Using NGS to Sequence Whole Genomes to Identify Genes Underlying ALS
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA883502 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Using NGS to Sequence Whole Genomes to Identify Genes Underlying ALS
| PRJNA883503 | ENA
Project description:Identification of amyotrophic lateral sclerosis (ALS) associated genes. Post mortem spinal cord grey matter from sporadic and familial ALS patients compared with controls.
2007-09-26 | E-GEOD-833 | biostudies-arrayexpress
Project description:Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons. While several inherited pathogenic mutations have been identified as causative, the vast majority of cases are sporadic with no family history of disease. Thus, for the majority of ALS cases, a specific causal abnormality is not known and the disease may be a product of multiple inter-related pathways contributing to varying degrees in different ALS patients. Using unsupervised machine learning algorithms, we stratified the transcriptomes of 148 ALS decedent cortex tissue samples into three distinct and robust molecular subtypes. The largest cluster, identified in 61% of patient samples, displayed hallmarks of oxidative and proteotoxic stress. Another 20% of the ALS patient samples exhibited high levels of retrotransposon expression and other signatures of TDP-43 dysfunction. Finally, a third group showed predominant signatures of glial activation (19%). Together these results demonstrate that at least three distinct molecular signatures contribute to ALS disease. While multiple dysregulated components and pathways comprising these clusters have previously been implicated in ALS pathogenesis, unbiased analysis of this large survey demonstrated that sporadic ALS patient tissues can be segregated into distinct molecular subsets.
2019-09-20 | GSE122647 | GEO
Project description:Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons. While several inherited pathogenic mutations have been identified as causative, the vast majority of cases are sporadic with no family history of disease. Thus, for the majority of ALS cases, a specific causal abnormality is not known and the disease may be a product of multiple inter-related pathways contributing to varying degrees in different ALS patients. Using unsupervised machine learning algorithms, we stratified the transcriptomes of 148 ALS decedent cortex tissue samples into three distinct and robust molecular subtypes. The largest cluster, identified in 61% of patient samples, displayed hallmarks of oxidative and proteotoxic stress. Another 20% of the ALS patient samples exhibited high levels of retrotransposon expression and other signatures of TDP-43 dysfunction. Finally, a third group showed predominant signatures of glial activation (19%). Together these results demonstrate that at least three distinct molecular signatures contribute to ALS disease. While multiple dysregulated components and pathways comprising these clusters have previously been implicated in ALS pathogenesis, unbiased analysis of this large survey demonstrated that sporadic ALS patient tissues can be segregated into distinct molecular subsets.
2019-09-20 | GSE122648 | GEO
Project description:Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons. While several inherited pathogenic mutations have been identified as causative, the vast majority of cases are sporadic with no family history of disease. Thus, for the majority of ALS cases, a specific causal abnormality is not known and the disease may be a product of multiple inter-related pathways contributing to varying degrees in different ALS patients. Using unsupervised machine learning algorithms, we stratified the transcriptomes of 148 ALS decedent cortex tissue samples into three distinct and robust molecular subtypes. The largest cluster, identified in 61% of patient samples, displayed hallmarks of oxidative and proteotoxic stress. Another 20% of the ALS patient samples exhibited high levels of retrotransposon expression and other signatures of TDP-43 dysfunction. Finally, a third group showed predominant signatures of glial activation (19%). Together these results demonstrate that at least three distinct molecular signatures contribute to ALS disease. While multiple dysregulated components and pathways comprising these clusters have previously been implicated in ALS pathogenesis, unbiased analysis of this large survey demonstrated that sporadic ALS patient tissues can be segregated into distinct molecular subsets.
2019-09-20 | GSE122649 | GEO
Project description:Amyotrophic Lateral Sclerosis (ALS) results from the selective and progressive degeneration of motor neurons. Although the underlying disease mechanisms remain unknown, glial cells have been implicated in ALS disease progression. Here we examine the effects of glial cell/motor neuron interactions on gene expression, using the hSOD1G93A mouse model of ALS. We detect striking cell autonomous and non-autonomous changes in gene expression in co-cultured motor neurons and glia, revealing that the two cell types profoundly affect each other. In addition, we found a remarkable concordance between the cell culture data, expression profiles of whole spinal cords, and of acutely isolated spinal cord cells, during disease progression in the G93A mouse model, providing validation of the cell culture approach. Bioinformatics analyses identified changes in the expression of specific genes and signaling pathways that may contribute to motor neuron degeneration in ALS, among which are TGF-b signaling pathways. RNA-seq profiles of: 1) 43 Sandwich culture samples at 3 different time points (3, 7 and 14 days), in duplicate, in different combinations of genetic background WT/SOD1_G93A mutant glia and WT/SOD1_G93A mutant neurons; 2) 16 spinal cord samples at 4 different time points, WT and SOD1_G93A mutant.
2013-02-11 | E-GEOD-43879 | biostudies-arrayexpress