Blood is a rich source of protein biomarkers. However, it is one of the most analytically challenging matrices due to its high compound complexity. This complexity can be reduced by separation of cellular elements [e.g. red blood cells (RBCs), peripheral monocytes] from plasma. Many biomarker assays and studies have been conducted on plasma (or serum), but not on RBCs. Alpha-synuclein (SNCA), a known neuropathological biomarker of Parkinson’s disease, is an abundant RBC protein. Therefore, RBCs may provide a valid avenue for proteomics and the study of neurodegenerative diseases. However, proteomics analysis of RBCs still represents an analytical challenge, especially due to the large dynamic range and the high abundance of lipids. To determine the most efficient way to extract the RBC proteome, we evaluated six different trypsin digestion methods, namely (1) Urea, (2) Acetone followed by Urea, (3) Sodium deoxycholate (4) Acetone followed by sodium deoxycholate, (5) Acetonitrile and (6) Acetone followed by acetonitrile. We further established a standard curve of 15N-labelled α-synuclein to quantify endogenous α-synuclein, and also screened the RBC proteome for other neuropathological biomarkers. After RBC protein extraction and the tryptic digest, lysates were analyzed on an Agilent 6495 QQQ instrument in dynamic MRM mode, injecting 3μg and 10μg of total protein. The results show that RBC protein extraction with sodium deoxycholate gives the best proteome coverage with the highest peptide signal intensities when 3μg of total protein is injected. Extraction with acetonitrile is the 2nd best method, partially enriching a different set of peptides. Here, the 10μg injection gave the best results. Besides endogenous alpha-synuclein, protein deglycase DJ-1 (PARK7) and superoxide dismutase (SOD1) were also identified in RBC, all playing pivotal roles in neurodegenerative diseases. These results highlight the potential of RBCs for neuroproteomics.