Targeting Orexin Receptors for the Treatment of Insomnia: From Physiological Mechanisms to Current Clinical Evidence and Recommendations

After a detailed description of orexins and their roles in sleep and other medical disorders, we discuss here the current clinical evidence on the effects of dual (DORAs) or selective (SORAs) orexin receptor antagonists on insomnia with the aim to provide recommendations for their further assessment in a context of personalized and precision medicine. In the last decade, many trials have been conducted with orexin receptor antagonists, which represent an innovative and valid therapeutic option based on the multiple mechanisms of action of orexins on different biological circuits, both centrally and peripherally, and their role in a wide range of medical conditions which are often associated with insomnia. A very interesting aspect of this new category of drugs is that they have limited abuse liability and their discontinuation does not seem associated with significant rebound effects. Further studies on the efficacy of DORAs are required, especially on children and adolescents and in particular conditions, such as menopause. Which DORA is most suitable for each patient, based on comorbidities and/or concomitant treatments, should be the focus of further careful research. On the contrary, studies on SORAs, some of which seem to be appropriate also in insomnia in patients with psychiatric diseases, are still at an early stage and, therefore, do not allow to draw definite conclusions.

Family aggregation of sleep characteristics: Results of the Heinz Nixdorf Recall and the Multi-Generation Study

INTRODUCTION

Poor sleep is a risk factor for adverse health events. For health prevention, it may be helpful to know whether poor sleep or sleep disorders in individuals are associated with sleep problems in their partners or children.

METHODS

In the MultiGeneration Study (MGS, conducted from 2013 to 2016), 1237 partners (aged 27 to 90 years) and 1660 adult children (aged 18 to 66 years) of index persons were recruited. Index persons are participants of the Heinz Nixdorf Recall Study, a population-based cohort study in the Ruhr area (study start 1999-2001, 4841 participants aged 45-75 years). We used two analysis populations: one with 1181 index persons whose partners were in MGS, and one with 1083 index persons with at least one adult child in MGS. Sleep characteristics were assessed using questionnaires (including the Pittsburgh Sleep Quality Index). The exposure was the presence of a sleep characteristic of the index subject.

RESULTS

Children showed the investigated sleep characteristics more often if these were also present in their parent (e.g., RR (relative risk) = 1.28 (95% CI: 1.06-1.55) for poor sleep quality). In partners, strong associations were observed for rising times and napping, but only weak associations for snoring, poor sleep quality and sleep disorders. Snoring of the bed partner is a risk factor for poor sleep (e.g., RR = 1.67 (0.91-3.07) for difficulties falling asleep).

CONCLUSION

Aggregation is observed for many sleep characteristics in people living in partnerships as well as in parents and their adult children.

The heritability of insomnia: A meta-analysis of twin studies

Twin studies of insomnia exhibit heterogeneity in estimates of heritability. This heterogeneity is likely because of sex differences, age of the sample, the reporter and the definition of insomnia. The aim of the present study was to systematically search the literature for twin studies investigating insomnia disorder and insomnia symptoms and to meta-analyse the estimates of heritability derived from these studies to generate an overall estimate of heritability. We further examined whether heritability was moderated by sex, age, reporter and insomnia symptom. A systematic literature search of five online databases was completed on 24 January 2020. Two authors independently screened 5644 abstracts, and 160 complete papers for the inclusion criteria of twin studies from the general population reporting heritability statistics on insomnia or insomnia symptoms, written in English, reporting data from independent studies. We ultimately included 12 papers in the meta-analysis. The meta-analysis focussed on twin intra-class correlations for monozygotic and dizygotic twins. Based on these intra-class correlations, the meta-analytic estimate of heritability was estimated at 40%. Moderator analyses showed stronger heritability in females than males; and for parent-reported insomnia symptoms compared with self-reported insomnia symptoms. There were no other significant moderator effects, although this is likely because of the small number of studies that were comparable across levels of the moderators. Our meta-analysis provides a robust estimate of the heritability of insomnia, which can inform future research aiming to uncover molecular genetic factors involved in insomnia vulnerability.

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees

Motivation

Familial aggregation analysis is an important early step for characterizing the genetic determinants of phenotypes in epidemiological studies. To facilitate this analysis, a collection of methods to detect familial aggregation in large pedigrees has been made available recently. However, efficacy of these methods in real world scenarios remains largely unknown. Here, we assess the performance of five aggregation methods to identify individuals or groups of related individuals affected by a Mendelian trait within a large set of decoys. We investigate method performance under a representative set of combinations of causal variant penetrance, trait prevalence and number of affected generations in the pedigree. These methods are then applied to assess familial aggregation of familial hypercholesterolemia and stroke, in the context of the Cooperative Health Research in South Tyrol (CHRIS) study.

Results

We find that in some situations statistical hypothesis testing with a binomial null distribution achieves performance similar to methods that are based on kinship information, while kinship based methods perform better when information is available on fewer generations. Potential case families from the CHRIS study are reported and the results are discussed taking into account insights from the performance assessment.

Availability and implementation

The familial aggregation analysis package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg.

Supplementary information

Supplementary data are available at Bioinformatics online.

Dad's Snoring May Have Left Molecular Scars in Your DNA: the Emerging Role of Epigenetics in Sleep Disorders

The sleep-wake cycle is a biological phenomena under the orchestration of neurophysiological, neurochemical, neuroanatomical, and genetical mechanisms. Moreover, homeostatic and circadian processes participate in the regulation of sleep across the light-dark period. Further complexity of the understanding of the genesis of sleep engages disturbances which have been characterized and classified in a variety of sleep-wake cycle disorders. The most prominent sleep alterations include insomnia as well as excessive daytime sleepiness. On the other side, several human diseases have been linked with direct changes in DNA, such as chromatin configuration, genomic imprinting, DNA methylation, histone modifications (acetylation, methylation, ubiquitylation or sumoylation, etc.), and activating RNA molecules that are transcribed from DNA but not translated into proteins. Epigenetic theories primarily emphasize the interaction between the environment and gene expression. According to these approaches, the environment to which mammals are exposed has a significant role in determining the epigenetic modifications occurring in chromosomes that ultimately would influence not only development but also the descendants' physiology and behavior. Thus, what makes epigenetics intriguing is that, unlike genetic variation, modifications in DNA are altered directly by the environment and, in some cases, these epigenetic changes may be inherited by future generations. Thus, it is likely that epigenetic phenomena might contribute to the homeostatic and/or circadian control of sleep and, possibly, have an undescribed link with sleep disorders. An exciting new horizon of research is arising between sleep and epigenetics since it represents the relevance of the study of how the genome learns from its experiences and modulates behavior, including sleep.

Detecting Familial Aggregation

In addition to characterizing the distribution of genetic features of populations (mutation and allele frequencies; measures of Hardy-Weinberg equilibrium), genetic epidemiology and statistical genetics aim to explore and define the role of genomic variation in risk of disease or variation in traits of interest. To facilitate this kind of exploration, genetic epidemiology and statistical genetics address a series of questions: 1. Does the disease tend to cluster in families more than expected by chance alone? 2. Does the disease appear to follow a particular genetic model of transmission in families? 3. Does variation at a particular genomic position tend to cosegregate with disease in families? 4. Do specific genetic variants tend to be carried more frequently by those with disease than by those without these variants in a given population (or across families)? The first question can be examined using studies of familial aggregation or correlation. An ancillary question: "how much of the susceptibility to disease (or variation in disease-related traits) might be accounted for by genetic factors?" is typically answered by estimating heritability, the proportion of variance in a trait or in risk to a disease attributable to genetics. The second question can be formally tested using pedigrees for which disease affection status or trait values are available through a modeling approach known as segregation analysis. The third question can be answered with data on genomic markers in pedigrees with affected members informative for linkage, where meiotic cross-over events are estimated or assessed. The fourth question is answerable using genotype data on genomic markers on unrelated affected and unaffected individuals and/or families with affected members and unaffected members. All of these questions can also be explored for quantitative (or continuously distributed) traits by examining variation in trait values between family members or between unrelated individuals. While each of these questions and the analytical approaches for answering them is explored extensively in subsequent chapters (heritability in Chapters 8 and 9 ; segregation in Chapter 12 ; linkage in Chapters 13 - 17 ; and association in Chapters 18 - 20 ), this chapter focuses on statistical methods to address questions of familial aggregation of qualitative phenotypes (e.g., disease status) or quantitative phenotypes.While studies exploring genotype-phenotype correlations are arguably the most important and common type of statistical genetic study performed, these studies are performed under the assumption that genetic contributors at least partially explain risk of a disease or a trait of interest. This may not always be the case, especially with diseases or traits known to be strongly influenced by environmental factors. For this reason, before any of the last three questions described above can be answered, it is important to ask first whether the disease clusters among family members more than unrelated persons, as this constitutes evidence of a possible heritable contribution to disease, justifying the pursuit of studies answering the other questions. In this chapter, the underlying principles of familial aggregation studies are addressed to provide an understanding and set of analytical tools to help answer the question if diseases or traits of interest are likely to be heritable and therefore justify subsequent statistical genetic studies to identify specific genetic causes.