Pharmacological Validation of Candidate Causal Sleep Genes Identified in an N2 Cross

Abstract

Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, we completed large scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of REM, non-REM, sleep bout duration and sleep fragmentation. Here we describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications. Select small molecule antagonists and agonists were used to interrogate candidate causal gene function in rodent sleep polysomnography assays to determine impact on overall sleep architecture and to evaluate alignment with associated sleep-wake traits. Significant effects on sleep architecture were observed in validation studies using compounds targeting the muscarinic acetylcholine receptor M3 subunit (Chrm3)(wake promotion), nicotinic acetylcholine receptor alpha4 subunit (Chrna4)(wake promotion), dopamine receptor D5 subunit (Drd5)(sleep induction), serotonin 1D receptor (Htr1d)(altered REM fragmentation), glucagon-like peptide-1 receptor (Glp1r)(light sleep promotion and reduction of deep sleep), and Calcium channel, voltage-dependent, T type, alpha 1I subunit (Cacna1i)(increased bout duration slow wave sleep). Taken together, these results show the complexity of genetic components that regulate sleep-wake traits and highlight the importance of evaluating this complex behavior at a systems level. Pharmacological validation of genetically identified putative targets provides a rapid alternative to generating knock out or transgenic animal models, and may ultimately lead towards new therapeutic opportunities.

A Systems Approach Identifies Networks and Genes Linking Sleep and Stress: Implications for Neuropsychiatric Disorders

“…We focused on phenotypic QTL that overlapped with loci regulating gene expression (i.e., eQTL; see Extended Experimental Procedures) and utilized conditional independence models to determine whether expression variation of the gene mediates the QTL effect and causes phenotypic variations (Millstein et al, 2009; Schadt et al, 2005). This causality test is quite robust and has successfully identified causal genes for complex sleep traits (Millstein et al, 2011) that were later pharmacologically validated (Brunner et al, 2011). …”

Genetic and environmental regulation of caudate nucleus transcriptome: insight into schizophrenia risk and the dopamine system

“…The copyright holder for this this version posted November 20, 2020. ; https://doi.org/10.1101/2020.11.18.20230540 doi: medRxiv preprint decreased expression, suggesting that therapeutic targeting would involve increasing activity of this channel (36).…”

“…The copyright holder for this this version posted November 20, 2020. ; https://doi.org/10.1101/2020.11.18.20230540 doi: medRxiv preprint 14 therapeutic action targeting CACNA1I would be agonism, rather than antagonism which has previously been explored (36).…”

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

“…These datasets were downloaded from a public database hosted by Sage Bionetworks (www.synapse.org; dataset IDs for the sleep phenotypes and hypothalamus gene expression were syn113322 and syn113318, respectively). One hundred and one mice were hand scored for sleep at 11–13 weeks of age using electroencephalogram (EEG) and electromyogram (EMG) data collected over a 48 h period (Winrow et al, 2009; Brunner et al, 2011; Millstein et al, 2011; Fitzpatrick et al, 2012). Hypothalamus tissue was collected from each mouse and profiled following sleep recording (Millstein et al, 2011) to identify chronic gene expression variation associated with variation in 24 h REM sleep.…”