Disentangling the Genetic Relationship Between Sleep and Epilepsy
Abstract number :
1.124
Submission category :
12. Genetics / 12A. Human Studies
Year :
2024
Submission ID :
952
Source :
www.aesnet.org
Presentation date :
12/7/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Karen Oliver, PhD – University of Melbourne
Khang Le, MSc – Walter and Eliza Hall Institute
Rachel Stirling, PhD – University of Melbourne
Samuel Berkovic, MD, FRS – University of Melbourne
Ingrid Scheffer, MBBS, PhD, FRACP, FRS – University of Melbourne, Austin Hospital and Royal Children's Hospital, Florey and Murdoch Children’s Research Institutes
Philippa Karoly, PhD – Biomedical Engineering, University of Melbourne
Melanie Bahlo, PhD – The Walter and Eliza Hall Institute of Medical Research
Rationale: A close reciprocal relationship between sleep and epilepsy has long been appreciated. Sleep disorders are common in individuals with epilepsy, certain epilepsy syndromes predominantly or exclusively have seizures in sleep, and sleep deprivation often triggers seizures, particularly is patients with genetic generalised epilepsy (GGE). It is possible that genetic factors contribute to the complex relationship between epilepsy and sleep. Here, we investigated the shared genetic basis between multiple sleep traits and common epilepsies.
Methods: To analyse different aspects of shared genetic aetiology between sleep and epilepsy we applied linkage disequilibrium score (LDSC) regression and MiXeR. LDSC was applied to estimate genome-wide genetic correlations between all sleep traits and epilepsy phenotypes. For sleep traits we used genome-wide associate study (GWAS) data from 2019 on self-reported “morningness” chronotype (n=449,732 individuals), habitual short sleep (< 7h per 24h) (n=106,192), and the sleep disorder, insomnia (n=593,724 cases). For common epilepsies, we used the 2023 GWAS data for ‘all epilepsy’ (n=27,559 cases and 42,436 controls), focal epilepsy (n=14,939 cases) and GGE (n=6,952 cases). We then applied MiXeR to first estimate the number of variants influencing each trait (univariate analysis) and then quantify how many of these variants are shared between ‘all epilepsy’ and GGE with the three sleep traits (bivariate analysis); the focal epilepsy GWAS was underpowered for these analyses. Unlike LDSC, MiXeR does not require overlapping variants to have the same effect direction (e.g., it will capture variants that are protective for trait 1 yet increase risk for trait 2).
Results: Genetic correlation (rg) analysis with LDSC revealed significant positive correlations between short sleep with ‘all epilepsy’ (p=0.0007) and GGE (p=0.0002) (Figure 1A). Univariate MiXeR analyses estimated that sleep traits (9.4-8.6k trait-influencing variants) were almost three times more polygenic than ‘all epilepsy’ and GGE (2.8-3k variants) (Figure 1B). Bivariate MiXeR analyses estimated that > 90% (2.8k) of the 3.0k GGE-associated variants were shared with short sleep, whilst ‘all epilepsy’ was estimated to only share 1.9k loci (~60%). Conversely, an almost complete overlap of ‘all epilepsy’ variants ( > 95%) with “morningness” was estimated. The low genetic correlation (rg) between these two traits (rg=0.04) indicates mixed allelic effect directions amongst the estimated 2.7k shared variants.
Conclusions: Our study demonstrates a shared genetic architecture between sleep and epilepsy. A positive genetic correlation between short sleep duration and GGE was found, along with extensive genetic overlap between “morningness” chronotype (i.e., ‘being a morning person’) and epilepsy risk. Future work will disentangle these complex cross-trait relationships using additional techniques such as colocalization and fine-mapping. Enhancing our understanding of the genetic relationship between sleep and epilepsy will ensure that focused sleep counselling and targeted management are provided to patients with epilepsy.
Funding: NHMRC
Genetics