Cortical Thickness Differences Are Associated With Chemical Synaptic Transmission Upregulated Genes in Degeneration of Mild Cognitive Impairment

• Published in: Frontiers in aging neuroscience Vol. 13; p. 745381
• Main Authors: Cai, Suping, Huang, Kexin, Yang, Fan, Wang, Xuwen, Wu, Sijia, Wang, Yubo, Huang, Liyu
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 29.10.2021; Frontiers Media S.A
• Subjects: Alzheimer's disease; Biomarkers; Brain research; chemical synaptic transmission; Cognitive ability; cortical gene expression; cortical thickness differences; Datasets; Ethics; Gene expression; Genetic diversity; Health risk assessment; Magnetic resonance imaging; Medical imaging; Morphology; Neurodegeneration; Neurodegenerative diseases; Neuroscience; partial least squares regression; Prefrontal cortex; Quality control; structural magnetic resonance images; Synaptic transmission; Transcription; Values; weighted gene co-expression network analysis
• ISSN: 1663-4365; 1663-4365
• DOI: 10.3389/fnagi.2021.745381

Mild cognitive impairment (MCI) is a transition between normal cognition (NC) and Alzheimer’s disease (AD). Differences in cortical thickness (ΔCT) have been reported in cases that degenerate from MCI to AD. The aspects of genetic and transcriptional variation related to ΔCT are vague. In this study, using an 8-year longitudinal follow-up outcome, we investigated the genetic correlates of ΔCT in MCI subjects with degeneration from MCI to AD (MCI_AD). We employed partial least squares regression (PLSR) on brain T1-weighted magnetic resonance imaging (MRI) images of 180 participants [143 stable MCI (MCI_S) participants and 37 MCI_AD participants] and brain gene expression data from the Allen Institute for Brain Science (AIBS) database to investigate genes associated with ΔCT. We found that upregulated PLS component 1 ΔCT-related genes were enriched in chemical synaptic transmission. To verify the robustness and specificity of the results, we conducted PLSR analysis invalidation and specificity datasets and performed weighted gene co-expression network analysis instead of PLSR for the above three datasets. We also used gene expression data in the brain prefrontal cortex from the Gene Expression Omnibus (GEO) database to indirectly validate the robustness and specificity of our results. We conclude that transcriptionally upregulated genes involved in chemical synaptic transmission are strongly related to global ΔCT in MCI patients who experience degeneration from MCI to AD.