血管性认知障碍血浆生物标志物的研究进展

血管性认知障碍(VCI)主要由血管危险因素和脑血管疾病引起。VCI包括广泛的认知障碍,从轻度认知障碍到缺血性或出血性卒中引起的血管性痴呆,也包含合并阿尔茨海默病等混合性病理所致的不同程度的认知障碍。目前针对VCI的药物治疗研究多集中在VaD (重度VCI),且这些效果并未带来日常生活能力的明显改善。寻找新的生物标志物是对VCI进行诊断和治疗的关键一步。近年来,以血液为标本筛选合适的VCI生物标志物研究得到了广泛开展。本文旨在对血浆中血管性认知障碍生物标志物的研究现状进行综述,以寻找适合VCI患者诊断的生物学工具。Vascular cognitive impairment (VCI) is mainly caused by vascular risk factors and cerebrovascular disease. VCI includes a wide range of cognitive impairments, from mild cognitive impairment to vascular dementia due to ischemic or hemorrhagic stroke, as well as varying degrees of cognitive deficits due to comorbid pathologies such as Alzheimer’s disease. Current pharmacotherapy studies for VCI have focused on VaD (severe VCI), and these effects have not led to significant improvements in the ability to perform activities of daily living. The search for new biomarkers is a crucial step in the diagnosis and treatment of VCI. In recent years, blood-based specimen screening studies for suitable biomarkers of VCI have been widely conducted. The aim of this paper is to review the current status of research on biomarkers of vascular cognitive impairment in plasma in order to find suitable biological tools for the diagnosis of patients with VCI.

血管性认知障碍患者中miRNAs诊断价值的Meta分析

目的:本研究使用meta分析探究miRNAs在血管性认知障碍患者中的诊断性能。方法:本研究采用Cochrane的方法进行Meta分析,检索的范围为从成立到2024年5月1日,数据库为PubMed,web of science,Embase,The Cochrane Library,中国知网、维普、万方。涵盖的范围为使用miRNAs诊断血管性认知障碍的诊断性试验,使用固定与随机效应模型分析汇总的敏感度(sensitivity, Sen)、特异度(specificity, Spe)、阳性似然比(positive likelihood ratio, PLR)、阴性似然比(negative likelihood ratio, NLR)、诊断比值比(diagnostic odd ratio, DOR)、SROC,并按地域与失调状态进行亚组分析。结果:共纳入8篇文献,1160名患者,19种不同类型的miRNAs,合并灵敏度为0.73,95% CI 0.71~0.74;合并特异性为0.77,95% CI 0.75~0.79;合并阳性似然比为3.26,95% CI 2.42~4.38;合并阴性似然比为0.33,95% CI 0.26~0.43;合并诊断比值比为10.64,95% CI 6.42~17.61,AUC为0.83。结论:本研究表明,miRNAs在诊断VCI中具有很高的准确性,可以作为VCI的潜在诊断标志物。Objective: This meta-analysis investigates the diagnostic performance of miRNAs in patients with vascular cognitive impairment (VCI). Methods: We conducted a meta-analysis following Cochrane methodology. Literature searches were performed up to May 1, 2024, using PubMed, Web of Science, Embase, The Cochrane Library, CNKI, VIP, and Wanfang databases. Studies assessing the diagnostic efficacy of miRNAs in VCI using sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) were included. Subgroup analyses were conducted based on geographical regions and cognitive status. Results: Eight studies involving 1160 patients and examining 19 different types of miRNAs were included. The pooled sensitivity was 0.73 (95% CI 0.71~0.74), specificity was 0.77 (95% CI 0.75~0.79), positive likelihood ratio was 3.26 (95% CI 2.42~4.38), negative likelihood ratio was 0.33 (95% CI 0.26~0.43), diagnostic odds ratio was 10.64 (95% CI 6.42~17.61), and the SROC area under the curve was 0.83. Conclusion: This study demonstrates that miRNA profiles have high accuracy in diagnosing VCI and can serve as potential diagnostic biomarkers for VCI.