Spellman Daniel S, Wildsmith Kristin R, Honigberg Lee A, Tuefferd Marianne, Baker David, Raghavan Nandini, Nairn Angus C, Croteau Pascal, Schirm Michael, Allard Rene, Lamontagne Julie, Chelsky Daniel, Hoffmann Steven, Potter William Z
Department of Pharmacokinetics, Pharmacodynamics and Drug Metabolism, Merck Research Laboratories, Pennsylvania, PA, USA.
Department of Pharmacodynamic Biomarkers within Development Sciences, Genentech, Inc (a member of the Roche Group), South San Francisco, CA, USA.
Proteomics Clin Appl. 2015 Aug;9(7-8):715-31. doi: 10.1002/prca.201400178. Epub 2015 Apr 24.
We describe the outcome of the Biomarkers Consortium CSF Proteomics Project (where CSF is cerebral spinal fluid), a public-private partnership of government, academia, nonprofit, and industry. The goal of this study was to evaluate a multiplexed MS-based approach for the qualification of candidate Alzheimer's disease (AD) biomarkers using CSF samples from the AD Neuroimaging Initiative.
Reproducibility of sample processing, analytic variability, and ability to detect a variety of analytes of interest were thoroughly investigated. Multiple approaches to statistical analyses assessed whether panel analytes were associated with baseline pathology (mild cognitive impairment (MCI), AD) versus healthy controls or associated with progression for MCI patients, and included (i) univariate association analyses, (ii) univariate prediction models, (iii) exploratory multivariate analyses, and (iv) supervised multivariate analysis.
A robust targeted MS-based approach for the qualification of candidate AD biomarkers was developed. The results identified several peptides with potential diagnostic or predictive utility, with the most significant differences observed for the following peptides for differentiating (including peptides from hemoglobin A, hemoglobin B, and superoxide dismutase) or predicting (including peptides from neuronal pentraxin-2, neurosecretory protein VGF (VGF), and secretogranin-2) progression versus nonprogression from MCI to AD.
These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis.
我们描述了生物标志物联盟脑脊液蛋白质组学项目(其中CSF是脑脊液)的成果,该项目是政府、学术界、非营利组织和行业的公私合作项目。本研究的目的是使用来自阿尔茨海默病神经成像倡议的脑脊液样本,评估一种基于多重质谱的方法来鉴定候选阿尔茨海默病(AD)生物标志物。
对样本处理的可重复性、分析变异性以及检测各种感兴趣分析物的能力进行了全面研究。采用多种统计分析方法评估组套分析物是否与基线病理学(轻度认知障碍(MCI)、AD)与健康对照相关,或与MCI患者的病情进展相关,包括(i)单变量关联分析,(ii)单变量预测模型,(iii)探索性多变量分析,以及(iv)监督多变量分析。
开发了一种强大的基于靶向质谱的方法来鉴定候选AD生物标志物。结果鉴定出几种具有潜在诊断或预测效用的肽,在区分(包括来自血红蛋白A、血红蛋白B和超氧化物歧化酶的肽)或预测(包括来自神经元五聚体蛋白-2、神经分泌蛋白VGF(VGF)和分泌粒蛋白-2的肽)MCI到AD的进展与非进展方面,观察到以下肽的差异最为显著。
这些数据为AD和MCI进展中脑脊液的生物学特性提供了潜在见解,并为致力于提高诊断准确性、评估治疗效果和早期诊断的AD研究人员和临床医生提供了一种新工具。