Evidence map›Paper›PMID 37425912›Full record

ArticlemedRxiv : the preprint server for health sciences2023

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

Alejandro Martinez-Carrasco, Raquel Real, Michael Lawton, Hirotaka Iwaki, Manuela M X Tan, Lesley Wu, Nigel M Williams, Camille Carroll, Michele T M Hu, Donald G Grosset and 6 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 11 institutions in 5 countries.

Alejandro Martinez-CarrascoDepartment of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, UK.
Raquel RealDepartment of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, UK.
Michael LawtonPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Hirotaka IwakiCenter for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
Manuela M X TanDepartment of Neurology, Oslo University Hospital, Oslo, Norway.
Lesley WuDepartment of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, UK.
Nigel M WilliamsInstitute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
Camille CarrollFaculty of Health, University of Plymouth, Plymouth, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle, UK.
Michele T M HuNuffield Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK.
Donald G GrossetSchool of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
John HardyAligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815.
Mina RytenAligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815.
Tom FoltynieDepartment of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, UK.
Yoav Ben-ShlomoPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Maryam ShoaiAligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815.
Huw R MorrisDepartment of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, UK.
National Hospital for Neurology and Neurosurgery · GBUniversity of Bristol · GBCardiff University · GBGreat Ormond Street Hospital · GBHong Kong University of Science and Technology · HKNational Institutes of Health · USNewcastle University · GBOslo University Hospital · NOUK Dementia Research Institute · GBUniversity of Glasgow · GBUniversity of Oxford · GB

Funding

Medical Research Council MR/L010305/1Wellcome Trust
6 · The paper itself

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, 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.

Identifiers

PMID37425912
PMCPMC10327264
OpenAlexW4378672807

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.