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

神经退行性变 细胞外小泡 生物年龄 疾病 诊断生物标志物 生物信息学 医学 组学 老年学 癌症 神经科学 生物 病理 内科学 细胞生物学
作者
Stefano Salvioli,Maria Sofia Basile,Leonardo Bencivenga,Sara Carrino,Maria Conte,Sarah Damanti,Rebecca De Lorenzo,Eleonora Fiorenzato,Alessandro Gialluisi,Assunta Ingannato,Angelo Antonini,Nicola Baldini,Miriam Capri,Simone Cenci,Licia Iacoviello,Benedetta Nacmias,Olivieri Fabiola,Giuseppe Rengo,Patrizia Rovere‐Querini,Fabrizia Lattanzio
出处
期刊:Ageing Research Reviews [Elsevier BV]
卷期号:91: 102044-102044 被引量:72
标识
DOI:10.1016/j.arr.2023.102044
摘要

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
希望天下0贩的0应助xiaozhu采纳,获得10
1秒前
酚蓝8809发布了新的文献求助10
2秒前
小杨完成签到,获得积分10
2秒前
3秒前
YY发布了新的文献求助10
3秒前
SciGPT应助梅梅美美采纳,获得10
3秒前
QXS发布了新的文献求助10
4秒前
4秒前
勤恳的闭月完成签到,获得积分10
4秒前
所所应助池番采纳,获得10
5秒前
5秒前
6秒前
铅笔发布了新的文献求助10
6秒前
Mac完成签到,获得积分10
6秒前
6秒前
温暖的丹萱完成签到,获得积分10
7秒前
科研通AI6.4应助柴ab采纳,获得10
8秒前
Parker发布了新的文献求助10
10秒前
10秒前
jinyu完成签到 ,获得积分10
12秒前
14秒前
17秒前
Uyz完成签到 ,获得积分10
18秒前
大面包完成签到,获得积分10
18秒前
time发布了新的文献求助10
19秒前
19秒前
YY发布了新的文献求助10
19秒前
卿卿完成签到,获得积分10
20秒前
chen发布了新的文献求助10
21秒前
华仔应助乾渊采纳,获得10
21秒前
21秒前
21秒前
22秒前
卿卿发布了新的文献求助10
23秒前
Rui豆豆完成签到,获得积分10
23秒前
24秒前
zhu发布了新的文献求助10
24秒前
上官若男应助yq采纳,获得30
24秒前
haru发布了新的文献求助10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Single Cell Analysis of the Tumor Microenvironment Landscape Across the Disease Spectrum of Multiple Myeloma 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
The Cambridge History of China 英文版16册 600
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7330177
求助须知:如何正确求助?哪些是违规求助? 8944459
关于积分的说明 18973311
捐赠科研通 6985283
什么是DOI,文献DOI怎么找? 3216696
关于科研通互助平台的介绍 2383272
邀请新用户注册赠送积分活动 2196214