PurposeHere, we combined a longitudinal design to assess whole-brain hyper- and hypo-connectivity in the different clinical phases of Alzheimer's disease (AD) with a multimodal approach to understand how such connectivity changes were related to glucose hypometabolism.MethodsWe selected a longitudinal cohort of N = 66 subjects with clinical, cerebrospinal fluid and FDG-PET assessments, from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. N = 31 AD individuals were assessed at three stages: mild cognitive impairment (AD-MCI, T0), early phase of dementia (mild-AD, T1) and dementia (AD-D, T2). We included N = 35 age/sex-matched healthy controls. We assessed longitudinal metabolic connectivity using Pearson's correlation, clustering analysis and graph theory metrics.ResultsIn the MCI-AD stages, hypo- and hyper-connectivity coexisted. Data-driven, longitudinal clustering analysis identified specific pathological clusters: a default mode network cluster, with prevalent hypo-connectivity and severe, persistent hypometabolism; a limbic cluster showing hyper-connectivity and steeper metabolic decline. Metabolism in hyper-connected limbic regions showed a mediation effect on worsening of AD-like parieto-temporal hypometabolism and predicted faster conversion to dementia.ConclusionHypo- and hyper-connectivity, especially in early stages, may have different roles in AD neurodegenerative processes, with metabolism in hyper-connected regions acting as a mediator on the neurodegeneration of core regions of AD pathology.

Galli, A., Inglese, M., Presotto, L., Malito, R., Di, X., Toschi, N., et al. (2025). Glucose metabolism in hyper-connected regions predicts neurodegeneration and speed of conversion in Alzheimer’s disease. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 52(12), 4639-4651 [10.1007/s00259-025-07379-9].

Glucose metabolism in hyper-connected regions predicts neurodegeneration and speed of conversion in Alzheimer’s disease

Inglese M.;Toschi N.;
2025-01-01

Abstract

PurposeHere, we combined a longitudinal design to assess whole-brain hyper- and hypo-connectivity in the different clinical phases of Alzheimer's disease (AD) with a multimodal approach to understand how such connectivity changes were related to glucose hypometabolism.MethodsWe selected a longitudinal cohort of N = 66 subjects with clinical, cerebrospinal fluid and FDG-PET assessments, from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. N = 31 AD individuals were assessed at three stages: mild cognitive impairment (AD-MCI, T0), early phase of dementia (mild-AD, T1) and dementia (AD-D, T2). We included N = 35 age/sex-matched healthy controls. We assessed longitudinal metabolic connectivity using Pearson's correlation, clustering analysis and graph theory metrics.ResultsIn the MCI-AD stages, hypo- and hyper-connectivity coexisted. Data-driven, longitudinal clustering analysis identified specific pathological clusters: a default mode network cluster, with prevalent hypo-connectivity and severe, persistent hypometabolism; a limbic cluster showing hyper-connectivity and steeper metabolic decline. Metabolism in hyper-connected limbic regions showed a mediation effect on worsening of AD-like parieto-temporal hypometabolism and predicted faster conversion to dementia.ConclusionHypo- and hyper-connectivity, especially in early stages, may have different roles in AD neurodegenerative processes, with metabolism in hyper-connected regions acting as a mediator on the neurodegeneration of core regions of AD pathology.
2025
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore PHYS-06/A - Fisica per le scienze della vita, l'ambiente e i beni culturali
Settore IBIO-01/A - Bioingegneria
English
Glucose metabolism
Graph theory
Hyper-connectivity
Hypo-connectivity
Mild cognitive impairment
Prodromal
Galli, A., Inglese, M., Presotto, L., Malito, R., Di, X., Toschi, N., et al. (2025). Glucose metabolism in hyper-connected regions predicts neurodegeneration and speed of conversion in Alzheimer’s disease. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 52(12), 4639-4651 [10.1007/s00259-025-07379-9].
Galli, A; Inglese, M; Presotto, L; Malito, R; Di, X; Toschi, N; Pilotto, A; Padovani, A; Tassorelli, C; Perani, D; Sala, A; Caminiti, Sp
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/437030
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