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. 2022 Jan 7;11(2):198.
doi: 10.3390/cells11020198.

Correcting Differential Gene Expression Analysis for Cyto-Architectural Alterations in Substantia Nigra of Parkinson's Disease Patients Reveals Known and Potential Novel Disease-Associated Genes and Pathways

Federico Ferraro  1 , Christina Fevga  1 , Vincenzo Bonifati  1 , Wim Mandemakers  1 , Ahmed Mahfouz  2   3   4 , Marcel Reinders  2   3   4   5
Affiliations

Correcting Differential Gene Expression Analysis for Cyto-Architectural Alterations in Substantia Nigra of Parkinson's Disease Patients Reveals Known and Potential Novel Disease-Associated Genes and Pathways

Federico Ferraro et al. Cells. .

Abstract

Several studies have analyzed gene expression profiles in the substantia nigra to better understand the pathological mechanisms causing Parkinson's disease (PD). However, the concordance between the identified gene signatures in these individual studies was generally low. This might have been caused by a change in cell type composition as loss of dopaminergic neurons in the substantia nigra pars compacta is a hallmark of PD. Through an extensive meta-analysis of nine previously published microarray studies, we demonstrated that a big proportion of the detected differentially expressed genes was indeed caused by cyto-architectural alterations due to the heterogeneity in the neurodegenerative stage and/or technical artefacts. After correcting for cell composition, we identified a common signature that deregulated the previously unreported ammonium transport, as well as known biological processes such as bioenergetic pathways, response to proteotoxic stress, and immune response. By integrating with protein interaction data, we shortlisted a set of key genes, such as LRRK2, PINK1, PRKN, and FBXO7, known to be related to PD, others with compelling evidence for their role in neurodegeneration, such as GSK3β, WWOX, and VPC, and novel potential players in the PD pathogenesis. Together, these data show the importance of accounting for cyto-architecture in these analyses and highlight the contribution of multiple cell types and novel processes to PD pathology, providing potential new targets for drug development.

Keywords: Parkinson’s disease; cyto-architecture; interactome analysis; meta-analysis; transcriptome analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Summary of this study. (A) Human substantia nigra microarrays from PD and CTRL were downloaded from GEO. (B) Cell-proportion deconvolution for six cell types. (C) Differential expression analysis with and without cell proportions. (D) GSEA on the expression matrix. (E) Central protein identification in PPI network around detected differentially expressed genes. Drawings of substantia nigra and cells were obtained from Servier Medical Art templates (Creative Commons Attribution 3.0 Unported License; https://smart.servier.com accessed on 1 May 2021).
Figure 2
Figure 2
Cyto-architectural heterogeneity as estimated from bulk transcriptomics using the deconvolution strategy of TOAST. (A) Cell estimates of six cell types in substantia nigra across different datasets and conditions. Blue, CTRL; red, PD. Significant variations are indicated by asterisk (p < 0.05). (B) Bar plot of the standardized mean differences (SMD) in cell estimates from the random-effects meta-analysis conducted with metafor. BH-adjusted p-values are reported between brackets, significant differences are indicated by asterisks “*” (BH p < 0.05), and standard errors for each cell type are reported as error bars. (C) Number of DEGs of the cell proportion-aware LMM probed by a specific number of microarrays in our dataset.
Figure 3
Figure 3
Comparison of the GSEA for the genes ranked by the two linear mixed models (LMMs). Top 10 significant hits of the cell proportion-aware (second) LMM (diamond) compared with their respective values from the cell proportion-unaware (first) LMM (circle). Each shape is colored by the normalized enriched scores (NES); −log10 of the adjusted p-value is reported on the x-axis. The significance threshold (BHp = 0.05) is indicated by the dashed vertical line. (A) Top results for gene ontology cellular component (GOCC); (B) Top results for gene ontology molecular function (GOMF); (C) Top results for gene ontology biological process (GOBP); (D) Top results for canonical data set.
Figure 4
Figure 4
PPI network analyses. (A) EWCE results for the full network and central protein. The number of standard deviations of the expression of each list from the mean level expression of 10,000 equally sized random lists is reported for each cell type. BH-corrected p-values are reported between brackets. (B) GSEA results of the nodes in the network ranked by betweenness centrality. The −log10 value of the adjusted p-value is reported on the x-axis, and the significance threshold (BHp = 0.05) is indicated by the dashed vertical line. (C) Network of the central proteins extracted from the full PPI network. Label size is proportional to the protein degree, edge thickness, and color proportional to the edge betweenness. PD-causing genes (LRRK2, PINK1, PRKN) and the genes closest to a risk factor (BAG3) are highlighted in brick red and cerulean blue, respectively.
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