MRI Clustering Reveals Three ALS Subtypes With Unique Neurodegeneration Patterns

Area of Science:

• Neuroscience
• Neurology
• Radiology

Background:

• Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease.
• Understanding ALS subtypes is crucial for targeted therapies and improved patient outcomes.

Purpose of the Study:

• To identify distinct subtypes of amyotrophic lateral sclerosis (ALS) using brain magnetic resonance imaging (MRI).
• To explore the unique clinical and cognitive phenotypes associated with each identified ALS subtype.

Main Methods:

• Utilized T1-weighted and diffusion tensor imaging in 488 ALS patients and 338 controls.
• Applied a network-based clustering algorithm to MRI data to define neurodegeneration patterns.
• Assessed clinical characteristics, cognitive profiles, and longitudinal stability of identified subgroups.

Main Results:

• Identified three ALS subgroups based on neurodegeneration patterns: pure motor (PM), frontotemporal (FT), and cingulate-parietal-temporal (CPT).
• Subgroups exhibited significant differences in sex ratio, age at onset, bulbar symptoms, and cognitive impairment rates (FT and CPT showed higher impairment).
• Clustering remained stable longitudinally, with 90.4% of patients consistently belonging to their baseline subgroup.

Conclusions:

• ALS manifests in three primary cerebral neurodegeneration patterns, each linked to specific clinical and cognitive characteristics.
• A novel neuroimaging phenotype involving posterior cingulate, parietal, temporal, and cerebellar regions was identified.
• These findings support distinct neuroimaging-based subtypes of ALS, including pure motor, FTD-like, and a newly described pattern.