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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378041%3A_____%2F24%3A00587704" target="_blank" >RIV/68378041:_____/24:00587704 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11110/24:10483278 RIV/00216208:11140/24:10483278 RIV/00064165:_____/24:10483278
Result on the web
<a href="https://www.nature.com/articles/s41588-024-01763-1" target="_blank" >https://www.nature.com/articles/s41588-024-01763-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41588-024-01763-1" target="_blank" >10.1038/s41588-024-01763-1</a>

Result language
angličtina
Original language name
Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction
Original language description
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.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30204 - Oncology

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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