ABSTRACT
Background Little is known about the dynamics of SARS-CoV-2 antigen burden in respiratory samples in different patient populations at different stages of infection. Current rapid antigen tests cannot quantitate and track antigen dynamics with high sensitivity and specificity in respiratory samples. Methods We developed and validated an ultra-sensitive SARS-CoV-2 antigen assay with smartphone readout using the Microbubbling Digital Assay previously developed by our group, which is a platform that enables highly sensitive detection and quantitation of protein biomarkers. A computer vision-based algorithm was developed for microbubble smartphone image recognition and quantitation. A machine learning-based classifier was developed to classify the smartphone images based on detected microbubbles. Using this assay, we tracked antigen dynamics in serial swab samples from COVID patients hospitalized in ICU and immunocompromised COVID patients. Results The limit of detection (LOD) of the Microbubbling SARS-CoV-2 Antigen Assay was 0.5 pg/mL (10.6 fM) recombinant nucleocapsid (N) antigen or 4000 copies/mL inactivated SARS-CoV-2 virus in nasopharyngeal (NP) swabs, comparable to many rRT-PCR methods. The assay had high analytical specificity towards SARS-CoV-2. Compared to EUA-approved rRT-PCR methods, the Microbubbling Antigen Assay demonstrated a positive percent agreement (PPA) of 97% (95% confidence interval (CI), 92-99%) in symptomatic individuals within 7 days of symptom onset and positive SARS-CoV-2 nucleic acid results, and a negative percent agreement (NPA) of 97% (95% CI, 94-100%) in symptomatic and asymptomatic individuals with negative nucleic acid results. Antigen positivity rate in NP swabs gradually decreased as days-after-symptom-onset increased, despite persistent nucleic acid positivity of the same samples. The computer vision and machine learning-based automatic microbubble image classifier could accurately identify positives and negatives, based on microbubble counts and sizes. Total microbubble volume, a potential marker of antigen burden, correlated inversely with Ct values and days-after-symptom-onset. Antigen was detected for longer periods of time in immunocompromised patients with hematologic malignancies, compared to immunocompetent individuals. Simultaneous detectable antigens and nucleic acids may indicate the presence of replicating viruses in patients with persistent infections. Conclusions The Microbubbling SARS-CoV-2 Antigen Assay enables sensitive and specific detection of acute infections, and quantitation and tracking of antigen dynamics in different patient populations at various stages of infection. With smartphone compatibility and automated image processing, the assay is well-positioned to be adapted for point-of-care diagnosis and to explore the clinical implications of antigen dynamics in future studies.
Subject(s)
Nasopharyngitis , Hematologic NeoplasmsABSTRACT
Cancer patients have increased morbidity and mortality from Coronavirus Disease 2019 (COVID-19), but the underlying immune mechanisms are unknown. In a cohort of 100 cancer patients hospitalized for COVID-19 at the University of Pennsylvania Health System, we found that patients with hematologic cancers had a significantly higher mortality relative to patients with solid cancers after accounting for confounders including ECOG performance status and active cancer status. We performed flow cytometric and serologic analyses of 106 cancer patients and 113 non-cancer controls from two additional cohorts at Penn and Memorial Sloan Kettering Cancer Center. Patients with solid cancers exhibited an immune phenotype similar to non-cancer patients during acute COVID-19 whereas patients with hematologic cancers had significant impairment of B cells and SARS-CoV-2-specific antibody responses. High dimensional analysis of flow cytometric data revealed 5 distinct immune phenotypes. An immune phenotype characterized by CD8 T cell depletion was associated with a high viral load and the highest mortality of 71%, among all cancer patients. In contrast, despite impaired B cell responses, patients with hematologic cancers and preserved CD8 T cells had a lower viral load and mortality. These data highlight the importance of CD8 T cells in acute COVID-19, particularly in the setting of impaired humoral immunity. Further, depletion of B cells with anti-CD20 therapy resulted in almost complete abrogation of SARS-CoV-2-specific IgG and IgM antibodies, but was not associated with increased mortality compared to other hematologic cancers, when adequate CD8 T cells were present. Finally, higher CD8 T cell counts were associated with improved overall survival in patients with hematologic cancers. Thus, CD8 T cells likely compensate for deficient humoral immunity and influence clinical recovery of COVID-19. These observations have important implications for cancer and COVID-19-directed treatments, immunosuppressive therapies, and for understanding the role of B and T cells in acute COVID-19.