Dataset Information

Gene Expression Signature Shared in Autoimmune Diseases Not in Unaffected Family Members

ABSTRACT: Even though autoimmune diseases are heterogeneous, believed to result from the interaction between genetic and environmental components, patients with these disorders exhibit reproducible patterns of gene expression in their peripheral blood mononuclear cells. A portion of this gene expression profile reflects family resemblance rather than the actual presence of an autoimmune disease. Here we wanted to identify that portion of this gene expression pattern that is independent of family resemblance and determine if it is a product of disease duration, disease onset, or other factors. By increasing the number of autoimmune samples in our analysis and employing supervised clustering algorithms, we identified 100 genes whose expression profiles are shared in individuals with various autoimmune diseases but are not shared by first-degree relatives of individuals with autoimmune disease or by controls. Individuals with early disease (1 yr after onset) and established disease (10 yr after onset) exhibit a near identical expression pattern suggesting that this unique profile reflects disease onset rather than disease duration. Keywords: gene expression signatures

ORGANISM(S): Homo sapiens

PROVIDER: GSE3447 | GEO | 2005/10/15

SECONDARY ACCESSION(S): PRJNA93375

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, associated with the degeneration of both upper and lower motor neurons of the motor cortex, brainstem and spinal cord. Death in most patients results from respiratory failure within 3-4 years from symptom onset. However, due to disease heterogeneity some individuals survive only months from symptom onset while others live for several years. Identifying specific biomarkers that aid in establishing disease prognosis, particularly in terms of predicting disease progression, will help our understanding of ALS pathophysiology and could be used to monitor a patient’s response to drugs and therapeutic agents. Transcriptomic profiling technologies are continually evolving, enabling us to identify key gene changes in biological processes associated with disease. MicroRNAs (miRNAs) are small non-coding RNAs typically associated with regulating gene expression, by degrading mRNA or reducing levels of gene expression. Being able to associate gene expression changes with corresponding miRNA changes would help to distinguish a more complex biomarker signature enabling us to address key challenges associated with complex diseases such as ALS. The present study aimed to investigate the transcriptomic profile (mRNA and miRNA) of lymphoblastoid cell lines (LCLs) from ALS patients to identify key signatures that are distinguishable in those patients who suffered a short disease duration (< 12 months) compared to those that had a longer disease duration (>6 years). Transcriptional profiling of miRNA-mRNA interactions from LCL’s in ALS patients revealed dysregulation of genes involved in cell cycle, DNA damage and RNA processing in patients with longer survival from disease onset compared to those with short survival. Understanding these particular miRNA-mRNA interactions and the pathways in which they are involved may help to distinguish potential therapeutic targets that could exert neuroprotective effects to prolong the life expectancy of ALS patients.

Dataset Information

Gene Expression Signature Shared in Autoimmune Diseases Not in Unaffected Family Members

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure