Kawasaki Disease and Other Febrile Illnesses
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE15297 | GEO | 2009/08/12
SECONDARY ACCESSION(S): PRJNA116591
REPOSITORIES: GEO
Similar Datasets
Project description:ABSTRACT Background. Acute Kawasaki disease (KD) is difficult to distinguish from other acute rash/fever illnesses, in part because the etiologic agent(s) and pathophysiology remain poorly characterized. As a result, diagnosis and critical therapies may be delayed. Methods. We used DNA microarrays to identify possible diagnostic features of KD. We compared gene expression patterns in the blood of 23 children with acute KD and 18 age-matched febrile children with three illnesses that resemble KD. Results. Genes associated with platelet and neutrophil activation were expressed at higher levels in KD patients than in patients with acute adenovirus infections or systemic adverse drug reactions but not in patients with scarlet fever; genes associated with B cell activation were also expressed at higher levels in KD patients than in controls. A striking absence of interferon-stimulated gene expression in the KD patients was confirmed in an independent cohort of KD subjects. We successfully predicted the diagnosis in 21 of 23 KD patients and 7 of 8 adenovirus patients using a set of 38 gene transcripts. Conclusions. These findings provide insight into the molecular features that distinguish KD from other febrile illnesses, and support the feasibility of developing novel diagnostic reagents for KD based on the host response. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: One of Kawasaki Disease (KD) or control (C) of Scarlet fever (C-sf), adenovirus infection (C-ai) or drug reaction (C-dr) disease_state_design
2010-06-24 | E-GEOD-15297 | biostudies-arrayexpress
Project description:Background: Kawasaki disease (KD) is an acute self-limited vasculitis and the leading cause of acquired heart disease in children in developed countries. No etiologic agent(s) has been identified, and the processes that mediate formation of coronary artery aneurysms and abatement of fever following treatment with intravenous immunoglobulin (IVIG) remain poorly understood. Results: In an initial survey, we used DNA microarrays to examine patterns of gene expression in peripheral whole blood from 20 children with KD; each was sampled during the acute, subacute, and convalescent phases of the illness. Acute KD was characterized by increased relative abundance of gene transcripts associated with innate immune and proinflammatory responses and decreased abundance of transcripts associated with natural killer cells and CD8+ lymphocytes. There was significant temporal variation in transcript levels during the acute disease phase and stabilization thereafter. We confirmed these temporal patterns in a second cohort of 64 patients, and identified additional inter-individual differences in transcript abundance. Notably, higher levels of transcripts of the gene for carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) were associated with an increased percentage of unsegmented neutrophils, fewer days of illness, higher levels of C-reactive protein, and subsequent non-response to IVIG; this last association was confirmed by quantitative reverse transcription PCR in a third cohort of 33 patients, and was independent of day of illness. Conclusions: Acute KD is characterized by dynamic and variable gene-expression programs that highlight the importance of neutrophil activation state and apoptosis in KD pathogenesis. Our findings also support the feasibility of extracting biomarkers associated with clinical prognosis from gene-expression profiles of individuals with systemic inflammatory illnesses. Whole blood (PAXgene tubes) was obtained from 64 Kawasaki disease patients prior to treatment. RNA was amplified using the MessageAmp kit (Ambion), and reverse transcribed. Each sample was labelled with Cy5, and hybridized to a Lymphochip cDNA array along with amplified human reference RNA labelled with Cy3(Universal Human Reference RNA, Stratagene). Analysis was restricted to those array elements (LUIDs) with signal intensity/background of at least 2.5 in either channel for at least 80% of the samples, and a regression correlation of 0.6. Patterns of gene expression were correlated with clinical parameters, including subsequent response to treatment with intravenous immunoglobulin (IVIG). A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Phenotype: Patient responded (R) or not (NR) to IVIG therapy. Some patients were not classified because they were treated more than 10 days after onset of fever Keywords: disease_state_design
2007-12-13 | GSE9864 | GEO
Project description:To further development of our miRNA diagnostic approach to Kawasaki disease(KD), we have employed microRNA microarray expression profiling as a discovery platform to identify microRNAs as the potential biomarkers to rapidly diagnose Kawasaki disease. Pooled exosome of serum in equal amount from 5 healthy children, 5 KD patients and 5 KD patients after Intravenous immunoglobulin (IVIG) therapy were used for microRNA microarray analysis. MicroRNA profile of exosome from Kawasaki disease(KD) was analyzed by microRNA microarray analysis in 5 healthy children, 5 KD patients and 5 KD patients after IVIG therapy.
2014-09-03 | E-GEOD-60965 | biostudies-arrayexpress
Project description:The diagnosis of Kawasaki disease (KD) is often difficult to distinguish from adenovirus (HAdV) and Group A streptococcal disease (GAS). We sought to: 1) to define the KD transcriptional signature that can aid in the diagnosis of complete and incomplete KD in children; 2) to identify specific biomarkers that objectively discriminate between KD and other mimicking conditions, including HAdV and 3) to test the prognostic utility of GEP to determine response to IVIG therapy and development of coronary artery lesions (CAL). Methods: Blood RNA samples were analyzed from 76 pediatric patients with complete KD, 13 with incomplete KD, 19 patients with HAdV, 17 patients with GAS disease, and age- and sex-matched healthy controls (HC). We used class comparisons (MW p< 0.01, Benjamini-Hochberg, and 1.25 fold change filter), class prediction, modular analysis and MDTH analyses to define the specificity of the KD profiles and identify markers of severity. Results: Statistical group comparisons identified 7,899 genes differentially expressed in 39 complete KD patients versus HC (KD biosignature). This signature was validated in another 37 patients with complete KD and in 13 patients with incomplete KD. Modular analysis in children with complete KD demonstrated overexpression of inflammation, neutrophils, myeloid cell, coagulation cascade, and cell cycle genes. The KNN class prediction algorithm identified 25-classifier genes that differentiated children with KD vs HAdV infection in two independent cohorts of patients with 96% (95% CI [80%-99%]) sensitivity and 95% [74%-99%] specificity. MDTH scores in KD patients significantly correlated with the baseline c-reactive protein (R=0.29, p=0.008) and was four fold higher than in children with HAdV (p<0.01). In addition, KD patients that remained febrile 36 hours after treatment with IVIG (non-responders) demonstrated higher baseline, pre-treatment MDTH values compared with responders [12,290 vs. 5,572 respectively; p=0.009]. Conclusion: Transcriptional signatures can be used as a tool to discriminate between KD and HAdV infection, and may also provide prognostic information. 113 samples, no replicates, 9 HAdV, 57 cKD, 12 FUO, 13 GAS, 3 GAS/SF, 5 inKD, 14 healthy control
2016-04-14 | E-GEOD-68004 | biostudies-arrayexpress
Project description:Background: We report the detailed development of biomarkers to predict the clinical outcome under dengue infection. Transcriptional signatures from purified peripheral blood mononuclear cells were derived from whole-genome gene-expression microarray data and validated by quantitative PCR and tested in independent samples. Methodology/Principal Findings: The study was performed on patients of a well-characterized dengue cohort from Recife, Brazil. The samples analyzed were collected prospectively from acute febrile dengue patients who evolved with different degrees of disease severity, classic dengue fever or dengue hemorrhagic fever (DHF) and compared with similar samples from other non-dengue febrile illnesses. The DHF samples were collected 2-3 days before the presentation of the plasma leakage symptoms. Differentially-expressed genes were selected by univariate statistical tests as well as multivariate classification techniques. The results showed that at early stages of dengue infection, the genes involved in effector mechanisms of innate immune response presented a weaker activation on patients who later developed hemorrhagic fever, whereas the genes involved in apoptosis were expressed in higher levels. Conclusions/Significance: Some of the gene expression signatures displayed estimated accuracy rates of more than 95%, indicating that expression profiling with these signatures may provide a useful means of DHF prognosis at early stages of infection The samples correspond to blood samples from 26 patients from a cohort in Brazil, divided into three classes, DHF, DF, ND, as follows: 18 were confirmed dengue 3, genotype III cases, among which 10 were diagnosed as dengue hemorrhagic fever (DHF) and 8 as classical dengue fever (DF), and 8 control samples (ND) from febrile patients confirmed to be not infected with dengue. None of the DHF patients presented vasculopathy signs and symptoms at the time the samples used in the functional genomic characterization were collected. At the time of collection the patients referred approximately 5 days of disease and the absence of fever was reported two to three days after enrollment. The samples from the DF, DHF and ND patients were matched to avoid significant differences regarding patient age, gender, dengue infection history and days of symptoms among the groups.
2010-09-01 | E-GEOD-18090 | biostudies-arrayexpress
Project description:Background: Kawasaki disease (KD) is an acute self-limited vasculitis and the leading cause of acquired heart disease in children in developed countries. No etiologic agent(s) has been identified, and the processes that mediate formation of coronary artery aneurysms and abatement of fever following treatment with intravenous immunoglobulin (IVIG) remain poorly understood. Results: In an initial survey, we used DNA microarrays to examine patterns of gene expression in peripheral whole blood from 20 children with KD; each was sampled during the acute, subacute, and convalescent phases of the illness. Acute KD was characterized by increased relative abundance of gene transcripts associated with innate immune and proinflammatory responses and decreased abundance of transcripts associated with natural killer cells and CD8+ lymphocytes. There was significant temporal variation in transcript levels during the acute disease phase and stabilization thereafter. We confirmed these temporal patterns in a second cohort of 64 patients, and identified additional inter-individual differences in transcript abundance. Notably, higher levels of transcripts of the gene for carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) were associated with an increased percentage of unsegmented neutrophils, fewer days of illness, higher levels of C-reactive protein, and subsequent non-response to IVIG; this last association was confirmed by quantitative reverse transcription PCR in a third cohort of 33 patients, and was independent of day of illness. Conclusions: Acute KD is characterized by dynamic and variable gene-expression programs that highlight the importance of neutrophil activation state and apoptosis in KD pathogenesis. Our findings also support the feasibility of extracting biomarkers associated with clinical prognosis from gene-expression profiles of individuals with systemic inflammatory illnesses. Whole blood RNA (PAXgene tubes) was collected from 20 Kawasaki patients during the acute, sub-acute (post-IVIG treatment) and convalescent phases of the disease. RNA was amplified using the MessageAmp kit (Ambion), and reverse transcribed. Each sample was labelled with Cy5, and hybridized to a Lymphochip cDNA array along with amplified human reference RNA labelled with Cy3(Universal Human Reference RNA, Stratagene). Analysis was restricted to those array elements (LUIDs) with signal intensity/background of at least 2.5 in either channel for at least 80% of the samples, and a regression correlation of 0.6. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Keywords: disease_state_design
2007-12-13 | GSE9863 | GEO
Project description:Background: We report the detailed development of biomarkers to predict the clinical outcome under dengue infection. Transcriptional signatures from purified peripheral blood mononuclear cells were derived from whole-genome gene-expression microarray data and validated by quantitative PCR and tested in independent samples. Methodology/Principal Findings: The study was performed on patients of a well-characterized dengue cohort from Recife, Brazil. The samples analyzed were collected prospectively from acute febrile dengue patients who evolved with different degrees of disease severity, classic dengue fever or dengue hemorrhagic fever (DHF) and compared with similar samples from other non-dengue febrile illnesses. The DHF samples were collected 2-3 days before the presentation of the plasma leakage symptoms. Differentially-expressed genes were selected by univariate statistical tests as well as multivariate classification techniques. The results showed that at early stages of dengue infection, the genes involved in effector mechanisms of innate immune response presented a weaker activation on patients who later developed hemorrhagic fever, whereas the genes involved in apoptosis were expressed in higher levels. Conclusions/Significance: Some of the gene expression signatures displayed estimated accuracy rates of more than 95%, indicating that expression profiling with these signatures may provide a useful means of DHF prognosis at early stages of infection
2010-09-01 | GSE18090 | GEO
Project description:To further development of our miRNA diagnostic approach to Kawasaki disease(KD), we have employed microRNA microarray expression profiling as a discovery platform to identify microRNAs as the potential biomarkers to rapidly diagnose Kawasaki disease. Pooled exosome of serum in equal amount from 5 healthy children, 5 KD patients and 5 KD patients after Intravenous immunoglobulin (IVIG) therapy were used for microRNA microarray analysis.
2014-09-03 | GSE60965 | GEO
Project description:The diagnosis of Kawasaki disease (KD) is often difficult to distinguish from adenovirus (HAdV) and Group A streptococcal disease (GAS). We sought to: 1) to define the KD transcriptional signature that can aid in the diagnosis of complete and incomplete KD in children; 2) to identify specific biomarkers that objectively discriminate between KD and other mimicking conditions, including HAdV and 3) to test the prognostic utility of GEP to determine response to IVIG therapy and development of coronary artery lesions (CAL). Methods: Blood RNA samples were analyzed from 76 pediatric patients with complete KD, 13 with incomplete KD, 19 patients with HAdV, 17 patients with GAS disease, and age- and sex-matched healthy controls (HC). We used class comparisons (MW p< 0.01, Benjamini-Hochberg, and 1.25 fold change filter), class prediction, modular analysis and MDTH analyses to define the specificity of the KD profiles and identify markers of severity. Results: Statistical group comparisons identified 7,899 genes differentially expressed in 39 complete KD patients versus HC (KD biosignature). This signature was validated in another 37 patients with complete KD and in 13 patients with incomplete KD. Modular analysis in children with complete KD demonstrated overexpression of inflammation, neutrophils, myeloid cell, coagulation cascade, and cell cycle genes. The KNN class prediction algorithm identified 25-classifier genes that differentiated children with KD vs HAdV infection in two independent cohorts of patients with 96% (95% CI [80%-99%]) sensitivity and 95% [74%-99%] specificity. MDTH scores in KD patients significantly correlated with the baseline c-reactive protein (R=0.29, p=0.008) and was four fold higher than in children with HAdV (p<0.01). In addition, KD patients that remained febrile 36 hours after treatment with IVIG (non-responders) demonstrated higher baseline, pre-treatment MDTH values compared with responders [12,290 vs. 5,572 respectively; p=0.009]. Conclusion: Transcriptional signatures can be used as a tool to discriminate between KD and HAdV infection, and may also provide prognostic information.
2016-04-14 | GSE68004 | GEO