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Updated: Jun 19, 2026

Olfactory Assays for Mouse Models of Neurodegenerative Disease
Published on: August 25, 2014
Evaluation of idiopathic olfactory dysfunction as a warning marker for early parkinson's disease: a population-based
Zahra Vedadi1, Elaheh Ebrahimi Miandehi2, Masoumeh Akbari2
1Department of Pharmacodynamics and Toxicology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran.
Abstract:
This study investigates clinically idiopathic olfactory disorder (IOD) as a potential early marker for Parkinson's disease (PD), using a two-stage screening approach to identify at-risk individuals and enable timely interventions. 1,044 participants aged 18 and older were screened using the Iran Rapid Smell Identification Test (Rapid IR-SIT). After excluding 343 individuals with known causes of OD, 701 participants were assessed for PD risk factors, following the Movement Disorder Society (MDS) guidelines (2015 version). The participants had a mean age of 45.6 years, with 51.3% male participants. While 59.8% scored 6 on the smell test, 25% of those over 50 exhibited IOD, compared to less than 10% in younger individuals. Lower olfactory scores were significantly associated with current smoking (p = 0.001), male sex (p = 0.022), regular pesticide exposure (p = 0.010), non-caffeine use (p = 0.021), and constipation (p = 0.004). Using an 80% probability threshold for prodromal PD, one participant met the criteria, leading to a confirmed early-stage PD diagnosis. These findings highlight the potential of a two-stage screening approach-starting with olfactory testing followed by MDS-based risk assessment - to identify individuals at risk of PD. Although the yield of prodromal cases was low (1/701), this likely reflects stringent IOD criteria and the study's cross-sectional design. The identification of a prodromal PD case underscores the value of olfactory testing in risk stratification, particularly in resource-limited settings. Future longitudinal studies are needed to validate these findings and refine the predictive accuracy of this approach.
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