Soluble biomarkers in osteoarthritis in 2022: year in review

生物标志物 骨关节炎 医学 软骨 生物标志物发现 生物信息学 软骨寡聚基质蛋白 蛋白质组学 叙述性评论 小RNA 内科学 病理 生物 重症监护医学 基因 替代医学 解剖 生物化学
作者
Francisco Airton Castro Rocha,Shabana Amanda Ali
出处
期刊:Osteoarthritis and Cartilage [Elsevier BV]
卷期号:31 (2): 167-176 被引量:28
标识
DOI:10.1016/j.joca.2022.09.005
摘要

Objective To review articles reporting on the development of soluble biomarkers in osteoarthritis (OA) over the past year. Design Two literature searches were conducted using the PubMed database for articles published between April 1, 2021 and March 31, 2022. Two searches were done, one on soluble biomarkers and another on circulating non-coding RNAs in OA. Additional articles were hand-picked to highlight emerging biomarker trends in OA. Results Of 348 publications retrieved, we included 20 articles with 3 that were hand-picked for the narrative synthesis. We review recent data on soluble biomarkers and circulating non-coding microRNAs in OA using the BIPED classification system. We highlight studies using proteomics to show that cartilage acidic protein 1 (CRTAC1) is a promising biomarker, helping diagnose and estimate severity in hand, hip, and knee OA. Subtle changes in the structure of glycosaminoglycans from the extracellular cartilage matrix were shown to discriminate OA from non-OA cartilage. C-reactive protein metabolite (CRPM) and collagen metabolites may help discriminate subsets of OA patients as well as disease progression. Additionally, physical activity may impact determination of biomarkers. We also report on circulating microRNAs, lncRNAs, and circRNAs in OA and their predictive accuracy in diagnosis and prognosis. Conclusions Biomarkers for routine use are still an unmet need in the OA clinical scenario. Emerging data and novel classes of biomarkers (i.e., non-coding RNAs) show promise. Although still requiring validation in multiple independent cohorts, the past year brought advances towards a ready-to-use, reproducible, cost-effective biomarker, namely CRTAC1, to better manage the OA patient.

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
刚刚
刚刚
123654发布了新的文献求助10
1秒前
直率发带发布了新的文献求助10
1秒前
2秒前
六六发布了新的文献求助30
2秒前
2秒前
酷波er应助赖羊羊采纳,获得10
3秒前
Sam完成签到,获得积分10
3秒前
4秒前
星辰大海应助碧蓝柠檬采纳,获得10
4秒前
张鸿杰发布了新的文献求助10
5秒前
5秒前
cheveux发布了新的文献求助10
6秒前
ultrac发布了新的文献求助10
6秒前
6秒前
blues发布了新的文献求助10
6秒前
啊啊啊应助浊酒采纳,获得10
6秒前
6秒前
ttt完成签到,获得积分10
7秒前
pignai发布了新的文献求助10
7秒前
小羊完成签到,获得积分0
8秒前
zqq123完成签到,获得积分10
8秒前
上官若男应助free2030采纳,获得10
9秒前
李健的小迷弟应助rzxhygr采纳,获得10
9秒前
今后应助晴云采纳,获得10
9秒前
9秒前
9秒前
闪闪完成签到,获得积分10
9秒前
shancui发布了新的文献求助10
9秒前
如初完成签到,获得积分20
10秒前
10秒前
10秒前
PhDL1发布了新的文献求助10
11秒前
11秒前
YXCT发布了新的文献求助20
11秒前
打打应助cuicuisha采纳,获得10
11秒前
12秒前
深情安青应助Forever采纳,获得10
12秒前
可爱的函函应助Khr1stINK采纳,获得10
13秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
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 7582505
求助须知:如何正确求助?哪些是违规求助? 9161468
关于积分的说明 19603244
捐赠科研通 7164661
什么是DOI,文献DOI怎么找? 3266154
关于科研通互助平台的介绍 2431016
邀请新用户注册赠送积分活动 2257371