Sleep and Activity Patterns in Autism Spectrum Disorder.

Background: Autism spectrum disorder (ASD) is a highly heritable and heterogeneous neurodevelopmental disorder characterized by impaired social interactions, repetitive behaviors, and a wide range of comorbidities. Between 44-83% of autistic individuals report sleep disturbances, which may share an underlying neurodevelopmental basis with ASD. Methods: We recruited 382 ASD individuals and 223 of their family members to obtain quantitative ASD-related traits and wearable device-based accelerometer data spanning three consecutive weeks. An unbiased approach identifying traits associated with ASD was achieved by applying the elastic net machine learning algorithm with five-fold cross-validation on 6,878 days of data. The relationship between sleep and physical activity traits was examined through linear mixed-effects regressions using each night of data. Results: This analysis yielded 59 out of 242 actimetry measures associated with ASD status in the training set, which were validated in a test set (AUC: 0.777). For several of these traits (e.g. total light physical activity), the day-to-day variability, in addition to the mean, was associated with ASD. Individuals with ASD were found to have a stronger correlation between physical activity and sleep, where less physical activity decreased their sleep more significantly than that of their non-ASD relatives. Conclusions: The average duration of sleep/physical activity and the variation in the average duration of sleep/physical activity strongly predict ASD status. Physical activity measures were correlated with sleep quality, traits, and regularity, with ASD individuals having stronger correlations. Interventional studies are warranted to investigate whether improvements in both sleep and increased physical activity may improve the core symptoms of ASD.

The relationship between autism spectrum and sleep-wake traits.

Autistic children and adults often have sleep disturbances, which may affect their and their family's quality of life. Yet, the relationship between sleep-wake patterns and autism spectrum traits is understudied. Identifying such relationships could lead to future research elucidating common mechanistic underpinnings. Thus, we aimed to determine whether sleep-wake patterns, specifically related to sleep, physical activity, and the daily sleep-wake rhythm (i.e., circadian rhythm), are associated with autism spectrum-related traits. Accelerometer-derived sleep-wake parameters were estimated in individuals with autistic spectrum traits and their family members (N = 267). We evaluated autism spectrum traits using the Social Responsiveness Scale (SRS) to assess the presence and severity of social impairment and the Behavior Rating Inventory of Executive Function (BRIEF) to assess executive function. The linear multivariate regression analysis (using SOLAR-Eclipse) showed that in adults, increased core autism spectrum traits and executive dysfunction were associated with disruption of several sleep-wake parameters, particularly related to the daily sleep-wake rhythm, and that executive dysfunction was associated with disrupted sleep quality and level of physical activity. We highlight the interplay between daytime function and disrupted sleep-wake patterns, specifically related to the daily sleep-wake rhythm, that could guide future research into common mechanisms. LAY SUMMARY: Autistic children and adults often report sleep disturbances. To dissect the relationship between a range of autism spectrum traits and sleep-wake patterns, we assessed social interaction and executive function in participants who also wore actimetry watches on their wrists to assess their sleep-wake patterns. We found that increased impairments in social and executive function occurred with increased sleep-wake disturbances, particularly those related to the circadian rhythm, suggesting that these perturbations/disruptions in the sleep-wake cycle could be connected to autism spectrum traits.

Twin-based heritability of actimetry traits.

There is a critical need for phenotypes with substantial heritability that can be used as endophenotypes in behavioral genetic studies. Activity monitoring, called actimetry, has potential as a means of assessing sleep and circadian rhythm traits that could serve as endophenotypes relevant to a range of psychopathologies. This study examined a range of actimetry traits for heritability using a classic twin design. The sample consisted of 195 subjects from 45 monozygotic (MZ) and 50 dizygotic (DZ) twin pairs aged 16-40 years. Subjects wore both a research-grade actimeter (GENEActiv) and a consumer-oriented device (FitBit) for 2 weeks. Sleep and circadian traits were extracted from GENEActiv data using PennZzz and ChronoSapiens software programs. Sleep statistics for a limited number of FitBit-collected traits were generated by its accompanying mobile app. Broad sense heritability was computed on a set of 33 MZ and 38 DZ twin pairs with complete data using both OpenMX and SOLAR software. These analyses yielded a large number of actimetry-derived traits, 20 of which showed high heritability (h2 > 0.6), seven of which remain significant after Bonferroni correction. These results indicate that actimetry enables assessing a range of phenotypes with substantial heritability that may be useful as endophenotypes for genetic studies.

Genetic pleiotropy between mood disorders, metabolic, and endocrine traits in a multigenerational pedigree.

Bipolar disorder (BD) is a mental disorder characterized by alternating periods of depression and mania. Individuals with BD have higher levels of early mortality than the general population, and a substantial proportion of this is due to increased risk for comorbid diseases. To identify the molecular events that underlie BD and related medical comorbidities, we generated imputed whole-genome sequence data using a population-specific reference panel for an extended multigenerational Old Order Amish pedigree (n = 394), segregating BD and related disorders. First, we investigated all putative disease-causing variants at known Mendelian disease loci present in this pedigree. Second, we performed genomic profiling using polygenic risk scores (PRS) to establish each individual's risk for several complex diseases. We identified a set of Mendelian variants that co-occur in individuals with BD more frequently than their unaffected family members, including the R3527Q mutation in APOB associated with hypercholesterolemia. Using PRS, we demonstrated that BD individuals from this pedigree were enriched for the same common risk alleles for BD as the general population (ß = 0.416, p = 6 × 10-4). Furthermore, we find evidence for a common genetic etiology between BD risk and polygenic risk for clinical autoimmune thyroid disease (p = 1 × 10-4), diabetes (p = 1 × 10-3), and lipid traits such as triglyceride levels (p = 3 × 10-4) in the pedigree. We identify genomic regions that contribute to the differences between BD individuals and unaffected family members by calculating local genetic risk for independent LD blocks. Our findings provide evidence for the extensive genetic pleiotropy that can drive epidemiological findings of comorbidities between diseases and other complex traits.

Draft Genome Sequence of the Terrestrial Cyanobacterium Scytonema millei VB511283, Isolated from Eastern India.

We report here the draft genome sequence of Scytonema millei VB511283, a cyanobacterium isolated from biofilms on the exterior of stone monuments in Santiniketan, eastern India. The draft genome is 11,627,246 bp long (11.63 Mb), with 118 scaffolds. About 9,011 protein-coding genes, 117 tRNAs, and 12 rRNAs are predicted from this assembly.

Draft Genome Sequence of Exopolysaccharide-Producing Cyanobacterium Aphanocapsa montana BDHKU 210001.

We report for the first time the draft genome sequence of Aphanocapsa montana BDHKU 210001, a halotolerant cyanobacterium isolated from India. This is a marine exopolysaccharide (EPS)-producing cyanobacterium. The genome of this species is assembled into 11.50 million bases, with 296 scaffolds carrying approximately 7,296 protein-coding genes.