ORCID Profile
0000-0002-6578-4219
Current Organisation
The University of Auckland
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Wiley
Date: 18-06-2020
DOI: 10.1002/MDS.28144
Publisher: Oxford University Press (OUP)
Date: 30-01-2022
Abstract: The latest meta-analysis of genome-wide association studies 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 utilized an approach combining spatial (chromosomal conformation capture) and functional (expression quantitative trait loci) data. We identified 518 genes subject to regulation by 76 Parkinson’s variants across 49 tissues, whicih 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 & Mb, or on different chromosomes). Of particular interest is the identification of a novel trans-expression quantitative trait loci–gene connection between rs10847864 and SYNJ1 in the adult brain cortex, highlighting a convergence between familial studies and Parkinson’s disease genome-wide association studies loci for SYNJ1 (PARK20) for the first time. Furthermore, we identified 16 neurodevelopment-specific expression quantitative trait loci–gene regulatory connections within the foetal cortex, consistent with hypotheses suggesting a neurodevelopmental involvement in the pathogenesis of Parkinson’s disease. Through utilizing Louvain clustering we extracted nine significant and highly intraconnected 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 disease. 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.
Publisher: Cold Spring Harbor Laboratory
Date: 09-04-2021
DOI: 10.1101/2021.04.08.439080
Abstract: The latest meta-analysis of genome wide association studies (GWAS) identified 90 independent single nucleotide polymorphisms (SNPs) across 78 genomic regions associated with Parkinson’s disease (PD), 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 PD-SNPs, 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 PD-SNPs 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 PD 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 PD. 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 PD. Together, our results not only contribute to an overall understanding of the mechanisms and impact of specific combinations of PD-SNPs, but also highlight the potential impact gene regulatory networks may have when elucidating aetiological subtypes of PD.
Publisher: Cold Spring Harbor Laboratory
Date: 03-07-2021
DOI: 10.1101/2021.06.29.21259734
Abstract: Parkinson’s disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium, the UK Biobank, and NeuroX. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the brain cerebellum were also recognized to confer major PD risk. These findings warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Sophie Farrow.