Variations in Genes Related to Sleep Patterns in Children With Autism Spectrum Disorder.

BACKGROUND: Sleep disturbance is a frequent comorbidity in children with autism spectrum disorder (ASD), affecting an estimated 40-80% of cases. Previous reports have shown relationships between several circadian rhythm-related genes and sleep problems in ASD. The purpose of the present study was to relate variation in and around melatonin synthesis and suprachiasmatic nucleus genes to sleep problems in a large sample of children with ASD. METHOD: This secondary analysis used existing genotypic and phenotypic data for 2,065 children, aged 4-18 years, from the Simons Simplex Collection (SSC). Sleep problems were measured with the SSC Sleep Interview. Expression quantitative trait loci and single nucleotide polymorphisms in 25 circadian genes were chosen primarily for their impact on expression levels of target genes in the brain. Associations between variants and composite sleep problems, nighttime problems, daytime problems, and sleep duration problems were calculated using logistic regression analysis. Age, sex, nonverbal IQ, ASD severity, gastrointestinal distress, seizures, and ancestry were included as covariates. Transmission disequilibrium tests were performed to test for overtransmission of alleles in the same variants. RESULTS: No significant associations or transmission disequilibrium were found between gene variants and sleep problems in this sample of children with ASD. CONCLUSION: Variation in expression of investigated genes in the melatonin synthesis and suprachiasmatic nucleus pathways did not have notable impacts on sleep problems in this large sample of children with ASD. Future research could explore translational and posttranslational effects of these genes or the effects of genes in other sleep-homeostasis pathways on sleep patterns.

Psychometric Properties of the Simons Simplex Collection Sleep Interview.

BACKGROUND AND PURPOSE: An estimated 40%-80% of children with autism spectrum disorders (ASD) have sleep problems. The Simons Simplex Collection Sleep Interview (SSCSI) is a parent-report questionnaire assessing bedtime and nighttime sleep problems and daytime function. The present study evaluated the factorial model of the SSCSI that best characterizes children aged 4-18 years with ASD. METHODS: Exploratory factor analysis was performed using principal component analysis and promax rotation, beginning with 16 items and ending with 10 items. RESULTS: Exploratory factor analysis concluded with ten dichotomous items, plus ageand regular sleep duration, in three factors: nighttime problems, daytime problems, andsleep duration problems. The analysis was performed on the full sample, and onprepubertal (4-8-years), pubertal (9-13-years), and postpubertal (14-18-years) subgroups. CONCLUSION: Further refinement, including confirmatory factor analysis, test-retest reliability, and convergent validity testing, is needed.

Symptom Science: Repurposing Existing Omics Data.

Omics approaches, including genomics, transcriptomics, proteomics, epigenomics, microbiomics, and metabolomics, generate large data sets. Once they have been used to address initial study aims, these large data sets are extremely valuable to the greater research community for ancillary investigations. Repurposing available omics data sets provides data to address research questions, generate and test hypotheses, replicate findings, and conduct mega-analyses. Many well-characterized, longitudinal, epidemiological studies collected extensive phenotype data related to symptom occurrence and severity. While the main phenotype of interest for many of these studies was often not symptom related, these data were collected to better understand the primary phenotype of interest. A search for symptom data (i.e., cognitive impairment, fatigue, gastrointestinal distress/nausea, sleep, and pain) in the database of genotypes and phenotypes (dbGaP) revealed many studies that collected symptom and omics data. There is thus a real possibility for nurse scientists to be able to look at symptom data over time from thousands of individuals and use omics data to identify key biological underpinnings that account for the development and severity of symptoms without recruiting participants or generating any new data. The purpose of this article is to introduce the reader to resources that provide omics data to the research community for repurposing, provide guidance on using these databases, and encourage the use of these data to move symptom science forward.

Adolescent Sleep and the Impact of Technology Use Before Sleep on Daytime Function.

UNLABELLED: Technology has become pervasive in our culture, particularly among adolescents. The purpose of this study is to examine associations between use of technology before sleep and daytime function in adolescents. DESIGN AND METHODS: This study is a secondary analysis of respondents aged 13 to 21 years (N = 259) from the 2011 National Sleep Foundation's Sleep in America Poll. The survey included questions on demographics, sleep habits, and use of technology in the hour before bedtime. Daytime sleepiness was assessed with the Epworth Sleepiness Scale (ESS). Student's t-tests, Mann-Whitney U, and Fischer's exact tests were performed to detect differences in demographics, sleep duration, and technology use in the total sample, and between respondents with "adequate" compared to "inadequate" sleep. Correlations were calculated between technology frequency and daytime function. RESULTS: Adolescents had mean sleep duration of 7.3 ± 1.3 h. Almost all respondents (97%) used some form of technology before sleep. Increased technology use and the frequency of being awoken in the night by a cell phone were significantly associated with waking too early, waking unrefreshed, and daytime sleepiness (p < 0.05). Adolescents who reported "inadequate" sleep had shorter sleep duration, greater frequency of technology use before bedtime, feeling unrefreshed on waking, and greater daytime sleepiness than those reporting "adequate" sleep (all p-values < 0.05). CONCLUSION: Technology use before sleep by adolescents had negative consequences on nighttime sleep and on daytime function. PRACTICE IMPLICATIONS: Healthcare professionals who interact with adolescents should encourage technology to be curtailed before bedtime and for adolescents to value obtaining adequate sleep.

Screening and evaluation tools for sleep disorders in older adults.

The negative effects of impaired sleep on physical and mental well-being in older adults have recently been recognized by health care professionals. However, researchers and clinicians may be unaware of reliable and valid screening and evaluation tools for evaluating sleep disorders in older adults. The purpose of this article is to present subjective and objective instruments that measure sleep quality, excessive daytime sleepiness, obstructive sleep apnea, insomnia and restless leg syndrome that are appropriate for use in adult and older adult patients.