Khoonsari Payam Emami, Häggmark Anna, Lönnberg Maria, Mikus Maria, Kilander Lena, Lannfelt Lars, Bergquist Jonas, Ingelsson Martin, Nilsson Peter, Kultima Kim, Shevchenko Ganna
Department of Medical Sciences, Cancer Pharmacology and Computational Medicine, Uppsala University, Uppsala, Sweden.
Affinity Proteomics, Science for Life Laboratory, School of Biotechnology, KTH Royal Institute of Technology, Stockholm, Sweden.
PLoS One. 2016 Mar 7;11(3):e0150672. doi: 10.1371/journal.pone.0150672. eCollection 2016.
Alzheimer's disease is a neurodegenerative disorder accounting for more than 50% of cases of dementia. Diagnosis of Alzheimer's disease relies on cognitive tests and analysis of amyloid beta, protein tau, and hyperphosphorylated tau in cerebrospinal fluid. Although these markers provide relatively high sensitivity and specificity for early disease detection, they are not suitable for monitor of disease progression. In the present study, we used label-free shotgun mass spectrometry to analyse the cerebrospinal fluid proteome of Alzheimer's disease patients and non-demented controls to identify potential biomarkers for Alzheimer's disease. We processed the data using five programs (DecyderMS, Maxquant, OpenMS, PEAKS, and Sieve) and compared their results by means of reproducibility and peptide identification, including three different normalization methods. After depletion of high abundant proteins we found that Alzheimer's disease patients had lower fraction of low-abundance proteins in cerebrospinal fluid compared to healthy controls (p<0.05). Consequently, global normalization was found to be less accurate compared to using spiked-in chicken ovalbumin for normalization. In addition, we determined that Sieve and OpenMS resulted in the highest reproducibility and PEAKS was the programs with the highest identification performance. Finally, we successfully verified significantly lower levels (p<0.05) of eight proteins (A2GL, APOM, C1QB, C1QC, C1S, FBLN3, PTPRZ, and SEZ6) in Alzheimer's disease compared to controls using an antibody-based detection method. These proteins are involved in different biological roles spanning from cell adhesion and migration, to regulation of the synapse and the immune system.
阿尔茨海默病是一种神经退行性疾病，占痴呆病例的50%以上。阿尔茨海默病的诊断依赖于认知测试以及对脑脊液中β淀粉样蛋白、tau蛋白和过度磷酸化tau蛋白的分析。尽管这些标志物对疾病早期检测具有相对较高的敏感性和特异性，但它们并不适合用于监测疾病进展。在本研究中，我们使用无标记鸟枪法质谱分析阿尔茨海默病患者和非痴呆对照的脑脊液蛋白质组，以鉴定阿尔茨海默病的潜在生物标志物。我们使用五个程序（DecyderMS、Maxquant、OpenMS、PEAKS和Sieve）处理数据，并通过重现性和肽段鉴定比较它们的结果，包括三种不同的归一化方法。在去除高丰度蛋白质后，我们发现与健康对照相比，阿尔茨海默病患者脑脊液中低丰度蛋白质的比例较低（p<0.05）。因此，与使用添加的鸡卵清蛋白进行归一化相比，发现全局归一化的准确性较低。此外，我们确定Sieve和OpenMS具有最高的重现性，而PEAKS是鉴定性能最高的程序。最后，我们使用基于抗体的检测方法成功验证，与对照相比，阿尔茨海默病患者中八种蛋白质（A2GL、APOM、C1QB、C1QC、C1S、FBLN3、PTPRZ和SEZ6）的水平显著降低（p<0.05）。这些蛋白质参与从细胞黏附和迁移到突触和免疫系统调节等不同的生物学功能。
