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: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: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
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
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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
Project description:Osteosarcoma (OS) is the primary bone tumor in children and young adults. Currently, there are no reliable, non-invasive biological markers to detect the presence or progression of disease, assess therapy response, or provide upfront prognostic insights. Using a qPCR-based platform that analyzes more than 750 miRNAs, we analyzed control and diseased-associated plasma from a genetically engineered mouse model of OS to identify a profile of four plasma miRNAs. Plasma from mice with OS were profiled for miRNAs and compared with the profile of plasma from disease-free mice
2015-01-24 | E-GEOD-65236 | biostudies-arrayexpress
Project description:Cell-free RNA (cfRNA) in plasma reflects gene expression profiles of both localized sites of cancer and at the systemic host response. Here we explore the diagnostic potential of cell-free transcriptomes by mRNA sequencing. We sequenced total cell-free plasma RNA from 90 plasma samples from two independent sample cohorts representing two cancer types, two pre-cancerous conditions and non-cancer donors. We identified distinct gene sets and built classification models that could distinguish cancer patients with specific cancer types from premalignant conditions and non-cancer individuals with high accuracy. Determination of multiple myeloma from its pre-cancerous monoclonal gammopathy of undetermined significance (MGUS) yielded an accuracy of 90% (17/19). Detection of primary liver cancer from its premalignant condition cirrhosis yielded an accuracy of 100% (12/12). This work lays the foundation for developing low cost assays by measuring mRNA transcript levels in plasma using a small panel of genes for detection that can distinguish the presence of cancer from pre-cancerous conditions and non-cancer individuals.
2022-04-25 | GSE182824 | GEO