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[Preprint]. 2023 May 30:2023.05.24.23290362.
doi: 10.1101/2023.05.24.23290362.

Genetic meta-analysis of levodopa induced dyskinesia in Parkinson's disease

Alejandro Martinez-Carrasco  1   2   3 , Raquel Real  1   2   3 , Michael Lawton  4 , Hirotaka Iwaki  5   6 , Manuela M X Tan  7 , Lesley Wu  1   2   3 , Nigel M Williams  8 , Camille Carroll  9 , Michele T M Hu  10   11 , Donald G Grosset  12 , John Hardy  3   13   14   15   16   17 , Mina Ryten  3   18   19 , Tom Foltynie  1 , Yoav Ben-Shlomo  4 , Maryam Shoai  3   13   14 , Huw R Morris  1   2   3
Affiliations

Genetic meta-analysis of levodopa induced dyskinesia in Parkinson's disease

Alejandro Martinez-Carrasco et al. medRxiv. .

Update in

  • Genetic meta-analysis of levodopa induced dyskinesia in Parkinson's disease.
    Martinez-Carrasco A, Real R, Lawton M, Iwaki H, Tan MMX, Wu L, Williams NM, Carroll C, Hu MTM, Grosset DG, Hardy J, Ryten M, Foltynie T, Ben-Shlomo Y, Shoai M, Morris HR. Martinez-Carrasco A, et al. NPJ Parkinsons Dis. 2023 Aug 31;9(1):128. doi: 10.1038/s41531-023-00573-2. NPJ Parkinsons Dis. 2023. PMID: 37652906 Free PMC article.

Abstract

Importance: Forty percent of Parkinson's disease patients develop levodopa-induced-dyskinesia (LiD) within 4 years of starting levodopa. The genetic basis of LiD remains poorly understood, and there have been few well powered studies.

Objective: To discover common genetic variants in the PD population that increase the probability of developing LiD.

Design setting and participants: We performed survival analyses to study the development of LiD in 5 separate longitudinal cohorts. We performed a meta-analysis to combine the results of genetic association from each study based on a fixed effects model weighting the effect sizes by the inverse of their standard error. The selection criteria was specific to each cohort. We studied individuals that were genotyped from each cohort and that passed our analysis specific inclusion criteria.

Main outcomes and measures: We measured the time for PD patients on levodopa treatment to develop LiD as defined by reaching a score higher or equal than 2 from the MDS-UPDRS part IV, item 1, which is equivalent to a range of 26%-50% of the waking time with dyskinesia. We carried out a genome-wide analysis of the hazard ratio and the association of genome-wide SNPs with the probability of developing LiD using cox proportional hazard models (CPH).

Results: This study included 2,784 PD patients of European ancestry, of whom 14.6% developed LiD. Consistent with previous studies, we found female gender (HR = 1.35, SE = 0.11, P = 0.007) and younger age at onset (HR = 1.8, SE = 0.14, P = 2 × 10 -5 ) to increase the probability of developing LiD. We identified three loci significantly associated with time-to-LiD onset. rs72673189 on chromosome 1 (HR = 2.77, SE = 0.18, P = 1.53 × 10 -8 ) located in the LRP8 locus, rs189093213 on chromosome 4 (HR = 3.06,, SE = 0.19, P = 2.81 × 10 -9 ) in the non-coding RNA LINC02353 locus, and rs180924818 on chromosome 16 (HR = 3.13, SE = 0.20, P = 6.27 × 10 -9 ) in the XYLT1 locus. Subsequent colocalization analyses on chromosome 1 identified DNAJB4 as a candidate gene associated with LiD through a change in gene expression. We computed a PRS based on our GWAS meta-analysis and found high accuracy to stratify between PD-LID and PD (AUC 83.9). We also performed a stepwise regression analysis for baseline features selection associated with LiD status. We found baseline anxiety status to be significantly associated with LiD (OR = 1.14, SE = 0.03, P = 7.4 × 10 -5 ). Finally, we performed a candidate variant analysis and found that genetic variability in ANKK1 ( rs1800497 , Beta = 0.24, SE = 0.09, P = 8.89 × 10 -3 ) and BDNF ( rs6265 , Beta = 0.19, SE = 0.10, P = 4.95 × 10 -2 ) loci were significantly associated with time to LiD in our large meta-analysis.

Conclusion: In this association study, we have found three novel genetic variants associated with LiD, as well as confirming reports that variability in ANKK1 and BDNF loci were significantly associated with LiD probability. A PRS nominated from our time-to-LiD meta-analysis significantly differentiated between PD-LiD and PD. In addition, we have found female gender, young PD onset and anxiety to be significantly associated with LiD.

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Conflict of interest statement

Competing Interests statement

H.R.M. reports paid consultancy from Roche. Research Grants from Parkinson’s UK, Cure Parkinson’s Trust, PSP Association, CBD Solutions, Drake Foundation, Medical Research Council (MRC), Michael J. Fox Foundation. Dr Morris is a co-applicant on a patent application related to C9ORF72 - Method for diagnosing a neurodegenerative disease (PCT/GB2012/052140).

D.G.G. has received grants from Michael’s Movers, the Neurosciences Foundation, and Parkinson’s UK, and honoraria from AbbVie, BIAL Pharma, Britannia Pharmaceuticals, GE Healthcare, and consultancy fees from Acorda Therapeutics and the Glasgow Memory Clinic.

M.T.M.H. received funding/grant support from Parkinson’s UK, Oxford NIHR BRC, University of Oxford, CPT, Lab10X, NIHR, Michael J. Fox Foundation, H2020 European Union, GE Healthcare and the PSP Association. She also received payment for Advisory Board attendance/consultancy for Biogen, Roche, Sanofi, CuraSen Therapeutics, Evidera, Manus Neurodynamica, Lundbeck.

Y.B.-S. has received grant funding from the MRC, NIHR, Parkinson’s UK, NIH, and ESRC. C.C receives salary from University Hospitals Plymouth NHS Trust and National Institute of Health and Care Research. She has received advisory, consulting or lecture fees from AbbVie, Bial, Scient, Orkyn, Abidetex, UCB, Pfizer, EverPharma, Lundbeck, Global Kinetics, Kyowa Kirin, Britannia and Medscape, and research funding from Parkinson’s UK, Edmond J Safra Foundation, National Institute of Health and Care Research and Cure Parkinson’s. J.H. is supported by the UK Dementia Research Institute, which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK. He is also supported by the MRC, Wellcome Trust, Dolby Family Fund, National Institute for Health Research University, College London Hospitals Biomedical Research Centre.

All other authors report no competing interests.

Figures

Figure 1.
Figure 1.. LiD GWSS meta-analysis Manhattan plot.
The GWSS was conducted using a Cox proportional hazards model in each cohort separately, and results were meta-analysed. Red dots indicate the variant with the lowest P-value at each genome-wide significant genetic locus. Genome-wide significance was set at 5×10−8 and is indicated by the red dashed line.
Figure 2.
Figure 2.. Forest plots of top hits of GWSS meta-analysis.
a, LRP8 rs72673189 variant (I2 = 0 ; Cochran’s Q test: 2 = 0.24 , df = , P = 1.53e-08). b, LINC02353 rs189093213 variant (I2 = 21.4 ; 2 = 5.09, df = , P = 1.67e-09). c, LINC02353 rs180924818 variant (I2 = 0; 2 = 0.77, df = 3, P = 6.27e-09). HR hazard ratio, CI confidence interval, P p-value, r2 imputation info score.
Figure 3.
Figure 3.. Survival curves of candidate SNPs.
a, Kaplan-Meier curve for Survival probability (LiD free probability) based on rs72673189 carrier status in PD patients. b, Kaplan-Meier curve for Survival probability (LiD free probability) based on rs189093213 carrier status in PD patients. c, Kaplan-Meier curve for Survival probability (LiD free probability) based on rs180924818 carrier status in PD patients. The blue curve represents genetic variant carriers, whereas the yellow curve represents non-carriers. p = p-value. Number at risk represents the number of PD patients remaining on the study at the different time points (0, 5, 10, 15 years). The colour expansion on each curve represents the confidence interval (CI).
Figure 4.
Figure 4.. LRP8 locus fine-mapping and brain cell type specific regulatory marks.
From top to bottom, locus plot, transcript plot, the fine-mapping nominated variants across fine-mapping tools, brain cell type specific regulatory element marks. In the locus plot, the SNPs are coloured in red as LD (given by R2) increases, and blue as the LD decreases. In the fine-mapping track, we highlight the SNPs with the highest posterior probabilities for each fine-mapping tool (ABF, FINEMAP, SUSIE, POLYFUN_SUSIE). In addition, we highlight in yellow the Consensus SNP with the highest mean Posterior Probability (mean). In the cell type specific regulatory element marks, the first 4 rows are the density marks (y-axis) from ATAC-seq assay (in pink), and CHIP-seq assays (H3K27ac in blue, and H3K4me3 in cyan), in astrocytes, microglia, neurons, and oligodendrocytes. The next four rows are the distal anchored chromatin loops (black curves). We see how, only in neurons, there is a chromatin loop forming from the LRP8 GWS and the fine-mapped consensus variant towards the LRP8 promoter (purple).
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