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Multimodal diagnostic tools further improve the detection of PD. This review synthesizes advances in three key domains of PD detection. First, fluid and tissue biomarkers, particularly using \u03b1-synuclein (\u03b1Syn) seed amplification assays, allow detection of synucleinopathy in cerebrospinal fluid, blood, saliva, and skin. This supports pathological diagnosis and differential classification. Extracellular vesicles provide cell-type-specific cargo profiles, while neurofilament light chain indicates neuroaxonal injury. Second, neuroimaging captures in vivo pathology. MRI identifies nigral degeneration (nigrosome-1 loss, iron accumulation, neuromelanin depletion), MRS reveals metabolic and neurotransmitter imbalances, and \u03b1Syn positron emission tomography tracers enable direct visualization of aggregation. Third, digital biomarkers derived from wearable devices, videos, and audios quantify real-world motor and non-motor symptoms, enabling continuous, ecological monitoring. Integration of these complementary biomarker streams is essential for biological definition and stratification of PD patients, and development of targeted therapies. Standardization of assays, multicenter validations, and clear guidance on who should be tested, when testing is appropriate, and how results should inform diagnosis, stratification, or monitoring are required for the translation of these methods into clinical practice in PD.<\/jats:p>","DOI":"10.1186\/s40035-026-00558-0","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T06:53:22Z","timestamp":1779951202000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["From phenotype to biology: a multi-modal roadmap of biofluid, tissue, imaging, and digital biomarkers in Parkinson\u2019s disease"],"prefix":"10.1186","volume":"15","author":[{"given":"Zhenwei","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongning","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siming","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinuan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kang","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,28]]},"reference":[{"issue":"12","key":"558_CR1","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1002\/mds.26424","volume":"30","author":"RB Postuma","year":"2015","unstructured":"Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, et al. 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