A recent study identified 164 risk loci for restless legs syndrome, significantly increasing the number from previous research, and highlighted druggable genes like glutamate receptors 1 and 4.
The study, published in Nature Genetics, has elucidated the genetic architecture and potential therapeutic targets for restless legs syndrome (RLS), a condition affecting up to 10% of older adults. This condition is often associated with delayed diagnosis and insufficient treatment. Researchers conducted a genome-wide association meta-analysis involving 116,647 individuals with RLS and 1,546,466 controls of European ancestry.
The number of known RLS risk loci increased from previous studies, identifying 164 risk loci, with three on the X chromosome. Genetic predispositions to RLS were found to be similar between sexes, with a high genetic correlation (rg = 0.96). The analysis revealed druggable genes (i.e., glutamate receptors 1 and 4), indicating these could serve as novel therapeutic targets.
Gene set enrichment analyses identified pathways related to neurodevelopment, neuron migration, axon guidance, and synapse formation. Enrichment was particularly strong in fetal and prenatal stages, suggesting critical periods where genetic contributors to RLS susceptibility act.
Mendelian randomization analyses indicated that RLS may be a causal risk factor for diabetes and other conditions. Furthermore, machine learning models integrating genetic and non-genetic data demonstrated an area under the curve ranging from 0.82 to 0.91 in predicting RLS risk. These findings suggest that such integrative approaches could enhance risk prediction and identify individuals at elevated risk for RLS more effectively.
Clinical implications of this study include the identification of druggable targets such as glutamate receptors and the cholecystokinin B receptor, which could lead to new treatment options. Small trials have shown promising responses to glutamate receptor antagonists in RLS, indicating potential for repurposing existing drugs.
However, the study acknowledges limitations, including the need for larger, diverse cohorts and detailed longitudinal data to further understand the environmental and genetic interactions in RLS.
Full disclosures are available in the original study.
