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

Cai, Suping, Huang, Kexin, Yang, Fan, Wang, Xuwen, Wu, Sijia, Wang, Yubo, Huang, Liyu·2021·Frontiers in Aging Neuroscience
DOI 10.3389/fnagi.2021.745381PMC PMC8585991
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Abstract

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.

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Crossref · 10.3389/fnagi.2021.745381

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FIGURE 1 Flowchart of this study. (A) Cortical thickness difference (ΔCT) of 308 brain regions between the MCI_S and MCI_AD groups. (B) Regional expression of 20,647 genes in 308 brain regions from the AIBS. (C) Partial least squares regression (PLSR) analysis using gene expression as a predictor variable and ΔCT as a response variable. (D) PLSR weights of all genes in line with its contribution to the overall model in each component (FDR correction, z-score > 1.96). (E) Upregulated genes are tested for enrichment analysis and spatial expression of von Economo classes. (F) Validation of robustness and specificity of our results. (G) Validation of robustness and specificity.
FIGURE 1 Flowchart of this study. (A) Cortical thickness difference (ΔCT) of 308 brain regions between the MCI_S and MCI_AD groups. (B) Regional expression of 20,647 genes in 308 brain regions from the AIBS. (C) Partial least squares regression (PLSR) analysis using gene expression as a predictor variable and ΔCT as a response variable. (D) PLSR weights of all genes in line with its contribution to the overall model in each component (FDR correction, z-score > 1.96). (E) Upregulated genes are tested for enrichment analysis and spatial expression of von Economo classes. (F) Validation of robustness and specificity of our results. (G) Validation of robustness and specificity.CC BY · PubMed Central
FIGURE 2 Correlation of ΔCT and gene loading value between the discovery, validation, and specificity datasets (A–F).
FIGURE 2 Correlation of ΔCT and gene loading value between the discovery, validation, and specificity datasets (A–F).CC BY · PubMed Central
FIGURE 3 Gene enrichment results from PLSR and WGCNA in the discovery dataset (A,C) and the validation dataset (B,D).
FIGURE 3 Gene enrichment results from PLSR and WGCNA in the discovery dataset (A,C) and the validation dataset (B,D).CC BY · PubMed Central
FIGURE 4 Protein–protein interaction network and identified MCODE components (A–F) from PLS1 gene enrichment.
FIGURE 4 Protein–protein interaction network and identified MCODE components (A–F) from PLS1 gene enrichment.CC BY · PubMed Central
FIGURE 5 Biological processes involved in chemical synaptic transmission from QuickGO.
FIGURE 5 Biological processes involved in chemical synaptic transmission from QuickGO.CC BY · PubMed Central
FIGURE 6 ΔCT and von Economo classes of PLS1 in the discovery dataset (A,C), and the validation dataset (B,D).
FIGURE 6 ΔCT and von Economo classes of PLS1 in the discovery dataset (A,C), and the validation dataset (B,D).CC BY · PubMed Central
FIGURE 7 ΔCT-related genes (PLS1) for cell type-specific analysis in discovery dataset. (A) The number of overlapping genes for each cell type (all permutated p-values were adjusted by FDR; (B) Gene Ontology terms enriched for ΔCT related PLS1 genes for each cell type.
FIGURE 7 ΔCT-related genes (PLS1) for cell type-specific analysis in discovery dataset. (A) The number of overlapping genes for each cell type (all permutated p-values were adjusted by FDR; (B) Gene Ontology terms enriched for ΔCT related PLS1 genes for each cell type.CC BY · PubMed Central

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Metadata

Authors
Cai, S., Huang, K., Yang, F., Wang, X., Wu, S., Wang, Y., & Huang, L.
Venue
Frontiers in Aging Neuroscience
Publisher
Frontiers Media SA
Published
2021-10-29
Volume
13
ISSN
1663-4365
DOI
10.3389/fnagi.2021.745381
PMC
PMC8585991
Cited by
11
References
11
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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