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Bridging the gap between cortical morphometric remodeling and gene expression can help to clarify the effects of the selective brain accumulation of Amyloid- β (A β) and tau proteins occurring in the Alzheimer's disease (AD). To this aim, we derived morphometric similarity (MS) networks from 126 A β - and tau-positive (A β +/tau+) and 172 A β −/tau− subjects, and we investigated the association between group-wise regional MS differences and transcriptional correlates thanks to an imaging transcriptomics approach grounded in the Allen Human Brain Atlas (AHBA). The expressed gene with the highest correlation with MS alterations was BCHE, a gene related to A β homeostasis. In addition, notably, among the most promising results derived from the enrichment analysis, we found the immune response to be a biological process and astrocytes, microglia, and oligodendrocyte precursors for the cell types. In summary, by relating cortical MS and AHBA-derived transcriptomics, we were able to retrieve findings suggesting the biological mechanisms underlying the A β - and tau- induced cortical MS alterations in the AD continuum. [ABSTRACT FROM AUTHOR]

INTRODUCTION: We investigated in vivo the microstructural integrity of the pathway connecting the locus coeruleus to the transentorhinal cortex (LC‐TEC) in patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD). METHODS: Diffusion‐weighted MRI scans were collected for 21 AD, 20 behavioral variants of FTD (bvFTD), and 20 controls. Fractional anisotropy (FA), mean, axial, and radial diffusivities (MD, AxD, RD) were computed in the LC‐TEC pathway using a normative atlas. Atrophy was assessed using cortical thickness and correlated with microstructural measures. RESULTS: We found (i) higher RD in AD than controls; (ii) higher MD, RD, and AxD, and lower FA in bvFTD than controls and AD; and (iii) a negative association between LC‐TEC MD, RD, and AxD, and entorhinal cortex (EC) thickness in bvFTD (all p < 0.050). DISCUSSION: LC‐TEC microstructural alterations are more pronounced in bvFTD than AD, possibly reflecting neurodegeneration secondary to EC atrophy. Highlights: Microstructural integrity of LC‐TEC pathway is understudied in AD and bvFTD.LC‐TEC microstructural alterations are present in both AD and bvFTD.Greater LC‐TEC microstructural alterations in bvFTD than AD.LC‐TEC microstructural alterations in bvFTD are associated to EC neurodegeneration. [ABSTRACT FROM AUTHOR]

Background: The mechanisms driving primary progressive and relapsing–remitting multiple sclerosis (PPMS/RRMS) phenotypes are unknown. Magnetic resonance imaging (MRI) studies support the involvement of gray matter (GM) in the degeneration, highlighting its damage as an early feature of both phenotypes. However, the role of GM microstructure is unclear, calling for new methods for its decryption. Purpose To investigate the morphometric and microstructural GM differences between PPMS and RRMS to characterize GM tissue degeneration using MRI. Study Type: Prospective cross‐sectional study. Subjects: Forty‐five PPMS (26 females) and 45 RRMS (32 females) patients. Field Strength/Sequence: 3T scanner. Three‐dimensional (3D) fast field echo T1‐weighted (T1‐w), 3D turbo spin echo (TSE) T2‐w, 3D TSE fluid‐attenuated inversion recovery, and spin echo‐echo planar imaging diffusion MRI (dMRI). Assessment T1‐w and dMRI data were employed for providing information about morphometric and microstructural features, respectively. For dMRI, both diffusion tensor imaging and 3D simple harmonics oscillator based reconstruction and estimation models were used for feature extraction from a predefined set of regions. A support vector machine (SVM) was used to perform patients' classification relying on all these measures. Statistical Tests: Differences between MS phenotypes were investigated using the analysis of covariance and statistical tests (P < 0.05 was considered statistically significant). Results: All the dMRI indices showed significant microstructural alterations between the considered MS phenotypes, for example, the mode and the median of the return to the plane probability in the hippocampus. Conversely, thalamic volume was the only morphometric feature significantly different between the two MS groups. Ten of the 12 features retained by the selection process as discriminative across the two MS groups regarded the hippocampus. The SVM classifier using these selected features reached an accuracy of 70% and a precision of 69%. Data Conclusion: We provided evidence in support of the ability of dMRI to discriminate between PPMS and RRMS, as well as highlight the central role of the hippocampus. Level of Evidence: 2 Technical Efficacy Stage: 3 [ABSTRACT FROM AUTHOR]