Amyloid‐β and tau pathologies relate to distinctive brain dysconnectomics in autosomal‐dominant Alzheimer's disease. (December 2021)

• Record Type: Journal Article
• Authors: Guzman‐Velez, Edmarie; Diez, Ibai Palacio; Schoemaker, Dorothee; Pardilla‐Delgado, Enmanuelle; Fox‐Fuller, Joshua T.; Vila‐Castelar, Clara; Baena, Ana Y.; Sperling, Reisa A.; Johnson, Keith A.; Lopera, Francisco; Sepulcre, Jorge; Quiroz, Yakeel T.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.056134
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Alzheimer's disease (AD)‐related pathology (i.e., amyloid‐β and neurofibrillary tangles) disrupts functional networks that support higher‐order cognitive functions. Yet, it is not well known how the brain's functional architecture is differentially associated with in vivo pathology in preclinical AD, which is critical for predicting disease risk and progression. We intersected functional connectivity and PET images to examine how in vivo amyloid‐β and tau pathologies are associated with weighted‐degree centrality patterns, known to be important for understanding network organization and information transmission hubs, in cognitively‐unimpaired individuals with autosomal‐dominant AD due to the Presenilin‐1 (PSEN‐1) E280A mutation. Method: 21 cognitively‐unimpaired PSEN1 E280A carriers and 31 non‐carriers underwent resting‐state fMRI, 11 C Pittsburgh compound B‐PET and 18 F Flortaucipir‐PET. We used graph‐based network analyses to examine weighted‐degree centrality, the sum of weights from edges connecting to a node. A general linear model was used to compare connectivity maps between groups, and partial correlations were used to examine the relationship between individual‐subject maps with whole‐brain amyloid‐β and tau PET. A significance threshold of p<0.05 was used. Analyses were covaried for age and corrected for multiple comparisons. Result: Compared to non‐carriers, mutation carriers exhibited reduced weighted‐degree in the medial occipitoparietal and posterior cingulate cortices. Greater amyloid‐β was associated with reduced weighted‐degree in the lateral temporal lobe and fusiform gyrus, and greater weighted‐degree in the lateral and medial prefrontal cortices. In turn, greater tau burden was associated with greater weighted‐degree in the lateral and medial temporal regions, anterior and posterior cingulate cortices, lateral parietal cortex and precuneus, and decreased weighted‐degree in dorsomedial prefrontal cortex. Conclusion: Our findings show that cognitively‐unimpaired individuals who are genetically‐determined to develop AD dementia in their forties have abnormal patterns of functional connectivity that resemble spatial patterns of amyloid‐β and tau propagation. Regions that had weaker connections with nearby and distant regions showed greater amyloid‐β burden, while regions that were highly functionally connected exhibited greater tau burden, which has been suggested to increase the probability of tau seeding and propagation. These findings contribute to our understanding of how functional connectivity patterns can help predict risk and monitor AD progression from preclinical to clinical stages.