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Abstract: parkinson's disease (PD) is the second most common neurodegenerative disorder, and continues to present significant challenges in early diagnosis, precise subtyping, and prognosis assessment. In recent years, the field of biomarker research has undergone a profound paradigm shift from static concentration measurements to functional activity detection. The most revolutionary breakthrough is the α-synuclein seed amplification assay (α-Syn-SAA), which enables ultrasensitive and specific detection of pathological α-Syn in both clinical and prodromal stages, thus providing an unprecedented window for early intervention. Substantial progress has also been made in the development of biomarkers such as neurofilament light chain (NfL), Alzheimer's disease-related biomarkers, genetic biomarkers, and detection technologies based on peripheral samples. The integrated application of cutting-edge technologies, such as RT-QuIC, high-resolution mass spectrometry, and high-field magnetic resonance imaging (MRI), is advancing the field into a new stage characterized by a focus on pathological activity, multi-omics integration, and non- or minimally invasive approaches. In this review, we explore recent advances in PD biomarkers, focusing on core pathophysiological markers. We examine the potential of multi-omics and artificial intelligence (AI) to enhance diagnostic, subtyping, and prognostic accuracy, while also outlining the pivotal role and future directions of biomarkers in advancing PD precision medicine.