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Proteomics in aging research: A roadmap to clinical, translational research

The identification of plasma proteins that systematically change with age and, independent of chronological age, predict accelerated decline of health is an expanding area of research. Circulating proteins are ideal translational “omics” since they are final effectors of physiological pathways and b...

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Detalles Bibliográficos
Autores principales: Moaddel, Ruin, Ubaida‐Mohien, Ceereena, Tanaka, Toshiko, Lyashkov, Alexey, Basisty, Nathan, Schilling, Birgit, Semba, Richard D, Franceschi, Claudio, Gorospe, Myriam, Ferrucci, Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045948/
https://www.ncbi.nlm.nih.gov/pubmed/33730416
http://dx.doi.org/10.1111/acel.13325
Descripción
Sumario:The identification of plasma proteins that systematically change with age and, independent of chronological age, predict accelerated decline of health is an expanding area of research. Circulating proteins are ideal translational “omics” since they are final effectors of physiological pathways and because physicians are accustomed to use information of plasma proteins as biomarkers for diagnosis, prognosis, and tracking the effectiveness of treatments. Recent technological advancements, including mass spectrometry (MS)‐based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan), and Proximity Extension Assay (PEA, O‐Link), have allowed for the assessment of thousands of proteins in plasma or other biological matrices, which are potentially translatable into new clinical biomarkers and provide new clues about the mechanisms by which aging is associated with health deterioration and functional decline. We carried out a detailed literature search for proteomic studies performed in different matrices (plasma, serum, urine, saliva, tissues) and species using multiple platforms. Herein, we identified 232 proteins that were age‐associated across studies. Enrichment analysis of the 232 age‐associated proteins revealed metabolic pathways previously connected with biological aging both in animal models and in humans, most remarkably insulin‐like growth factor (IGF) signaling, mitogen‐activated protein kinases (MAPK), hypoxia‐inducible factor 1 (HIF1), cytokine signaling, Forkhead Box O (FOXO) metabolic pathways, folate metabolism, advance glycation end products (AGE), and receptor AGE (RAGE) metabolic pathway. Information on these age‐relevant proteins, likely expanded and validated in longitudinal studies and examined in mechanistic studies, will be essential for patient stratification and the development of new treatments aimed at improving health expectancy.