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阿尔茨海默病神经影像学计划2014年更新:自启动以来发表论文综述

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

作者信息

Weiner Michael W, Veitch Dallas P, Aisen Paul S, Beckett Laurel A, Cairns Nigel J, Cedarbaum Jesse, Green Robert C, Harvey Danielle, Jack Clifford R, Jagust William, Luthman Johan, Morris John C, Petersen Ronald C, Saykin Andrew J, Shaw Leslie, Shen Li, Schwarz Adam, Toga Arthur W, Trojanowski John Q

机构信息

Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.

Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA.

出版信息

Alzheimers Dement. 2015 Jun;11(6):e1-120. doi: 10.1016/j.jalz.2014.11.001.

DOI:10.1016/j.jalz.2014.11.001
PMID:26073027
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5469297/
Abstract

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

摘要

阿尔茨海默病神经影像学倡议(ADNI)是一项正在进行的纵向多中心研究,旨在开发用于早期检测和跟踪阿尔茨海默病(AD)的临床、影像学、遗传学和生物化学生物标志物。最初的研究ADNI - 1招募了400名早期轻度认知障碍(MCI)患者、200名早期AD患者和200名认知正常的老年对照。2009年,ADNI - 1通过一项为期2年的重大机遇资助以及一项竞争性延续项目ADNI - 2得到扩展,ADNI - 2又招募了550名参与者,并将持续到2015年。本文回顾了该倡议启动以来发表的所有论文,并总结了截至2013年底的结果。ADNI的主要成就如下:(1)在多中心环境中开发了用于临床试验、磁共振成像(MRI)、正电子发射断层扫描(PET)和脑脊液(CSF)生物标志物的标准化方法;(2)阐明了对照受试者、MCI患者和AD患者中影像学和CSF生物标志物测量的变化模式和速率。CSF生物标志物在很大程度上与β - 淀粉样蛋白级联反应(Hardy,J Alzheimer's Dis 2006;9(增刊3):151 - 3)和AD的tau介导的神经退行性变假说预测的疾病轨迹一致,而脑萎缩和代谢减退水平显示出预测模式,但根据区域和疾病严重程度表现出不同的变化速率;(3)评估诊断分类的替代方法。目前,最佳分类器从多种模式中选择并组合最佳特征,包括MRI、[(18)F] - 氟脱氧葡萄糖 - PET、淀粉样蛋白PET、CSF生物标志物和临床试验;(4)开发用于AD的血液生物标志物,作为用于AD诊断的CSF生物标志物的潜在非侵入性和低成本替代物,并评估α - 突触核蛋白作为一种额外的生物标志物;(5)开发AD的早期检测方法。CSF生物标志物β - 淀粉样蛋白42和tau以及淀粉样蛋白PET可能反映轻度症状甚至无症状受试者中AD病理的最早阶段,并且是在临床前期检测AD的主要候选指标;(6)通过识别最有可能在未来即将出现临床衰退的受试者并使用更敏感的结局指标来减少样本量,从而提高临床试验效率。纳入APOE状态和纵向MRI的多模式方法被证明对未来衰退的预测性最高。用作结局指标的临床试验的改进,如临床痴呆评定量表 - 方框总和,进一步减少了样本量;(7)开创全基因组关联研究,利用定量影像学和生物标志物表型,包括纵向数据,来确认最近确定的基因座CR1、CLU和PICALM,并识别新的AD风险基因座;(8)通过在日本、澳大利亚、阿根廷、中国台湾、韩国以及欧洲和意大利建立类似ADNI的项目,在全球范围内产生影响;(9)通过整合ADNI生物标志物和临床数据来理解正常衰老、MCI和AD的生物学和病理生物学,以促进解决关于AD病因发病机制的相互竞争假说的争议的研究,从而推动寻找AD疾病修饰药物的努力;(十)建立基础设施,允许在无禁运的情况下向全世界感兴趣的科学研究人员共享所有原始和处理后的数据。

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Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative.了解疾病进展和改善阿尔茨海默病临床试验:阿尔茨海默病神经影像学倡议的最新重点。
Alzheimers Dement. 2019 Jan;15(1):106-152. doi: 10.1016/j.jalz.2018.08.005. Epub 2018 Oct 13.
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Characterization of Alzheimer Disease Biomarker Discrepancies Using Cerebrospinal Fluid Phosphorylated Tau and AV1451 Positron Emission Tomography.使用脑脊液磷酸化tau 和 AV1451 正电子发射断层扫描技术对阿尔茨海默病生物标志物差异进行特征分析。
JAMA Neurol. 2020 Apr 1;77(4):508-516. doi: 10.1001/jamaneurol.2019.4749.
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Introduction to special issue: Overview of Alzheimer's Disease Neuroimaging Initiative.特刊引言:阿尔茨海默病神经影像学计划概述
Alzheimers Dement. 2015 Jul;11(7):730-3. doi: 10.1016/j.jalz.2015.05.007.

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Conducting MRI trials in Alzheimer's patients: Challenges and Guidelines.在阿尔茨海默病患者中进行磁共振成像试验:挑战与指南
medRxiv. 2025 Jul 2:2025.07.02.25330723. doi: 10.1101/2025.07.02.25330723.
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Resting-state functional magnetic resonance imaging in a randomized clinical trial for Alzheimer's disease.阿尔茨海默病随机临床试验中的静息态功能磁共振成像
Neuroimage Rep. 2021 Sep 24;1(4):100055. doi: 10.1016/j.ynirp.2021.100055. eCollection 2021 Dec.
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Plasma neurofilament light chain mediates the effect of subsyndromal symptomatic depression on cognitive decline in older adults.

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Sparse Multi-Task Regression and Feature Selection to Identify Brain Imaging Predictors for Memory Performance.用于识别记忆表现的脑成像预测指标的稀疏多任务回归与特征选择
Proc IEEE Int Conf Comput Vis. 2011:557-562. doi: 10.1109/ICCV.2011.6126288.
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Coalition Against Major Diseases/European Medicines Agency biomarker qualification of hippocampal volume for enrichment of clinical trials in predementia stages of Alzheimer's disease.反对主要疾病联盟/欧洲药品管理局 对海马体积的生物标志物资格进行认证,以在阿尔茨海默病的痴呆前阶段临床试验中进行富集。
Alzheimers Dement. 2014 Jul;10(4):421-429.e3. doi: 10.1016/j.jalz.2013.07.003.
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血浆神经丝轻链介导亚综合征症状性抑郁对老年人认知衰退的影响。
Front Aging Neurosci. 2025 May 14;17:1547394. doi: 10.3389/fnagi.2025.1547394. eCollection 2025.
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Differences in Glucose Metabolism Between Single Memory Domain and Multidomain Subjective Cognitive Decline: A Longitudinal Study From SILCODE.单一记忆领域与多领域主观认知衰退之间的葡萄糖代谢差异:来自SILCODE的纵向研究
CNS Neurosci Ther. 2025 May;31(5):e70264. doi: 10.1111/cns.70264.
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Integrative Multi-Omics and Multivariate Longitudinal Data Analysis for Dynamic Risk Estimation in Alzheimer's Disease.用于阿尔茨海默病动态风险评估的整合多组学与多变量纵向数据分析
Stat Med. 2025 May;44(10-12):e70105. doi: 10.1002/sim.70105.
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MRI-based mild cognitive impairment and Alzheimer's disease classification using an algorithm of combination of variational autoencoder and other machine learning classifiers.基于磁共振成像的轻度认知障碍和阿尔茨海默病分类:使用变分自编码器与其他机器学习分类器相结合的算法
J Alzheimers Dis Rep. 2024 Oct 18;8(1):1434-1452. doi: 10.1177/25424823241290694. eCollection 2024.
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Perceptions and practices of imaging personnel and physicians regarding the use of brain MRI for dementia diagnosis in Uganda.乌干达影像工作人员和医生对使用脑部磁共振成像进行痴呆症诊断的认知与实践
PLoS One. 2025 Jan 17;20(1):e0305788. doi: 10.1371/journal.pone.0305788. eCollection 2025.
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Pharmacogenomics for neurodegenerative disorders - a focused review.神经退行性疾病的药物基因组学——一篇聚焦综述。
Front Pharmacol. 2024 Dec 20;15:1478964. doi: 10.3389/fphar.2024.1478964. eCollection 2024.
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Harmonizing AI governance regulations and neuroinformatics: perspectives on privacy and data sharing.协调人工智能治理法规与神经信息学:关于隐私和数据共享的观点
Front Neuroinform. 2024 Dec 17;18:1472653. doi: 10.3389/fninf.2024.1472653. eCollection 2024.
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The ADNI Administrative Core: Ensuring ADNI's success and informing future AD clinical trials.ADNI管理核心:确保ADNI取得成功并为未来的AD临床试验提供信息。
Alzheimers Dement. 2024 Dec;20(12):9004-9013. doi: 10.1002/alz.14311. Epub 2024 Nov 13.
Qualification of a surrogate matrix-based absolute quantification method for amyloid-β₄₂ in human cerebrospinal fluid using 2D UPLC-tandem mass spectrometry.
使用二维超高效液相色谱-串联质谱法对基于替代基质的人脑脊液中β淀粉样蛋白42绝对定量方法的验证
J Alzheimers Dis. 2014;41(2):441-51. doi: 10.3233/JAD-132489.
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Approaches and costs for sharing clinical research data.共享临床研究数据的方法与成本。
JAMA. 2014 Mar 26;311(12):1201-2. doi: 10.1001/jama.2014.850.
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CSF Apo-E levels associate with cognitive decline and MRI changes.脑脊液载脂蛋白E水平与认知功能减退及磁共振成像变化相关。
Acta Neuropathol. 2014 May;127(5):621-32. doi: 10.1007/s00401-013-1236-0. Epub 2014 Jan 3.
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Integration and relative value of biomarkers for prediction of MCI to AD progression: spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers.用于预测轻度认知障碍(MCI)向阿尔茨海默病(AD)进展的生物标志物的整合与相对价值:脑萎缩的空间模式、认知评分、载脂蛋白E(APOE)基因型和脑脊液生物标志物
Neuroimage Clin. 2013 Nov 28;4:164-73. doi: 10.1016/j.nicl.2013.11.010. eCollection 2014.
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Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.用于阿尔茨海默病/轻度认知障碍诊断的基于堆叠自动编码器的潜在特征表示。
Brain Struct Funct. 2015 Mar;220(2):841-59. doi: 10.1007/s00429-013-0687-3. Epub 2013 Dec 22.
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Medication for Alzheimer's disease and associated fall hazard: a retrospective cohort study from the Alzheimer's Disease Neuroimaging Initiative.治疗阿尔茨海默病和相关跌倒危险的药物:来自阿尔茨海默病神经影像学倡议的回顾性队列研究。
Drugs Aging. 2014 Feb;31(2):125-9. doi: 10.1007/s40266-013-0143-3.
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Effects of T2-Weighted MRI Based Cranial Volume Measurements on Studies of the Aging Brain.基于T2加权磁共振成像的颅腔容积测量对衰老大脑研究的影响。
Proc SPIE Int Soc Opt Eng. 2013 Mar 13;8669:86693M-. doi: 10.1117/12.2006727.
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Identifying informative imaging biomarkers via tree structured sparse learning for AD diagnosis.通过树状结构稀疏学习识别有信息的成像生物标志物,用于 AD 诊断。
Neuroinformatics. 2014 Jul;12(3):381-94. doi: 10.1007/s12021-013-9218-x.