Plasma Cell-free RNA Signatures of Inflammatory Syndromes in Children
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PROVIDER: PRJNA1075432 | ENA |
REPOSITORIES: ENA
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Project description: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.
2024-09-11 | GSE255555 | GEO
Project description: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.
| S-EPMC11406294 | biostudies-literature
Project description:Cell-free RNAs in biofluids provide opportunities to monitor cancer in a non-invasive manner. Although extracellular microRNAs are extensively characterized, fragmented cell-free long RNAs are not well investigated. Here, we developed Detector-seq (depletion-assisted multiplexing cell-free total RNA sequencing) to enable the deciphering of the cell-free transcriptome. After demonstrating the superior performance of detecting fragmented cell-free long RNAs, we applied Detector-seq to compare cell-free RNAs in human plasma and its extracellular vesicle (EV). Distinct human and microbial RNA signatures were revealed. Structured circular RNA, tRNA, and Y RNA were enriched in plasma, while mRNA and srpRNA were enriched in EV. Meanwhile, cell-free RNAs derived from the virus were more enriched in plasma than in EV. We identified RNAs that showed a selective distribution between plasma and EV and uncovered their distinct functional pathways, that is RNA splicing, antimicrobial humoral response enriched in plasma and transcriptional activity, cell migration, and antigen receptor-mediated immune signals enriched in EV. Although distinctive cancer-relevant RNA signals were identified in plasma and EV, a comparable performance of distinguishing cancer patients from normal individuals could be achieved. Compared to human RNAs, microbe-derived RNA features enabled better classification between colorectal and lung cancer. And for these microbial RNAs, plasma RNAs outperformed EV RNAs for the discrimination of cancer types. Overall, our work provides insights into the unexplored difference of cell-free RNA signals between plasma and EV, thus offering practical guidance for proper selection (with/without EV enrichment) when launching an RNA-based liquid biopsy study. Furthermore, with the ability to capture understudied cell-free long RNA fragments, Detector-seq offers new possibilities for transcriptome-wide characterization of cell-free RNAs to facilitate the understanding of extracellular RNA biology and clinical advances of liquid biopsy.
2024-03-27 | GSE216561 | GEO
Project description:Multisystem inflammatory syndrome in Children (MIS-C) occurs in children between two and six weeks following an initial SARS-CoV-2 infection. The mechanism through which a minority of children develop the hyperinflammation characteristic of MIS-C, while others remain well, is unknown. In this study we present an in-depth assessment of the proteome of children before and after SARS-CoV-2 infection, including children with MIS-C. Reassuringly, these data show that there were minimal changes to the circulating proteome in healthy children as result of SARS-CoV2 infection and there was no evidence of continued inflammation following SARS-CoV-2 infection in children. However, activation of pro-inflammatory pathways and raised circulating markers of myocardial and vascular damage were found to be significantly associated with MIS-C. Our findings have been verified in silico using publicly available proteomic datasets and hence several promising candidate biomarker proteins for diagnosis of MIS-C are identified and described herein.
2025-08-25 | PXD051939 | Pride
Project description:We investigated the spectra of circulating miRNAs in plasma of myelodysplastic syndromes (MDS) patients. Peripheral blood plasma from MDS patients with different risk scores was used for Agilent miRNA expression microarray analysis to define miRNA profile and to find miRNAs with discriminatory levels for lower risk and higher risk MDS. Results were further validated using droplet digital PCR on a larger cohort, enabling absolute quantification of plasma miRNAs and defining miRNAs with prognostic value for the disease. We analyzed expression profile of circulating miRNAs in plasma from 21 individuals: 7 controls and 14 MDS patients.
2016-01-13 | E-GEOD-76775 | biostudies-arrayexpress
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Project description:While fewer cases of severe Coronavirus Disease 2019 (COVID-19) are reported globally in children, a small proportion of SARS-CoV-2 infected children develop a novel pediatric febrile entity called multisystem inflammatory syndrome in children (MIS-C) that develops 2 to 5 weeks after initial SARS-CoV-2 exposure. MIS-C primarily effects male children and children of Hispanic or black descent. MIS-C manifests as a severe and uncontrolled inflammatory response with multiorgan involvement. A hyperinflammatory state is evidenced by clinical makers of inflammation including high levels of C-reactive protein (CRP), ferritin, and D-dimers, and an increased expression of pro-inflammatory cytokines. Children often present with persistent fever, severe gastrointestinal symptoms, cardiovascular manifestations, respiratory symptoms and neurological symptoms6-11,13. Cardiovascular manifestations include hypotension, shock, cardiac dysfunction, myocarditis and pericardial effusion. In the united states, admission to the intensive care unit occurs in approximately 58% of cases. To understand disease pathogenesis of MIS-C and proteins associated with the severe form of disease we performed proteomics analysis of serum or plasma samples. We collected serum from healthy children (SARS-CoV-2 negative, n=20), mild MIS-C (non-ICU, n=5) and severe MIS-C (ICU, n = 20) patients. MIS-C definition and diagnosis was performed according to CDC guidelines. Healthy adult serum (n = 4) was also used for reference ranges quality control and we obtained plasma samples from Kawasaki Disease (KD; n=7) patients that were recruited before the Coronavirus Disease 2019 (COVID-19) pandemic.
2021-09-29 | PXD025462 | Pride
Project description:We investigated the spectra of circulating miRNAs in plasma of myelodysplastic syndromes (MDS) patients. Peripheral blood plasma from MDS patients with different risk scores was used for Agilent miRNA expression microarray analysis to define miRNA profile and to find miRNAs with discriminatory levels for lower risk and higher risk MDS. Results were further validated using droplet digital PCR on a larger cohort, enabling absolute quantification of plasma miRNAs and defining miRNAs with prognostic value for the disease.
2016-01-13 | GSE76775 | GEO
Project description:We report the application of high-throughput RNA sequencing technology to examine expression profiling of plasma transfer RNA (tRNA)-derived small RNAs (tsRNAs) in children with fulminant myocarditis during acute phase (FM-A group), children with fulminant myocarditis during convalescent phase (FM-C group), and healthy volunteers (Con group). A total of 750 precisely matched tsRNAs were identified in the plasma from the three groups. We find that a total of 13 tsRNAs were differentially expressed in FM-A and CON samples, of which 11 tsRNAs were upregulated and 2 were downregulated, and 694 tsRNAs were excluded ; a total of 8 tsRNAs were differentially expressed in paired FM-C and CON samples, of which 2 tsRNAs were upregulated and 6 were downregulated and 703 tsRNAs were excluded . This study provides new ideas for future research on elucidating the mechanisms of myocarditis through regulating tsRNAs levels.
2020-12-29 | GSE163944 | GEO