Sleep-associated Genes Overlap with Epilepsy and Other Cns-associated Genes
Abstract number :
2.322
Submission category :
12. Genetics / 12A. Human Studies
Year :
2022
Submission ID :
2204056
Source :
www.aesnet.org
Presentation date :
12/4/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:23 AM
Authors :
Jonathan Gaillard, MD – University of Michigan; Gita Gupta, MD – Pulmonology Fellow, Pediatrics, Division of Pediatric Pulmonology, University of Michigan; Heather Mefford, MD, PhD – Center for Pediatric Neurological Disease Research – St. Jude Children's Research Hospital; Louise O'Brien, PhD, MS – Associate Professor, Neurology, Obstetrics and Gynecology and Oral and Maxillofacial Surgery, University of Michigan; Renée Shellhaas, MD, MS – Clinical Professor, Pediatrics, Division of Pediatric Neurology, University of Michigan; Louis Dang, MD, PhD – Assistant Professor, Pediatrics, Division of Pediatric Neurology, University of Michigan
Rationale: Although sleep and epilepsy have a close, bidirectional relationship, the mechanisms linking epilepsy and sleep remain poorly understood. Many people with epilepsy report difficulty sleeping or excessive daytime sleepiness, and it is unclear whether this is due to the seizures, the epilepsy treatment, or an underlying genetic epilepsy etiology. We hypothesized that epilepsy and sleep disorders share underlying genetic causes. We used genome-wide association study (GWAS) data from the Sleep Database Knowledge Portal (SDKP), to evaluate associations between sleep-associated genes and known epilepsy genes, as well as genes associated with other neurological conditions and cell types of the CNS.
Methods: Gene sets for conditions and cell types: Gene sets from diagnostic gene panels for neurological conditions and a random set of 1200 genes were generated. Sets of genes highly expressed in specific CNS cell types (neurons, astrocytes, oligodendrocytes, microglia, and endothelial cells) were taken from single-cell RNA-sequencing data (McKenzie et al., 2018).
Sleep GWAS data extraction: The SDKP provides summary statistics for GWAS data for each single nucleotide polymorphism (SNP) across a range of sleep phenotypes (Table 1). For each gene in each gene set, we extracted the p-value for each SNP to reveal the strength of association of that SNP to its respective sleep phenotype. We calculated the minimum p-value among all the SNPs and all the sleep phenotypes for each gene to compare the distribution of these values between different gene sets.
Statistics: After -log10 transformation, the distribution of minimum p-values for the random and epilepsy gene sets were compared to each other. Additional comparisons were performed between the random gene set to gene sets associated with other neurological conditions and CNS cells. Overlapping genes between any two sets were removed from each gene set prior to analysis. We used the Wilcoxon rank sum test, and the resulting p-values were adjusted using Bonferroni method, with padj-value < 0.05 as significant.
Genetics