Development of a serum miRNA panel for detection of Alzheimer's Disease

小RNA 疾病 阿尔茨海默病 医学 内科学 生物 遗传学 基因
作者
Xinyu Zhang,Chang Su,Yuan Cao,Songtao Yang,Qi Qin,Yi Tang
出处
期刊:Alzheimers & Dementia [Wiley]
卷期号:20 (S2)
标识
DOI:10.1002/alz.084560
摘要

Abstract Background An urgent need exists for minimally invasive testing for accurate detection of Alzheimer’s disease (AD). Circulating microRNAs (miRNAs) have been investigated as a promising candidate biomarker for AD diagnosis and prediction because of their involvement in multiple brain signaling pathways in both health and disease. This study developed and validated a serum miRNA panel in discriminating clinically diagnosed AD from age‐matched cognitively healthy controls. Method 383 serum samples (194 AD, 189 cognitively healthy controls) were divided into three cohorts: discovery (n=59), training (n=126), and validation (n=198). In the discovery cohort, 49 miRNAs curated from literature databases were verified using individual serum sample via reserve transcriptase‐quantitative Polymerase chain amplification (RT‐qPCR). A logistic regression model was built with 11 differentially expressed miRNAs using the training cohort, and the final panel comprising 7 miRNAs with superior diagnostic performance was established. The diagnostic efficacy of the 7‐miRNA panel was further evaluated in the validation cohort by the receiver operating characteristic (ROC) analysis. Result Of the initial 49 screened serum miRNAs, 11 differentially expressed miRNAs were selected for logistic regression model construction based on their potential for detecting AD patients (AUC ≥ 0.7). After model optimization and validation via RT‐qPCR, a 7‐miRNA panel (miR‐146a‐5p, let‐7i‐5p, miR‐21‐5p, miR‐29c‐3p, miR‐92a‐3p, let‐7f‐5p, and miR‐1285‐5p) was identified with area under the curve (AUC) of 0.970 and 0.932 in the training and validation cohorts, respectively. The sensitivity of 7‐miR test was 88%, and the specificity was 85% in the validation cohort. Conclusion These findings suggest that the 7‐miRNA signature in serum serves as a novel noninvasive tool for the adjunctive diagnosis of AD. The panel shows promise for clinical application, setting the stage for future studies across diverse populations.

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
3秒前
撒上大声说完成签到,获得积分10
3秒前
4秒前
Tinker完成签到,获得积分10
5秒前
goodgoodstudy完成签到 ,获得积分10
5秒前
哇咔咔发布了新的文献求助20
5秒前
5秒前
ztq完成签到 ,获得积分10
6秒前
8秒前
8秒前
水水的完成签到,获得积分10
8秒前
小蘑菇应助无辜秋珊采纳,获得10
9秒前
April完成签到 ,获得积分10
9秒前
10秒前
yyyyyy发布了新的文献求助10
10秒前
英姑应助收到采纳,获得10
11秒前
yy发布了新的文献求助10
11秒前
Xu发布了新的文献求助10
12秒前
水水的发布了新的文献求助10
12秒前
呆萌若云完成签到,获得积分10
15秒前
沉默寄凡完成签到,获得积分10
16秒前
16秒前
16秒前
木村修完成签到,获得积分10
17秒前
wanshishunli发布了新的文献求助30
18秒前
咚咚完成签到,获得积分10
18秒前
opus17完成签到,获得积分10
18秒前
壮观复天发布了新的文献求助10
20秒前
懦弱的乐蕊完成签到 ,获得积分10
20秒前
21秒前
luo发布了新的文献求助10
21秒前
cdercder应助Shelley采纳,获得10
23秒前
Mr_龙在天涯完成签到,获得积分10
24秒前
geneontology发布了新的文献求助10
25秒前
留胡子的萝给留胡子的萝的求助进行了留言
25秒前
zzs完成签到,获得积分10
25秒前
25秒前
cdercder应助yu采纳,获得10
26秒前
JingP完成签到,获得积分10
26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
Cronologia da história de Macau 5000
Petrology and Plate Tectonics 800
Electrode Potentials 550
Matrix Methods in Data Mining and Pattern Recognition 510
Trees of tropical Asia : an illustrated guide to diversity 500
Materials Informatics Molecules, Crystals and Beyond A volume in Acta Materialia Book Series 400
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 7045398
求助须知:如何正确求助?哪些是违规求助? 8711620
关于积分的说明 18446917
捐赠科研通 6558892
什么是DOI,文献DOI怎么找? 3118211
关于科研通互助平台的介绍 2203736
邀请新用户注册赠送积分活动 2093646