Whole blood transcriptome profile identifies motor neurone disease (MND) RNA biomarker signatures
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ABSTRACT:
PROVIDER: PRJNA1163403 | ENA |
REPOSITORIES: ENA
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Project description:(1) Background: Blood-based biomarkers for motor neuron disease are needed for better di-agnosis, progression prediction, and clinical trial monitoring. We used whole blood-derived total RNA and performed whole transcriptome analysis to compare the gene expression pro-files in (motor neurone disease) MND patients to the control subjects. (2) Methods: We com-pared 42 MND patients to 42 aged and sex-matched healthy controls and described the whole transcriptome profile characteristic for MND. In addition to the formal differential analysis, we performed functional annotation of the genomics data and identified the molecular path-ways that are differentially regulated in MND patients. (3) Results: We identified 12,972 genes differentially expressed in the blood of MND patients compared to age and sex-matched con-trols. Functional genomic annotation identified activation of the pathways related to neuro-degeneration, RNA transcription, RNA splicing and extracellular matrix reorganisation. (4) Conclusions: Blood-based whole transcriptomic analysis can reliably differentiate MND pa-tients from controls and can provide useful information for the clinical management of the disease and clinical trials.
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Project description:Gene expression profiling has been performed previously on motor cortex and spinal cord homogenates and of sporadic ALS cases and controls, to identify genes and pathways differentially expressed in ALS. More recent studies have combined the use of laser capture microdissection (LCM) with gene expression profiling to isolate the motor neurons from the surrounding cells, such as microglia and astrocytes, in order to determine those genes differentially expressed in the vulnerable cell population – i.e. motor neuron. The aim of the present study is to combine LCM and microarray analysis to determine those genes and pathways differentially expressed in MNs from human SOD1-related MND and to establish potential pathways for therapeutic intervention. Keywords: Human motor neurons The aim of this study was to determine the gene expression profiles from a small subset of cases which all carry mutations in the SOD1 gene. Expression profiles from isolated motor neurons in SOD1-related ALS cases were compared to those from control motor neurons, in order to establish the pathways implicated in SOD1-related motor neuronal cell death. The 'control' samples were originally submitted to GEO as GSE19332.
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Project description:Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a meta-analysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR)?<0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-reactive protein levels). Our transcriptomic study provides potential insights into the effects of cigarette smoking on gene expression in whole blood and their relations to smoking-related diseases. The results of such analyses may highlight attractive targets for treating or preventing smoking-related health effects.
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Project description:In the present work, we have used whole genome expression profiling of peripheral blood samples from 51 patients with biopsy-proven acute kidney transplant rejection and 24 patients with excellent function and biopsy-proven normal transplant histology. The results demonstrate that there are 1738 probesets on the Affymetrix HG-U133 Plus 2.0 GeneChip representing 1472 unique genes which are differentially expressed in the peripheral blood during an acute kidney transplant rejection. By ranking these results we have identified minimal sets of 50 to 150 probesets with predictive classification accuracies for AR of greater than 90% established with several different prediction tools including DLDA and PAM. We have demonstrated that a subset of peripheral blood gene expression signatures can also diagnose four different subtypes of AR (Banff Borderline, IA, IB and IIA) and the top 100 ranked classifiers have greater than 89% predictive accuracy. Finally, we have demonstrated that there are gene signatures for early and late AR defined as less than or greater than one year post-transplant with greater than 86% predictive accuracies. We also confirmed that there are 439 time-independent gene classifiers for AR. Based on these results, we conclude that peripheral blood gene expression profiling can be used to diagnose AR at any time in the first 5 years post-transplant in the setting of acute kidney transplant dysfunction not caused by BK nephropathy, other infections, drug-induced nephrotoxicity or ureteral obstruction. Keywords: kidney transplantation, peripheral blood, DNA microarrays, acute kidney rejection, biomarkers Microarray profiles of peripheral blood from 51 biopsy-proven acute kidney rejection (AR) and 24 well-functioning kidney transplants were randomized and compared using class comparisons, network and biological function analyses.
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