This dataset is composed of the unique patients (276; at the Day 1 timepoint) that are present in the six other GEO datasets published by Hector Wong and the Genomics of Pediatric SIRS and Septic Shock Investigators. This dataset thus includes all unique patients from GSE4607, GSE8121, GSE9692, GSE13904, GSE26378, and GSE26440. These are only from the Day 1 timepoint.
A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set.
Specimen part, DiseaseView Samples
Dietary gluten proteins (prolamins) from wheat, rye, and barley are the driving forces behind celiac disease, an organ-specific autoimmune disorder that targets both the small intestine and organs outside the gut. In the small intestine, gluten induces inflammation and a typical morphological change of villous atrophy and crypt hyperplasia. Gut lesions improve and heal when gluten is excluded from the diet and the disease relapses when patients consume gluten. Oral immune tolerance towards gluten may be kept for years or decades before breaking tolerance in genetically susceptible individuals. Celiac disease provides a unique opportunity to study autoimmunity and the transition in immune cells as gluten breaks oral tolerance. Seventy-three celiac disease patients on a long-term gluten-free diet ingested a known amount of gluten daily for six weeks. A peripheral blood sample and intestinal biopsies were taken before and six weeks after initiating the gluten challenge. Biopsy results were reported on a continuous numeric scale that measured the villus height to crypt depth ratio to quantify gluten-induced gut mucosal injury. Pooled B and T cells were isolated from whole blood, and RNA was analyzed by DNA microarray looking for changes in peripheral B- and T-cell gene expression that correlated with changes in villus height to crypt depth, as patients maintained or broke oral tolerance in the face of a gluten challenge.
A B-Cell Gene Signature Correlates With the Extent of Gluten-Induced Intestinal Injury in Celiac Disease.
Specimen part, Disease, Disease stage, Treatment, SubjectView Samples
In this study, we examined transcriptional profiles from 3 different microarray platforms, across 103 peripheral blood samples with and without acute rejection, to find a critical gene-set for the diagnosis of acute renal rejection that matched biopsy diagnosis, irrespective of patient demographics, clinical confounders, concomitant infection, immunosuppression usage or sample processing methods. We hypothesized that changes in peripheral blood expression profiles correlate with biopsy-proven rejection, and that these changes could be used as biomarkers for the diagnosis and prediction of acute rejection.
A peripheral blood diagnostic test for acute rejection in renal transplantation.
Disease, Disease stageView Samples
CONTEXT Slowly progressive chronic tubulo-interstitial damage jeopardizes long-term renal allograft survival. Both immune and non-immune mechanisms are thought to contribute, but the most promising targets for timely intervention have not been identified. OBJECTIVE In the current study we seek to determine the driving force behind progressive histological damage of renal allografts, without the interference of donor pathology, delayed graft function and acute graft rejection. DESIGN We used microarrays to examine whole genome expression profiles in renal allograft protocol biopsies, and analyzed the correlation between gene expression and the histological appearance over time. The gene expression profiles in these protocol biopsies were then compared with gene expression of biopsies with acute T-cell mediated rejection. PATIENTS Human renal allograft biopsies (N=120) were included: 96 rejection-free protocol biopsies and 24 biopsies with T-cell mediated acute rejection. RESULTS In this highly cross-validated study, we demonstrate the significant association of established, ongoing and future chronic histological damage with regulation of adaptive immune gene expression (T-cell and B-cell transcript sets) and innate immune response gene expression (dendritic cell, NK-cell, mast cell and granulocyte transcripts). We demonstrate the ability of gene expression analysis to perform as a quantitative marker for ongoing inflammation with a wide dynamic range: from subtle subhistological inflammation prior to development of chronic damage, over moderate subclinical inflammation associated with chronic histological damage, to marked inflammation of Banff-grade acute T-cell mediated rejection. CONCLUSION Progressive chronic histological damage after kidney transplantation is associated with significant regulation of both innate and adaptive immune responses, months before the histological lesions appear. This study therefore corroborates the hypothesis that quantitative inflammation below the diagnostic threshold of classic T-cell or antibody-mediated rejection is associated with early subclinical stages of progressive renal allograft damage.
Progressive histological damage in renal allografts is associated with expression of innate and adaptive immunity genes.
Specimen part, TimeView Samples
Acute Myeloid Leukemia AML is a cancer in which the process of normal cell hematopoietic differentiation is disrupted. Evidence exists that AML comprises a hierarchy with leukemic stem cells giving rise to more differentiated, but immature and functionally incompetent populations. The similarity of these AML subpopulations to normal stages of hematopoietic differentiation has not been dissected comprehensively at the transcriptional level. Here we introduce Normal Memory Analysis (NorMA), a data analysis method that extracts from omic data the remnants of the healthy normal-like phenotype. Applying NorMA to gene expression data from AML uncovered a wealth of information in the normal-like component of data: the normal hematopoietic memory of AML tumor cells. We found significant variation within the patient population, and we found strong association of this normal hematopoietic memory with survival. We found that undifferentiated NorMA phenotype has significantly worse survival than differentiated NorMA phenotype, showing that the NorMA classification of tumors captures a biologically meaningful stratification of patients, with highly significant survival association. Patients with NorMA phenotype in the undifferentiated Hematopoietic Stem Cell HSC stage had the worst survival, with median survival time under 6 months. We further found significant survival differences between tumor groups with differentiated NorMA phenotype, depending on their hematopoietic path: AML patients with NorMA phenotype in megakaryocyte-erythroid progenitor MEP stage had significantly better survival than those with NorMA phenotype in granulocyte-macrophage progenitor GMP stage. Thus NorMA produced a stratification of AML cohorts by differentiation stage, with significant outcome differences. It also provided clean molecular signatures for these stages. NorMA can be used in many other contexts, to explore for example the tumor cell of origin, or disease predisposition.
An LSC epigenetic signature is largely mutation independent and implicates the HOXA cluster in AML pathogenesis.
Specimen partView Samples
Gene expression profiling using microarray has been limited to profiling of differentially expressed genes at comparison setting since probesets for different genes have different sensitivities. We overcome this limitation by using a very large number of varied microarray datasets as a common reference, so that statistical attributes of each probeset, such as dynamic range or a threshold between low and high expression can be reliably discovered through meta-analysis. This strategy is implemented in web-based platform named Gene Expression Commons (http://gexc.stanford.edu/ ) with datasets of 39 distinct highly purified mouse hematopoietic stem/progenitor/functional cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, any scientist can explore gene expression of any gene, search by expression pattern of interest, submit their own microarray datasets, and design their own working models.
Gene Expression Commons: an open platform for absolute gene expression profiling.
Sex, AgeView Samples
Using meta-analysis of eight independent transplant datasets (236 graft biopsy samples) from four organs, we identified a common rejection module (CRM) consisting of 11 genes that were significantly overexpressed in acute rejection (AR) across all transplanted organs. The CRM genes could diagnose AR with high specificity and sensitivity in three additional independent cohorts (794 samples). In another two independent cohorts (151 renal transplant biopsies), the CRM genes correlated with the extent of graft injury and predicted future injury to a graft using protocol biopsies. Inferred drug mechanisms from the literature suggested that two FDA-approved drugs (atorvastatin and dasatinib), approved for non-transplant indications, could regulate specific CRM genes and reduce the number of graft infiltrating cells during acute rejection. We treated mice with HLA-mismatched murine cardiac transplant with atorvastatin and dasatinib and showed reduction of the CRM genes, significant reduction of graft infiltrating cells, and extended graft survival. We further validated the beneficial effect of atorvastatina on graft survival by retrospective analysis of electronic medical records of a single-center cohort of 2,515 renal transplant patients. In conclusion, we identified a CRM in transplantation that provides new opportunities for diagnosis, drug repositioning and rational drug design.
A common rejection module (CRM) for acute rejection across multiple organs identifies novel therapeutics for organ transplantation.
Specimen partView Samples
The biopsy samples obtained at implantation segregated in 2 distinct groups according to donor origin, with a cluster of 319 unique identified genes higher expressed in DD compared to LD kidneys, and 329 genes lower expressed (false discovery rate <5%). Using pathway analysis software a significant local renal overrepresentation of complement genes in DD implantation biopsies was identified. Complement gene expression in DD kidneys related both to donor death and cold ischemia duration, and was associated with a slower onset of renal allograft function. In post-transplantation protocol biopsies, there was a continued overexpression of complement genes, regardless of donor source. The local renal complement gene expression variability in post-transplantation biopsies correlated with renal graft function.
Expression of complement components differs between kidney allografts from living and deceased donors.
No sample metadata fieldsView Samples