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Understanding the Human Aging Proteome Using Epidemiological Models.
Ubaida-Mohien, Ceereena; Moaddel, Ruin; Moore, Zenobia; Kuo, Pei-Lun; Tharakan, Ravi; Tanaka, Toshiko; Ferrucci, Luigi.
Afiliação
  • Ubaida-Mohien C; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA.
  • Moaddel R; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA.
  • Moore Z; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA.
  • Kuo PL; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA.
  • Tharakan R; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA.
  • Tanaka T; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA.
  • Ferrucci L; Biomedical Research Centre, National Institute on Aging, NIH, Baltimore, MD, USA. ferruccilu@grc.nia.nih.gov.
Methods Mol Biol ; 2399: 173-192, 2022.
Article em En | MEDLINE | ID: mdl-35604557
ABSTRACT
Human aging is a complex multifactorial process associated with a decline of physical and cognitive function and high susceptibility to chronic diseases, influenced by genetic, epigenetic, environmental, and demographic factors. This chapter will provide an overview on the use of epidemiological models with proteomics data as a method that can be used to identify factors that modulate the aging process in humans. This is demonstrated with proteomics data from human plasma and skeletal muscle, where the combination with epidemiological models identified a set of mitochondrial, spliceosome, and senescence proteins as well as the role of energetic pathways such as glycolysis, and electron transport pathways that regulate the aging process.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoma / Modelos Epidemiológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Methods Mol Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoma / Modelos Epidemiológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Methods Mol Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos