Alzheimer’s disease (AD) represents the most common neurodegenerative disease. The first clinical symptom that usually brings an individual under clinical attention is the emergence of episodic memory pitfalls, which however occur when the underlying pathology has already reached a certain degree of spreading. In recent years, these neural alterations have been observed to largely overlap with known functional networks, especially the Default Mode (DMN) and the Frontoparietal (FPN) networks. However, much debate exists regarding whether functional alterations can be detected years before symptoms offset, i.e. that is in the prodromal disease stage of Mild Cognitive Impairment (MCI), and their predictive power of MCI-to-AD progression. In this study, we tried to fill this gap by investigating the relationship between topological networks’ alteration and the emergence of episodic memory difficulties at 2 years’ follow-up. We did so using a recently developed neuroimaging analytic tool, namely graph theory, and a specific battery of tests, assessing all stages of memory encoding, retrieval and recall in a sample of MCI patients and healthy controls. Our results suggest that increased DMN segregation might represent an early biomarker of cognitive worsening in episodic memory encoding. In particular, the study emphasizes that functional compensatory mechanisms in prefrontal nodes of the DMN might be a more prominent feature of the pathology at its prodromal stages, representing an early stressor. These findings might be potentially useful in the early detection of patients at higher risk of clinical progression and for whom resilience boosting interventions might still be put in place.
La malattia di Alzheimer (AD) rappresenta una delle malattie neurodegenerative più comuni. Il primo sintomo clinico che generalmente porta un soggetto sotto osservazione è l'emergere di errori di memoria episodica, che però accadono quando la patologia ha già raggiunto certo grado di diffusione. In anni recenti, è stato osservato che queste alterazioni neuronali presentano una certa sovrapposizione con networks cerebrali come il Default Mode Network (DMN) e il Network Frontoparietale (FPN). Tuttavia, non è chiaro se le alterazioni funzionali possano essere rilevate anni prima dell'emergere dei sintomi clinici, nella fase prodromica della malattia, il Mild Cognitive Impairment (MCI), e il loro potere predittivo di progressione da MCI ad AD. In questo studio, abbiamo tentato di risolvere questa lacuna investigando la relazione tra le alterazioni topologiche dei due network sopracitati e l'emergere di difficoltà di memoria episodica dopo 2 anni di follow-up. Pe fare ciò, abbiamo utilizzando uno strumento analitico di recente sviluppo, la graph theory, e una batteria di test specifica che valuta tutti le fasi della memoria (codifica, recupero e ricordo) in un campione di soggetti sani e pazienti MCI. I nostri risultati suggeriscono che un aumento nella segregazione del DMN potrebbe rappresentare un biomarker precoce di peggioramento cognitivo nella codifica di informazioni. In particolare, questo studio enfatizza anche il meccanismo compensatorio funzionale nei nodi prefrontal dello stesso network, i quali potrebbero rappresentare una caratteristica importante della patologia nella sua fase prodromica. Questi risultati potrebbero essere utili nel rilevamento precoce di pazienti ad alto rischio di progressione clinica e per i quali potrebbero ancora attuati interventi di recupero.
Brain topological alterations related to cognitive changes in Mild Cognitive Impairment and Alzheimer’s Disease
DEI CAS, LUCREZIA
2022/2023
Abstract
Alzheimer’s disease (AD) represents the most common neurodegenerative disease. The first clinical symptom that usually brings an individual under clinical attention is the emergence of episodic memory pitfalls, which however occur when the underlying pathology has already reached a certain degree of spreading. In recent years, these neural alterations have been observed to largely overlap with known functional networks, especially the Default Mode (DMN) and the Frontoparietal (FPN) networks. However, much debate exists regarding whether functional alterations can be detected years before symptoms offset, i.e. that is in the prodromal disease stage of Mild Cognitive Impairment (MCI), and their predictive power of MCI-to-AD progression. In this study, we tried to fill this gap by investigating the relationship between topological networks’ alteration and the emergence of episodic memory difficulties at 2 years’ follow-up. We did so using a recently developed neuroimaging analytic tool, namely graph theory, and a specific battery of tests, assessing all stages of memory encoding, retrieval and recall in a sample of MCI patients and healthy controls. Our results suggest that increased DMN segregation might represent an early biomarker of cognitive worsening in episodic memory encoding. In particular, the study emphasizes that functional compensatory mechanisms in prefrontal nodes of the DMN might be a more prominent feature of the pathology at its prodromal stages, representing an early stressor. These findings might be potentially useful in the early detection of patients at higher risk of clinical progression and for whom resilience boosting interventions might still be put in place.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/53959