Human Blood Virome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1240009 | ENA |
REPOSITORIES: ENA
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2016-04-08 | GSE79970 | GEO
Project description:Viromics Study of 421 Serum Samples (Single Samples, Non-Pooled)
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Project description:Viromics Study of Serum Samples from 214 Febrile Patients, Pooled into 54 Pools
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Project description:Global untargeted profiles of dried blood microsamples were studied in comparison to conventional plasma and blood samples using Gas Chromatography-Mass Spectrometry (GC-MS). Venous blood from 10 healthy, overnight-fasted individuals was collected and used to produce dried microsamples on Whatman cards, Capitainer and Mitra devices. In parallel paired plasma samples were collected. The metabolite extraction protocol was optimized and methanol was selected as the extraction solvent, while methoximation and trimethylsilylation derivatization was applied. Blood microsampling, mainly from Mitra and Capitainer devices, provided equivalent or greater information than plasma, considering the number and intensity of features, precision, and annotated metabolites intensity. Furthermore, blood microsample metabolic profiles collected from the fingertip of three individuals were compared against paired plasma and blood. Overall, the results suggest that blood microsampling is a viable alternative for untargeted blood metabolomics, providing comparable information. Capillary blood collected using Mitra devices exhibits variations when compared to venous whole blood and plasma, with distinct trends observed across several metabolites. Consequently, further research is necessary to determine the applicability of this approach in specific contexts.
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Project description:Background: Clinical transcriptomics of peripheral blood mononuclear cells (PBMC) are coming into focus as a surrogate approach for prognosis, diagnosis, biomarker discovery and examination disease mechanisms. However, bioassays paired with transcriptomic analytic tools are yet to be developed and made available at point of care. Harnessing personal dynamic genomic responses to tailor patient asthma treatment or prevent disease exacerbations remain unmet medical needs. Method: We developed a rhinovirus-stimulated peripheral blood based-assay (virogram assay) coupled with single-subject analytics (N-of-1-patwhays) to capture dynamic genome-wide expression and dysregulated pathways to retrospectively predict childhood asthma exacerbation. We hypothesized that some genomic factors might predispose any given individual, healthy or asthmatic, to a set of similar transcriptional responses to rhinovirus stimulation. We first generated a classifier from paired sample microarrays, control and stimulated PBMC from healthy subjects and applied this classifier on the transcriptomic analysis of control and HRV-stimulated PBMC samples (virogram assay) from children with asthma. Results: The analysis of the different genomic responses of single-subject paired PBMC samples (HRV-stimulated and control) derived from healthy individuals (external dataset) enabled the discovery of dysregulated pathways related to acquired immunity, epigenetics and morphogenesis. The classifier built on these results and applied on the transcriptional analysis derived from the virogram assay predicted that the risk of asthma exacerbation among asthmatic subjects with an accuracy of 70%. Conclusion: We provide evidence that clinical prognosis can be predicted with a PBMC based-bioassay aligned with adequate single-subject analytics to assess dynamic transcriptomic response to specific disease-associated stimuli.
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Project description:We report a 29-gene diagnostic signature, which distinguishes individuals with NSCLC from controls with non-malignant lung disease with 91% Sensitivity, 79% Specificity and a ROC AUC of 92%. Accuracy on an independent set of 18 NSCLC samples from the same location was 79%. Samples from an independent location including 12 stage 1 NSCLC and 15 controls, achieved an accuracy of 74%. A study of 18 paired samples taken pre and post surgery shows that the PBMC associated “cancer” signature is significantly reduced after tumor removal, supporting the hypothesis that the signature detected in pre-surgery samples is a response to the presence of the tumor.
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