulated genes were predominantly involved in the viral and antiviral activity in blood cells, reflecting the intense viral replication and the active reaction of immune system in the severe patients. Pathway analysis of downregulated genes in plasma DNA and lung cells also demonstrated the diminished adenosine triphosphate synthesis function in lung cells, which was evidenced to correlate with the severe COVID-19 symptoms, such as a cytokine storm and acute respiratory distress. Overall, this study revealed tissue involvement, provided insights into the mechanism of COVID-19 progression, and highlighted the utility of cfDNA as a noninvasive biomarker for disease severity inspections.

Characterization of respiratory microbial dysbiosis in hospitalized COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, the microbial composition of the respiratory tract and other infected tissues as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Between 27 January and 26 February 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients in Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. We identified distinct signatures of microbial dysbiosis among severely ill COVID-19 patients on broad spectrum antimicrobial therapy. Co-detection of other human respiratory viruses (including human alphaherpesvirus 1, rhinovirus B, and human orthopneumovirus) was demonstrated in 30.8% (4/13) of the severely ill patients, but not in any of the mildly affected patients. Notably, the predominant respiratory microbial taxa of severely ill patients were Burkholderia cepacia complex (BCC), Staphylococcus epidermidis, or Mycoplasma spp. (including M. hominis and M. orale). The presence of the former two bacterial taxa was also confirmed by clinical cultures of respiratory specimens (expectorated sputum or nasal secretions) in 23.1% (3/13) of the severe cases. Finally, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes was demonstrated in one severely ill patient, which might accelerate his disease deterioration and death occurring one month after ICU admission. Our findings point to SARS-CoV-2-related microbial dysbiosis and various antibiotic-resistant respiratory microbes/pathogens in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking strategies are needed to prevent the spread of antimicrobial resistance, improve the treatment regimen and clinical outcomes of hospitalized, severely ill COVID-19 patients.

Initial whole-genome sequencing and analysis of the host genetic contribution to COVID-19 severity and susceptibility.

The COVID-19 pandemic has accounted for millions of infections and hundreds of thousand deaths worldwide in a short-time period. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed interindividual phenotypic variability. Here, we report the first host genetic study in the Chinese population by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third People's Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe, and critical ill patients after the correction of potential confounding factors. Pedigree analysis suggested a potential monogenic effect of loss of function variants in GOLGA3 and DPP7 for critically ill and asymptomatic disease demonstration. Genome-wide association study suggests the most significant gene locus associated with severity were located in TMEM189-UBE2V1 that involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We identified that the HLA-A*11:01, B*51:01, and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial genomic study of Chinese patients provides genetic insights into the phenotypic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.

Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples.

BACKGROUND: COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. METHODS: We applied a novel multiplex PCR amplicon (amplicon)-based and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. RESULTS: We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. CONCLUSIONS: This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses.