Project description:Methylome-wide DNA methylation profiling of whole blood samples in health children to find age-associated methylation sites. The Illumina Infinium 450k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 485,000 CpGs in 48 samples. Samples included 29 boys and 19girls.
Project description:We used Affymetrix CytoScan750K array to detect the pathogenic copy number variations in 7 Chinese children with congenital heart disease
Project description:The objective of this study was to identify gene expression markers of disease severity in a cohort of RSV infected children Respiratory syncytial virus (RSV) is the number one pathogen causing lower respiratory tract infection that leads to hospitalization in young children. Despite growing insights in the disease pathogenesis, the clinical presentation in these children is highly variable and heterogeneous, and reliable markers predictive of disease progression are lacking. We characterized the host response to acute RSV infection to identify biomarkers associated with RSV disease and disease severity. Whole genome transcriptome was analysed early on the disease course in blood samples from otherwise healthy children <2 years of age, who were either hospitalized (n = 110) or evaluated as outpatients (n = 37) due to RSV infection. Age-matched non-RSV-infected healthy children (n = 51) were analysed in parallel. A clustering approach on the transcriptome data revealed biologically meaningful biomarkers associated with progression to severe RSV disease. Overall, the whole blood transcriptome pointed to alterations in frequency of specific immune cell types (neutrophils, T- and B-lymphocytes, NK cells, monocytes) in RSV-infected children. In addition, a cluster enriched for neutrophil degranulation genes, was highly correlated with clinical disease severity. The driver genes of this cluster (OLFM4, ELANE, MMP8, BPI, CEACAM8, LCN2, LTF and MPO) were selected and validated in independent existing transcriptomics datasets. We identified a set of genes involved in neutrophil degranulation as markers for RSV disease severity. Additional prospective studies using these markers are required to further confirm their value as predictive tool in routine clinical care.
Project description:Genome-wide DNA methylation profiling of white blood cells was conducted using the Illumina Infinium Human Methylation 850K Genechip. According to the internal exposure level of deoxynivalenol, 32 participants were divided into two groups (high exposure DON group and low exposure DON group). Samples included 16 peripheral blood samples from children with high DON exposure and 16 peripheral blood samples from children with low DON exposure.
Project description:Type 1 diabetes (T1D) is an autoimmune disease caused by selective destruction of insulin producing pancreatic beta-cells in the islets of the Langerhans. The progression to clinical diabetes is characterized by the appearance of autoantibodies against islet cells (ICA) and beta-cell-specific antigens (IAA, IA-2 and GADA), which are considered the first markers signifying onset of autoimmunity. The mechanisms initiating or enhancing the autoimmune process remain poorly understood. Transcriptomic profiling on whole blood samples provides an approach for monitoring T1D disease process. In these investigations of pathways that are changed during the disease process, we have analyzed RNA from longitudinal peripheral blood samples of children who have developed T1D associated autoantibodies and eventually clinical type 1 diabetes . All study subjects were participants of the Type 1 Diabetes Prediction and Prevention (DIPP) study in Finland (38). Whole-blood RNA samples were collected during periodic clinic visits, typically at 3 to 12 month intervals. 2.5 ml venous blood was drawn into PAXgene Blood RNA tubes (Becton-Dickinson) and stored at -70°C. T1D-associated autoantibodies were measured from blood samples taken at each visit. Prospective samples from 3 children who developed T1D (subjects T1D_1 - T1D_3) and 2 children who developed ICA (subjects ICA_1 and ICA_2) during the DIPP follow-up were selected to the present study. Control children for the T1D cases (subjects T1D_C1 - T1D_C2) were matched for age, gender, birth place and HLA-genotype, from families who have no first-degree relatives with T1D. All samples (n=60) were processed and hybridized on Affymetrix Human Genome U133 Plus 2.0 arrays.
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.
Project description:RNA sequencing data were generated from the whole blood of children with a range of acute febrile illnesses. These data were used as the validation cohort for a multiclass diagnostic gene expression signature for the discrimination of 18 infectious and inflammatory diseases which was discovered using publicly available microarray datasets.