Periodic Reporting for period 2 - FamilySleeps (Disrupted Circadian Rhythms in Families - an Endophenotype of Autism Spectrum Disorder?)
Reporting period: 2022-12-01 to 2024-05-31
Sleep disturbances are highly prevalent in children with neurodevelopmental conditions, and this adversely impacts the whole family’s wellbeing. While the origins of neurodevelopmental conditions are considered largely genetic, the mechanisms that underlie sleep disruption, and their relationship to neurodevelopment, is relatively unexplored. Chronotype is our daily preference for morning or evening time, and a recent large-scale genome-wide association study highlighted its significant relationship with the most common neurodevelopmental condition, autism spectrum disorder (ASD, herein referred to as autism). Chronotype is an indication of our circadian rhythms, which alongside environmental factors, influences sleep disturbance. However, challenges in obtaining objective circadian rhythm and sleep timing measurements in autism mean we are uncertain about their role.
The FamilySleeps research programme will challenge the view that sleep disruption in autistic children is driven only by environmental and behavioural factors. FamilySleeps will address two hypotheses;
1) that a disruption to circadian rhythms is an endophenotype of autism
2) that a disruption to circadian rhythms has an independent common genetic component.
To test these hypotheses, FamilySleeps will ask if autistic children show sleep and circadian rhythm disturbances compared to non-autistic children; if unaffected siblings have disturbed sleep and circadian rhythm patterns; and if sleep and circadian rhythm disruption correlates with a genetic predisposition to autism.
FamilySleeps will apply technologically advanced and non-invasive sensors to obtain a one-year longitudinal objective measure of sleep disturbances and circadian rhythms in 60 families. We will generate genomic risk scores to establish the genetic link with autism. FamilySleeps will lead a breakthrough in understanding the role of circadian rhythms in autism, which has implications for breakthroughs in other neurodevelopmental conditions, and understanding a process fundamental to life – sleep.
The FamilySleeps research programme will challenge the view that sleep disruption in autistic children is driven only by environmental and behavioural factors. FamilySleeps will address two hypotheses;
1) that a disruption to circadian rhythms is an endophenotype of autism
2) that a disruption to circadian rhythms has an independent common genetic component.
To test these hypotheses, FamilySleeps will ask if autistic children show sleep and circadian rhythm disturbances compared to non-autistic children; if unaffected siblings have disturbed sleep and circadian rhythm patterns; and if sleep and circadian rhythm disruption correlates with a genetic predisposition to autism.
FamilySleeps will apply technologically advanced and non-invasive sensors to obtain a one-year longitudinal objective measure of sleep disturbances and circadian rhythms in 60 families. We will generate genomic risk scores to establish the genetic link with autism. FamilySleeps will lead a breakthrough in understanding the role of circadian rhythms in autism, which has implications for breakthroughs in other neurodevelopmental conditions, and understanding a process fundamental to life – sleep.
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.
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.
The FamilySleeps work programme will progress the following:
For work package one, we have secured access to state of the art and appropriate technology to measure sleep in a particularly vulnerable group in a family setting.
For work package two, we will undertake longitudinal measuring over 12 months. We will recruit 30 families with one autistic child aged 6-8, and one non-autistic child aged 6-12 years old and 30 families with two non-autistic children; one aged 6-8 years old and the other 6–12 years old, with no history of neuropsychiatric conditions in the immediate family or in first degree relatives of both parents.
The specific objectives of the research are:
1. To collect sensor and actigraphy data for 12 months to assess sleep, physical activity and circadian rhythms in families
2. To collect questionnaire data at three timepoints (the beginning, middle and end of the study) during the 12-month study
3. To collect saliva samples for DNA extraction at one timepoint during the study (at the beginning of the study)
4. To undertake statistical genetics analysis that will estimate the familial aggregation of the sleep phenotypes (an indicator of heritability) and their relationship to autism using SOLAR (Sequential Oligogenic Linkage Analysis Routines) and to compute polygenic risk scores (PRS) for autism and chronotype for each family member
For work package three, we will undertake genomic risk score profiling. We will undertake our genomic workflow in related individuals (using UK Biobank and ABCD datasets). From the genome-wide single nucleotide polymorphism data generated in work package 2, we will compute the polygenic risk score for autism and chronotype for each family member. We will ask if a polygenic risk score for autism correlates with autism diagnosis in families, if a polygenic risk score for chronotype correlates with circadian rhythm and sleep disturbance in families and if the children with circadian rhythm disruption have a higher polygenic risk score from autism than family controls, and higher than non-autistic controls.
Throughout FamilySleeps, our research team has ensured wide dissemination, public engagement and sustained public and patient involvement at every stage of the research lifecycle – from project development, research analysis and results dissemination.
For work package one, we have secured access to state of the art and appropriate technology to measure sleep in a particularly vulnerable group in a family setting.
For work package two, we will undertake longitudinal measuring over 12 months. We will recruit 30 families with one autistic child aged 6-8, and one non-autistic child aged 6-12 years old and 30 families with two non-autistic children; one aged 6-8 years old and the other 6–12 years old, with no history of neuropsychiatric conditions in the immediate family or in first degree relatives of both parents.
The specific objectives of the research are:
1. To collect sensor and actigraphy data for 12 months to assess sleep, physical activity and circadian rhythms in families
2. To collect questionnaire data at three timepoints (the beginning, middle and end of the study) during the 12-month study
3. To collect saliva samples for DNA extraction at one timepoint during the study (at the beginning of the study)
4. To undertake statistical genetics analysis that will estimate the familial aggregation of the sleep phenotypes (an indicator of heritability) and their relationship to autism using SOLAR (Sequential Oligogenic Linkage Analysis Routines) and to compute polygenic risk scores (PRS) for autism and chronotype for each family member
For work package three, we will undertake genomic risk score profiling. We will undertake our genomic workflow in related individuals (using UK Biobank and ABCD datasets). From the genome-wide single nucleotide polymorphism data generated in work package 2, we will compute the polygenic risk score for autism and chronotype for each family member. We will ask if a polygenic risk score for autism correlates with autism diagnosis in families, if a polygenic risk score for chronotype correlates with circadian rhythm and sleep disturbance in families and if the children with circadian rhythm disruption have a higher polygenic risk score from autism than family controls, and higher than non-autistic controls.
Throughout FamilySleeps, our research team has ensured wide dissemination, public engagement and sustained public and patient involvement at every stage of the research lifecycle – from project development, research analysis and results dissemination.