BACKGROUND AND OBJECTIVES

The ALS diagnosis requires an integrative approach, combining the clinical examination and supporting tests. Nevertheless, in several cases, the diagnosis proves to be suboptimal, and for this reason, new diagnostic methods and novel biomarkers are catching on. The F-fluorodeoxyglucose (F-FDG)-PET could be a helpful method, but it still requires additional research for sensitivity and specificity. We performed an F-FDG-PET single-subject analysis in a sample of familial ALS patients carrying different gene mutations, investigating the genotype-phenotype correlations and exploring metabolism correlations with clinical and neuropsychological data.

METHODS

We included ten ALS patients with pathogenic gene mutation who underwent a complete clinical and neuropsychological evaluation and an F-FDG-PET scan at baseline. Patients were recruited between 2018 and 2022 at the ALS Tertiary Centre in Novara, Italy. Patients were selected based on the presence of ALS gene mutation (C9orf72, SOD1, TBK1, and KIF5A). Following a validated voxel-based Statistical Parametric Mapping (SPM) procedure, we obtained hypometabolism maps at single-subject level. We extracted regional hypometabolism from the SPM maps, grouping significant hypometabolism regions into three meta-ROIs (motor, prefrontal association and limbic). Then, the corresponding F-FDG-PET regional hypometabolism was correlated with clinical and neuropsychological features.

RESULTS

Classifying the patients with C9orf72-ALS based on the rate of disease progression from symptoms onset to the time of scan, we observed two different patterns of brain hypometabolism: an extensive motor and prefrontal hypometabolism in patients classified as fast progressors, and a more limited brain hypometabolism in patients grouped as slow progressors. Patients with SOD1-ALS showed a hypometabolic pattern involving the motor cortex and prefrontal association regions, with a minor involvement of the limbic regions. The patient with TBK1-ALS showed an extended hypometabolism, in limbic systems, along with typical motor involvement, while the hypometabolism in the patient with KIF5A-ALS involved almost exclusively the motor regions, supporting the predominantly motor impairment linked to this gene mutation. Additionally, we observed strong correlations between the hypometabolism in the motor, prefrontal association and limbic meta-ROI and the specific neuropsychological performances.

CONCLUSIONS

To our knowledge, this is the first study investigating brain hypometabolism at the single-subject level in genetic ALS patients carrying different mutations. Our results show high heterogeneity in the hypometabolism maps and some commonalities in groups sharing the same mutation. Specifically, in patients with C9orf72-ALS the brain hypometabolism was larger in patients classified as fast progressors than slow progressors. In addition, in the whole group, the brain metabolism showed specific correlations with clinical and neuropsychological impairment, confirming the ability of F-FDG-PET in revealing pattern of neuronal dysfunction, aiding the diagnostic workup in genetic ALS patients.