Diffuse gliomas (grades II-IV) are the most frequent and devastating primary brain tumours of adults. Currently, the clinical management for glioma patients involves a tissue biopsy for diagnostics and routine neuro-radiographic assessments, both of which have major limitations for accurate clinical assessment. With efforts to improve the clinical management of glioma, comes a growing trend to design minimally-invasive liquid biopsies (i.e. blood tests) that can routinely measure glioma-derived molecules in body fluids and allow for tumour evolution to be assessed in real-time. In this regard, extracellular vesicles (EVs; 30-1000 nm membranous particles) hold major promise as biomarker reservoirs. EVs encapsulate molecules that reflect the identity and molecular state of their cell-of-origin and their release is upregulated in neoplasia. EVs also cross the blood-brain-barrier into the circulation where they are stable and readily accessible. Despite their suitability as biomarkers, in-depth proteomic characterisation of circulating-EVs by traditional shot-gun proteomics has been hindered by the complexity of the blood and the co-isolation of highly abundant blood proteins. In this study, a data-independent acquisition (DIA) proteomics platform, sequential window acquisition of all theoretical fragment ion spectra (SWATH), was used in conjunction with a targeted data extraction strategy to achieve in-depth protein profiles of circulating-EVs from glioma patients. EVs were isolated by size exclusion chromatography from the plasma of pre-operative glioma II-IV patients and controls. Nanoparticle tracking and transmission electron microscopy confirmed the isolation of small-EV subtypes (< 200 nm). The plasma-EV peptides were sequenced by SWATH-MS, and the identities and quantities of the proteins were extracted using a custom spectral library comprised of 8662-protein species, developed using peptide samples from a range of glioma specimens, including cell lysates, tumour tissues and EVs. A total of 4054 proteins were identified in the plasma-EVs of all sample groups. Of these proteins, 463 changed significantly across the glioma and non-glioma cohorts (adj. p < 0.05), and included proteins previously reported to have significance in glioma-EVs. Principal component analysis showed excellent discrimination between the patient groups, with samples observed to cluster with their respective glioma subtype/grade. Using SWATH mass spectrometry we describe the most comprehensive proteomic plasma-EV profiles for glioma reported to-date, for which future studies using larger longitudinal cohorts could define a set of circulating-EV biomarkers, capable of stratifying glioma patients and detecting recurrence, progression and treatment resistance.