Identification and Validation of N-Acetylputrescine in Combination With Non-Canonical Clinical Features As a Parkinson’s Disease Biomarker Panel

Abstract Parkinson’s disease is a progressive neurodegenerative disorder in which loss of dopaminergic neurons in the substantia nigra results in a clinically heterogeneous group with variable motor and non-motor symptoms with a degree of misdiagnosis. Only 3-5% of sporadic Parkinson’s patients present with genetic abnormalities, thus environmental, metabolic, and other unknown causes contribute to the pathogenesis of Parkinson’s disease, which highlights the critical need for biomarkers. There could be a significant clinical benefit to treating Parkinson’s disease at the earliest stage and identify at-risk populations once disease-modifying treatments are available. In the present study, we prospectively collected and analyzed plasma samples from 201 Parkinson’s disease patients and 199 age-matched non-diseased controls. Multiomic and Bayesian artificial intelligence analysis of molecular and clinical data identified the diagnostic utility of N-acetyl putrescine (NAP) in combination with smell (B-SIT), depression/anxiety (HADS), and acting out dreams (RBD1Q) clinical measurements. The clinical and biomarker panel demonstrated an area under the curve, AUC = 0.9, positive predictive value, PPV = 0.91, and negative predictive value, NPV = 0.66 utilizing all four variables. The assessed diagnostic panel demonstrates combinatorial utility in diagnosing Parkinson’s disease, allowing for an integrated interpretation of disease pathophysiology and highlighting the use of multi-tiered panels in neurological disease diagnosis.