Neurodegenerative diseases are a growing burden and there is an urgent need for better biomarkers for diagnosis, prognosis and treatment efficacy. Structural and functional brain alterations are reflected in the protein composition of cerebrospinal fluid (CSF). Alzheimer’s disease (AD) patients have higher CSF levels of tau, but we lack knowledge of systems-wide changes of CSF protein levels that accompany AD. Here we present a highly reproducible mass spectrometry (MS)-based proteomics workflow for the in-depth analysis of CSF from minimal sample amounts. From three independent studies (>200 individuals), we characterize differences in proteins by AD status (>1,000 proteins, CV<20%). Proteins with previous links to neurodegeneration such as tau, SOD1 and PARK7 differed most strongly by AD status, providing strong positive controls for our approach. CSF proteome changes in Alzheimer’s disease prove to be widespread and often correlated with tau concentrations. Our unbiased screen also reveals a consistent glycolytic signature across our and a recent report (bioRxiv.org doi.org/10.1101/806752). Successful reclassification of individual patients and a machine learning model suggests clinical utility of our proteomic signature.