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Ancestry-specific and multi-ancestry genome-wide association studies of restless legs syndrome

nature.com 30.10.2026 01:00 7 views

Restless legs syndrome is a neurological disorder that disrupts sleep and quality of life, but its genetics have mostly been studied in individuals of European ancestry. Here, we perform GWAS of restless legs syndrome using data from individuals of African, Latin American, and European ancestry, followed by a multi-ancestry meta-analysis. We leverage biobank-based cohorts that established RLS diagnosis using validated clinical criteria, allowing for precise phenotypic characterization.

We perform ancestry-specific association studies and post-GWAS analyses to prioritize candidate genes. Our analyses reveal ancestry differences in the genetics of restless legs syndrome. At the MEIS1 and BTBD9 loci, lead variants showed lower allele frequencies and did not reach genome-wide significance in African ancestry.

We identify ancestry-specific and shared risk loci, including novel associations near GYPC/TEX51 and PRIMA1 in African ancestry and ISX in Latin American ancestry. The European meta-analysis identifies 11 additional loci and replicates 50 previously reported associations. The combined multi-ancestry analysis finds ten new loci.

This multi-ancestry study broadens the genetic understanding of restless legs syndrome, and the absence or reduced frequency of key European restless legs syndrome alleles in individuals of African ancestry provides insights into known epidemiological differences. We thank Suleyman Can Akerman and Paige Jarreau for their meticulous editing of this manuscript and figures. This research was supported, in part, by the Intramural Research Program of the National Institutes of Health (NIH).

The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.

This work utilized the computational resources of the NIH HPC Biowulf cluster. (http://hpc.nih.gov). The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. In addition, the All of Us Research Program would not be possible without the partnership of its participants.

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