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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).

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High-Throughput Human Cerebrospinal Fluid Proteome Analysis with Direct Data-Independent Acquisition (dDIA)

  • 实验方案

  • 发表日期：

    2025年

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  • Ramón Díaz-Peña,
  • Pol Andrés-Benito,
  • Erica Peral,
  • Raúl Domínguez,
  • Mónica Povedano,
  • Enrique Santamaría,
  • Joaquín Fernández-Irigoyen

摘要

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).