Introduction

A pathological role of α-synuclein (aSyn) aggregation in the etiology of Parkinson disease (PD) is well established. Here, we applied spatial transcriptomics (ST) on brain sections derived from a rodent mouse model of α-synucleinopathy (transgenic M83+/+ line). Our ST data revealed that induction of aSyn pathology in the brainstem of rodents triggered upregulation of pathways controlling energy metabolism. At a later stage, characterized by movement disability, the ST data indicated a drastic downregulation of mitochondrial metabolic pathways along with perturbed expression of mRNA translation machinery. Furthermore, analyses of microarrays datasets derived from 4 independent cohorts of PD patients led to the identification of aberrant osteopontin (SPP1) signaling and increased expression of CREB-binding protein as consistent markers associated with the progression of aSyn pathology in the rodent model and in PD brains. We anticipate that our findings hold promise for biomarker discovery and/or mechanism-based therapies in PD and related neurodegenerative disorders.




Please cite the PD spatial database as:

Lin Lin, Nanna M. Jensen, Alberto Delaidelli, Sara A. Ferreira, Fatemeh Yarmahmoudi, Poul H. Sorensen, Marina Romero-Ramos, Poul H. Jensen, Ian R. Mackenzie, Jens R. Nyengaard, Asad Jan, Spatial transcriptomics reveals the molecular signatures of prodromal and advanced α-synucleinopathy, iScience, Volume 29, Issue 3, 2026, 114845, ISSN 2589-0042








Gene Summary


            

Differential expressed genes in different time points compared to sham

* Wilcoxon Rank Sum test were used to identify differentially expressed genes between two groups of cells
* pct: The percentage of cells where the gene detected in the group
* avg_log2FC: log fold-chage of the average expression between the two groups.
* p_val_adj: Adjusted p-value, based on bonferroni correction using all genes in the dataset

Spatial gene expression: Spatial plot

Download PDF


Spatial geneset score: Spatial plot

Download PDF

Cell information vs gene expression on reduced dimensions

In this tab, users can visualise both cell information and gene expression side-by-side on low-dimensional representions.

Dimension Reduction

Cell information

Download PDF Download PNG

Cell numbers / statistics

Gene expression

Download PDF Download PNG

Cell information vs cell information on dimension reduction

In this tab, users can visualise two cell informations side-by-side on low-dimensional representions.

Dimension Reduction

Cell information 1

Download PDF Download PNG

Cell information 2

Download PDF Download PNG

Gene expression vs gene expression on dimension reduction

In this tab, users can visualise two gene expressions side-by-side on low-dimensional representions.

Dimension Reduction

Gene expression 1

Download PDF Download PNG

Gene expression 2

Download PDF Download PNG

Coexpression of two genes on reduced dimensions

In this tab, users can visualise the coexpression of two genes on low-dimensional representions.

Dimension Reduction

Gene Expression

Download PDF Download PNG

Cell information / gene expression violin plot / box plot

In this tab, users can visualise the gene expression or continuous cell information (e.g. Number of UMIs / module score) across groups of cells (e.g. libary / clusters).



Download PDF Download PNG

Proportion / cell numbers across different cell information

In this tab, users can visualise the composition of single cells based on one discrete cell information across another discrete cell information. Usage examples include the library or cellcycle composition across clusters.



Download PDF Download PNG

Gene expression bubbleplot / heatmap

In this tab, users can visualise the gene expression patterns of multiple genes grouped by categorical cell information (e.g. library / cluster).
The normalised expression are averaged, log-transformed and then plotted.




Download PDF Download PNG

GeneSet Score violin plot / box plot

In this tab, users can visualise a total of 24604 GeneSet score from MsigDB across groups of cells (e.g. libary / clusters).



Download PDF Download PNG

All rights reserved.

Copyright 2022 Steno Diabetes Center Aarhus (SDCA); Aarhus University

Created by DREAMlab, Department of Biomedicine, Aarhus University

Get in touch with us: lin.lin@biomed.au.dk

This webpage was made using ShinyCell