Your browser doesn't support javascript.
loading
Understanding the Human Aging Proteome Using Epidemiological Models.
Ubaida-Mohien, Ceereena; Moaddel, Ruin; Moore, Zenobia; Kuo, Pei-Lun; Tharakan, Ravi; Tanaka, Toshiko; Ferrucci, Luigi.
Affiliation
  • 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 in 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.
Subject(s)
Key words
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteome / Epidemiological Models Type of study: Prognostic_studies Limits: Humans Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Document type: Article Affiliation country: United States
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteome / Epidemiological Models Type of study: Prognostic_studies Limits: Humans Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Document type: Article Affiliation country: United States