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Schormair, B. ; Zhao, C. ; Bell, S.* ; Didriksen, M.* ; Nawaz, M.S.* ; Schandra, N. ; Stefani, A.* ; Högl, B.* ; Dauvilliers, Y.* ; Bachmann, C.G.* ; Kemlink, D.* ; Sonka, K.* ; Paulus, W.* ; Trenkwalder, C.* ; Oertel, W.H. ; Hornyak, M.* ; Teder-Laving, M.* ; Metspalu, A.* ; Hadjigeorgiou, G.M.* ; Polo, O.* ; Fietze, I.* ; Ross, O.A.* ; Wszolek, Z.K.* ; Ibrahim, A.* ; Bergmann, M.* ; Kittke, V. ; Harrer, P. ; Dowsett, J.* ; Chenini, S.* ; Ostrowski, S.R.* ; Sørensen, E.* ; Erikstrup, C.* ; Pedersen, O.B.* ; Topholm Bruun, M.* ; Nielsen, K.R.* ; Butterworth, A.S.* ; Soranzo, N.* ; Ouwehand, W.H.* ; Roberts, D.J.* ; Danesh, J.* ; Burchell, B.* ; Furlotte, N.A.* ; Nandakumar, P.* ; Earley, C.J.* ; Ondo, W.G.* ; Xiong, L.* ; Desautels, A.* ; Perola, M.* ; Vodicka, P.* ; Dina, C.* ; Stoll, M.* ; Franke, A.* ; Lieb, W.* ; Stewart, A.F.R.* ; Shah, S.H.* ; Gieger, C. ; Peters, A. ; Rye, D.B.* ; Rouleau, G.A.* ; Berger, K.* ; Stefansson, H.* ; Ullum, H.* ; Stefansson, K.* ; Hinds, D.A.* ; di Angelantonio, E.* ; Oexle, K. ; Winkelmann, J.

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction.

Nat. Genet. 56, 1090-1099 (2024)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (rg = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82-0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Diagnostic-criteria; Association; Iron; Variants; Trial; Gwas
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
ISSN (print) / ISBN 1061-4036
e-ISSN 1546-1718
Zeitschrift Nature Genetics
Quellenangaben Band: 56, Heft: 6, Seiten: 1090-1099 Artikelnummer: , Supplement: ,
Verlag Nature Publishing Group
Verlagsort New York, NY
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Neurogenomics (ING)
Institute of Epidemiology (EPI)
POF Topic(s) 30205 - Bioengineering and Digital Health
30202 - Environmental Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-503200-001
G-504091-004
G-504000-010
G-504090-001
Förderungen Heart and Stroke Foundation of Canada
Charles University Cooperation Program in Neuroscience
RLS and AL Williams Jr. Family Foundations
Institute of Epidemiology and Social Medicine
Dean of the medical faculty, both at the University of Muenster
German Center for Cardiovascular Disease
University of Muenster from the German Restless Legs Society (RLS e.V. Deutsche Restless Legs Vereinigung)
Boehringer Ingelheim Pharma, Mundipharma Research, Roche Pharma, NeuroBioTec and UCB (Schwarz Pharma)
Helmholtz Zentrum Muenchen-German Research Center for Environmental Health
German Federal Ministry of Education and Research (BMBF), state of Bavaria
Munich Center of Health Sciences, Ludwig-Maximilians-Universitaet, LMUinnovativ
NIH Research Cambridge Biomedical Research Centre
National Institute for Health and Care Research (NIHR)
NIHR Bio Resource
Canadian Diabetes Association
Natural Sciences and Engineering Research Council of Canada
Deutsche Forschungsgemeinschaft
European Regional Development Fund
University of Thessaly
NIH-NIA
NIH-NINDS
Mayo Clinic Center for Regenerative Medicine
Albertson Parkinson's Research Foundation
National Institutes of Health National Institute of Neurological Disorders and Stroke
Mayo Clinic Neuroscience Focused Research Team (Cecilia and Dan Carmichael Family Foundation)
James C. and Sarah K. Kennedy Fund for Neurodegenerative Disease Research
Canadian Institutes of Health Research
NIHR Cambridge Biomedical Research Centre
NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR )
NIHR BTRU in Donor Health and Behaviour
Cancer Research UK
National Institute for Health Research (NIHR)
European Commission
NHSBT
Wellcome Trust
European Commission Framework Programme 7
NIHR
NIHR Senior Investigator Award
LX22 NPO
Danish Council for Independent Research-Medical Sciences
Danish Administrative Regions and Bio- and Genome Bank Denmark
Danish Blood Donor Research Foundation
Science and Technology Facilities Council
Wellcome. Regarding the INTERVAL data
UK Medical Research Council
British Heart Foundation
NIHR Cambridge BRC
Health Data Research UK
Engineering and Physical Sciences Research Council
Economic and Social Research Council
Department of Health and Social Care (England)
Chief Scientist Office of the Scottish Government Health and Social Care Directorates
Health and Social Care Research and Development Division (Welsh Government)
Public Health Agency (Northern Ireland)
Novo Nordisk Foundation Challenge Program
DOI 10.1038/s41588-024-01763-1
WOS ID 001444055500001
WOS ID 001242316600003
Scopus ID 85196230476
PubMed ID 38839884
Erfassungsdatum 2024-06-18
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