Abstract
There is evidence that gray matter networks are disrupted in Mild Cognitive Impairment (MCI) and associated with cognitive impairment and faster disease progression. However, it remains unknown how these alterations are related to the presence of Apolipoprotein E isoform E4 (ApoE4), the most prominent genetic risk factor for late-onset Alzheimer’s disease (AD). To investigate this topic at the individual level, we explore the impact of ApoE4 and the disease progression on the Single-Subject Gray Matter Networks (SSGMNets) using the graph theory approach. Our data sample comprised 200 MCI patients selected from the ADNI database, classified as non-Converters and Converters (will progress into AD). Each group included 50 ApoE4-positive (‘Carriers', ApoE4 + ) and 50 ApoE4-negative ('non-Carriers', ApoE4-). The SSGMNets were estimated from structural MRIs at two-time points: baseline and conversion. We investigated whether altered network topological measures at baseline and their rate of change (RoC) between baseline and conversion time points were associated with ApoE4 and disease progression. We also explored the correlation of SSGMNets attributes with general cognition score (MMSE), memory (ADNI-MEM), and CSF-derived biomarkers of AD (Aβ42, T-tau, and P-tau). Our results showed that ApoE4 and the disease progression modulated the global topological network properties independently but not in their RoC. MCI converters showed a lower clustering index in several regions associated with neurodegeneration in AD. The SSGMNets' topological organization was revealed to be able to predict cognitive and memory measures. The findings presented here suggest that SSGMNets could indeed be used to identify MCI ApoE4 Carriers with a high risk for AD progression.
Highlights
Late-Onset Alzheimer’s Disease (LOAD) is the most common cause of dementia, accounting for 60% to 80% of cases (Hardy, 1997)
We found a good/excellent reproducibility for all SSGMNets global network attributes with Intraclass correlation measure (ICC) > 0.8
The main results of this research can be summarized as follows: 1) At baseline the Apolipoprotein E isoform E4 (ApoE4) and the future pro gression to Alzheimer’s disease (AD) status modulate topological network properties differ ently; 2) the Rate of Change (RoC) of characteristic path length and Clux-Normalized were affected by ApoE4 and disease progression status interaction; 3) The Clux-Normalized values were lower in Mild Cognitive Impairment (MCI) who will progress into AD compared to those who will not; 4) CluxNormalized decreased in several regions belonging to the Default Mode Network (DMN) in MCI Converters respect to non-Converters; 5) ApoE4 and disease progression affect the association between specific topological network features and CSF Aβ42; and MMSE variables
Summary
Late-Onset Alzheimer’s Disease (LOAD) is the most common cause of dementia, accounting for 60% to 80% of cases (Hardy, 1997). There are currently no disease-modifying treatments and clinical drug trials have a high failure rate (Cummings et al, 2014). The postulate for this result is that AD brain pathology begins years before the cognitive decline. In recent years, research has moved toward the study of the earliest clinical signs of neurodegeneration that are likely to evolve to AD In this effort, a particular interest has been dedicated to Mild Cognitive Impairment (MCI) as a transitional phase between the cognitive changes associated with aging and early AD (Petersen, 2004; Petersen et al, 2001). It is a window in which it may be possible to intervene and modulate the disease progression (Albert et al, 2011; Gauthier et al, 2006; Mueller et al, 2005; Petersen et al, 1999)
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