TOWARD A FUNCTIONAL NEUROMARKER FOR PRECLINICAL AD: EIGENVECTOR CENTRALITY REVEALS PRECLINICAL DIFFERENCES OF FUNCTIONAL INFORMATION FLOW IN THE HIPPOCAMPUS, PRECUNEUS, CEREBELLUM AND INFERIOR PARIETAL LOBULE

Abstract

AD is characterized by complex neuronal changes including compensatory mechanisms in response to atrophy, affected by multiple factors such as age, gender and education. A comprehensive account of the functional changes associated with each progressive stage along the continuum of AD, including the preclinical stage, is required to enhance clinical assessment protocols. Eigenvector centrality is an advanced measure of network information flow that has recently become computable for fMRI data. We investigated significant differences in eigenvector centrality across the entire continuum of AD, from health to dementia, as reflected by the cerebrospinal fluid ratio of phosphorylated tau protein over beta-amyloid peptide 42. Additionally, significant differences of functional connectivity of the identified network hubs were examined comparatively between each pair of consecutive stages across the disease continuum, while controlling for the effects of age, gender and education throughout all analyses (n=96). SyGN normalization was employed, all analyses were data-driven and performed with corrections for multiple comparisons across the whole brain at voxel resolution. During resting-state fMRI, inferior parietal areas show decreasing centrality, whereas the thalamus and cingulate cortex show the opposite effect, across the disease continuum. Complementary analyses suggest that most centrality changes are related to episodic memory decline. Comparisons between consecutive stages of the disease reveal an informative sequence of network-degradation and network-compensation patterns as differences of functional connectivity between the identified network hubs and several prominent brain areas. Importantly, during the preclinical stage, significant alterations in functional connectivity are observed in areas that are typically affected by atrophy many years later (e.g. hippocampus, precuneus, cerebellum, inferior parietal lobule). The identified changes in network centrality and functional connectivity provide a comprehensive account of the incremental changes in neural information flow associated with each progressive stage of AD. These findings suggest specific patterns of functional connectomics for the detection of the preclinical stage and for monitoring clinical progression and therapeutic efficacy in AD. The methodological approach is being further evaluated, using an independent sample, with regards to its potential for diagnostic utility and the development of a neuromarker for the preclinical stage of AD. fMRI results. The first column (a) shows clusters with eigenvector centrality correlating with the p- tau/Aβ42 biomarker index. Significant positive correlations with p-tau/Aβ42 are indicated in medial cingulate (1a), posterior cingulate (2a), thalamus (3a), anterior cingulate (4a); significant negative correlation with p- tau/Aβ42 is indicated in the left inferior parietal lobule (5a). These five clusters were used as seed regions for functional connectivity analyses. The results of the comparison of functional connectivity maps between subject groups are shown separately for the five seed clusters in each row. Columns (b), (c) and (d) show significant differences between subject groups in functional connectivity with the seed cluster of the respective row (red and blue colors depict significant increases and decreases respectively; e.g. cell 1.b shows that during the preclinical stage of AD, the functional connectivity of the medial cingulate decreases with the left hippocampus and increases with the precuneus). Images are shown in neurological convention; variance due to age, gender and education has been accounted by covariates in all analyses; all results are corrected for voxel-wise multiple comparisons (p < 0.05). Conjunction between EC correlations with p-tau/Aβ42 and EC correlations with cognitive measures. The main regression analysis (see Methods section) was repeated twice, replacing p-tau/Aβ42 with score on memory alteration test (M@T; Rami et al., 2007) and score on free recall of selective reminding test (Grober & Buschke, 1987), controlling for age, gender and level of education. Results were corrected for whole-brain multiple comparisons using identical methods to the main analysis. Top row left: significant positive correlations between EC and p-tau/Aβ42; top row middle: significant negative correlations between EC and M@T scores; top row right: green voxels display regions where EC correlated significantly with both p- tau/Aβ42 and M@T scores. Bottom row left: significant negative correlation between EC and p-tau/Aβ42; bottom row middle: significant positive (red) and significant negative (blue) correlations between EC and scores of free recall; bottom row right: green voxels display regions where EC correlated significantly with both p-tau/Aβ42 and free recall scores.