Parkinson's disease (PD), the second most common progressive neurodegenerative disease, develops and progresses for 10-15 years before the clinical diagnostic symptoms of the disease are manifested. Furthermore, several aspects of PD pathology overlap with other neurodegenerative diseases (NDDs) linked to alpha-synuclein aggregation, also called synucleinopathies. Therefore, there is an urgent need to discover and validate early diagnostic and prognostic markers that reflect disease pathophysiology, progression, severity, and potential differences in disease mechanisms between PD and other NDDs. The close association between alpha-synuclein (aSyn) and the development of pathology in synucleinopathies, along with the identification of aSyn species in biological fluids, has led to increasing interest in aSyn species as potential biomarkers to detect PD and differentiate it from other synucleinopathies. In this review, we 1) provide an overview of the progress toward mapping the distribution of aSyn species in the brain, peripheral tissues, and biological fluids; 2) present comparative and critical analysis of previous studies to measure total aSyn as well as specific forms of monomeric, modified and aggregated forms of aSyn in different biological fluids; and 3) highlight conceptual and technical gaps and challenges that could hinder the development and validation of reliable aSyn biomarkers and outline a series of recommendations to address these challenges. Finally, we propose a combined biomarker approach based on integrating total aSyn levels with specific biomarkers based on the biochemical features (posttranslational modifications), aggregation and structure of aSyn, in addition to other biomarkers of neurodegeneration. We believe that capturing the diversity of aSyn species is essential to developing robust assays and diagnostics for early detection, patient stratification, monitoring of disease progression, and differentiation between synucleinopathy subtypes. This could transform clinical trial design and implementation, accelerate the development of new therapies, and improve clinical decisions and treatment strategies.