Researchers combined mass spectrometry-based proteomic phenotyping with machine learning to identify blood biomarkers in early Parkinson's disease.
By Pooja Toshniwal PahariaReviewed by Danielle Ellis, B.Sc.Jun 20 2024 In a recent study published in Nature Communications, researchers combined mass spectrometry -based proteomic phenotyping with machine learning to identify blood biomarkers in early Parkinson's disease .
About the study In the present study, researchers developed a targeted multiplexed proteomic mass spectrometry assay to identify individuals at risk of Parkinson's disease. In Phase II, the researchers created a validated, high-throughput, multiplexed mass spectrometric targeted proteomic assay based on the putative biomarkers revealed during the discovery phase. In this phase, they also found significant protein differences between HC and de novo PD , OND, and prodromal isolated REM sleep behavior disorder groups.
Assay Central Nervous System Dopaminergic Heat Machine Learning Mass Spectrometry Molecule Nervous System Parkinson's Disease Protein Protein Expression Proteomics Serine Sleep Spectrometry Stress
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