Aims: This study aimed to characterize the topological changes in glucose metabolism covariance networks in amyotrophic lateral sclerosis (ALS). Methods: We assessed the interregional coordination of 18F-FDG-PET data to examine topological alterations in individualized glucose metabolism covariance networks in 127 ALS patients compared to 128 healthy controls (HC). Results: Compared to HC, ALS patients showed reduced small-worldness (lower normalized clustering coefficient, higher normalized characteristic path length) and decreased global and local efficiency, suggesting impaired global integration and local segregation. These network metrics correlated with disease progression and motor function. Regionally, altered degree centrality affected motor and default mode networks, and related to GABAa and mGluR5 receptor expression. Transcriptomic associations further linked these changes to immune function, synaptic signaling, and protein regulation. Bidirectional shifts in connectivity strength were observed, with both increased connectivity and disease progression independently predicting reduced survival. Conclusion: Our findings may provide valuable biomarkers for monitoring the progression of ALS and suggest potential mechanistic pathways for the development of innovative therapeutic strategies for this disorder.

Disrupted Glucose Metabolism Covariance Network in Amyotrophic Lateral Sclerosis

Grecucci, Alessandro;
2025-01-01

Abstract

Aims: This study aimed to characterize the topological changes in glucose metabolism covariance networks in amyotrophic lateral sclerosis (ALS). Methods: We assessed the interregional coordination of 18F-FDG-PET data to examine topological alterations in individualized glucose metabolism covariance networks in 127 ALS patients compared to 128 healthy controls (HC). Results: Compared to HC, ALS patients showed reduced small-worldness (lower normalized clustering coefficient, higher normalized characteristic path length) and decreased global and local efficiency, suggesting impaired global integration and local segregation. These network metrics correlated with disease progression and motor function. Regionally, altered degree centrality affected motor and default mode networks, and related to GABAa and mGluR5 receptor expression. Transcriptomic associations further linked these changes to immune function, synaptic signaling, and protein regulation. Bidirectional shifts in connectivity strength were observed, with both increased connectivity and disease progression independently predicting reduced survival. Conclusion: Our findings may provide valuable biomarkers for monitoring the progression of ALS and suggest potential mechanistic pathways for the development of innovative therapeutic strategies for this disorder.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/552976
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