DAT-SPECT-based subtype and stage inference in Parkinson's disease

Area of Science:

• Neuroscience
• Radiology
• Neurology

Background:

• Parkinson's disease (PD) presents with heterogeneous nigrostriatal degeneration, complicating patient prognosis and treatment.
• Accurate characterization of degeneration patterns is crucial for understanding PD progression.

Purpose of the Study:

• To apply the Subtype and Stage Inference (SuStaIn) algorithm to dopamine transporter single-photon emission computed tomography (DAT-SPECT) data to identify distinct patterns of nigrostriatal degeneration in Parkinson's disease.
• To evaluate the longitudinal stability and clinical relevance of identified degeneration subtypes.

Main Methods:

• Analysis of DAT-SPECT data from 636 drug-naive sporadic Parkinson's disease patients and 126 healthy controls using atlas-based 12-region segmentation.
• Application of the SuStaIn algorithm to multi-regional DAT-SPECT data acquired at baseline and at 1, 2, and 4 years post-baseline.
• Correlation of identified subtypes with baseline clinical characteristics (age, cognitive/psychiatric burden, CSF α-synuclein seeding) and longitudinal treatment response (motor symptoms, depression, anxiety, impulsive-compulsive behaviors).

Main Results:

• SuStaIn identified three reproducible and longitudinally stable subtypes of nigrostriatal dopaminergic degeneration: S1 (left posterior putamen), S2 (right posterior putamen), and S3 (bilateral caudate).
• At baseline, S3 patients were older, had higher cognitive and psychiatric burden, and lower CSF α-synuclein seeding positivity compared to other subtypes.
• Longitudinally, S1 and S2 showed greater motor symptom improvement with treatment initiation than S3. Depression and anxiety worsened more in S2, while S3 exhibited increased impulsive-compulsive behaviors.

Conclusions:

• DAT-SPECT-based SuStaIn successfully reconstructs biologically plausible patterns of dopaminergic progression in Parkinson's disease.
• The identified subtypes possess short-term prognostic relevance, differentiating patients based on baseline characteristics and response to treatment.
• This approach offers a valuable tool for stratifying Parkinson's disease patients and tailoring therapeutic strategies.