TY - JOUR
T1 - Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction
AU - 23andMe Research Team
AU - D.E.S.I.R. study group
AU - Schormair, Barbara
AU - Zhao, Chen
AU - Bell, Steven
AU - Didriksen, Maria
AU - Nawaz, Muhammad S.
AU - Schandra, Nathalie
AU - Stefani, Ambra
AU - Högl, Birgit
AU - Dauvilliers, Yves
AU - Bachmann, Cornelius G.
AU - Kemlink, David
AU - Sonka, Karel
AU - Paulus, Walter
AU - Trenkwalder, Claudia
AU - Oertel, Wolfgang H.
AU - Hornyak, Magdolna
AU - Teder-Laving, Maris
AU - Metspalu, Andres
AU - Hadjigeorgiou, Georgios M.
AU - Polo, Olli
AU - Fietze, Ingo
AU - Ross, Owen A.
AU - Wszolek, Zbigniew K.
AU - Ibrahim, Abubaker
AU - Bergmann, Melanie
AU - Kittke, Volker
AU - Harrer, Philip
AU - Dowsett, Joseph
AU - Chenini, Sofiene
AU - Ostrowski, Sisse Rye
AU - Sørensen, Erik
AU - Erikstrup, Christian
AU - Pedersen, Ole B.
AU - Topholm Bruun, Mie
AU - Nielsen, Kaspar R.
AU - Butterworth, Adam S.
AU - Soranzo, Nicole
AU - Ouwehand, Willem H.
AU - Roberts, David J.
AU - Danesh, John
AU - Burchell, Brendan
AU - Furlotte, Nicholas A.
AU - Nandakumar, Priyanka
AU - Potier, Louis
AU - Bonnefond, Amélie
AU - Earley, Christopher J.
AU - Ondo, William G.
AU - Xiong, Lan
AU - Desautels, Alex
AU - Perola, Markus
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/6
Y1 - 2024/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85196230476&partnerID=8YFLogxK
U2 - 10.1038/s41588-024-01763-1
DO - 10.1038/s41588-024-01763-1
M3 - Article
C2 - 38839884
AN - SCOPUS:85196230476
SN - 1061-4036
VL - 56
SP - 1090
EP - 1099
JO - Nature Genetics
JF - Nature Genetics
IS - 6
ER -