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Lila Patel

Restless Legs Syndrome: Genetic Discoveries Advance Treatment and Risk Prediction

New Research Findings, ING,

Researchers at Helmholtz Munich and the Technical University of Munich (TUM) together with international collaborators have conducted the largest genetic investigation of the restless legs syndrome to date. Their findings, published in Nature Genetics, represent a significant advancement in deciphering the genetic basis of this disorder and open novel pathways for patient care.

Restless legs syndrome (RLS) is still an underrecognized disorder although 2 to 3% of elderly individuals of European ancestry warrant medical treatment. Patients suffer from chronic sleep deprivation, significantly reduced quality of life, and lower general health. This multifaceted disorder arises from complex interactions between genetic and environmental factors, yet its underlying biology remains largely elusive, hindering the development of effective treatment and prevention strategies. 

Harnessing the Power of Genetics 

A scientific team around Prof. Juliane Winkelmann, Director of the Institute of Neurogenomics at Helmholtz Munich and Director of the Institute of Human Genetics at TUM, Prof. Konrad Oexle, Group Leader at the Institute of Neurogenomics at Helmholtz Munich and TUM Professor, and researchers Dr. Steven Bell and Prof. Emanuele Di Angelantonio, from the Cardiovascular Epidemiology Unit at the University of Cambridge, now combined three genome-wide association studies, creating a powerful dataset with more than 100.000 patients to address these shortcomings. This effort included data from the International EU-RLS-GENE consortium, from the INTERVAL study, and from research at the personal genomics company 23andMe using data of 23andMe customers who consented to participate in research.  

The scientists raised the number of genetic risk loci for RLS from 22 to 164 and conducted the first sex-specific genetic investigation for RLS. Applying state-of-the-art statistical tools, the team identified potential new drug targets among candidate genes, along with elucidating risk factors and their interplay with RLS and other traits. Notably, they identified 13 genes targeted by approved drugs, offering promising avenues for repurposing medications for RLS treatment.  

“We have created a powerful dataset that has allowed us to identify a significant number of genetic risk loci and potential drug targets. These findings represent a major step forward in improving patient care,” says Dr. Barbara Schormair, Deputy Head of the Institute of Neurogenomics at Helmholtz Munich, main coordinator and one the first authors of the study. 

Deciphering disease risk 

Expanding beyond RLS, the study’s Mendelian randomization analysis indicated RLS as a risk factor for type 2 diabetes. Further investigations could therefore aid in tackling the growing type 2 diabetes epidemic. Moreover, Dr. Chen Zhao, Senior Research Associate at the Institute of Neurogenomics at Helmholtz Munich and the Institute of Human Genetics at TUM, and one the first authors of the study, employed machine learning techniques to predict RLS risk. This approach showcased optimal performance when incorporating both genetic and non-genetic factors, including their intricate non-linear interactions. Such insights could enhance risk prediction for various other prevalent illnesses. 

The findings of this study have the potential to significantly influence the lives of millions of RLS patients, offering a pathway towards the development of enhanced, personalized interventions aimed at effectively treating or even preemptively addressing the disease. 

“For the first time, we achieved the ability to sufficiently assess the risk for RLS. It has been a long journey, but now we are empowered to not only treat but to learn how to prevent this condition,” says Juliane Winkelmann, who has been a key scientist driving research on the genetics of RLS for more than 25 years. 

 

Original publication 

Schormair et al., 2024: Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology, and risk prediction. Nature Genetics. DOI: 10.1038/s41588-024-01763-1 

 

About the scientists:

Dr. Barbara Schormair, Deputy Head of the Institute of Neurogenomics at Helmholtz Munich and Senior Research Associate at the Institute of Human Genetics at TUM 

Dr. Chen Zhao, Senior Research Associate at the Institute of Neurogenomics at Helmholtz Munich and the Institute of Human Genetics at TUM 

Prof. Juliane Winkelmann, Director of the Institute of Neurogenomics at Helmholtz Munich and Director of the Institute of Human Genetics at TUM 

Prof. Konrad Oexle, Group Leader “Neurogenetic Systems Analysis” at the Institute of Neurogenomics at Helmholtz Munich and Professor at the Institute of Human Genetics at TUM 

Dr. Steven Bell, Senior Research Associate, Department of Oncology, at the University of Cambridge 

Prof. Emanuele Di Angelantonio, Professor of Clinical Epidemiology and Donor Health, Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care at the University of Cambridge 

Prof. Dr. Juliane Winkelmann

Head of Institute