DAT-SPECT profiling for biological definition of two prospective Parkinson’s disease cohorts

Background

There is a need for simplified classification systems capable of effectively stratifying Parkinson’s disease (PD) in routine clinical practice.

Objectives

Identification of PD subtypes integrating neuroimaging and clinical features, widely used to support clinical diagnosis.

Methods

We included, from Parkinson’s Progression Markers Initiative (PPMI), 249 de novo early diagnosed PD patients. Two step clustering analysis was run on ¹²³ I-FP-CIT-SPECT striatal uptake [D+/D] and motor impairment [M+/M]. The emerging subgroups were evaluated for demographic, clinical, cerebrospinal fluid biomarkers, brain morphometry and longitudinal clinical progression. Mediation analysis evaluated the effect of biomarkers on the relationship between subgroups and cognitive decline. We validated the proposed classification algorithm through an independent validation cohort (n=84).

Results

Four distinct subtypes emerged: [D+/M+]: poorer memory performance, greater Aβ _1-42 and α-synuclein pathology and atrophy in the inferior temporo-occipital cortex. At follow-up D+/M+ showed faster progression of motor disability, motor complications and cognitive decline. [D/M]: higher levels of anxiety and gray matter volume reductions in the precuneus, fusiform gyrus and the precentral gyrus. [D/M+]: marked by pronounced rigidity and apathy, atrophy in motor and sensorimotor areas, and a more rapid progression of rigidity. [D+/M]: severe impulsiveness, lower working memory performance and thalamic atrophy.

Aβ _1-42 showed significant mediational effect on the relationship between D+/M+ and cognitive decline.

The validation cohort supported the clinical findings observed in the PPMI cohort.

Conclusions

PD can be categorized into distinct subgroups using information widely available in clinical and research settings. These data offer valuable insights into the underlying co-pathology, disease progression and severity.