Genetic Variation in Sleep Under Normal Conditions and during Inflammatory Disease

Several sleep and circadian disorders, including narcolepsy, advanced sleep phase syndrome (ASPS), and fatal familial insomnia (FFI), have known genetic determinants. For example, canine narcolepsy is transmitted as a single autosomal recessive trait with full penetrance (Mignot et al. 1991). The critical genetic determinant for canine narcolepsy is a mutation in the hypocretin receptor gene HCRTR2 (Lin et al. 1999). This finding spurred studies that revealed low levels of hypocretin-1 in the cerebral spinal fluid of human patients with narcolepsy (Baumann, Khatami, Werth, and Bassetti 2006; Nishino, Ripley, Overeem, Lammers, and Mignot 2000; Peyron et al. 2000; Thannickal et al. 2000). Individuals with ASPS have persistent early diurnal onset of sleep and early awakenings; this syndrome shows a strong genetic link to an autosomal dominant allele of the human period-2 gene (Jones and Ptacek 1999; Toh et al. 2001). FFI is a rare disorder characterized by progressively worsening insomnia, motor disturbances, dysautonomia, and eventual death (Lugaresi et al. 1986). A point mutation in the prion protein gene on Chr 20 has been implicated as the causative factor leading to FFI (Medori et al. 1992; Plazzi et al. 2002).

Polymorphisms in sleep-modulatory immune mediators may also alter sleep and susceptibility to sleep disorders. For example, a TNF-a (-308A) allele is significantly associated with obstructive sleep apnea (OSA) (Riha et al. 2005). Siblings with OSA were significantly more likely to carry the TNF-a (-308A) allele than siblings from a control group. OSA is also associated with allelic variation in the angiotensin converting enzyme (ACE) (Zhang et al. 2000), apolipoprotein E genotype e4 (Gottlieb et al. 2004; Larkin, Patel, Redline, Mignot, Elston, and Hallmayer 2006; Saarelainen, Lehtimaki, Nikkila, Solakivi, Nieminen, and Jaakkola 2000), and serotonin receptor type 2A and 2C (Sakai et al.2005).

Associations between HLA haplotypes and sleep disorders are also frequent in the literature. For example, numerous studies have revealed significant links between HLA haplotypes and narcolepsy in various patient populations (Juji, Satake, Honda, and Doi 1984; Lin, Hungs, and Mignot 2001). REM-sleep behavior disorder has been associated with the HLA-DQ1 (Schenck, Garcia-Rill, Segall, Noreen, and Mahowald 1996), and Kleine-Levin syndrome with the HLA-DQB1*0201 (Dauvilliers et al. 2002). The HLA associations found in narcolepsy, REMS disorder behavior, and Kleine-Levin syndrome suggest a likely link between sleep and immune mechanisms, mediated by cytokine, endocrine, and other factors that influence both immune function and sleep regulation (Dauvilliers, Maret, and Tafti 2005; Marshall and Born 2002).

Differences in normal physiological sleep are well known in humans, with variations occurring in the total amount of time spent in SWS and REMS, the diurnal timing of sleep, the daily amount of sleep needed for daily recuperation, and other measures. Twin studies have revealed both genetic and environmental components of sleep phenotypes. Geyer (1937) and Gedda (1951) produced the first reports of a higher concordance in the sleep habits in monozygotic versus dizygotic twins. Others have confirmed and extended these reports (Heath, Kendler, Eaves, and Martin 1990; Linkowski 1999; Partinen, Kaprio, Koskenvuo, Putkonen, and Langinvainio 1983; Webb and Campbell 1983). Moreover, a higher correlation of sleep duration occurs in monozygotic twins, whether living either together or apart, than in dizygotic twins (Gedda and Brenci 1983).

Different strains of inbred mice also exhibit consistent variations in their sleep patterns, and several independent laboratories have demonstrated genetic influences on various facets of sleep. For example, EEG delta power during NREMS has been linked to a region on chromosome 13 (Dpsl at ~ 15cM, Dps2, Dps3) (Franken, Chollet, and Tafti 2001b). Similarly, the amount of time spent in REMS has been linked to loci on Chr 2, 4, 16, 17, and 19 (Tafti, Franken, Kitahama, Malafosse, Jouvet, and Valatx 1997; Toth and Williams 1999b). The Tcpl region of mouse Chr 17 influences the regulation of high affinity choline uptake, which is a critical step in acetylcholine (ACh) synthesis. Because cholinergic mechanisms are central to regulation of REMS, these findings suggest that differences in the rate of ACh synthesis may contribute to strain differences in REMS.

As with sleep patterns, certain features of the EEG are also under genetic regulation in mice. EEG theta and delta power vary significantly across mouse strains (Franken, Chollet, and Tafti 2001a; Franken, Malafosse, and Tafti 1998). EEG frequency during REMS is inherited as an autosomal recessive trait and is modulated by the gene Acad (acylcoenzyme-A-dehydrogenase) (Tafti et al. 2003). Analysis of delta power during recovery after sleep deprivation of recombinant inbred (RI) mice revealed a quantitative trait locus (QTL) on Chr 13 that accounted for 49% of the genetic variance (Franken et al. 2001a). This locus (Dpsl, or delta power in SWS QTL1), incorporates a number of genes associated with brain energy metabolism (e.g., neurotrophic tyrosine kinase-2 receptor, growth hormone releasing hormone (GHRH), glycogen phosphorylase, adenosine deaminase). DBA/2J mice show lower delta power during SWS and predominant theta power in the EEG (Franken et al. 2001a). Furthermore, their sleep is fragmented, and sleep pressure accumulates at a slower rate in this strain as compared to other inbred strains (Franken et al. 2001a). Analysis of these traits revealed association to a polymorphism in the retinoic acid receptor beta (Rarb) gene (Maret, Franken, Dauvilliers, Ghyselinck, Chambon, and Tafti 2005). Some EEG variants (e.g., 16-19/s beta waves) follow a Mendelian autosomal dominant mode of inheritance in humans (Vogel 1965).

14.5.3 The Intersection of Genetic Variation in Sleep and Inflammation

A growing body of literature indicates that variation in the inflammatory response may influence sleep, and perhaps that variation in sleep may impact recuperation and prognosis. Numerous studies have shown that marked but varied alterations in sleep develop during infectious diseases and inflammatory processes. For example, in mice, influenza infection leads to increased somnolence in some strains, but impaired sleep in others (Toth and Verhulst 2003). Inbred strains of mice also vary in their sensitivity and responses to numerous infectious challenges. Strain-related differences in the cytokine milieu and other factors produced over the course of an infection could contribute to quantitative and qualitative variation in sleep during infectious diseases. For example, the sleep responses to some viral challenges, but not others, are influenced by the gene If-1, which regulates production of the cytokine IFN-y in response to viral challenge (De Maeyer and De Maeyer-Guignard 1970). Congenic B6.C-H28c mice, which have the If-1 allele for low IFN-a production on a C57BL/6J genetic background, show a C57BL/6J-like sleep phenotype after influenza infection, but a BALB/cByJ-like phenotype after infection with Newcastle disease virus. These data suggest that specific genes may influence sleep changes in response to some infectious challenges, but not others. In response to influenza infection, 7 of 13 RI strains showed a BALB/cByJ-like response (reduced SWS) during the light phase, whereas six showed a C57BL/6J-like response (normal SWS). In contrast, during the dark phase, nine RI strains showed a C57BL/6J-like response (enhanced sleep), whereas four had a BALB/cByJ-like responses (normal SWS). These data suggest that different genetic factors influence influenza-induced changes in SWS during the light and dark phases of the diurnal cycle (Toth and Williams 1999c). Linkage analysis of the light phase trait revealed a QTL (sleep response to influenza, light phase, or Srilp that is delineated by markers D6Mit74 and D6Mit188 on chromosome 6 (Toth and Williams 1999a). The 95% confidence interval that defines Srilp incorporates several likely candidate genes, including Ghrhr (growth hormone releasing hormone-receptor), Crhr2 (corticotrophin releasing hormone receptor 2), and Cd8a (cytotoxic T lymphocytes epitope). Several of these have now been eliminated as candidates (Ding and Toth

2006; Toth and Hughes 2004). However, C57BL/6J-lit/lit mice bear a spontaneous single nucleotide point mutation in Ghrhr that generates a nonfunctional receptor (Godfrey, Rahal, Beamer, Copeland, Jenkins, and Mayo 1993; Lin, Lin, Gukovsky, Lusis, Sawchenko, and Rosenfeld 1993). As compared to normal C57BL/6J mice, lit/lit mice show less sleep both under normal conditions and during influenza infection (Alt, Obal, Traynor, Gardi, Majde, and Krueger 2003), suggesting that Ghrhr may contribute to the sleep phenotype. Furthermore, influenza infection altered hypothalamic mRNA for IL-ip and TNF-a in normal C57BL/6J mice but not in lit/lit mice (Alt et al. 2003), supporting a role for Ghrhr in the cytokine response, which could in turn be related to the sleep phenotype.

As with influenza, various strains of inbred mice demonstrate a variety of sleep responses and varying severity of disease after inoculation with C. albicans (Ashman, Fulurija, and Papadimitriou 1997; Hector, Domer, and Carrow 1982; Marquis, Montplaisir, Pelletier, Mousseau, and Auger 1986; Tuite et al. 2005) (Toth and Hughes, Compar Med, in press). The marked interstrain differences in patterns of both sleep and clinical disease suggest that genetic factors influence both of these pathophysiologic responses to challenge. Changes in sleep and core temperature were highly correlated in Candida-infected mice, as were renal Candida titers and blood urea nitrogen, relative neutrophilia, and serum IL-6 concentrations, suggesting that common factors may elicit these diverse responses. The immune system, like other physiologic systems, generally employs functionally overlapping mechanisms to protect homeostatic regulation. These mechanisms could, by analogy, also influence sleep and other pathophysiologic responses that develop during microbial infections.

The involvement of macrophages in the generation of peripheral signals that induce sleep during influenza infection is an intriguing possibility. Macrophages both produce and metabolize somnogenic substances after microbial challenge (Fincher, Johannsen, Kapas, Takahashi, and Krueger 1996; Johannsen, Wecke, Obal, and Krueger 1991). Furthermore, manipulations designed to impair macrophage function attenuate or prevent influenza-related sleep enhancement in C57BL/6J mice (Toth and Hughes 2004). Murine macrophages are highly susceptible to infection with influenza virus and respond to the virus by secreting an array of inflammatory substances, including TNF-a and MIP-1a (Gong et al. 1991; Hofmann et al. 1997). Targeted mutation of the gene Ccl3 (previously named both Scya3 and Mip1a) converts the C57BL/6J sleep phenotype (dark phase sleep enhancement) into a BALB/cByJ-like phenotype (normal amounts of SWS during the dark phase) (Toth and Hughes 2004). This observation suggests that Ccl3 may underlie, at least in part, the phenotypic differences in sleep that distinguish these two mouse strains during influenza infection. Supporting a modulatory role for Ccl3, two Ccl3 polymorphisms have been identified, and C57BL/6J and BALB/cAn mouse strains possess different allelic variants (Blackburn, Griffith, and Morahan 1995; Wilson et al. 1990). Furthermore, influenza infection is associated with increased monocyte and epithelial cell expression of Mip1a (Bussfeld, Kaufmann, Meyer, Gemsa, and Sprenger 1998). Mip1 a-deficient mice show major abnormalities in monocyte recruitment and cytokine expression (Lu et al. 1998) and reduced pneumonitis but higher viral titers after challenge with influenza (Cook et al. 1995). However, to our knowledge, the somnogenic properties of CCL3/MIP-1a have not been evaluated to date.

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