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Transcriptomic analysis of elderly women with low muscle mass: association with immune system pathway.
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.
Afiliação
  • Jales Neto LH; Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Hounkpe BW; Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Fernandes GH; Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Takayama L; Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Caparbo VF; Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Lopes NHM; Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Pereira AC; Laboratory of Genetics and Molecular Cardiology, Instituto do Coração (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
  • Pereira RMR; Bone Metabolism Laboratory, Rheumatology Division Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.
Aging (Albany NY) ; 13(17): 20992-21008, 2021 09 07.
Article em En | MEDLINE | ID: mdl-34493690
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; p-value <0.01). From this list, 45 predictors of LMM were detected by SVM and validated with 0.7 of accuracy. Our results revealed that the well-described association of inflammation, immunity and metabolic alterations is also relevant at transcriptomic level. WGCNA highlighted a correlation of genes modules involved in immunity pathways with vitamin D level (R = 0.63, p = 0.004) and the Agatston score (R = 0.51, p = 0.02). Our study generated a predicted regulatory network and revealed significant metabolic pathways related to aging processes, showing key mediators that warrant further investigation.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Músculo Esquelético / Redes Reguladoras de Genes / Sarcopenia / Transcriptoma / Sistema Imunitário / Inflamação Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Aged / Aged80 / Female / Humans Idioma: En Revista: Aging (Albany NY) Assunto da revista: GERIATRIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Músculo Esquelético / Redes Reguladoras de Genes / Sarcopenia / Transcriptoma / Sistema Imunitário / Inflamação Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Aged / Aged80 / Female / Humans Idioma: En Revista: Aging (Albany NY) Assunto da revista: GERIATRIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos