Autism is a heritable neurodevelopmental condition marked by impaired social interaction, repetitive behavior, and co-occurring conditions. Sleep disturbances are common in autism. This study uses low-cost wearable devices to compare sleep, physical activity, and circadian behavior in autistic adults and their non-autistic relatives. We recruited 318 autistic individuals and 130 family members, collecting accelerometer data over 3 weeks (8249 days). Using a data-driven approach, we identified actimetry-derived features associated with autism. We examined 308 traits using the elastic net algorithm and linear mixed effects regressions. We identified 52 actimetry measures associated with autism (area under the curve: 0.812; confidence interval: 0.761–0.862), validated in a test set (area under the curve: 0.756; confidence interval: 0.700–0.813). Both mean and day-to-day variability in several measures (e.g., time spent sedentary, total light physical activity) were associated with autism. In autistic individuals, reduced physical activity during wake was more strongly associated with shorter sleep time than in non-autistic relatives (likelihood ratio: 41.6; p = 1.13e−10). Reduced physical activity in autistic individuals was linked to increased social impairment, as measured by the Social Responsiveness Scale. Long inactivity periods and lower physical activity levels were associated with autism, correlating with less sleep and later sleep onset. Interventional studies are needed to explore if improving sleep and physical activity can improve the quality of life for autistic individuals. Lay Abstract Autistic individuals frequently report problems with their sleep, though what aspects of sleep are most affected is not well understood. In this study, we recruited 318 adult autistic participants without intellectual disability and 130 of their non-autistic family members to measure their sleep, physical activity, and daily routines. Study participants wore accelerometer-based wrist-worn devices over 3 consecutive weeks to record their movement and activity. In total, 154 distinct physical activity, sleep, and behavioral traits were identified from the recordings, 52 of which were found to associate with autism. Many of these traits were related to physical activity, where autistic individuals were more likely to be less active for longer periods and have lower overall physical activity levels. Long periods of inactivity also associated with less sleep, with a stronger association in those with autism. For example, for every hour of inactivity, autistic participants had on average ~23 min less of sleep compared to ~17 min in their family members. Autistic individuals with lower levels of physical activity showed higher social impairment as measured by the Social Responsiveness Scale. Overall, lower physical activity may impair sleep and worsen the core features of autism. Interventional studies aimed to increase physical activity may improve the quality of life of autistic individuals.
COMPREHENSIVE GENETIC INVESTIGATION REVEALS HETEROGENEOUS PATHWAYS TO OBSTRUCTIVE SLEEP APNEA
ABSTRACT Obstructive sleep apnea (OSA) is a common, heritable disorder with diverse clinical presentations and etiologies. We conducted a genome-wide association meta-analysis of 492,107 individuals, including 46,028 OSA cases, identifying 14 genome-wide significant loci, eight of which are novel. Analyses adjusting for body mass index (BMI) revealed three loci independent of obesity, implicating alternative biological pathways contributing to disease. Integrative functional analyses, including chromatin interaction mapping, fine-mapping, and eQTL colocalization, prioritized candidate effector genes. Notably, implicated genes in chondrocytes were associated with craniofacial morphology in both mouse and human multivariate genotype-phenotype mapping, supporting a role for craniofacial structure in OSA risk. These findings highlight key genetic pathways (obesity-related, neurological, and craniofacial) underlying the development of OSA, offering new insights into its complex etiology.
Multisite validation of a simple electronic health record algorithm for identifying diagnosed obstructive sleep apnea