Transcriptomic analysis of elderly women with low muscle mass: association with immune system pathway

Despite the well-established association of gene expression deregulation with low muscle mass (LMM), the associated biological mechanisms remain unclear. Transcriptomic studies are capable to identify key mediators in complex diseases. We aimed to identify relevant mediators and biological mechanism...

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Bibliographic Details
Published in:Aging (Albany, NY.) NY.), 2021-09, Vol.13 (17), p.20992-21008
Main Authors: Jales Neto, Levi H, Hounkpe, Bidossessi W, Fernandes, Georgea H, Takayama, Liliam, Caparbo, Valéria F, Lopes, Neuza H M, Pereira, Alexandre C, Pereira, Rosa M R
Format: Article
Language:English
Subjects:
Aged
Aged, 80 and over
Aging
Female
Gene Expression Profiling
Gene Regulatory Networks
Humans
Immune System
Inflammation - genetics
Inflammation - metabolism
Logistic Models
Metabolic Networks and Pathways
Muscle, Skeletal
Research Paper
Sarcopenia - genetics
Sarcopenia - metabolism
Support Vector Machine
Transcriptome
Vitamin D - blood
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Summary:Despite the well-established association of gene expression deregulation with low muscle mass (LMM), the associated biological mechanisms remain unclear. Transcriptomic studies are capable to identify key mediators in complex diseases. We aimed to identify relevant mediators and biological mechanisms associated with age-related LMM. LMM-associated genes were detected by logistic regression using microarray data of 20 elderly women with LMM and 20 age and race-matched controls extracted from our SPAH Study (GSE152073). We performed weighted gene co-expression analysis (WGCNA) that correlated the identified gene modules with laboratorial characteristics. Gene enrichment analysis was performed and an LMM predictive model was constructed using Support Vector Machine (SVM). Overall, 821 discriminating transcripts clusters were identified (|beta coefficient| >1; -value
ISSN:1945-4589
1945-4589
DOI:10.18632/aging.203505