Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective.
Artificial Intelligence
Biomarkers of aging
Frailty
Inflammaging
Multimorbidity
Journal
Ageing research reviews
ISSN: 1872-9649
Titre abrégé: Ageing Res Rev
Pays: England
ID NLM: 101128963
Informations de publication
Date de publication:
11 2023
11 2023
Historique:
received:
19
07
2023
revised:
24
08
2023
accepted:
25
08
2023
medline:
2
11
2023
pubmed:
31
8
2023
entrez:
30
8
2023
Statut:
ppublish
Résumé
According to the Geroscience concept that organismal aging and age-associated diseases share the same basic molecular mechanisms, the identification of biomarkers of age that can efficiently classify people as biologically older (or younger) than their chronological (i.e. calendar) age is becoming of paramount importance. These people will be in fact at higher (or lower) risk for many different age-associated diseases, including cardiovascular diseases, neurodegeneration, cancer, etc. In turn, patients suffering from these diseases are biologically older than healthy age-matched individuals. Many biomarkers that correlate with age have been described so far. The aim of the present review is to discuss the usefulness of some of these biomarkers (especially soluble, circulating ones) in order to identify frail patients, possibly before the appearance of clinical symptoms, as well as patients at risk for age-associated diseases. An overview of selected biomarkers will be discussed in this regard, in particular we will focus on biomarkers related to metabolic stress response, inflammation, and cell death (in particular in neurodegeneration), all phenomena connected to inflammaging (chronic, low-grade, age-associated inflammation). In the second part of the review, next-generation markers such as extracellular vesicles and their cargos, epigenetic markers and gut microbiota composition, will be discussed. Since recent progresses in omics techniques have allowed an exponential increase in the production of laboratory data also in the field of biomarkers of age, making it difficult to extract biological meaning from the huge mass of available data, Artificial Intelligence (AI) approaches will be discussed as an increasingly important strategy for extracting knowledge from raw data and providing practitioners with actionable information to treat patients.
Identifiants
pubmed: 37647997
pii: S1568-1637(23)00203-9
doi: 10.1016/j.arr.2023.102044
pii:
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
102044Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare no conflict of interest.