Biomarkers of aging in frailty and age-associated disorders: State of the art and future perspective.


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
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

102044

Informations 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.

Auteurs

Stefano Salvioli (S)

Department of Medical and Surgical Science, University of Bologna, Bologna, Italy; IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy. Electronic address: stefano.salvioli@unibo.it.

Maria Sofia Basile (MS)

IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.

Leonardo Bencivenga (L)

Department of Translational Medical Sciences, University of Naples Federico II, Napoli, Italy.

Sara Carrino (S)

Department of Medical and Surgical Science, University of Bologna, Bologna, Italy.

Maria Conte (M)

Department of Medical and Surgical Science, University of Bologna, Bologna, Italy.

Sarah Damanti (S)

IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy.

Rebecca De Lorenzo (R)

IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy.

Eleonora Fiorenzato (E)

Parkinson's Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), Department of Neurosciences, University of Padova, Padova, Italy.

Alessandro Gialluisi (A)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy; EPIMED Research Center, Department of Medicine and Surgery, University of Insubria, Varese, Italy.

Assunta Ingannato (A)

Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.

Angelo Antonini (A)

Parkinson's Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), Department of Neurosciences, University of Padova, Padova, Italy; Center for Neurodegenerative Disease Research (CESNE), Department of Neurosciences, University of Padova, Padova, Italy.

Nicola Baldini (N)

IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.

Miriam Capri (M)

Department of Medical and Surgical Science, University of Bologna, Bologna, Italy.

Simone Cenci (S)

IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy.

Licia Iacoviello (L)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy; EPIMED Research Center, Department of Medicine and Surgery, University of Insubria, Varese, Italy.

Benedetta Nacmias (B)

Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.

Fabiola Olivieri (F)

Department of Clinical and Molecular Sciences, Università Politecnica Delle Marche, Ancona, Italy; Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy.

Giuseppe Rengo (G)

Department of Translational Medical Sciences, University of Naples Federico II, Napoli, Italy; Istituti Clinici Scientifici Maugeri IRCCS, Scientific Institute of Telese Terme, Telese Terme, Italy.

Patrizia Rovere Querini (PR)

IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milano, Italy.

Fabrizia Lattanzio (F)

Scientific Direction, IRCCS INRCA, Ancona, Italy.

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