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Reliable progression models are essential for clinical decision-making and trial design in Parkinson’s disease. We discuss linear, exponential, and sigmoidal patterns in PET and SPECT data, emphasizing the mismatch between biomarker and clinical trajectories. We propose more adaptable modeling strategies to improve patient stratification, support trial outcomes, and align imaging biomarkers with real-world disease complexity.
Carbon monoxide (CO) produced during smoking has been proposed to be a protective factor for Parkinson’s disease (PD). In rats, increasing CO levels have recently been shown to induce hypoxic response-like pathway activation. Smoking thus may strengthen the hypoxia response systems by challenging the oxygen transport system, resulting in increased cellular resilience. Here we outline the overlaps between two novel promising approaches against PD, low-dose CO inhalations and hypoxia conditioning.
We applied biologic criteria and NSD-ISS to Synuclein Sampling Study, a PD sample with range of durations since clinical diagnosis. 93% of evaluable participants met biologic criteria. The majority were NSD-ISS stage3 or less, including >40% of the advanced PD group. Interpretation of staging in medicated patients is challenging. Biologic criteria and clinico-biomarker staging are important steps forward, but quantitative biomarkers of disease progression, not influenced by medications, are critically needed.
