RESUMEN
Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circulating cell-free RNA (cfRNA) in plasma as an analyte for the differential diagnosis and characterization of pediatric inflammatory syndromes. We profiled cfRNA in 370 plasma samples from pediatric patients with a range of inflammatory conditions, including Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), viral infections, and bacterial infections. We developed machine learning models based on these cfRNA profiles, which effectively differentiated KD from MIS-C-two conditions presenting with overlapping symptoms-with high performance [test area under the curve = 0.98]. We further extended this methodology into a multiclass machine learning framework that achieved 80% accuracy in distinguishing among KD, MIS-C, viral, and bacterial infections. We further demonstrated that cfRNA profiles can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system, and the upper respiratory tract. Overall, this study identified cfRNA as a versatile analyte for the differential diagnosis and characterization of a wide range of pediatric inflammatory syndromes.
Asunto(s)
Ácidos Nucleicos Libres de Células , Aprendizaje Automático , Síndrome Mucocutáneo Linfonodular , Síndrome de Respuesta Inflamatoria Sistémica , Humanos , Niño , Síndrome de Respuesta Inflamatoria Sistémica/diagnóstico , Síndrome de Respuesta Inflamatoria Sistémica/sangre , Preescolar , Ácidos Nucleicos Libres de Células/sangre , Ácidos Nucleicos Libres de Células/genética , Masculino , Femenino , Síndrome Mucocutáneo Linfonodular/diagnóstico , Síndrome Mucocutáneo Linfonodular/sangre , Síndrome Mucocutáneo Linfonodular/genética , Diagnóstico Diferencial , Lactante , Inflamación/sangre , Infecciones Bacterianas/diagnóstico , Infecciones Bacterianas/sangre , Adolescente , Virosis/diagnóstico , Virosis/sangre , Virosis/genética , Biomarcadores/sangre , COVID-19/complicacionesRESUMEN
Hematopoietic Stem Cell Transplantation (HSCT) is one of the oldest and most successful immunotherapies. Yet, despite long-standing success in the use of HSCT for the treatment of blood cancers and severe immune disorders, monitoring post-transplant complications remains a challenge due to a lack of informative diagnostic tests. Here, we investigate the utility of cell-free RNA (cfRNA) in plasma as a liquid biopsy to monitor allogeneic HSCT recipients during and after treatment. We assayed longitudinal samples from 92 HSCT recipients by cfRNA sequencing and show that cfRNA provides insight into treatment and recovery trajectories, immune dynamics in response to transplantation, infection, and solid-tissue injury associated with Graft-Versus-Host Disease. Collectively, our results provide support for the use of plasma cfRNA profiling to monitor complications of HSCT.
RESUMEN
Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circulating cell-free RNA (cfRNA) in plasma as an analyte for the differential diagnosis and characterization of pediatric inflammatory syndromes. We profiled cfRNA in 370 plasma samples from pediatric patients with a range of inflammatory conditions, including Kawasaki disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), viral infections and bacterial infections. We developed machine learning models based on these cfRNA profiles, which effectively differentiated KD from MIS-C - two conditions presenting with overlapping symptoms - with high performance (Test Area Under the Curve (AUC) = 0.97). We further extended this methodology into a multiclass machine learning framework that achieved 81% accuracy in distinguishing among KD, MIS-C, viral, and bacterial infections. We further demonstrated that cfRNA profiles can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system, and the upper respiratory tract. Overall, this study identified cfRNA as a versatile analyte for the differential diagnosis and characterization of a wide range of pediatric inflammatory syndromes.
RESUMEN
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 COVID-19 or MIS-C across three hospitals. Profiling of plasma cell-free nucleic acids uncovers distinct signatures of cell injury and death between COVID-19 and MIS-C, with increased multiorgan involvement in MIS-C encompassing diverse cell types, including endothelial and neuronal cells, and an enrichment of pyroptosis-related genes. Whole-blood RNA profiling reveals upregulation of similar pro-inflammatory 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 but complementary signatures for each disease state. Our work provides a systems-level view of immune responses and tissue damage in COVID-19 and MIS-C and informs future development of new disease biomarkers.
Asunto(s)
COVID-19 , Ácidos Nucleicos Libres de Células , Ácidos Nucleicos , Humanos , Niño , COVID-19/genética , ARN , BiomarcadoresRESUMEN
The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2-8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.