Welcome to the ESPID 2022 Meeting Calendar

Backgrounds:

Metabolomic alterations have been identified in adults with SARS-CoV-2 infection, however this approach has not been used in children so far. Children usually have a mild course, although a small percentage may develop severe disease or Multisystem Inflammatory Syndrome (MIS-C).

Methods

We carried out a prospective comparative cohort study (April 2020 to June 2021) enrolling children referred to our COVID-center for symptoms related to acute SARS-CoV-2 infection (positive nasopharyngeal swab) or MIS-C and a cohort of age- and sex-matched children who served as controls. Metabolomic analysis was performed by Gas Chromatography Mass Spectroscopy approach using blood samples collected at admission, acute phase, discharge and a follow-up visit scheduled after negativization. All enrolled patients were hospitalized and classified into mild-to-moderate or severe COVID-19 according to clinical, radiological, and biochemical features.

Results:

A specific metabolomic signature was identified in 92 children (48 males, mean age 3.69±5.1 years) with acute SARS-CoV-2 infection, compared to 41 controls (permutation test statistic p=0.0015, Figure) involving specific pathways, such as: inflammation (spermidine and hypoxanthine), reactive oxygen species pathway (riboflavin) and glicerolipids pathways.

Distinct metabolic signatures were significantly associated with child’s age (mainly > 3 years), clinical and biochemical severity and timing from SARS-CoV-2 infection.

Children with MIS-C (n=9) showed a unique metabolomic signature and different from age- and sex-matched SARS-CoV-2-infected patients or controls characterized by an alteration of spermidine and sphingolipids.

Conclusions/Learning Points:

Pediatric SARS-CoV-2 infection has a characteristic metabolomic signature suggesting a possible involvement of intestinal microbiome, that varies according to patients’ age and disease phenotype. Metabolomic approach may be a useful tool to identify possible early markers of disease and predictors of severe diseases evolution or multi-system inflammatory syndrome.

Backgrounds:

The Multisystem Inflammatory Syndrome in Children (MIS-C) is a rare but potentially severe complication of COVID-19.

Methods

This is a retrospective observational study of children aged <18 years hospitalized with MIS-C in 10 tertiary hospitals in Greece during three pandemic waves characterized by different SARS-CoV-2 variant: i. from August 2020 to January 2021 (EU1-B.1.177), ii. from February 2021 to July 2021 (Alpha-B.1.1.7) and iii. from August 2021 to December 2021 (Delta-B.1.617.2). The aim of the study was to document the incidence over time, clinical characteristics and outcome of children admitted with MIS-C in Greek hospitals during the COVID-19 pandemic.

Results:

In total, 119 patients were included, 91.6% (109/119) met the WHO criteria of MIS-C diagnosis: 26.9% (32/119), 39.5% (47/119) and 33.6% (40/119) were hospitalized during the 1st, 2nd, and 3rd study period, respectively. Demographic and clinical characteristics are shown in Table 1. No cases were found before October 2020. The incidence of MIS-C significantly decreased over the three waves from 3.3/1000 to 0.25/1000 confirmed COVID-19 cases (P <0.0001). No other significant difference was observed in the clinical manifestations and disease severity of children hospitalized with MIS-C over the three waves.

Conclusions/Learning Points:

This study indicates that the incidence of MIS-C may vary according to the predominant variant. Outcome remains favourable regardless of the variant leading to MIS-C. Larger studies are needed to clarify if clinical characteristics and/or disease severity may differ, as well.

Backgrounds:

Multisystem Inflammatory Syndrome in Children (MIS-C) occurs several weeks after SARS-CoV-2 infection with symptoms including fever, shock and multiorgan failure. Clinical features of MIS-C overlap with Kawasaki Disease (KD), bacterial, and viral infections, making accurate diagnosis challenging. Host genes, measurable through whole blood transcriptomics, are an alternative tool for diagnosing infectious and inflammatory diseases.

Methods

Patients with MIS-C, KD, bacterial, and viral infections were recruited to the EU-funded PERFORM and DIAMONDS studies and the NIH-funded PREVAIL study. Patients were phenotyped using a standardised algorithm. Genome wide RNA sequencing of whole blood was undertaken, and feature selection was performed to identify a diagnostic signature for distinguishing between MIS-C and other infectious and inflammatory conditions. The expression levels of the genes identified were measured using RT-qPCR assays in an independent validation cohort.

Results:

Through feature selection and differential expression analysis, 11 genes with diagnostic potential were identified and taken forward into cross-platform validation using RT-qPCR. With up to 11 genes, it was possible to distinguish between MIS-C vs. KD, bacterial, and viral infections with high accuracy, with an AUC of 92.9% (95% CI: 88.2%-97.6%) in the validation cohort. The diagnostic gene signature retained its high performance when tested within the groups separately in the validation cohort: MIS-C vs. bacterial infections (AUC: 94.6%), vs. viral infections (AUC: 93.1%), and vs. KD (AUC: 89.8%).

Conclusions/Learning Points:

Despite the clinical similarities between MIS-C and other infectious and inflammatory conditions, there are key differences in gene expression profiles that can be used in diagnostic contexts. It will be necessary for the genes reported here to undergo further validation prior to their development into tests with clinical utility.