A gene expression-based diagnostic classifier for identification of severe COVID-19 and multisystem inflammatory syndrome in children (MIS-C)

MIS-C is a severe hyperinflammatory condition with involvement of multiple organs that occurs in children who had COVID-19 infection. Accurate diagnostic tests are needed to guide management and appropriate treatment and to inform clinical trials of experimental drugs and vaccines, yet the diagnosis of MIS-C is highly challenging due to overlapping clinical features with other acute syndromes in hospitalized patients. Here we developed a gene expression-based classifier for MIS-C by RNA-Seq transcriptome profiling and machine learning based analyses of 195 whole blood RNA and 76 plasma cell-free RNA samples from 191 subjects, including 95 MIS-C patients, 66 COVID-19 infected patients with moderately severe to severe disease, and 30 uninfected controls. We divided the group into a training set (70%) and test set (30%). After selection of the top 300 differentially expressed genes in the training set, we simultaneously trained 13 classification models to distinguish patients with MIS-C and COVID-19 from controls using five-fold cross-validation and grid search hyperparameter tuning. The final optimal classifier models had 100% diagnostic accuracy for MIS-C (versus non-MIS-C) and 85% accuracy for severe COVID-19 (versus mild/asymptomatic COVID-19). Orthogonal validation of a random subset of 11 genes from the final models using quantitative RT-PCR confirmed the differential expression and ability to discriminate MIS-C and COVID-19 from controls. These results underscore the utility of a gene expression classifier for diagnosis of MIS-C and severe COVID-19 as specific and objective biomarkers for these conditions.

Nucleic acid biomarkers of immune response and cell and tissue damage in children with COVID-19 and MIS-C

Differential host responses in coronavirus disease 2019 (COVID-19) and multisystem inflammatory syndrome in children (MIS-C) remain poorly characterized. Here we use next-generation sequencing to longitudinally analyze blood samples from pediatric patients with acute COVID-19 (n=70) or MIS-C (n=141) across three hospitals. Profiling of plasma cell-free nucleic acids uncovers distinct signatures of cell injury and death between these two disease states, with increased heterogeneity and multi-organ involvement in MIS-C encompassing diverse cell types such as endothelial and neuronal Schwann cells. Whole blood RNA profiling reveals upregulation of similar pro-inflammatory signaling pathways in COVID-19 and MIS-C, but also MIS-C specific downregulation of T cell-associated pathways. Profiling of plasma cell-free RNA and whole blood RNA in paired samples yields different yet complementary signatures for each disease state. Our work provides a systems-level, multi-analyte view of immune responses and tissue damage in COVID-19 and MIS-C and informs the future development of new disease biomarkers.

Kinetics of viral clearance and antibody production across age groups in SARS-CoV-2 infected children

ObjectivesTo improve understanding of transition from viral infection to viral clearance, and antibody response in pediatric patients with SARS-CoV-2 infection. Study designThis retrospective analysis of children tested for SARS-CoV-2 by RT-PCR and IgG antibody at a quaternary-care, free-standing pediatric hospital between March 13th, 2020 to June 21st, 2020 included 6369 patients who underwent PCR testing and 215 patients who underwent antibody testing. During the initial study period, testing focused primarily on symptomatic children; the later study period included asymptomatic patients who underwent testing as preadmission or preprocedural screening. We report the proportion of positive and negative tests, time to viral clearance, and time to seropositivity. ResultsThe rate of positivity varied over time due to viral circulation in the community and transition from targeted testing of symptomatic patients to more universal screening of hospitalized patients. Median duration of viral shedding (RT-PCR positivity) was 19.5 days and RT-PCR negativity from positivity was 25 days. Of note, patients aged 6 to 15 years demonstrated a longer period of RT-PCR negativity from positivity, compared to patients aged 16 to 22 years (median=32 versus 18 days, p=0.015). Median time to seropositivity from RT-PCR positivity was 18 days while median time to reach adequate levels of neutralizing antibodies (defined as equivalent to 160 titer) was 36 days. ConclusionsThe majority of patients demonstrated a prolonged period of viral shedding after infection with SARS CoV-2. Whether this correlates with persistent infectivity is unknown. Only 17 of 33 patients demonstrated neutralizing antibodies, suggesting that some patients may not mount significant immune responses to infection. It remains unknown if IgG antibody production correlates with immunity and how long measurable antibodies persist and protect against future infection.