Background: Timely diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a prerequisite for treatment and prevention. The serology characteristics and complement diagnosis value of the antibody test to RNA test need to be demonstrated.Method: Serial sera of 80 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) were collected at the First Affiliated Hospital of Zhejiang University, Hangzhou, China. Total antibody (Ab), IgM and IgG antibodies against SARS-CoV-2 were detected, and the antibody dynamics during the infection were described.Results: The seroconversion rates for Ab, IgM and IgG were 98.8%, 93.8% and 93.8%, respectively. The first detectible serology marker was Ab, followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days post exposure (d.p.e.) or 9, 10 and 12 days post onset (d.p.o.), respectively. The antibody levels increased rapidly beginning at 6 d.p.o. and were accompanied by a decline in viral load. For patients in the early stage of illness (0–7 d.p.o), Ab showed the highest sensitivity (64.1%) compared with IgM and IgG (33.3% for both; p<0.001). The sensitivities of Ab, IgM and IgG increased to 100%, 96.7% and 93.3%, respectively, 2 weeks later. When the same antibody type was detected, no significant difference was observed between enzyme-linked immunosorbent assays and other forms of immunoassays.Conclusions: A typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing in the later stages of illness for pathogenic-specific diagnosis and helpful information to evaluate the adapted immunity status of patients.
Immune inhibitory receptors play an important role in chronic infections. However, little is known about their role in hepatitis B virus (HBV) infection. Here, we analyzed the relationship between programmed death-1 (PD-1) and lymphocyte activation gene-3 (LAG-3) expression on CD4+ T cells and HBV disease progression. PD-1 and LAG-3 expression was significantly higher on CD4+ T cells from HBV patients than on those from the HCs. In addition, a significant positive correlation was found between the PD-1 and LAG-3 expression levels and the ALT(alanine aminotransferase) level. CD4+ T cell function was inhibited by high PD-1 and LAG-3 levels, and CD4+ T cells with high PD-1 and LAG-3 expression lost the ability to secrete IFN-γ, IL-2 and TNF-α. Furthermore, blockade of the PD-1 and LAG-3 pathways reversed the damage to CD4+ T cell proliferation and cytokine secretion. CD4+ T cell exhaustion during chronic HBV had high PD-1 and LAG-3 expression and the absence of helper T cell cytokines, including IFN-γ, IL-2 and TNF-α. After blocking PD-L1 and LAG-3, CD4+ T cell function in chronic hepatitis B patients was partially restored.
In this study, we show that although plasma mNGS testing significantly improved the detection rate of tested samples, nearly one in four (24.5%, 48/196) mNGS tests reported organisms were not clinically relevant, emphasizing the importance of cautious interpretation and infectious disease consultation. Moreover, based on clinical adjudication, plasma mNGS testing resulted in no or a negative impact in nearly half (43.5%, 64/147) of patients in the current study, indicating that how best to integrate this advanced method into current infectious disease diagnostic frameworks to maximize its clinical utility in real-world practice is an important question.
Nanopore sequencing, known for real-time analysis, shows promise for rapid clinical infection diagnosis but lacks effective assays for bloodstream infections (BSIs). We prospectively assessed the performance of a novel nanopore targeted sequencing (NTS) assay in identifying pathogens and predicting antibiotic resistance in BSIs, analyzing 387 blood samples from December 2021 to April 2023. The positivity rate for NTS (69.5%, 269/387) nearly matches that of metagenomic next-generation sequencing (mNGS) (74.7%, 289/387; p=0.128) and surpasses the positivity rate of conventional blood culture (BC) (33.9%, 131/387; p<0.01). Frequent pathogens detected by NTS included Klebsiella pneumoniae (n=54), Pseudomonas aeruginosa (n=36), Escherichia coli (n=36), Enterococcus faecium(n=30), Acinetobacter baumannii(n=26), Staphylococcus aureus(n=23), and Human cytomegalovirus (n=37). Against a composite BSI diagnostic standard, NTS demonstrated a sensitivity and specificity of 84.0% (95% CI 79.5%-87.7%) and 90.1% (95% CI 81.7%-88.5%), respectively. The concordance between NTS and mNGS results (the percentage of total cases where both either detected BSI-related pathogens or were both negative) was 90.2% (359/387), whereas the consistency between NTS and BC was only 60.2% (233/387). In 80.6% (50/62) of the samples with identical pathogens identified by both NTS tests and BCs, the genotypic resistance identified by NTS correlated with culture-confirmed phenotypic resistance. Using NTS, 95% of samples can be tested and analyzed in approximately 7hours, allowing for early patient diagnosis. NTS is rapid, sensitive, and efficient for detecting BSIs and drug-resistant genes, making it a potential preferred diagnostic tool for early infection identification in critically ill patients.