Bridging the Gap Between Morphometric Similarity Mapping and Gene Transcription in Alzheimer’s Disease

Abstract

Disruptions in brain connectivity have been widely reported in Alzheimer’s disease (AD). Morphometric similarity (MS) mapping provides a new way of estimating structural connectivity by interregional correlation of T1WI- and DTI-derived parameters within individual brains. Here, we aimed to identify AD-related MS changing patterns and genes related to the changes and further explored the molecular and cellular mechanism underlying MS changes in AD. Both 3D-T1WI and DTI data of 106 AD patients and 106 well-matched healthy elderly individuals from the ADNI database were included in our study. Cortical regions with significantly decreased MS were found in the temporal and parietal cortex, increased MS was found in the frontal cortex and variant changes were found in the occipital cortex in AD patients. Mean MS in regions with significantly changed MS was positively or negatively associated with memory function. Negative MS-related genes were significantly downregulated in AD, specifically enriched in neurons, and participated in biological processes, with the most significant term being synaptic transmission. This study revealed AD-related cortical MS changes associated with memory function. Linking gene expression to cortical MS changes may provide a possible molecular and cellular substrate for MS abnormality and cognitive decline in AD.

MIND Networks: Robust Estimation of Structural Similarity from Brain MRI

“…The finding that morphometric similarity networks are spatially co-located with transcriptional similarity or gene co-expression networks (Seidlitz et al, 2018) has spurred subsequent research efforts to link MRI-derived connectomes to underlying transcriptional patterns (Seidlitz et al, 2020; Morgan et al, 2019; Zhang et al, 2021).…”

“…For example, by combining cortical transcriptomic data from the Allen Human Brain Atlas (Hawrylycz et al, 2015) with structural MRI from subjects with one of six different chromosomal copy number variation (CNV) disorders, Seidlitz et al (2020) demonstrated that the changes in morphometric similarity induced by each CNV closely resembled the spatial expression patterning of genes from the affected chromosome. Other studies have shown that changes in morphometric similarity in psychotic disorders (Morgan et al, 2019), major depressive disorder (Li et al, 2021), and Alzheimer’s disease (Zhang et al, 2021) correspond to the cortical expression of disease-relevant genes.…”

Morphometric similarity differences in drug‐naive Parkinson's disease correlate with transcriptomic signatures

“…MS network analysis has been used to explore the correlation between brain structural changes and underlying transcriptomic signatures for various mental and neurological diseases. 22 , 23 , 24 , 25 However, this novel approach has not been applied to PD patients, particularly early drug‐naive PD patients, which could avoid the potential confounding influence of medication and disease duration.…”

Alzheimer's genetic risk effects on cerebral blood flow across the lifespan are proximal to gene expression

“…Specifically, we sought to investigate whether brain-wide AD-related gene expression correlates with regional variation in CBF. While prior investigations have determined associations between gene expression and MRI based markers of regional aging / AD – associated atrophy, this approach has not yet been considered for cerebrovascular architecture ( Groot et al, 2021 ; Vidal-Pineiro et al, 2020 ; Zhang et al, 2021 ). These analyses will establish the regional cortical co-expression of AD risk genes and AD-risk gene related CBF reductions, providing a plausible mechanistic link between AD risk loci and a well-established pathophysiological process in AD.…”