{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T23:11:21Z","timestamp":1791501081625,"version":"4.3.4"},"reference-count":36,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JPD"],"published-print":{"date-parts":[[2022,5,24]]},"abstract":"<jats:p>Background: While cutoffs for abnormal levels of the cerebrospinal fluid (CSF) biomarkers amyloid-\u03b2 1-42 (A\u03b2142), total tau (t-tau), phosphorylated tau (p-tau), and the ratios of t-tau\/A\u03b2142 and p-tau\/A\u03b2142, have been established in Alzheimer\u2019s disease (AD), biologically relevant cutoffs have not been studied extensively in Parkinson\u2019s disease (PD). Objective: Assess the suitability and diagnostic accuracy of established AD-derived CSF biomarker cutoffs in the PD population. Methods: Baseline and longitudinal data on CSF biomarkers, cognitive diagnoses, and PET amyloid imaging in 423 newly diagnosed patients with PD from the Parkinson\u2019s Progression Markers Initiative (PPMI) cohort were used to evaluate established AD biomarker cutoffs compared with optimal cutoffs derived from the PPMI cohort. Results: Using PET amyloid imaging as the gold standard for AD pathology, the optimal cutoff of A\u03b2142 was higher than the AD cutoff, the optimal cutoffs of t-tau\/A\u03b2142 and p-tau\/A\u03b2142 were lower than the AD cutoffs, and their confidence intervals (CIs) did not overlap with the AD cutoffs. Optimal cutoffs for t-tau and p-tau to predict cognitive impairment were significantly lower than the AD cutoffs, and their CIs did not overlap with the AD cutoffs. Conclusion: Optimal cutoffs for the PPMI cohort for A\u03b2142, t-tau\/A\u03b2142, and p-tau\/A\u03b2142 to predict amyloid-PET positivity and for t-tau and p-tau to predict cognitive impairment differ significantly from cutoffs derived from AD populations. The presence of additional pathologies such as alpha-synuclein in PD may lead to disease-specific CSF biomarker characteristics.<\/jats:p>","DOI":"10.3233\/jpd-212989","type":"journal-article","created":{"date-parts":[[2022,4,15]],"date-time":"2022-04-15T10:54:26Z","timestamp":1650020066000},"page":"1155-1167","source":"Crossref","is-referenced-by-count":29,"title":["Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer\u2019s Disease to Parkinson\u2019s Disease"],"prefix":"10.1177","volume":"12","author":[{"given":"Sarah","family":"Weinshel","sequence":"first","affiliation":[{"name":"Swarthmore College, Swarthmore, PA, USA"},{"name":"Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David J.","family":"Irwin","sequence":"additional","affiliation":[{"name":"Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panpan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Weintraub","sequence":"additional","affiliation":[{"name":"Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA"},{"name":"Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA"},{"name":"Michael J. 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