We studied 28 adolescents/young adults with autism spectrum disorders (ASD) and 13 age/sex matched individuals of typical development (TD). Structured sleep histories, validated questionnaires, actigraphy (four weeks), and salivary cortisol and melatonin (four days each) were collected. Compared to those with TD, adolescents/young adults with ASD had longer sleep latencies and more difficulty going to bed and falling asleep. Morning cortisol, evening cortisol, and the morning-evening difference in cortisol did not differ by diagnosis (ASD vs. TD). Dim light melatonin onsets (DLMOs) averaged across participants were not different for the ASD and TD participants. Average participant scores indicated aspects of poor sleep hygiene in both groups. Insomnia in ASD is multifactorial and not solely related to physiological factors.

Aim: Digital ELISA-based assays for blood biomarkers of neurological disease are on the verge of clinical use. Here, we aimed to determine whether different preanalytical blood processing techniques influence results. Materials & methods: Concentrations of neurofilament light chain (NfL), Tau and amyloid beta (Aβ) were measured in human plasma and serum specimens using digital ELISA and compared between blood products. Measured levels of NfL were highly equivalant between serum and plasma in all analyses, however, measured levels of Tau and Aβ were consistently lower in serum relative to plasma. Conclusion: Tau and Aβ are likely lost during clotting in serum preparations, and should be assayed in plasma to get an accurate measure of circulating levels.

No abstract

Background: Although many of the proposed mediating processes of self-management interventions are operationally defined as cognitive processes (e.g., acquiring and using information, self-efficacy, motivation, decision-making), little is known about their underlying brain mechanisms. Brain biomarkers of how people process health information may be an important characteristic on which to individualize health information to optimize self-management of chronic conditions.

No abstract

While many factors contribute to sleep difficulties in children with autism spectrum disorder (ASD), behavioral sleep education is often effective. However, providing families with the educational tools and the support they need to help their children sleep can be challenging given limited access to care. We piloted the use of a 5-week home sleep education program in 10 parents of children with ASD, ages 3-9 years. Parents read a sleep education manual (extracted from a book on sleep and ASD) and then implemented the suggested strategies with their children. The Children's Sleep Habits Questionnaire, the Family Inventory of Sleep Habits, and actigraphy were completed prior to and after the intervention. Parents also completed a postintervention interview to assess understanding and comfort with implementation. Of 8 completers, 6 children showed improvement in sleep patterns, which included bedtime resistance, time to fall asleep, night wakings, and cosleeping. Actigraphy data showed improvements in sleep latency (time to fall asleep) for most of the children. Two children were able to discontinue supplemental melatonin. All parents reported good to excellent understanding of the manual and reported high comfort levels with implementation. Our pilot findings suggest that some parents can learn effective strategies for promoting sleep and teach them to their children with ASD without the guidance of a trained educator.

The identification of precision blood biomarkers which can accurately indicate damage to brain tissue could yield molecular diagnostics with the potential to improve how we detect and treat neurological pathologies. However, a majority of candidate blood biomarkers for neurological damage that are studied today are proteins which were arbitrarily proposed several decades before the advent of high-throughput omic techniques, and it is unclear whether they represent the best possible targets relative to the remainder of the human proteome. Here, we leveraged mRNA expression data generated from nearly 12,000 human specimens to algorithmically evaluate over 17,000 protein-coding genes in terms of their potential to produce blood biomarkers for neurological damage based on their expression profiles both across the body and within the brain. The circulating levels of proteins associated with the top-ranked genes were then measured in blood sampled from a diverse cohort of patients diagnosed with a variety of acute and chronic neurological disorders, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, Alzheimer’s disease, and multiple sclerosis, and evaluated for their diagnostic performance. Our analysis identifies several previously unexplored candidate blood biomarkers of neurological damage with possible clinical utility, many of which whose presence in blood is likely linked to specific cell-level pathologic processes. Furthermore, our findings also suggest that many frequently cited previously proposed blood biomarkers exhibit expression profiles which could limit their diagnostic efficacy.

Background Building nursing research data repositories with the goal of comparing and synthesizing results across numerous studies and public sharing of data is still in early stages of development. Objectives We describe the process of using common data elements (CDEs) to build a data repository for research addressing self-management of chronic conditions. Issues in the development of CDEs, lessons learned in the creation of a combined data set across seven studies of different chronic condition populations, and recommendations for creating and sharing harmonized nursing research data sets are provided. Methods In 2014, at initiation of a National Institutes of Health-funded Centers of Excellence in Self-Management Research, our center investigators defined a set of CDEs for use in future center-funded pilot studies consisting of populations having different chronic conditions with the intent to combine the study data sets. Over the next 4 years, center investigators were provided with standardized codebooks and data collection protocols for applying the CDEs and data storage. Data from seven pilot studies were subsequently combined. Results Although each pilot study was small—with sample sizes ranging from 18 to 31 participants—our combined data set of 179 participants provides us with a sample size sufficient to conduct analyses that could not be done with the individual small samples alone. The research data repository addressing self-management of chronic conditions will soon be available for public sharing. Discussion Our experience demonstrates that, with careful, upfront planning and ongoing vigilant oversight, CDEs can be applied across studies consisting of different chronic condition populations to combine data sets to create research data repositories for public sharing.