Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature

BACKGROUND

To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections.

METHODS

Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and April 2021 were prospectively recruited. Whole-blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C (n = 38) to those from children with KD (n = 136), definite bacterial (DB; n = 188) and viral infections (DV; n = 138). Genes significantly differentially expressed (SDE) between MIS-C and comparator groups were identified. Feature selection was used to identify genes that optimally distinguish MIS-C from other diseases, which were subsequently translated into RT-qPCR assays and evaluated in an independent validation set comprising MIS-C (n = 37), KD (n = 19), DB (n = 56), DV (n = 43), and COVID-19 (n = 39).

RESULTS

In the discovery set, 5696 genes were SDE between MIS-C and combined comparator disease groups. Five genes were identified as potential MIS-C diagnostic biomarkers (HSPBAP1, VPS37C, TGFB1, MX2, and TRBV11-2), achieving an AUC of 96.8% (95% CI: 94.6%-98.9%) in the discovery set, and were translated into RT-qPCR assays. The RT-qPCR 5-gene signature achieved an AUC of 93.2% (95% CI: 88.3%-97.7%) in the independent validation set when distinguishing MIS-C from KD, DB, and DV.

CONCLUSIONS

MIS-C can be distinguished from KD, DB, and DV groups using a 5-gene blood RNA expression signature. The small number of genes in the signature and good performance in both discovery and validation sets should enable the development of a diagnostic test for MIS-C.

Characterisation of the blood RNA host response underpinning severity in COVID-19 patients

Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups. Increasing COVID-19 severity was characterised by an abundance of inflammatory immune response genes and pathways, including many related to neutrophils and macrophages, in addition to an upregulation of immunoglobulin genes. In this study, for the first time, we show how immunomodulatory treatments commonly administered to COVID-19 patients greatly alter the transcriptome. Our insights into COVID-19 severity reveal the role of immune dysregulation in the progression to severe disease and highlight the need for further research exploring the interplay between SARS-CoV-2 and the inflammatory immune response.

Tobacco cessation outcomes in a cohort of patients attending a chest medicine outpatient clinic in Bangalore city, southern India

BACKGROUND & OBJECTIVES

Nicotine dependence is a widely prevalent and harmful chronic addictive disorder. Quitting tobacco use is however, uncommon in India. We present long-term treatment outcomes of out-patient, tobacco cessation treatments from a specialty clinic setting in southern India.

METHODS

Patients seen in a tobacco cessation clinic were characterized for tobacco use, nicotine dependence and motivation for quitting and offered pharmacologic/non-pharmacologic treatment. They were subsequently contacted telephonically at a mean (±standard deviation) of 24 (±9.1) months to assess tobacco cessation outcome defined as 'point prevalence of 1-month abstinence' by self-reporting.

RESULTS

The mean age of participants was 48.0 ±14.0 yr. Tobacco use distribution was: beedis only (22%), cigarettes only (49%), beedis and cigarettes (18%), chewing only (2%), and smoking and chewing (9%). Two-thirds had high level of nicotine dependence. Of the 189 patients enrolled, only 15 per cent attended follow up clinics. Only 106 (56%) patients were successfully contacted telephonically and 83 (44%) were lost to follow up. Self-reported point prevalence abstinence was 5 per cent by 'intent-to-treat' analysis and 10 per cent by 'responder' analysis. Two clinical parameters - high level of nicotine dependence [estimated by the heaviness of smoking index (HSI)] and the absence of vascular or other chronic disease were found to be associated with successful quitting; these were however, not significant on multivariate analysis.

INTERPRETATION & CONCLUSIONS

Our study has identified low quit-rates in a cohort of patients attending a hospital-based tobacco cessation clinic. In the absence of clear-cut predictors of cessation with low quit-rates, there should be continued efforts to improve cessation outcomes and identify predictors for action.