Establishing gene regulatory networks from Parkinson’s disease risk loci

Abstract

The latest meta-analysis of genome wide association studies (GWAS) identified 90 independent variants across 78 genomic regions associated with Parkinson’s disease, yet the mechanisms by which these variants influence the development of the disease remains largely elusive. To establish the functional gene regulatory networks associated with Parkinson’s disease risk variants, we utilised an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci; eQTL) data. We identified 518 genes subject to regulation by 76 Parkinson’s-variants across 49 tissues, that encompass 36 peripheral and 13 CNS tissues. Notably, one third of these genes were regulated via trans- acting mechanisms (distal; risk locus-gene separated by > 1Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-eQTL-gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and Parkinson’s disease GWAS loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neuro-development specific eQTL-gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of Parkinson’s disease. Through utilising Louvain clustering we extracted nine significant and highly intra-connected clusters within the entire gene regulatory network. The nine clusters are enriched for specific biological processes and pathways, some of which have not previously been associated with Parkinson’s. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of Parkinson’s disease variants, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of Parkinson’s disease.

Parkinson’s disease-associated genetic variants synergistically shape brain networks

“…To date, a large number of SNPs have been identified to be associated with the risk of PD, nevertheless, the underlying neural mechanisms of previously reported SNPs were largely unknown (Chang et al, 2017;Nalls et al, 2019). Some preliminary studies have identified PDassociated SNPs were associated with common pathological pathways in PD, such as endocytosis, autophagy, lysosome, mitochondria metabolism, immunological surveillance, DNA replication, synaptic vesicle recycling, and microtubule polymerization (Chang et al, 2017;Cui, Xu, Zhang, & Wang, 2021;Farrow et al, 2022), which were consistent with our functional enrichment results (Figure supplement 2) based on PPI network derived from differentially expressed genes. Interestingly, we found nuclear pore complex was a new biological pathway associated with PD-associated SNPs.…”

A proteogenomic view of Parkinson’s disease causality and heterogeneity

“…CTSB cleaves alpha-synuclein fibrils with the potential for decreasing alpha-synuclein aggregation 25 . Both the CTSB locus 26 and a specific genetic variant of CTSB have been found to be associated with the risk of developing PD 27 . FCGR2A and FCGR2B are involved in phagocytosis and modulate inflammatory responses 28 .…”

Genetic Architecture of Parkinson’s Disease

“…The research community has taken the first and successful steps in this direction, but there is still a lot to be done in the epigenetic "finishing" of the building. This will require the development of fundamentally new approaches both in studying molecular events associated with the epigenome and data analysis using machine learning and artificial intelligence methods [97,98].…”