Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases.

BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2. The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki disease or severe bacterial and viral infections, is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases. METHODS: Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n = 22), Kawasaki disease (n = 23), definite bacterial (n = 28) and viral (n = 27) disease and healthy controls (n = 8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C and association with severity of illness. RESULTS: Plasma levels of CD163, CXCL9 and PCSK9 were significantly elevated in MIS-C with a combined area under the receiver operating characteristic curve of 85.7% (95% confidence interval: 76.6%-94.8%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring inotropes, pediatric intensive care unit admission or with shock. CONCLUSION: Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology.

Subgroups of children with Kawasaki disease: a data-driven cluster analysis.

BACKGROUND: Although Kawasaki disease is commonly regarded as a single disease entity, variability in clinical manifestations and disease outcome has been recognised. We aimed to use a data-driven approach to identify clinical subgroups. METHODS: We analysed clinical data from patients with Kawasaki disease diagnosed at Rady Children's Hospital (San Diego, CA, USA) between Jan 1, 2002, and June 30, 2022. Patients were grouped by hierarchical clustering on principal components with k-means parcellation based on 14 variables, including age at onset, ten laboratory test results, day of illness at the first intravenous immunoglobulin infusion, and normalised echocardiographic measures of coronary artery diameters at diagnosis. We also analysed the seasonality and Kawasaki disease incidence from 2002 to 2019 by subgroup. To explore the biological underpinnings of identified subgroups, we did differential abundance analysis on proteomic data of 6481 proteins from 32 patients with Kawasaki disease and 24 healthy children, using linear regression models that controlled for age and sex. FINDINGS: Among 1016 patients with complete data in the final analysis, four subgroups were identified with distinct clinical features: (1) hepatobiliary involvement with elevated alanine transaminase, gamma-glutamyl transferase, and total bilirubin levels, lowest coronary artery aneurysm but highest intravenous immunoglobulin resistance rates (n=157); (2) highest band neutrophil count and Kawasaki disease shock rate (n=231); (3) cervical lymphadenopathy with high markers of inflammation (erythrocyte sedimentation rate, C-reactive protein, white blood cell, and platelet counts) and lowest age-adjusted haemoglobin Z scores (n=315); and (4) young age at onset with highest coronary artery aneurysm but lowest intravenous immunoglobulin resistance rates (n=313). The subgroups had distinct seasonal and incidence trajectories. In addition, the subgroups shared 211 differential abundance proteins while many proteins were unique to a subgroup. INTERPRETATION: Our data-driven analysis provides insight into the heterogeneity of Kawasaki disease, and supports the existence of distinct subgroups with important implications for clinical management and research design and interpretation. FUNDING: US National Institutes of Health and the Irving and Francine Suknow Foundation.

Adeno-associated virus 2 infection in children with non-A-E hepatitis.

An outbreak of acute hepatitis of unknown aetiology in children was reported in Scotland1 in April 2022 and has now been identified in 35 countries2. Several recent studies have suggested an association with human adenovirus with this outbreak, a virus not commonly associated with hepatitis. Here we report a detailed case-control investigation and find an association between adeno-associated virus 2 (AAV2) infection and host genetics in disease susceptibility. Using next-generation sequencing, PCR with reverse transcription, serology and in situ hybridization, we detected recent infection with AAV2 in plasma and liver samples in 26 out of 32 (81%) cases of hepatitis compared with 5 out of 74 (7%) of samples from unaffected individuals. Furthermore, AAV2 was detected within ballooned hepatocytes alongside a prominent T cell infiltrate in liver biopsy samples. In keeping with a CD4+ T-cell-mediated immune pathology, the human leukocyte antigen (HLA) class II HLA-DRB1*04:01 allele was identified in 25 out of 27 cases (93%) compared with a background frequency of 10 out of 64 (16%; P = 5.49 × 10-12). In summary, we report an outbreak of acute paediatric hepatitis associated with AAV2 infection (most likely acquired as a co-infection with human adenovirus that is usually required as a 'helper virus' to support AAV2 replication) and disease susceptibility related to HLA class II status.

Sanger sequencing.

This poster beautifully illustrates the process and importance of Sanger sequencing. Developed by Diego Estrada-Rivadeneyra, it won one of the three 50th anniversary science communication competition prizes.

A resource for functional profiling of noncoding RNA in the yeast Saccharomyces cerevisiae.

Eukaryotic genomes are extensively transcribed, generating many different RNAs with no known function. We have constructed 1502 molecular barcoded ncRNA gene deletion strains encompassing 443 ncRNAs in the yeast Saccharomyces cerevisiae as tools for ncRNA functional analysis. This resource includes deletions of small nuclear RNAs (snRNAs), transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), and other annotated ncRNAs as well as the more recently identified stable unannotated transcripts (SUTs) and cryptic unstable transcripts (CUTs) whose functions are largely unknown. Specifically, deletions have been constructed for ncRNAs found in the intergenic regions, not overlapping genes or their promoters (i.e., at least 200 bp minimum distance from the closest gene start codon). The deletion strains carry molecular barcodes designed to be complementary with the protein gene deletion collection enabling parallel analysis experiments. These strains will be useful for the numerous genomic and molecular techniques that utilize deletion strains, including genome-wide phenotypic screens under different growth conditions, pooled chemogenomic screens with drugs or chemicals, synthetic genetic array analysis to uncover novel genetic interactions, and synthetic dosage lethality screens to analyze gene dosage. Overall, we created a valuable resource for the RNA community and for future ncRNA research.

Stenotrophomonas maltophilia in Mexico: antimicrobial resistance, biofilm formation and clonal diversity.

Stenotrophomonas maltophilia is an important multidrug-resistant nosocomial pathogen associated with high mortality. Our aim was to examine antimicrobial susceptibility, biofilm production and clonal relatedness of clinical isolates of S. maltophilia. S. maltophilia isolates were collected between 2006 and 2013 from two tertiary care hospitals in Mexico. Antimicrobial susceptibility was evaluated by the broth microdilution method. PCR was used to determine the presence of ß-lactamase genes L1 and L2. Biofilm formation was assessed with crystal violet staining. Clonal relatedness was determined by PFGE. Among the 119 collected S. maltophilia isolates, 73 (61.3%) were from the respiratory tract. Resistance levels exceeded 75% for imipenem, meropenem, ampicillin, aztreonam, gentamicin and tobramycin. Resistance to trimethoprim-sulfamethoxazole was 32.8%. L1 and L2 genes were detected in 77.1% (91/118) and 66.9% (79/118) of isolates, respectively. All S. maltophilia strains were able to produce biofilms. Strains were classified as weak (47.9%, 57/119), moderate (38.7%, 46/119), or strong (13.4%, 16/119) biofilm producers. A total of 89 distinct PFGE types were identified and 21.6% (22/102) of the isolates were distributed in nine clusters. This is the first study in Mexico to reveal characteristics of clinical isolates of S. maltophilia. Clonal diversity data indicate low cross-transmission of S. maltophilia in a hospital setting. The high antibiotic resistance underscores the need for continuous surveillance of S. maltophilia in hospital settings in Mexico.