Mobile Menu

Parkinson’s Disease-associated Variants Operate Through Gene Regulation

Written by Vered Smith, Science Writer 

Scientists have demonstrated that genetic variants associated with Parkinson’s disease perform regulatory functions. 

Researchers published a paper in BMC Medicine that elucidated the mechanism of action of SNPs previously associated with Parkinson’s disease (PD). They performed the first functional genomics study of PD, by combining a series of analyses and experiments to examine the functional effects of SNPs. They identified 44 transcription factor binding-disrupting SNPs in PD risk loci, and further validated that 15 of these had regulatory effects on other genes.  

Parkinson’s Disease  

PD is a neurodegenerative disease, characterised by Lewy bodies and loss of dopaminergic neurons in the substantia nigra. The core symptoms are motor-related, such as shaking, impaired balance and difficulty walking. However, they also include non-motor symptoms such as sleeping difficulties, cognitive impairments and psychiatric symptoms. Currently, treatments used in the clinic target symptoms of PD, but there are no treatments that slow neurodegeneration. Further understanding the mechanisms that cause PD is therefore crucial to enable development of new treatment strategies.  

The exact cause of PD is unknown, but it is thought to be a complex combination of both environmental and genetic factors. Specific genes that contribute to autosomal recessive or autosomal dominant PD have been identified, although these only account for a low number of cases, as most are non-Mendelian. Several genome-wide association studies (GWASs) have identified SNPs at risk loci, but these were in non-coding regions of the genome. The scientists used this data as a basis for understanding how these risk variants can lead to PD by regulating gene expression.  

Identification of Transcription Factor Binding-disrupting SNPs 

The scientists first processed Chip-Seq data from human brain or neuronal cells to sequence the DNA binding motifs of 30 transcription factors. They then identified transcription factor binding-disrupting SNPs using GWAS data.  

In total, they identified 44 SNPs that disrupted the ability of 12 transcription factors to bind their DNA binding sequence, 37 of which were in intergenic or intronic regions. Some transcription factors were affected by many SNPs: 12 SNPs disrupted CTCF binding, 11 disrupted POLR2A binding, 8 disrupted REST binding, and 7 disrupted RAD21 binding.  

Additionally, some SNPs disrupted the binding of more than one transcription factor. For example, 5 SNPs disrupted both CTCF and RAD21 binding. This suggested that the SNPs may lead to PD pathogenesis by affecting transcription factor binding.  

Validation of Regulatory Function of 15 SNPs  

The scientists randomly selected 15 of the 44 SNPs and performed a series of analyses and experiments on them, including reporter gene assays, transcription factor knockdowns, allelic-specific expression (ASE) analysis, and CRISPR-Cas9-mediated genome editing. The results indicated that the majority of those 15 SNPs function by regulating gene expression. 

Interestingly, one of these 15 SNPs (rs11575895) is located in the promoter or first exon (depending on the transcript) of MAPT, a gene previously associated with PD. 

Scientists consequently carried out eQTL analyses to link these SNPs to their potential target genes. Four of the target genes identified (AMT, DALRD3, GPNMB, and RHOBTB2) had significantly different mRNA expression levels in PD patients compared to controls, suggesting that SNPs may increase risk of PD by regulating these genes.  

New Avenues to Explore 

Future research includes investigating risk variants that affect transcription factors not included in this study, and researching other types of genetic variations, such as copy number variations and chromosome structural variants. Additionally, the candidate genes pinpointed in this study can be used to perform further functional characterisation and may in future lead to the development of new therapies.  

Image Credit: Canva