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. 2015 May 5;11(5):835-48.
doi: 10.1016/j.celrep.2015.04.003. Epub 2015 Apr 23.

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

Peng Jiang  1 , Joseph R Scarpa  2 , Karrie Fitzpatrick  1 , Bojan Losic  2 , Vance D Gao  1 , Ke Hao  2 , Keith C Summa  1 , He S Yang  1 , Bin Zhang  2 , Ravi Allada  1 , Martha H Vitaterna  1 , Fred W Turek  3 , Andrew Kasarskis  4
Affiliations

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

Peng Jiang et al. Cell Rep. .

Abstract

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.

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Figures

Figure 1
Figure 1. Experimental design and analytic approach
A population of (B6×A/J) F2 mice underwent a chronic unpredictable stress protocol, data collected during which enables modeling of genetic and molecular networks underlying responses to these stresses. (A) The sequence of chronic unpredictable stress treatments and phenotypic data collection (see Extended Experimental Procedures for details). (B) Schematic diagram of the molecular and physiological data collection and integrative analysis.
Figure 2
Figure 2. Phenotypic interactions observed in the chronically stressed (B6×A/J) F2 mice
(A–D) Correlation coefficients between pairs of phenotypes. The phenotypes were ordered according to their phenotypic categories. (E–H) Statistical significance of observed associations. The phenotypes were ordered exactly the same as in (A–D). Abbreviations: BL, baseline; SDR, sleep deprivation recovery; Rst, after restraint stress; AUC, area under the curve. Note: 93 sleep measurements that were not grouped into any of the sleep categories are not presented here, but are included in Table S2.
Figure 3
Figure 3. Identification of QTL that influence stress and sleep phenotypes
(A) Genetic landscape of stress and sleep. Genomic locations of the 142 identified QTL (FDR < 0.2) are shown (also see Table S3). Abbreviations: BL, baseline; SDR, sleep deprivation recovery; Rst, after restraint stress. (B) A highly significant QTL for plasma TSH level on Chr.4. LOD, log of odds. (C) Median ± inter quartile range of plasma TSH level as a function of genotype at rs4224864, the most strongly associated SNP in the Chr.4 QTL region. (D) Distinct QTL were linked to blood pressure measured at different times of the chronic stress protocol. (E) Baseline plasma glucose levels were linked to QTL with consistent effect throughout the chronic stress treatment as well as QTL specific to different stages of the protocol. Note that while a 6-h fasting procedure preceded the glucose tolerance test and the glucose measurement at time 0 (i.e., week 7), it did not appear to have a significant effect on the genetic control of glucose, as it did not result in presence or absence of a QTL specific to the baseline glucose measurement at week 7. The most distinct genetic regulations of baseline glucose levels were observed between week 2 (i.e., most naïve) and week 12–13 (i.e., most experienced).
Figure 4
Figure 4. A network view of striatal genes causal to selected behavioral and sleep phenotypes
Circles represent genes and squares represent phenotypic categories. The circle is sized in proportion to the number of phenotypes for which the gene tests causal. Circles and squares are colored according to phenotype categories, with colors assigned to genes from the category of the phenotypes for which the genes test causal. The 5 pink circles represent genes causal to phenotypes of multiple distinct categories. Insert: the number of genes found causal to at least one phenotype in each category. Abbreviations: BL, baseline; SDR, sleep deprivation recovery; Rst, after restraint stress. See Table S4 for the full list.
Figure 5
Figure 5. Identification of gene co-expression modules relevant to selected behavioral and sleep phenotypes
(A) The topological overlap matrix (TOM) plot corresponds to the striatal gene coexpression network. Darker color indicate stronger co-regulation between a pair of genes (in rows and columns). Gene modules are identified by hierarchical clustering of the matrix, as labeled by arbitrarily assigned color bars on the top and at the left. (B) Identification of modules (rows) significantly associated with selected phenotypes (columns) organized in categories. Gene modules are indicated by their assigned color at the left. Red bars indicate significant associations (P < 0.05 and FDR < 0.05). (C) Ranking of modules (rows) based on relevance to individual phenotypic categories and combined categories of interest (columns). Module rankings for a phenotypic category were determined by the number of significant module-trait associations within the phenotypic category. For a combination of multiple phenotypic categories, rankings for each category were summed to determine a composite ranking for each module. Darker color indicate higher ranking. The actual rankings are also labeled. Abbreviations: BL, baseline sleep; SDR, sleep deprivation recovery; Rst, sleep after restraint stress.
Figure 6
Figure 6. Striatal Bayesian networks downstream of Mical2
Each node represents a gene and each directed edge indicates a causal link between genes. Nodes are colored according to their module assignments, using the names of the respective modules. Key driver genes are represented by larger square nodes. Nodes with red rims denote homologs of human GWAS candidates for neuropsychiatric disorders, and nodes with yellow rims denote candidate genes identified in this study as causal to stress and sleep phenotypes. One node is labeled with a half red and half yellow rim, as the represented gene (St8sia2) is a both reported GWAS candidate for bipolar disorder and tested causal to a REM sleep phenotype in this study.
Figure 7
Figure 7. Striatal Bayesian networks downstream of Htt and Bsn
Each node represents a gene and each directed edge indicates a causal link between genes. Nodes are colored according to their module assignments, using the names of the respective modules. Key driver genes are represented by larger square nodes.
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