Pharmacological validation of candidate causal sleep genes identified in an N2 cross

Herbal medicines for insomnia through regulating 5-hydroxytryptamine receptors: a systematic review

Insomnia is a common sleep disorder without effective therapy and can affect a person's life. The mechanism of the disease is not completely understood. Hence, there is a need to understand the targets related to insomnia, in order to develop innovative therapies and new compounds. Recently, increasing interest has been focused on complementary and alternative medicines for treating or preventing insomnia. Research into their molecular components has revealed that their sedative and sleep-promoting properties rely on the interactions with various neurotransmitter systems in the brain. In this review, the role of 5-hydroxytryptamine (5-HT) in insomnia development is summarized, while a systematic analysis of studies is conducted to assess the mechanisms of herbal medicines on different 5-HT receptors subtypes, in order to provide reference for subsequent research.

Gene expression analysis in the mouse brainstem identifies Cart and Nesfatin as neuropeptides coexpressed in the Calbindin-positive neurons of the Nucleus papilio

Study Objectives: The brainstem contains several neuronal populations, heterogeneous in terms of neurotransmitter/neuropeptide content, which are important for controlling various aspects of the rapid eye movement (REM) phase of sleep. Among these populations are the Calbindin (Calb)-immunoreactive NP^Calb neurons, located in the Nucleus papilio, within the dorsal paragigantocellular nucleus (DPGi), and recently shown to control eye movement during the REM phase of sleep. Methods: We performed in-depth data mining of the in situ hybridization data collected at the Allen Brain Atlas, in order to identify potentially interesting genes expressed in this brainstem nucleus. Our attention focused on genes encoding neuropeptides, including Cart (Cocaine and Amphetamine Regulated Transcripts) and Nesfatin 1. Results: While nesfatin 1 appeared ubiquitously expressed in this Calb-positive neuronal population, Cart was coexpressed in only a subset of these glutamatergic NP^Calb neurons. Furthermore, an REM sleep deprivation and rebound assay performed with mice revealed that the Cart-positive neuronal population within the DPGi was activated during REM sleep (as measured by c-fos immunoreactivity), suggesting a role of this neuropeptide in regulating some aspects of REM sleep. Conclusions: The assembled information could afford functional clues to investigators, conducive to further experimental pursuits.

A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders

Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders.

Systems-Level G Protein-Coupled Receptor Therapy Across a Neurodegenerative Continuum by the GLP-1 Receptor System

With our increasing appreciation of the true complexity of diseases and pathophysiologies, it is clear that this knowledge needs to inform the future development of pharmacotherapeutics. For many disorders, the disease mechanism itself is a complex process spanning multiple signaling networks, tissues, and organ systems. Identifying the precise nature and locations of the pathophysiology is crucial for the creation of systemically effective drugs. Diseases once considered constrained to a limited range of organ systems, e.g., central neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington' disease (HD), the role of multiple central and peripheral organ systems in the etiology of such diseases is now widely accepted. With this knowledge, it is increasingly clear that these seemingly distinct neurodegenerative disorders (AD, PD, and HD) possess multiple pathophysiological similarities thereby demonstrating an inter-related continuum of disease-related molecular alterations. With this systems-level appreciation of neurodegenerative diseases, it is now imperative to consider that pharmacotherapeutics should be developed specifically to address the systemic imbalances that create the disorders. Identification of potential systems-level signaling axes may facilitate the generation of therapeutic agents with synergistic remedial activity across multiple tissues, organ systems, and even diseases. Here, we discuss the potentially therapeutic systems-level interaction of the glucagon-like peptide 1 (GLP-1) ligand-receptor axis with multiple aspects of the AD, PD, and HD neurodegenerative continuum.

Computationally efficient permutation-based confidence interval estimation for tail-area FDR

Challenges of satisfying parametric assumptions in genomic settings with thousands or millions of tests have led investigators to combine powerful False Discovery Rate (FDR) approaches with computationally expensive but exact permutation testing. We describe a computationally efficient permutation-based approach that includes a tractable estimator of the proportion of true null hypotheses, the variance of the log of tail-area FDR, and a confidence interval (CI) estimator, which accounts for the number of permutations conducted and dependencies between tests. The CI estimator applies a binomial distribution and an overdispersion parameter to counts of positive tests. The approach is general with regards to the distribution of the test statistic, it performs favorably in comparison to other approaches, and reliable FDR estimates are demonstrated with as few as 10 permutations. An application of this approach to relate sleep patterns to gene expression patterns in mouse hypothalamus yielded a set of 11 transcripts associated with 24 h REM sleep [FDR = 0.15 (0.08, 0.26)]. Two of the corresponding genes, Sfrp1 and Sfrp4, are involved in wnt signaling and several others, Irf7, Ifit1, Iigp2, and Ifih1, have links to interferon signaling. These genes would have been overlooked had a typical a priori FDR threshold such as 0.05 or 0.1 been applied. The CI provides the flexibility for choosing a significance threshold based on tolerance for false discoveries and precision of the FDR estimate. That is, it frees the investigator to use a more data-driven approach to define significance, such as the minimum estimated FDR, an option that is especially useful for weak effects, often observed in studies of complex diseases.