Technical University of Munich: Largest Genetic Study on Restless Legs Syndrome Unveils New Treatment Approaches
Restless legs syndrome (RLS) is still an underrecognized disorder, although two to three percent of elderly individuals of European ancestry warrant medical treatment. Patients with restless legs syndrome experience a strong urge to move at night and suffer from unpleasant sensations such as pain or tingling in the legs. As a result, many 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.
“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 Prof. Juliane Winkelmann Director of the Institute of Human Genetics at TUM and the Institute of Neurogenomics at Helmholtz Munich. She has been been a key scientist driving research on the genetics of RLS for more than 25 years.
“A major step forward in improving patient care”
“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 the main coordinator of the study, Dr. Barbara Schormair, Deputy Head of the Institute of Neurogenomics at Helmholtz Munich.
The team led by Prof. Winkelmann, Prof. Konrad Oexle, TUM professor and group leader at the Institute of Neurogenomics at Helmholtz Munich, as well as Dr. Steven Bell and Prof. Emanuele Di Angelantonio from the Cardiovascular Epidemiology Unit at the University of Cambridge, combined three genome-wide association studies on RLS for their study, which was published in “Nature Genetics”. In this way, the researchers have created a powerful dataset with more than 100.000 patients. 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 customers who consented to participate in research.
Potential targets for drugs identified
Through their study, the scientists raised the number of known genetic risk loci for RLS, i.e. regions of our genome that contain changes associated with an increased risk of developing the disease, from 22 to 164. Applying state-of-the-art statistical tools, the team identified potential new drug targets among candidate genes including 13 genes targeted by approved drugs, offering promising avenues for repurposing medications for RLS treatment.
Risk factor for type 2 diabetes
The study also indicates 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.
According to the researchers, 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.