Genetics of Sleepwalking: Insights from whole exome sequencing.

Sleepwalking (SW) is a sleep disorder that belongs to the non-rapid eye movement (NREM) sleep family of parasomnias. Although linkage analyses in large families suggest that some forms of SW may follow a monogenic inheritance pattern, the genetic basis of SW has not been thoroughly investigated. The objective of this study was to investigate the role of rare genetic variants in sleepwalking by performing whole-exome sequencing (WES) in two independent cohorts. WES was performed on a cohort of 254 individuals diagnosed with SW (54.7% female, mean age: 39.1 {+/-} 10.7 years) and 124 control individuals were selected based on age and sex (52.4% female, all aged 18 years or older), from Montreal, Canada and Montpellier, France. To be included in the SW group, probands were required to have a primary complaint of SW, undergone at least one night of video-polysomnography, and to experience at least one parasomnia episode per month. By focusing on rare, potentially deleterious genetic variants, defined as having a minor allele frequency (MAF) [≤] 5% and a Combined Annotation Dependent Depletion (CADD) pathogenicity score [≥] 15, WES allowed us to detect novel contributors to the disorder that might be missed in studies focused on common variants. We first identified 99 genes significantly enriched in patients with SW compared to the control group, with 92 genes overlapping between the two clinical cohorts. By prioritizing genes expressed in the brain, we found a strong genetic overlap between the two populations, with 31 genes carrying rare variants in common, including the top 10 genes with the highest contribution to SW compared to controls: NPIPB13, SRRM2, SIRT1, CANT1, DPYSL5, ABCC10, ELF2, DPP9, RBM28 and MCF2L2. Results were validated using an independent control cohort from the CARTaGENE database, except for MCF2L2. The genes NPIPB13, SRRM2, and SIRT1 displayed the highest contributions in the population, with values of 13.1%, 7.5%, and 5.5%, respectively. This study represents an important step toward understanding the genetic architecture of sleepwalking, particularly the role of rare coding variants, in sleepwalking and opens new avenues for future research into the disorders underlying biological mechanisms.