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

Fragmentomics of plasma mitochondrial and nuclear DNA inform prognosis in COVID-19 patients with critical symptoms

BACKGROUND

The mortality rate of COVID-19 patients with critical symptoms is reported to be 40.5%. Early identification of patients with poor progression in the critical cohort is essential to timely clinical intervention and reduction of mortality. Although older age, chronic diseases, have been recognized as risk factors for COVID-19 mortality, we still lack an accurate prediction method for every patient. This study aimed to delve into the cell-free DNA fragmentomics of critically ill patients, and develop new promising biomarkers for identifying the patients with high mortality risk.

METHODS

We utilized whole genome sequencing on the plasma cell-free DNA (cfDNA) from 33 COVID-19 patients with critical symptoms, whose outcomes were classified as survival (n = 16) and death (n = 17). Mitochondrial DNA (mtDNA) abundance and fragmentomic properties of cfDNA, including size profiles, ends motif and promoter coverages were interrogated and compared between survival and death groups.

RESULTS

Significantly decreased abundance (~ 76% reduction) and dramatically shorter fragment size of cell-free mtDNA were observed in deceased patients. Likewise, the deceased patients exhibited distinct end-motif patterns of cfDNA with an enhanced preference for "CC" started motifs, which are related to the activity of nuclease DNASE1L3. Several dysregulated genes involved in the COVID-19 progression-related pathways were further inferred from promoter coverages. These informative cfDNA features enabled a high PPV of 83.3% in predicting deceased patients in the critical cohort.

CONCLUSION

The dysregulated biological processes observed in COVID-19 patients with fatal outcomes may contribute to abnormal release and modifications of plasma cfDNA. Our findings provided the feasibility of plasma cfDNA as a promising biomarker in the prognosis prediction in critically ill COVID-19 patients in clinical practice.

Plasma Cell-Free DNA Concentration and Fragmentomes Predict Neoadjuvant Chemotherapy Response in Cervical Cancer Patients

Cervical cancer remains one of the most lethal gynecological malignancies. However, biomarkers for more precise patient care are an unmet need. Herein, the concentration of 285 plasma cell-free DNA (cfDNA) samples are analyzed from 84 cervical patients and the clinical significance of cfDNA fragmentomic characteristics across the neoadjuvant chemotherapy (NACT) treatment. Patients with poor NACT response exhibit a significantly greater escalation in cfDNA levels following the initial cycle of treatment, in comparison to patients with a favorable response. Distinctive end motif profiles and promoter coverages of cfDNA in initial plasma are observed between patients with differing NACT responses. Notably, the DNASE1L3 analysis further demonstrates the intrinsic association between cfDNA characteristics and chemotherapy resistance. The cfDNA and motif ratios show a good discriminative capacity for predicting non-responders from responders (area under the curve (AUC) > 0.8). In addition, transcriptional start sites (TSS) coverages around promoters discern the alteration of biological processes associated with chemotherapy resistance and reflect the potential value in predicting chemotherapy response. These findings in predictive biomarkers may optimize treatment selection, minimize unnecessary treatment, and assist in establishing personalized treatment strategies for cervical cancer patients.

Periodontitis-Derived Dark-NETs in Severe Covid-19

The frequent severe COVID-19 course in patients with periodontitis suggests a link of the aetiopathogenesis of both diseases. The formation of intravascular neutrophil extracellular traps (NETs) is crucial to the pathogenesis of severe COVID-19. Periodontitis is characterised by an increased level of circulating NETs, a propensity for increased NET formation, delayed NET clearance and low-grade endotoxemia (LGE). The latter has an enormous impact on innate immunity and susceptibility to infection with SARS-CoV-2. LPS binds the SARS-CoV-2 spike protein and this complex, which is more active than unbound LPS, precipitates massive NET formation. Thus, circulating NET formation is the common denominator in both COVID-19 and periodontitis and other diseases with low-grade endotoxemia like diabetes, obesity and cardiovascular diseases (CVD) also increase the risk to develop severe COVID-19. Here we discuss the role of propensity for increased NET formation, DNase I deficiency and low-grade endotoxaemia in periodontitis as aggravating factors for the severe course of COVID-19 and possible strategies for the diminution of increased levels of circulating periodontitis-derived NETs in COVID-19 with periodontitis comorbidity.

Methylated ccfDNA from plasma biomarkers of Alzheimer's disease using targeted bisulfite sequencing

Aim: Noninvasive biomarkers such as methylated ccfDNA from plasma could help to support the diagnosis of Alzheimer's disease (AD). Methods: A targeted sequencing protocol was developed to identify candidate biomarkers of AD in methylated ccfDNA extracted from plasma. Results: The authors identified differentially methylated CpGs, regions of which were the same as those identified in previous AD studies. Specifically, a differentially methylated CpG of the LHX2 gene previously identified in a plasma study of AD was replicated in the study. The MBP and DUSP22 regions have been identified in other brain studies of AD and in the authors' study. Conclusion: Although these biomarkers must be validated in other cohorts, methylated ccfDNA could be a relevant noninvasive biomarker in AD.

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.