During the last two decades, over 100 proteomics studies have identified a variety of potential biomarkers in CSF of Alzheimer’s (AD) patients. Although several reviews have proposed specific biomarkers, to date, the statistical relevance of these proteins has not been investigated and no peptidomic analyses have been generated on the basis of specific up- or down- regulation. Herein, we perform an analysis of all unbiased explorative proteomics studies of CSF biomarkers in AD to critically evaluate whether proteins and peptides identified in each study are consistent in distribution; direction change; and significance, which would strengthen their potential use in studies of AD pathology and progression. We generated a database containing all CSF proteins whose levels are known to be significantly altered in human AD from 47 independent, validated, proteomics studies. Using this database, which contains 2022 AD and 2562 control human samples, we examined whether each protein is consistently present on the basis of reliable statistical studies; and if so, whether it is over- or under-represented in AD. Additionally, we performed a direct analysis of available mass spectrometric data of these proteins to generate an AD CSF peptide database with 3221 peptides for further analysis. Of the 162 proteins that were identified in 2 or more studies, we investigated their enrichment or depletion in AD CSF. This allowed us to identify 23 proteins which were increased and 50 proteins which were decreased in AD, some of which have never been revealed as consistent AD biomarkers (i.e. SPRC or MUC18). Regarding the analysis of the tryptic peptide database, we identified 87 peptides corresponding to 13 proteins as the most highly consistently altered peptides in AD. Analysis of tryptic peptide fingerprinting revealed specific peptides encoded by CH3L1, VGF, SCG2, PCSK1N, FBLN3 and APOC2 with the highest probability of detection in AD. Our study reveals a panel of 27 proteins and 21 peptides highly altered in AD with consistent statistical significance; this panel constitutes a potent tool for the classification and diagnosis of AD.

中文翻译：

---

对定义阿尔茨海默病的脑脊液蛋白和肽进行全面系统评价。

在过去的二十年中，超过 100 项蛋白质组学研究已经在阿尔茨海默病 (AD) 患者的脑脊液中鉴定出了多种潜在的生物标志物。尽管一些评论提出了特定的生物标志物，但迄今为止，这些蛋白质的统计相关性尚未得到研究，也没有基于特定上调或下调的肽组学分析进行生成。在此，我们对 AD 中脑脊液生物标志物的所有无偏见探索性蛋白质组学研究进行了分析，以批判性地评估每项研究中鉴定的蛋白质和肽的分布是否一致；方向改变；和意义，这将加强它们在 AD 病理学和进展研究中的潜在用途。我们根据 47 项独立、经过验证的蛋白质组学研究生成了一个包含所有 CSF 蛋白质的数据库，这些蛋白质的水平在人类 AD 中显着改变。使用这个包含 2022 年和 2562 个对照人类样本的数据库，我们在可靠的统计研究的基础上检查了每种蛋白质是否始终存在；如果是这样，它在 AD 中的代表性是否过高或过低。此外，我们对这些蛋白质的可用质谱数据进行了直接分析，以生成包含 3221 种肽的 AD CSF 肽数据库，以供进一步分析。在 2 项或多项研究中鉴定出的 162 种蛋白质中，我们研究了它们在 AD CSF 中的富集或消耗。这使我们能够鉴定出 AD 中 23 种增加的蛋白质和 50 种减少的蛋白质，其中一些蛋白质从未被揭示为一致的 AD 生物标志物（即 SPRC 或 MUC18）。通过对胰蛋白酶肽数据库的分析，我们确定了与 13 种蛋白质相对应的 87 种肽，它们是 AD 中变化最一致的肽。胰蛋白酶肽指纹图谱分析揭示了由 CH3L1、VGF、SCG2、PCSK1N、FBLN3 和 APOC2 编码的特定肽，在 AD 中检测到的概率最高。我们的研究揭示了一组 27 种蛋白质和 21 种肽在 AD 中发生了高度改变，具有一致的统计显着性；该小组构成了 AD 分类和诊断的有效工具。