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pmid:38540795

Sporadic Amyotrophic Lateral Sclerosis Skeletal Muscle Transcriptome Analysis: A Comprehensive Examination of Differentially Expressed Genes.

Elisa Gascón · Pilar Zaragoza · Ana Cristina Calvo · Rosario Osta

Biomolecules · 2024 doi:10.3390/biom14030377

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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title
Sporadic Amyotrophic Lateral Sclerosis Skeletal Muscle Transcriptome Analysis: A Comprehensive Examination of Differentially Expressed Genes.
doi
10.3390/biom14030377
pmid
38540795
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[0]
Elisa Gascón
[1]
Pilar Zaragoza
[2]
Ana Cristina Calvo
[3]
Rosario Osta
journal
Biomolecules
year
2024
abstract
Amyotrophic lateral sclerosis (ALS) that comprises sporadic (sALS) and familial (fALS) cases, is a devastating neurodegenerative disorder characterized by progressive degeneration of motor neurons, leading to muscle atrophy and various clinical manifestations. However, the complex underlying mechanisms affecting this disease are not yet known. On the other hand, there is also no good prognosis of the disease due to the lack of biomarkers and therapeutic targets. Therefore, in this study, by means of bioinformatics analysis, sALS-affected muscle tissue was analyzed using the GEO GSE41414 dataset, identifying 397 differentially expressed genes (DEGs). Functional analysis revealed 320 up-regulated DEGs associated with muscle development and 77 down-regulated DEGs linked to energy metabolism. Protein-protein interaction network analysis identified 20 hub genes, including EIF4A1, HNRNPR and NDUFA4. Furthermore, miRNA target gene networks revealed 17 miRNAs linked to hub genes, with hsa-mir-206, hsa-mir-133b and hsa-mir-100-5p having been previously implicated in ALS. This study presents new potential biomarkers and therapeutic targets for ALS by correlating the information obtained with a comprehensive literature review, providing new potential targets to study their role in ALS.
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Subsequently, the limma package’s moderated t-test, based on the empirical parametric Bayes method, identified differentially expressed genes (DEGs) between ALS patient and control samples.
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sections[4] "2.2. Identification and Analysis of Differentially Expressed Genes (DEGs)" paragraph 2
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Subsequently, the limma package’s moderated t-test, based on the empirical parametric Bayes method, identified differentially expressed genes (DEGs) between ALS patient and control samples.
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Data used in this study are publicly available on the gene expression omnibus (GEO) database and can be accessed through GSE41414.
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Therefore, in this study, by means of bioinformatics analysis, sALS-affected muscle tissue was analyzed using the GEO GSE41414 dataset, identifying 397 differentially expressed genes (DEGs).
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Therefore, in this study, by means of bioinformatics analysis, sALS-affected muscle tissue was analyzed using the GEO GSE41414 dataset, identifying 397 differentially expressed genes (DEGs).
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Therefore, in this study, by means of bioinformatics analysis, sALS-affected muscle tissue was analyzed using the GEO GSE41414 dataset, identifying 397 differentially expressed genes (DEGs).
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Gene expression analysis of ALS skeletal muscle
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Subsequently, the limma package’s moderated t-test, based on the empirical parametric Bayes method, identified differentially expressed genes (DEGs) between ALS patient and control samples.
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Complete file
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