Abstract
Background There is considerable interest in identifying peripheral biomarkers that reflect neuropathological changes in schizophrenia. Extracellular vesicles, including exosomes can cross the blood brain barrier with their contents intact and their cargo, including lipids, proteins and genetic materials can be assayed peripherally. Circulating exosomes have been studied in other neurodegenerative disorders, but there is scarce data in schizophrenia.
Methods We examined neuropathology relevant protein biomarkers in circulating exosomes from patients with schizophrenia and age and gender matched healthy controls using methods consistent with the recommended “Minimal information for studies of extracellular vesicles 2018” (MISEV2018) guidelines. Nanoparticle tracking analysis was used to determine the size and concentration of exosomes. Exosomal membrane marker (CD9) and specific target cargo proteins (glial fibrillary acid protein[GFAP], synaptophysin and α-II-spectrin) immunopositivity was examined using Western blot analyses and band intensity quantified.
Results No group differences were observed between schizophrenia and control samples in plasma exosomal concentration and size or in CD9 or calnexin positivity. Exosomal GFAP concentration was significantly higher and α-II-spectrin expression significantly lower in schizophrenia samples and there were no group differences observed for exosomal synaptophysin concentration.
Conclusions Our results demonstrate for the first time, a differential pattern of exosomal protein expression in schizophrenia compared to matched healthy controls, consistent with the hypothesized astro-glial pathology in this disorder. These results warrant further examination of circulating exosomes as vehicles of novel peripheral biomarkers of disease in schizophrenia and other neuropsychiatric disorders.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵# Joint second authors
To include results of protein quantification from western blots and correlations with clinical variables.