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Comparison of brain connectomes by MRI and genomics and its implication in Alzheimer’s disease
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Abstract
Background
The human brain is complex and interconnected structurally. Brain connectome change is associated with Alzheimer’s disease (AD) and other neurodegenerative diseases. Genetics and genomics studies have identified molecular changes in AD; however, the results are often limited to isolated brain regions and are difficult to interpret its findings in respect to brain connectome. The mechanisms of how one brain region impacts the molecular pathways in other regions have not been systematically studied. And how the brain regions susceptible to AD pathology interact with each other at the transcriptome level and how these interactions relate to brain connectome change are unclear.
Methods
Here, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer’s Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions.
Results
We observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort. The result suggests that disease associated white matter changes are focal. Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.03). And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.08 × 10−9). Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level. Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (Ppermutation = 1.0 × 10−2 and 4.9 × 10−4 for left and right respectively).
Conclusions
In summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.
Springer Science and Business Media LLC
Title: Comparison of brain connectomes by MRI and genomics and its implication in Alzheimer’s disease
Description:
Abstract
Background
The human brain is complex and interconnected structurally.
Brain connectome change is associated with Alzheimer’s disease (AD) and other neurodegenerative diseases.
Genetics and genomics studies have identified molecular changes in AD; however, the results are often limited to isolated brain regions and are difficult to interpret its findings in respect to brain connectome.
The mechanisms of how one brain region impacts the molecular pathways in other regions have not been systematically studied.
And how the brain regions susceptible to AD pathology interact with each other at the transcriptome level and how these interactions relate to brain connectome change are unclear.
Methods
Here, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer’s Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions.
Results
We observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort.
The result suggests that disease associated white matter changes are focal.
Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.
03).
And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.
08 × 10−9).
Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level.
Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (Ppermutation = 1.
0 × 10−2 and 4.
9 × 10−4 for left and right respectively).
Conclusions
In summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.
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