ArticleGenetics2016
Imputation of DNA Methylation Levels in the Brain Implicates a Risk Factor for Parkinson's Disease.
Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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.
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Who cites it
10 citing papers in PubMed.
- Diagnostic and Prognostic Value of Epigenetic Markers in Neurological Diseases. A Narrative Review.Cellular and molecular neurobiology · 2026Review
- An Overview of Epigenetic Changes in the Parkinson's Disease Brain.International journal of molecular sciences · 2024Review
- Understanding the pathogenesis of brain arteriovenous malformation: genetic variations, epigenetics, signaling pathways, and immune inflammation.Human genetics · 2023Review
- Alpha-synuclein overexpression induces epigenomic dysregulation of glutamate signaling and locomotor pathways.Human molecular genetics · 2022Article
- Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods.Environmental health perspectives · 2022Article
- DNA methylation as a mediator of genetic and environmental influences on Parkinson's disease susceptibility: Impacts of alpha-Synuclein, physical activity, and pesticide exposure on the epigenome.Frontiers in genetics · 2022Review
- The association of DAT gene methylation with striatal DAT availability in healthy subjects.EJNMMI research · 2021Article
- Differential blood DNA methylation across Lewy body dementias.Alzheimer's & dementia (Amsterdam, Netherlands) · 2021Article
- Nicotinamide-N-methyltransferase controls behavior, neurodegeneration and lifespan by regulating neuronal autophagy.PLoS genetics · 2018Article
- Mendelian Randomization Analysis Identifies CpG Sites as Putative Mediators for Genetic Influences on Cardiovascular Disease Risk.American journal of human genetics · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Understanding how genetic variation affects intermediate phenotypes, like DNA methylation or gene expression, and how these in turn vary with complex human disease provides valuable insight into disease etiology. However, intermediate phenotypes are typically tissue and developmental stage specific, making relevant phenotypes difficult to assay. Assembling large case-control cohorts, necessary to achieve sufficient statistical power to assess associations between complex traits and relevant intermediate phenotypes, has therefore remained challenging. Imputation of such intermediate phenotypes represents a practical alternative in this context. We used a mixed linear model to impute DNA methylation (DNAm) levels of four brain tissues at up to 1826 methylome-wide sites in 6259 patients with Parkinson's disease and 9452 controls from across five genome-wide association studies (GWAS). Six sites, in two regions, were found to associate with Parkinson's disease for at least one tissue. While a majority of identified sites were within an established risk region for Parkinson's disease, suggesting a role of DNAm in mediating previously observed genetic effects at this locus, we also identify an association with four CpG sites in chromosome 16p11.2. Direct measures of DNAm in the substantia nigra of 39 cases and 13 control samples were used to independently replicate these four associations. Only the association at cg10917602 replicated with a concordant direction of effect (P = 0.02). cg10917602 is 87 kb away from the closest reported GWAS hit. The employed imputation methodology implies that variation of DNAm levels at cg10917602 is predictive for Parkinson's disease risk, suggesting a possible causal role for methylation at this locus. More generally this study demonstrates the feasibility of identifying predictive epigenetic markers of disease risk from readily available data sets.
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Registered trials
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