Brain correlates of progressive olfactory loss in Parkinson's disease

Parkinsonism Relat Disord. 2017 Aug;41:44-50. doi: 10.1016/j.parkreldis.2017.05.005. Epub 2017 May 10.

Abstract

Background: Olfactory dysfunction is present in a large proportion of patients with Parkinson's disease (PD) upon diagnosis. However, its progression over time has been poorly investigated. The few available longitudinal studies lack control groups or MRI data.

Objective: To investigate the olfactory changes and their structural correlates in non-demented PD over a four-year follow-up.

Methods: We assessed olfactory function in a sample of 25 PD patients and 24 normal controls of similar age using the University of Pennsylvania Smell Identification test (UPSIT). Structural magnetic resonance imaging data, obtained with a 3-T Siemens Trio scanner, were analyzed using FreeSurfer software.

Results: Analysis of variance showed significant group (F = 53.882; P < 0.001) and time (F = 6.203; P = 0.016) effects, but the group-by-time interaction was not statistically significant. UPSIT performance declined ≥1.5 standard deviations in 5 controls and 7 patients. Change in UPSIT scores of patients correlated positively with volume change in the left putamen, right thalamus, and right caudate nucleus.

Conclusion: Olfactory loss over time in PD and controls is similar, but we have observed significant correlation between this loss and basal ganglia volumes only in patients.

Keywords: Longitudinal studies; Magnetic resonance imaging; Olfaction; Parkinson's disease.

MeSH terms

  • Aged
  • Brain / diagnostic imaging
  • Brain / pathology*
  • Case-Control Studies
  • Disease Progression
  • Female
  • Follow-Up Studies
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Male
  • Middle Aged
  • Neuropsychological Tests
  • Olfaction Disorders / diagnostic imaging
  • Olfaction Disorders / etiology*
  • Parkinson Disease / complications*
  • Parkinson Disease / pathology*
  • Retrospective Studies
  • Severity of Illness Index
  • Statistics as Topic