Extracellular vesicle protein levels are related to brain atrophy and cerebral white matter lesions in patients with manifest vascular disease: the SMART-MR study

OBJECTIVES: Extracellular vesicles (EVs) and their protein levels have been identified as a potential risk marker for the development of vascular disease. In the present study, we assessed whether levels of four previously identified EV proteins (cystatin C, serpin G1, serpin F2 and CD14) are associated with cerebral white matter lesions (WMLs) and brain atrophy. DESIGN: Cohort study; cross-sectional and prospective. SETTING: Single centre, secondary and tertiary setting. PARTICIPANTS: 1309 patients with manifest vascular disease from the Second Manifestations of ARTerial disease-MR (SMART-MR) study, of which 994 had successful brain MRI and EV protein level measurements. OUTCOMES: WML and brain parenchymal fraction (BPF), as parameter for brain atrophy, at baseline and follow-up. STATISTICAL METHODS: The relationship between EV protein levels and WML volume (expressed as log transformed percentage of intracranial volume) and BPF (expressed percentage of intracranial volume) on 1.5 T brain MRI was assessed with multivariable linear regression modelling. Subsequently, the relationship between baseline EV protein levels and progression of atrophy and WML was analysed in 534 patients, in whom a follow-up MRI was obtained after 4 years. RESULTS: Higher EV-cystatin C and EV-CD14 were significantly associated with larger WML volume (linear regression coefficient (95% CI) 0.10 log %/SD (0.04 to 0.17) and 0.14 log %/SD (0.07 to 0.20), respectively. Higher EV-CD14 was associated with more brain atrophy (–0.14%/SD; –0.27 to –0.01). Baseline EV-CD14 was significantly associated with increase of WMLs (0.11 log %/SD (0.04 to 0.18)). No relationship with EV-serpins was observed at baseline or at follow-up. CONCLUSIONS: EV proteins cystatin C and CD14 are related to cerebral WMLs and the progression of brain atrophy in patients with manifest vascular disease, potentially identifying EVs in the aetiology of structural brain changes.