Defining RNA Transcriptional Biosignatures to Distinguish Febrile Infants 60 Days of Age and Younger with Bacterial vs Non-Bacterial Infections
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE64456 | GEO | 2016/07/27
SECONDARY ACCESSION(S): PRJNA271056
REPOSITORIES: GEO
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Project description:The use of microbiological cultures for diagnosing bacterial infections in young febrile infants have substantial limitations, including false positive and false negative cultures, and non-ideal turn-around times. Analysis of host genomic expression patterns (âRNA biosignaturesâ) in response to the presence of specific pathogens, however, may provide an alternate and potentially improved diagnostic approach. This study was designed to define bacterial and non-bacterial RNA biosignatures to distinguish these infections in young febrile infants. A total of 279 febrile infants and 19 healthy afebrile control infants aged 0-6 months (for a total of 298 samples) for microarray analysis. For analytic purposes, we classified patients into two groups, those with bacterial infections (n=89) and those with non-bacterial infections (n=190). 144 of the samples were run on Illumina HT12 V4 R1 chips. Of these, there were 34 bacterial infections, 105 non-bacterial infections, and 5 healthy afebrile controls. 154 of the samples were run on Illumina HT12 V4 R2 chips. Of these, there were 55 bacterial infections, 85 non-bacterial infections, and 14 healthy afebrile controls.
2016-07-27 | E-GEOD-64456 | biostudies-arrayexpress
Project description:Viral infections are among the most common causes for fever without an apparent source (FWS) in young children; however, many febrile children are treated with antibiotics despite the absence of bacterial infection. Adenovirus, human herpesvirus 6 (HHV-6) and enterovirus are detected in children with FWS more often than other viral species. Virus and bacteria interact with pattern recognition receptors in circulating blood leukocytes and trigger specific host transcriptional programs that mediate immune response, and unique transcriptional signatures may be ascertained to discriminate between viral and bacterial causes for children with FWS. Microarray analyses were conducted on peripheral blood samples obtained from 51 pediatric patients with confirmed adenovirus, human herpesvirus 6 (HHV-6), enterovirus or bacterial infection. Whole blood transcriptional profiles could clearly distinguish febrile children from healthy controls, and febrile children with viral infections from afebrile children carrying the same virus. Molecular pathways regulating host immune response were the most affected in febrile children with infection. Pattern recognition programs were prominently activated in all febrile children with infection, while differential activation of transcriptional programs was observed among viral species. Interferon signaling pathway was uniquely activated in children with febrile viral infection, while a different set of pathways was uniquely activated in children with bacterial infection. Transcriptional signatures were identified and classified febrile children with viral or bacterial infection with 87% overall accuracy, an improvement from the current clinical practice of deducing from white blood cell (WBC) count status. Similar degree of accuracy was observed when we validated the signature probes on data sets from an independent study with different microarray platforms. The current study confirms the clinical utility of blood transcriptional analysis, suggests the composition of transcriptional signatures which can be used to ascertain the infectious etiology of febrile young children without an apparent source, thus limit the overuse of antibiotics on febrile children presenting with this common clinical complaint. Total RNA samples extracted from whole blood of young children were processed for hybridization onto Illumina Human-HT12 version 4 beadchips, and differential expression of the transcripts was analyzed between sick children with either viral or bacterial infection and healthy children.
2012-10-15 | E-GEOD-40396 | biostudies-arrayexpress
Project description:Viral infections are among the most common causes for fever without an apparent source (FWS) in young children; however, many febrile children are treated with antibiotics despite the absence of bacterial infection. Adenovirus, human herpesvirus 6 (HHV-6) and enterovirus are detected in children with FWS more often than other viral species. Virus and bacteria interact with pattern recognition receptors in circulating blood leukocytes and trigger specific host transcriptional programs that mediate immune response, and unique transcriptional signatures may be ascertained to discriminate between viral and bacterial causes for children with FWS. Microarray analyses were conducted on peripheral blood samples obtained from 51 pediatric patients with confirmed adenovirus, human herpesvirus 6 (HHV-6), enterovirus or bacterial infection. Whole blood transcriptional profiles could clearly distinguish febrile children from healthy controls, and febrile children with viral infections from afebrile children carrying the same virus. Molecular pathways regulating host immune response were the most affected in febrile children with infection. Pattern recognition programs were prominently activated in all febrile children with infection, while differential activation of transcriptional programs was observed among viral species. Interferon signaling pathway was uniquely activated in children with febrile viral infection, while a different set of pathways was uniquely activated in children with bacterial infection. Transcriptional signatures were identified and classified febrile children with viral or bacterial infection with 87% overall accuracy, an improvement from the current clinical practice of deducing from white blood cell (WBC) count status. Similar degree of accuracy was observed when we validated the signature probes on data sets from an independent study with different microarray platforms. The current study confirms the clinical utility of blood transcriptional analysis, suggests the composition of transcriptional signatures which can be used to ascertain the infectious etiology of febrile young children without an apparent source, thus limit the overuse of antibiotics on febrile children presenting with this common clinical complaint.
2012-10-15 | GSE40396 | GEO
Project description:Defining RNA Transcriptional Biosignatures to Distinguish Febrile Infants 60 Days of Age and Younger with Bacterial vs Non-Bacterial Infections
| PRJNA271056 | ENA
Project description:Non-specific clinical presentation and lack of sensitive acute-phase diagnostic reagents hinder early recognitiion and manangement of systemic infections. To identify pathogen-specific features of the acute host response to infection we examined genome-wide patterns of whole blood gene expression in febrile patients with well-defined bacterial and viral infections (n=49), as well as health controls (n=12)
2022-12-01 | GSE206829 | GEO
Project description:RNA sequencing data from children with febrile illness and multisystem inflammatory syndrome in children (MIS-C). Samples used were Whole Blood. Febrile illness controls include children with bacterial and viral infections and healthy controls. This dataset contains samples from patients recruited into the DIAMONDS study.
| EGAD00001011134 | EGA
Project description:Neonatal meningitis and neurocomplications are often a complication of neonatal bacterial bloodstream infections. As distinct bacterial organisms may cause different disease outcomes, we assessed two separate bacterial infections: E. coli and S. agalactiae (GBS). In this study we assessed differences in immune response within the brain tissue of neonates and the effect of gamma delta T cells to the brain during bacterial infection. As gamma delta T cells are resident to tissues, and can contribute to bacterial infections, we compared wild-type and TCRdKO mice, which lack gamma delta T cells, in two infections models: E. coli and GBS.
2024-01-16 | GSE253301 | GEO
Project description:Background: Distinguishing between bacterial and viral lower respiratory tract infections (LRTI) in hospitalized patients remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods: We performed whole blood transcriptional analysis in a cohort of 118 adult patients (median [IQR] age, 61 [50-76] years) hospitalized with bacterial, viral or viral-bacterial LRTI, and 40 age-matched healthy controls (60 [46-70] years). We applied class comparisons, modular analysis and class prediction algorithms to identify distinct biosignatures for bacterial and viral LRTI, which were validated in an independent group of patients. Results: Patients were classified as bacterial (B, n=22), viral (V, n=71) and bacterial-viral LRTI (BV, n=25) based on comprehensive microbiologic testing. Compared with healthy controls statistical group comparisons (p<0.01; with multiple test corrections) identified 3,376 differentially expressed genes in patients with B-LRTI; 2,391 in V-LRTI, and 2,628 in BV-LRTI. Independent of etiologic pathogen, patients with LRTI demonstrated overexpression of innate immunity and underexpression of adaptive immunity genes. Patients with B-LRTI showed significant overexpression of inflammation (B>BV>V) and neutrophils (B>BV>V) while those with V-LRTI displayed significantly greater overexpression of interferon genes (V>BV>B). The K-Nearest Neighbors (K-NN) algorithm identified 10 classifier genes that discriminated patients with bacterial vs viral LRTI with 97% [95%CI: 84-100] sensitivity and 92% [77-98] specificity. In comparison, procalcitonin classified bacterial vs viral LRTI with 38% [18-62] sensitivity and 91% [76-98] specificity. Conclusions: Transcriptional profiling can be used as a helpful tool for the diagnosis of adults hospitalized with LRTI. 158 samples, no replicates; bacterial LRTI n=22, viral LRTI n=71, bacterial-viral coinfections n=25, and healthy controls n=40
2015-09-14 | E-GEOD-60244 | biostudies-arrayexpress
Project description:Background: Distinguishing between bacterial and viral lower respiratory tract infections (LRTI) in hospitalized patients remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods: We performed whole blood transcriptional analysis in a cohort of 118 adult patients (median [IQR] age, 61 [50-76] years) hospitalized with bacterial, viral or viral-bacterial LRTI, and 40 age-matched healthy controls (60 [46-70] years). We applied class comparisons, modular analysis and class prediction algorithms to identify distinct biosignatures for bacterial and viral LRTI, which were validated in an independent group of patients. Results: Patients were classified as bacterial (B, n=22), viral (V, n=71) and bacterial-viral LRTI (BV, n=25) based on comprehensive microbiologic testing. Compared with healthy controls statistical group comparisons (p<0.01; with multiple test corrections) identified 3,376 differentially expressed genes in patients with B-LRTI; 2,391 in V-LRTI, and 2,628 in BV-LRTI. Independent of etiologic pathogen, patients with LRTI demonstrated overexpression of innate immunity and underexpression of adaptive immunity genes. Patients with B-LRTI showed significant overexpression of inflammation (B>BV>V) and neutrophils (B>BV>V) while those with V-LRTI displayed significantly greater overexpression of interferon genes (V>BV>B). The K-Nearest Neighbors (K-NN) algorithm identified 10 classifier genes that discriminated patients with bacterial vs viral LRTI with 97% [95%CI: 84-100] sensitivity and 92% [77-98] specificity. In comparison, procalcitonin classified bacterial vs viral LRTI with 38% [18-62] sensitivity and 91% [76-98] specificity. Conclusions: Transcriptional profiling can be used as a helpful tool for the diagnosis of adults hospitalized with LRTI.
2015-09-14 | GSE60244 | GEO