1
|
Harrer P, Mirza-Schreiber N, Mandel V, Roeber S, Stefani A, Naher S, Wagner M, Gieger C, Waldenberger M, Peters A, Högl B, Herms J, Schormair B, Zhao C, Winkelmann J, Oexle K. Epigenetic Association Analyses and Risk Prediction of RLS. Mov Disord 2023; 38:1410-1418. [PMID: 37212434 DOI: 10.1002/mds.29440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 04/12/2023] [Accepted: 04/26/2023] [Indexed: 05/23/2023] Open
Abstract
BACKGROUND As opposed to other neurobehavioral disorders, epigenetic analyses and biomarkers are largely missing in the case of idiopathic restless legs syndrome (RLS). OBJECTIVES Our aims were to develop a biomarker for RLS based on DNA methylation in blood and to examine DNA methylation in brain tissues for dissecting RLS pathophysiology. METHODS Methylation of blood DNA from three independent cohorts (n = 2283) and post-mortem brain DNA from two cohorts (n = 61) was assessed by Infinium EPIC 850 K BeadChip. Epigenome-wide association study (EWAS) results of individual cohorts were combined by random-effect meta-analysis. A three-stage selection procedure (discovery, n = 884; testing, n = 520; validation, n = 879) established an epigenetic risk score including 30 CpG sites. Epigenetic age was assessed by Horvath's multi-tissue clock and Shireby's cortical clock. RESULTS EWAS meta-analysis revealed 149 CpG sites linked to 136 genes (P < 0.05 after Bonferroni correction) in blood and 23 CpG linked to 18 genes in brain (false discovery rate [FDR] < 5%). Gene-set analyses of blood EWAS results suggested enrichments in brain tissue types and in subunits of the kainate-selective glutamate receptor complex. Individual candidate genes of the brain EWAS could be assigned to neurodevelopmental or metabolic traits. The blood epigenetic risk score achieved an area under the curve (AUC) of 0.70 (0.67-0.73) in the validation set, comparable to analogous scores in other neurobehavioral disorders. A significant difference in biological age in blood or brain of RLS patients was not detectable. CONCLUSIONS DNA methylation supports the notion of altered neurodevelopment in RLS. Epigenetic risk scores are reliably associated with RLS but require even higher accuracy to be useful as biomarkers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Philip Harrer
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Nazanin Mirza-Schreiber
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Vanessa Mandel
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Sigrun Roeber
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-Universität, Munich, Germany
| | - Ambra Stefani
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Shamsun Naher
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Matias Wagner
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Birgit Högl
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Jochen Herms
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Barbara Schormair
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Chen Zhao
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Chair of Neurogenetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Konrad Oexle
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| |
Collapse
|
2
|
Murat K, Grüning B, Poterlowicz PW, Westgate G, Tobin DJ, Poterlowicz K. Ewastools: Infinium Human Methylation BeadChip pipeline for population epigenetics integrated into Galaxy. Gigascience 2020; 9:5836679. [PMID: 32401319 PMCID: PMC7219210 DOI: 10.1093/gigascience/giaa049] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 02/24/2020] [Accepted: 04/21/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Infinium Human Methylation BeadChip is an array platform for complex evaluation of DNA methylation at an individual CpG locus in the human genome based on Illumina's bead technology and is one of the most common techniques used in epigenome-wide association studies. Finding associations between epigenetic variation and phenotype is a significant challenge in biomedical research. The newest version, HumanMethylationEPIC, quantifies the DNA methylation level of 850,000 CpG sites, while the previous versions, HumanMethylation450 and HumanMethylation27, measured >450,000 and 27,000 loci, respectively. Although a number of bioinformatics tools have been developed to analyse this assay, they require some programming skills and experience in order to be usable. RESULTS We have developed a pipeline for the Galaxy platform for those without experience aimed at DNA methylation analysis using the Infinium Human Methylation BeadChip. Our tool is integrated into Galaxy (http://galaxyproject.org), a web-based platform. This allows users to analyse data from the Infinium Human Methylation BeadChip in the easiest possible way. CONCLUSIONS The pipeline provides a group of integrated analytical methods wrapped into an easy-to-use interface. Our tool is available from the Galaxy ToolShed, GitHub repository, and also as a Docker image. The aim of this project is to make Infinium Human Methylation BeadChip analysis more flexible and accessible to everyone.
Collapse
Affiliation(s)
- Katarzyna Murat
- Center for Skin Sciences, University of Bradford, Richmond Road, Bradford BD7 1DP, UK
| | - Björn Grüning
- Freiburg Galaxy Team, University of Freiburg, Fahnenbergplatz, 79085 Freiburg im Breisgau, Germany
| | | | - Gillian Westgate
- Center for Skin Sciences, University of Bradford, Richmond Road, Bradford BD7 1DP, UK
| | - Desmond J Tobin
- The Charles Institute for Dermatology, Belfield, School of Medicine, University College Dublin, Ireland
| | - Krzysztof Poterlowicz
- Center for Skin Sciences, University of Bradford, Richmond Road, Bradford BD7 1DP, UK
| |
Collapse
|