Brain connectivity reveals causal insights into epilepsy subtypes through mendelian randomization
image: A study flowchart employing bidirectional two-sample Mendelian randomization analysis to investigate causal relationships between epilepsy subtypes and brain functional and structural connectivity.
Credit: [Yi Zhou, Sun Yat-sen University]
A research team led by Professor Yi Zhou from Zhongshan School of Medicine, Sun Yat-sen University, in collaboration with Professor Ziyi Chen from the First Affiliated Hospital of Sun Yat-sen University, has uncovered new insights into the causal relationship between epilepsy and brain connectivity using genetic epidemiological approaches. The study was published in Health Data Science.
Epilepsy, a major neurological disorder affecting over 70 million people worldwide, has long been associated with abnormalities in brain functional and structural connectivity within resting-state networks. However, most existing evidence comes from observational studies, making it difficult to determine whether these changes are causes or consequences of the disease. This uncertainty has limited the development of targeted prevention and intervention strategies.
To address this challenge, the researchers conducted a bidirectional two-sample Mendelian randomization (MR) analysis using large-scale genome-wide association study (GWAS) data from nearly 70,000 individuals and brain connectivity data from over 48,000 participants. This approach leverages genetic variants as instrumental variables, enabling more robust causal inference by minimizing confounding and reverse causation.
The findings revealed that an increased genetic risk of generalized epilepsy is causally associated with altered functional connectivity in the dorsal attention network and the somatomotor network—key systems involved in attention and sensorimotor processing. In contrast, reverse analyses showed no evidence that changes in brain connectivity causally increase the risk of epilepsy.
“Our findings provide a crucial bridge between genetic susceptibility and large-scale brain network dysfunction,” said Professor Yi Zhou. “They support the concept of epilepsy as a network disorder and offer new directions for targeted interventions across different epilepsy subtypes.”
These results not only advance the understanding of epilepsy pathogenesis but also highlight potential brain network targets for future therapeutic strategies. The research team plans to integrate single-cell epigenomics and dynamic brain network modeling to further explore the underlying regulatory mechanisms and improve precision diagnosis and treatment.