Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.
An individualized predictor of health and disease using paired reference and target samples.
Specimen part, Subject, Time
View SamplesAfrican-American individuals of the GENOA cohort
Genetic Architecture of Gene Expression in European and African Americans: An eQTL Mapping Study in GENOA.
Sex, Age, Specimen part
View SamplesA cardinal symptom of Major Depressive Disorder (MDD) is the disruption of circadian patterns. Yet, to date, there is no direct evidence of circadian clock dysregulation in the brains of MDD patients. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain was difficult to characterize. Here we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-hour cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ('Controls') and 34 MDD patients. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (AnCg), hippocampus (HC), amygdala (AMY), nucleus accumbens (NAcc) and cerebellum (CB). Several hundred transcripts in each region showed 24-hour cyclic patterns in Controls, and >100 transcripts exhibited consistent rhythmicity and phase-synchrony across regions. Among the top ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERB), DBP, BHLHE40(DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in MDD brains, due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This is the first transcriptome-wide analysis of cyclic patterns in the human brain and demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggest novel molecular targets for treatment of mood disorders.
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder.
Subject
View SamplesAsthma is caused by a combination of poorly understood genetic and environmental factors. We found multiple markers on chromosome 17q21 to be strongly and reproducibly associated with childhood onset asthma in family and case-referent panels with a combined P < 10-12. In independent replication studies the 17q21 locus showed strong association with diagnosis of childhood asthma in 2,320 subjects from a cohort of German children (P = 0.0003) and in 3,301 subjects from the British 1958 Birth Cohort (P = 0.0005). We systematically evaluated the relationships between markers of the 17q21 locus and transcript levels of genes in EBV-transformed lymphoblastoid cell lines from children in the asthma family panel used in our association study. The SNPs associated with childhood asthma were consistently and strongly associated (P <10-22) in cis with transcript levels of ORMDL3, a member of a gene family that encode transmembrane proteins anchored in the endoplasmic reticulum. The results indicate that genetic variants regulating ORMDL3 expression are determinants of susceptibility to childhood asthma.
Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma.
Sex
View SamplesWe have performed bioinformatic approaches to identify the level of enrichment between gene expression profiles characterizing MSI tumors and gene changes induced in vitro by the PARP-1 inhibitor Phenanthridinone and others using the Connectivity Map tool. In a first step, we have anyzed the expression of 300 colorectal cancers from the MECC study and generated a gene expression signature by microsatellite status. The criteria followed for selection of probe sets and detailed lists to be submitted subsequently to the Connectivity Map have been published previously by us in Clinical Cancer Research in 2009. In a second step, once we observed that deficiency in MRE11 exist among MSI tumors, our interest was focused on assessing if the homologous recombination pathway showed evidence of deregulation in MSI tumors. Therefore, we examined the expression levels of those genes integrated in the KEGG pathway hsa03440 using the previously generated gene expression data set.
MRE11 deficiency increases sensitivity to poly(ADP-ribose) polymerase inhibition in microsatellite unstable colorectal cancers.
Sex, Age
View SamplesThis SuperSeries is composed of the SubSeries listed below. A subset of samples profiled in this analysis were also profiled in Series GSE68127, and GSE104066. Corresponding glomerular transcriptome data can be found under GEO ID: GSE108109.
Metabolic pathways and immunometabolism in rare kidney diseases.
Specimen part
View SamplesThe transcriptional responses of human hosts towards influenza viral pathogens are important for understanding virus-mediated immunopathology. Despite great advances gained through studies using model organisms, the complete temporal host transcriptional responses in a natural human system are poorly understood. In a human challenge study using live influenza (H3N2/Wisconsin) viruses, we conducted a clinically uninformed (unsupervised) factor analysis on gene expression profiles and established an ab initio molecular signature that strongly correlates to symptomatic clinical disease. This is followed by the identification of 42 biomarkers whose expression patterns best differentiate early from late phases of infection. In parallel, a clinically informed (supervised) analysis revealed over-stimulation of multiple viral sensing pathways in symptomatic hosts and linked their temporal trajectory with development of diverse clinical signs and symptoms. The resultant inflammatory cytokine profiles were shown to contribute to the pathogenesis because their significant increase preceded disease manifestation by 36 hours. In subclinical asymptomatic hosts, we discovered strong transcriptional regulation of genes involved in inflammasome activation, genes encoding virus interacting proteins, and evidence of active anti-oxidant and cell-mediated innate immune response. Taken together, our findings offer insights into influenza virus-induced pathogenesis and provide a valuable tool for disease monitoring and management in natural environments.
Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Defining cell-type specificity at the transcriptional level in human disease.
Specimen part, Disease
View Samplessummary : Glomerular Transcriptome from European Renal cDNA Bank subjects and living donors. Samples included in this analysis have been previously analyzed using older CDF definitions and are included under previous GEO submissions - GSE47183 (chronic kidney disease samples), and GSE32591 (IgA nephropathy samples).
Metabolic pathways and immunometabolism in rare kidney diseases.
Specimen part, Disease
View Samplessummary : Tubulointerstitial transcriptome from ERCB subjects with chronic kidney disease and living donor biopsies. Samples included in this analysis have been previously analyzed using older CDF definitions and are included under previous GEO submissions - GSE47184 (chronic kidney disease samples), and GSE32591 (IgA nephropathy samples).
Metabolic pathways and immunometabolism in rare kidney diseases.
Specimen part, Disease
View Samples