Development of a simplified smell test to identify Parkinson’s disease using multiple cohorts, machine learning and item response theory

By Juan Li, PhD, Kelsey Grimes, MSc, Joseph Saade, Julianna Tomlinson, PhD, Tiago Mestre, Sebastian Schade, Sandrina Weber, Mohammed Dakna, Tamara Wicke, Elisabeth Lang, Claudia Trenkwalder, Natalina Salmaso, PhD, Andrew Frank, Tim Ramsay, Douglas Manuel, Brit Mollenhauer , MD and Michael Schlossmacher, MD
Published April 23, 2025
View Published Article

Output Details

Published April 23, 2025

Description
To develop a simplified smell test for identifying patients with Parkinson’s disease (PD), we reevaluated the Sniffin’-Sticks-Identification-Test (SST-ID) and University-of-Pennsylvania-Smell-Identification-Test (UPSIT), using three case-control studies. These included 301 patients with PD or dementia with Lewy bodies (DLB), 68 subjects with multiple-system atrophy (MSA) or progressive supranuclear palsy (PSP), and 281 healthy controls (HC). Scents were ranked by area-under-the-curve values for group classification and results leveraged by 8 published studies with 5853 individuals. PD/DLB patients showed markedly worse olfaction than controls, whereas scores for MSA/PSP subjects were intermediate. We identified and validated a subset of 7 shared odorants that performed similarly to the traditional 16-scent SST-ID and 40-scent UPSIT tests in distinguishing PD/DLB from HC. There, the identification of 4 or fewer scents out of 7 served as an effective cut-off between the two groups. We also identified a critical role for distractors (from correct answers) and age on olfaction performance.
Identifier (DOI)
10.1038/s41531-025-00904-5
Tags
  • Olfaction
  • Olfactory dysfunction
  • Original Research
  • Parkinson's disease
  • Parkinsonism
  • Prodromal PD
Team
Team Schlossmacher
Program
Collaborative Research Network
Theme
Circuitry and Brain-Body Interactions

Meet the Authors

Related Research

Dataset for: Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation

Clinical dataset relating to analysis of olfaction from multiple Parkinson disease cohorts. Olfactory performance was analyzed to create a simplified smell test as a screening tool for Parkinson disease and other forms of parkinsonism.

View Dataset

Code for analysis of smell test dataset included in: Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation

Code used for the analysis of smell test performance as reported in "Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation", Li et al., 2024

View Code

Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation

Reduced olfaction is a common feature of typical Parkinson disease (PD) and dementia with Lewy bodies (DLB). We have created a simplified smell test based on seven specific odorants that can distinguish PD/DLB patients from healthy controls.

View Article
View More Outputs