Hörmann Philipp, Barkovits Katalin, Marcus Katrin, Hiller Karsten
Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany.
Medizinisches Proteom-Center, Medical Faculty, Ruhr-University Bochum, Bochum, Germany.
Methods Mol Biol. 2019;2044:337-342. doi: 10.1007/978-1-4939-9706-0_21.
In the field of neurodegeneration, it is important to identify biomarkers that enable early disease prediction, since these disorders start decades before clinical symptoms manifest. Cerebrospinal fluid (CSF) is considered an excellent source for biomarker discovery since it is in direct contact with the extracellular space of the brain and directly reflects disease-specific changes.While the liquor drainage is no major risk factor for patients, it is still not as easy and popular as simple blood sampling and less liquid can be collected. Especially when a variety of experiments for one cohort is planned, the volume of CSF can be a limiting factor. Therefore, it is essential that extraction and analytical methods are adapted to low amounts of liquor. If in follow-up studies, additional replicates to increase statistical significance or different extraction approaches are planned, the required amounts have to be minimized.With this extraction method, a combined proteomics and metabolomics approach is possible. This opportunity implies a variety of advantages. First, a classification matrix based on the comprehensive data set has a potentially higher accuracy even without a deeper understanding of the biological meaning of the different omics changes. If the proteome and metabolome differences can be linked to each other, this approach can conceivably open so far unknown doors regarding the cause or progression of different diseases like Alzheimer's or Parkinson's disease.
在神经退行性疾病领域,识别能够实现疾病早期预测的生物标志物非常重要,因为这些疾病在临床症状出现前几十年就已开始。脑脊液(CSF)被认为是发现生物标志物的理想来源,因为它与脑的细胞外间隙直接接触,能直接反映疾病特异性变化。虽然脑脊液引流对患者来说并非主要风险因素,但它仍不像简单的血液采样那样容易且普及,而且能采集到的液体较少。特别是当为一个队列计划进行各种实验时,脑脊液的量可能成为一个限制因素。因此,提取和分析方法必须适用于少量脑脊液。如果在后续研究中计划增加重复实验以提高统计显著性或采用不同的提取方法,就必须将所需量减至最少。采用这种提取方法,蛋白质组学和代谢组学相结合的方法是可行的。这种可能性具有多种优势。首先,基于综合数据集的分类矩阵即使在对不同组学变化的生物学意义没有深入理解的情况下,也可能具有更高的准确性。如果蛋白质组和代谢组的差异能够相互关联,那么这种方法可能会为诸如阿尔茨海默病或帕金森病等不同疾病的病因或进展打开迄今为止未知的大门。