scholarly journals Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Catherine S. Storm ◽  
Demis A. Kia ◽  
Mona M. Almramhi ◽  
Sara Bandres-Ciga ◽  
Chris Finan ◽  
...  

AbstractParkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson’s disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson’s disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson’s disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson’s disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson’s disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson’s disease drug development.

Author(s):  
Catherine S. Storm ◽  
Demis A. Kia ◽  
Mona Almramhi ◽  
Sara Bandres-Ciga ◽  
Chris Finan ◽  
...  

SummaryParkinson’s disease (PD) is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation using human evidence. Here, we use Mendelian randomization to investigate more than 3000 genes that encode druggable proteins, seeking to predict their efficacy as drug targets for PD. We use expression and protein quantitative trait loci for druggable genes to mimic exposure to medications, and we examine the causal effect on PD risk (in two large case-control cohorts), PD age at onset and progression. We propose 23 potential drug targeting mechanisms for PD, of which four are repurposing opportunities of already-licensed or clinical-phase drugs. We identify two drugs which may increase PD risk. Importantly, there is remarkably little overlap between our MR-supported drug targeting mechanisms to prevent PD and those that reduce PD progression, suggesting that molecular mechanisms driving disease risk and progression differ. Drugs with genetic support are considerably more likely to be successful in clinical trials, and we provide compelling genetic evidence and an analysis pipeline that can be used to prioritise drug development efforts for PD.


2020 ◽  
Author(s):  
Catherine S. Storm ◽  
Demis A. Kia ◽  
Mona Almramhi ◽  
Dilan Athauda ◽  
Stephen Burgess ◽  
...  

AbstractBackgroundExenatide is a glucagon-like peptide 1 receptor (GLP1R) agonist used in type 2 diabetes mellitus that has shown promise for Parkinson’s disease in a phase II clinical trial. Drugs with genetic evidence are more likely to be successful in clinical trials. In this study we investigated whether the genetic technique Mendelian randomization (MR) can “rediscover” the effects of exenatide on diabetes and weight, and predict its efficacy for Parkinson’s disease.MethodsWe used genetic variants associated with increased expression of GLP1R in blood to proxy exenatide, as well as variants associated with expression of DPP4, TLR4 and 15 genes thought to act downstream of GLP1R or mimicking alternative actions of GLP-1 in blood and brain tissue. Using an MR approach, we predict the effect of exenatide on type 2 diabetes risk, body mass index (BMI), Parkinson’s disease risk and several Parkinson’s disease progression markers.ResultsWe found that genetically-raised GLP1R expression in blood was associated with lower BMI and possibly type 2 diabetes mellitus risk, but not Parkinson’s disease risk, age at onset or progression. Reduced DPP4 expression in brain tissue was significantly associated with increased Parkinson’s disease risk.ConclusionsWe demonstrate the usefulness of MR using expression data in predicting the efficacy of a drug and exploring its mechanism of action. Our data suggest that GLP-1 mimetics like exenatide, if ultimately proven to be effective in Parkinson’s disease, will be through a mechanism that is independent of GLP1R in blood.


Brain ◽  
2019 ◽  
Vol 143 (1) ◽  
pp. 234-248 ◽  
Author(s):  
Cornelis Blauwendraat ◽  
Xylena Reed ◽  
Lynne Krohn ◽  
Karl Heilbron ◽  
Sara Bandres-Ciga ◽  
...  

Abstract Parkinson’s disease is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of Parkinson’s disease, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as Parkinson’s disease and Lewy body dementia. These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4- to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known Parkinson’s disease risk variants. Using multiple, large case-control datasets, totalling 217 165 individuals (22 757 Parkinson’s disease cases, 13 431 Parkinson’s disease proxy cases, 622 Lewy body dementia cases and 180 355 controls), we identified 1691 Parkinson’s disease cases, 81 Lewy body dementia cases, 711 proxy cases and 7624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent Parkinson’s disease-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall Parkinson’s disease genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S induced pluripotent cell-derived neurons were shown to have decreased cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated Parkinson’s disease risk and age at onset, although the total contribution of common genetics variants is not large. We further demonstrate that common variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have implications for selection of GBA carriers for therapeutic interventions.


2020 ◽  
Vol 88 (5) ◽  
pp. 1043-1047
Author(s):  
Dylan M. Williams ◽  
Sara Bandres‐Ciga ◽  
Karl Heilbron ◽  
David Hinds ◽  
Alastair J. Noyce ◽  
...  

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Kimberley J. Billingsley ◽  
◽  
Ines A. Barbosa ◽  
Sara Bandrés-Ciga ◽  
John P. Quinn ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Carmen Domínguez-Baleón ◽  
Jue-Sheng Ong ◽  
Clemens R. Scherzer ◽  
Miguel E. Rentería ◽  
Xianjun Dong

AbstractPrevious observational studies have identified correlations between Parkinson’s disease (PD) risk and lifestyle factors. However, whether or not those associations are causal remains unclear. To infer causality between PD risk and smoking or alcohol intake, we conducted a two-sample Mendelian randomization study using genome-wide association study summary statistics from the GWAS & Sequencing Consortium of Alcohol and Nicotine use study (1.2 million participants) and the latest meta-analysis from the International Parkinson’s Disease Genomics Consortium (37,688 PD cases and 18,618 proxy-cases). We performed sensitivity analyses, including testing for pleiotropy with MR-Egger and MR-PRESSO, and multivariable MR modeling to account for the genetic effects of competing substance use traits on PD risk. Our results revealed causal associations of alcohol intake (OR 0.79; 95% CI 0.65–0.96; p = 0.021) and smoking continuation (which compares current vs. former smokers) (OR 0.64; 95% CI 0.46–0.89; p = 0.008) with lower PD risk. Multivariable MR analyses showed that the causal association between drinks per week and PD is unlikely due to confounding by smoking behavior. Finally, frailty analyses suggested that the causal effects of both alcohol intake and smoking continuation on PD risk estimated from MR analysis are not explained by the presence of survival bias alone. Our findings support the role of smoking as a protective factor against PD, but only when comparing current vs. former smokers. Similarly, increased alcohol intake had a protective effect over PD risk, with the alcohol dehydrogenase 1B (ADH1B) locus as a potential candidate for further investigation of the mechanisms underlying this association.


2020 ◽  
Author(s):  
Manuela MX Tan ◽  
Michael A Lawton ◽  
Edwin Jabbari ◽  
Regina H Reynolds ◽  
Hirotaka Iwaki ◽  
...  

Background: There are currently no treatments that stop or slow the progression of Parkinson's disease (PD). Case-control genome-wide association studies (GWASs) have identified variants associated with disease risk, but not progression. Objective: To identify genetic variants associated with PD progression in GWASs. Methods: We analysed three large, longitudinal cohorts: Tracking Parkinson's, Oxford Discovery, and the Parkinson's Progression Markers Initiative. We included clinical data for 3,364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington's disease, where we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analysed in linear regressions in GWASs. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis. Results: There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ϵ4 tagging variant, rs429358, was significantly associated with the rate of composite and cognitive progression in PD. No single variants were associated with motor progression. However in gene-based analysis, variation across ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (p=5.3 x 10^-6). Conclusions: This new method in PD improves measurement of symptom progression. We provide strong evidence that the APOE ϵ4 allele drives progressive cognitive impairment in PD. We have also reported loci of interest which need to be tested in further studies.


2010 ◽  
Vol 81 (11) ◽  
pp. e58-e58
Author(s):  
M. Perera ◽  
Y. Ben Shlomo ◽  
M. M. Wickremaratchi ◽  
R. Salmon ◽  
H. R. Morris

2021 ◽  
Author(s):  
Anni Moore ◽  
Sara Bandres-Ciga ◽  
Cornelis Blauwendraat ◽  
Monica Diez-Fairen

AbstractParkinson’s disease (PD) is a progressive neurological disorder caused by both genetic and environmental factors. A recent finding has suggested an association between KTN1 genetic variants and changes in its expression in the putamen and substantia nigra brain regions and an increased risk for PD. Here, we examine the link between PD susceptibility and KTN1 using individual-level genotyping data and summary statistics from the most recent genome-wide association studies (GWAS) for PD risk and age at onset from the International Parkinson’s Disease Genomics Consortium (IPDGC), as well as whole-genome sequencing data from the Accelerating Medicines Partnership Parkinson’s disease (AMP-PD) initiative. To investigate the potential effect of changes in KTN1 expression on PD compared to healthy individuals, we further assess publicly available expression quantitative trait loci (eQTL) results from GTEx v8 and BRAINEAC and transcriptomics data from AMP-PD. Overall, we found no genetic associations between KTN1 and PD in our cohorts but found potential evidence of differences in mRNA expression, which needs to be further explored.


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