Emerging role of a systems biology approach to elucidate factors of reduced penetrance: transcriptional changes in THAP1-linked dystonia as an example

Abstract

Pathogenic variants in THAP1 can cause dystonia with a penetrance of about 50 %. The underlying mechanisms are unknown and can be considered as means of endogenous disease protection. Since THAP1 encodes a transcription factor, drivers of this variability putatively act at the transcriptome level. Several transcriptome studies tried to elucidate THAP1 function in diverse cellular and mouse models, including mutation carrier-derived cells and iPSC-derived neurons, unveiling various differentially expressed genes and affected pathways. These include nervous system development, dopamine signalling, myelination, or cell-cell adhesion. A network diffusion analysis revealed mRNA splicing, mitochondria, DNA repair, and metabolism as significant pathways that may represent potential targets for therapeutic interventions.

Keywords: DYT-THAP1; dystonia; iPSC; reduced penetrance; whole transcriptome.

Figure 1

Phenotypic spectrum of reported carriers of THAP1 mutations. In the left panel, the presence (red) or absence (blue) of the indicated signs and symptoms is shown for 249 patients with THAP1 mutations. In the right panel, the age variability at onset is illustrated (modified from www.mdsgene.org [4]).

Figure 2

Protein Interaction Network related to THAP1. Interactions of the THAP1-mediated DEGs were obtained via StringDB. The colors of the nodes symbolize the affiliation to specific GO:terms, colors of the edges symbolize the type of protein interaction. The most frequent interaction among these genes is related to data mining in current studies (light yellow border). Only individual clusters are linked via co-expression (black edge) or experimental evidence.

Figure 3

Hypergeometric test on Reactome pathways of proteins affected by differential gene expression in THAP1 knockdown models. The dot plot includes pathways having at least three affected proteins at a significance cutoff of p < 0.05. Red and black font colors refer to up- and down-regulated pathways, respectively. The dot size corresponds to the pathway set size.