Transcriptional network analysis in frontal cortex in Lewy body diseases with focus on dementia with Lewy bodies

Abstract

The present study investigates global transcriptional changes in frontal cortex area 8 in incidental Lewy Body disease (iLBD), Parkinson disease (PD) and Dementia with Lewy bodies (DLB). We identified different coexpressed gene sets associated with disease stages, and gene ontology categories enriched in gene modules and differentially expressed genes including modules or gene clusters correlated to iLBD comprising upregulated dynein genes and taste receptors, and downregulated innate inflammation. Focusing on DLB, we found modules with genes significantly enriched in functions related to RNA and DNA production, mitochondria and energy metabolism, purine metabolism, chaperone and protein folding system and synapses and neurotransmission (particularly the GABAergic system). The expression of more than fifty selected genes was assessed with real time quantitative polymerase chain reaction. Our findings provide, for the first time, evidence of molecular cortical alterations in iLBD and involvement of several key metabolic pathways and gene hubs in DLB which may underlie cognitive impairment and dementia.

Keywords: GABA; Lewy body diseases; axonema; cerebral cortex; chaperones; dementia with Lewy bodies; dynein; mitochondria; neurotransmission; purine metabolism; synapses; taste receptors; transcriptome.

Figure 1

A. Heatmap representation of the enrichment scores of 1914 genes having at least one group of samples with enrichment scores other than 0. MA: middle‐aged, iLBD: incidental Lewy body disease, PD: Parkinson disease, DLB: dementia with Lewy bodies. B. Weighted gene coexpression network analysis of the frontal cortex transcriptome using 5114 gene expression values of 28 assessed samples identifies 13 gene modules. Modules are labeled by color and number (M1 to M13). Genes not assigned to any particular coexpression modules were labeled M0 or gray. Dendrogram obtained by hierarchical clustering of genes based on their topological overlap is shown at the top. Bottom rows indicate the correlation value of each gene expression and the spectrum of LBD pathology. Blue to red indicates negative to positive correlation values. None of our identified modules correlated with age.

Figure 2

A. Module eigengenes for each module by LB spectrum. B. Correlation values (univariate) and P‐values for the relationship between each module eigengene and each LBD stage compared separately with MA or various control variables. P‐values for LBD stages correspond to partial coefficients in the multivariate analysis. Color code indicates the significance of the correlation. Seven modules significantly correlate with different stages of LBD.

Figure 3

Enrichment score (‐log10 P‐value) of genes in selected modules in previously published brain gene sets associated with cell types or brain regions. Module‐brown (M6) is enriched in neuronal genes; module‐tan (M5) is enriched in microglial genes; module‐salmon (M6) has nonspecific enrichment.

Figure 4

Putative subnetworks of protein–protein interactions. A. M6‐tan module PPI subnetwork showing that spleen tyrosine kinase (encoded by SYK) interacting with 16 partners is the gene with the highest degree of nucleation. B. M4‐lightcyan module subnetwork showing high degree proteins such as CDK2, MSN and TP53. C. M9‐salmon PPI subnetwork shows a large connected node related to heat shock proteins encoded by STIP1, DNAJA1, DNAJB1, DNAJB4, HSPA5, HSAPA6, AHSA1 and HSPA1A, among others. D. M5‐brown module contains a large PPI subnetwork with several nodes including proteins encoded by YWHAB, GSK3B, PSMA3, ATP6V0D1, TPI1, ATP6V1A and SNCA, among others (circular network representation is shown in the small panel proteins ordered by degree, a zoom in the top degree proteins is shown in the larger panel).