Here, we applied our workflow to discover proteome changes in the CSF of PD patients with or without the disease-associated G2019S mutation in LRRK2. To maximize proteome depth and coverage, we generated cohort-specific hybrid spectral libraries by merging three sub-libraries: (1) a library constructed by data-dependent acquisition (DDA) consisting of 24 fractions of pooled CSF samples; (2) another DDA library consisting of eight fractions of extracellular vesicles enriched from pooled CSF samples; and (3) a direct-DIA library generated from the DIA analysis of all samples (see STAR Methods). This evidence concerns the gene LRRK2 and Parkinson disease.