Díaz-Peña Ramón, Andrés-Benito Pol, Peral Erica, Domínguez Raúl, Povedano Mónica, Santamaría Enrique, Fernández-Irigoyen Joaquín
Proteomics Platform, Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain.
Cognition and Behavior Study Group, Institut de Recerca Biomèdica de Lleida (IRBLleida), Lleida, Spain.
Methods Mol Biol. 2025;2914:129-139. doi: 10.1007/978-1-0716-4462-1_11.
Cerebrospinal fluid (CSF) is a low-risk, rapid, and mid-invasive sampling for diagnosis, prognosis, and treatment of neurological pathologies. The CSF liquid biopsies disponibility and sampling homogeneity foster the research for biomarker discovery for neurological disorders and pathologies and, importantly, enable extensive population studies. Liquid chromatography-mass spectrometry (LC-MS) proteomics is a powerful tool for biomarker discovery. Proteomics large studies provide more robust and reliable results, offering exceptional FDR control and outlier identification, allowing high-precision results. Consequently, a robust and reliable pipeline proteomics methodology must be required to analyze hundreds of samples, from sample preparation to data analysis. Here, we describe a detailed workflow for analyzing human CSF samples for large studies by direct data-independent (dDIA).
脑脊液(CSF)是一种用于神经病理学诊断、预后评估和治疗的低风险、快速且微创的采样方法。脑脊液液体活检的可行性和采样均一性促进了神经疾病和病理学生物标志物发现的研究,重要的是,能够开展广泛的人群研究。液相色谱-质谱联用(LC-MS)蛋白质组学是生物标志物发现的强大工具。大规模蛋白质组学研究能提供更稳健可靠的结果,具有出色的错误发现率(FDR)控制和异常值识别能力,可实现高精度结果。因此,必须要有一种稳健可靠的流水线式蛋白质组学方法来分析数百个样本,从样本制备到数据分析。在此,我们描述了一种通过直接数据非依赖采集(dDIA)对大量人类脑脊液样本进行分析的详细工作流程。