The FamilySleeps work programme consists of three work packages.
The aim of work package 1 is to optimise methods for characterising sleep and circadian phenotype. To date, we have developed and optimised monitoring systems that can address the issues of measuring rhythmicity and sleep in autistic children, providing a platform that can characterise the sleep phenotype, and facilitate the family-based genetic analyses in the later work packages of FamilySleeps. Remote sensors will be fitted in children’s bedrooms for 12 months. The sensors are unobtrusive, require no participant intervention, and acquire and store data passively over long time periods. The sensors are placed on a bed side table. Sleep and circadian rhythms will be inferred from patterns in movement detected by radar sensors over the study period. The sensor emits a band of radio waves and estimates movement based on the waves reflected from moving objects. The sensor also acquires data on (i) room temperature, (ii) air quality, (iii) noise levels, (iv) ambient light levels. We worked with our FamilySleeps Public and Patient Involvement (PPI) Panel throughout work package 1 and held focus groups to assess the feasibility and practically of our methods. This led to the change of one of our study protocols for measuring dim light melatonin.
The aim of work package 2 is to investigate disrupted circadian rhythms and disrupted sleep in autistic and non-autistic families. We have embedded PPI through our FamilySleeps PPI Panel in all aspects of our research development to ensure a solid foundation for research participant recruitment and retention in this work package. As part of work package two, we have also obtained access to data from the Adolescent Brain Cognitive Development (ABCD) Study that will allow us to address the hypotheses of FamilySleeps at a population level. The ABCD Study contains data on autism, circadian rhythms (accelerometery data) and health and lifestyle. These data will allow us to test whether disrupted circadian rhythms precede a diagnosis of autism or is associated with autistic traits.
The aim of work package 3 is to undertake genomic risk profiling in families. To progress this, we have investigated shared genetic influences that may contribute to circadian rhythm disruption and sleep issues in neurodevelopmental and neuropsychiatric conditions using UK Biobank data. We created genome-wide and pathway-based polygenic scores based on published large-scale genetic studies of autism, attention-deficit/hyperactivity disorder, schizophrenia, and bipolar disorder and tested their ability to predict chronotype and insomnia status of up to 409,630 participants in the UK Biobank based on their genotype data. Our findings from the polygenic score analysis reveal that polygenic scores for autism, schizophrenia, and bipolar disorder are associated with an evening chronotype, while polygenic scores for attention-deficit/hyperactivity disorder, autism, schizophrenia, and bipolar disorder are associated with insomnia. This indicates shared genetic variation between these phenotype pairs. Pathway analysis highlights the enrichment of shared genetic variation between chronotype and bipolar disorder in the NRF2-KEAP1 and mRNA splicing minor pathways. Previous studies have linked the NRF2-KEAP1 pathway to the pathology of bipolar disorder and schizophrenia. NRF2 and splicing components have both being previously reported to be rhythmically regulated by circadian clock genes. These results suggest a potential role for the NRF2-KEAP1 and mRNA splicing minor pathways in mediating circadian rhythm disturbances in bipolar disorder, providing insights into the genetic basis of sleep issues in neuropsychiatric conditions.