need ASAP.
Less than 8 hours.
Leading Edge
Review
Genetics of Sleep and Sleep Disorders
Amita Sehgal1,* and Emmanuel Mignot2
1Howard Hughes Medical institute, Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia,
PA 19104, USA
2Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, CA 94304, USA
*Correspondence: amita@mail.med.upenn.edu
DOI 10.1016/j.cell.2011.07.004
Sleep remains one of the least understood phenomena in biology—even its role in synaptic plas-
ticity remains debatable. Since sleep was recognized to be regulated genetically, intense research
has launched on two fronts: the development of model organisms for deciphering the molecular
mechanisms of sleep and attempts to identify genetic underpinnings of human sleep disorders.
In this Review, we describe how unbiased, high-throughput screens inmodel organisms are uncov-
ering sleep regulatory mechanisms and how pathways, such as the circadian clock network and
specific neurotransmitter signals, have conserved effects on sleep from Drosophila to humans.
At the same time, genome-wide association studies (GWAS) have uncovered �14 loci increasing
susceptibility to sleep disorders, such as narcolepsy and restless leg syndrome. To conclude,
we discuss how these different strategies will be critical to unambiguously defining the function
of sleep.
Sleep remains one of the big mysteries in biology. As a state that
seemingly freezes all productive activity and puts animals in
danger of being caught by predators, sleepmust serve an impor-
tant purpose because it has survived many years of evolution.
Nevertheless, the function of sleep and the molecular processes
that produce the need to sleep both remain elusive (Frank, 2006;
Mignot, 2008). In the past decade, researchers have made prog-
ress in addressing fundamental questions regarding sleep, and
several clinical centers have even established sleep as an inde-
pendent medical discipline. Major advances include the identifi-
cation of molecules regulating sleep (Allada and Siegel, 2008;
Andretic et al., 2008a; Cirelli, 2009; Crocker and Sehgal, 2010)
and the realization that sleep disorders are extremely common
and numerous. These disorders include insomnia, breathing
disturbances during sleep (i.e., sleep apnea), movement
disorders during sleep (i.e., restless leg syndrome, periodic leg
movements), and sleep-wake state dissociation disorders (i.e.,
narcolepsy, rapid eye movement [REM] sleep behavior disorder,
sleep walking).
It is now clear that sleep is genetically controlled. Although
environmental factors can impact the duration and intensity of
sleep, genetic regulation is borne out by the heritability of sleep
traits (Ambrosius et al., 2008; De Gennaro et al., 2008), the iden-
tification of specific genetic polymorphisms that affect these
traits (Maret et al., 2005; Tafti et al., 2003), and the existence of
familial sleep disorders. Genetic model systems—zebrafish, fruit
flies, and worms—were recently developed for studying sleep,
and they are starting to reveal the molecular underpinnings of
sleep (Allada and Siegel, 2008; Andretic et al., 2008a; Cirelli,
2009; Crocker and Sehgal, 2010). Some researchers may ques-
tion the relevance of these model organisms for mammalian
sleep. However, we contend that the function and regulation of
sleep are likely conserved through evolution, and thus, it would
194 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
be strange to restrict sleep research to only a few species. For
example, some would argue that the worm sleep model, which
consists of developmental periods of low activity (i.e., quies-
cence), is dramatically different from human sleep, but we note
that characteristics of sleep vary greatly even among different
mammalian species. Indeed, the genetic model systems for
studying sleep may not recapitulate all aspects of human sleep,
but the prediction is that some key features will be conserved. As
we describe in this Review, molecular and genetic studies in
these model systems are, in fact, beginning to uncover regula-
tory mechanisms underlying sleep, which are conserved from
worms to mammals.
Molecular Insights from Animal Models
The idea of using model systems to understand a biological
process of interest is clearly not new. However, until about
a decade ago, studies of sleep were primarily restricted to a
few mammalian and avian species. This restriction was partially
because sleep was defined on the basis of altered brain electri-
cal activity, recorded through electroencephalograms (EEGs),
and this definition was not easily applied to other animals.
EEGs reveal three major states of behavior: wake, rapid eye
movement (REM) sleep, and non-REM (NREM sleep). In hu-
mans, REM and NREM sleep occur in 90 min cycles through a
night of sleep. NREM sleep is divided into stages 1–3, which
together with REM constitute the normal ‘‘sleep architecture.’’
Furthermore, human sleep is mostly consolidated into a single
period during the night. This phenomenon is observed in only
a few other mammals that, compared with humans, have less
consolidated sleep and wake periods, which alternate during
the day and night. Slow wave sleep is the deepest stage of
sleep, and this occurs during stage 3 of NREM. Many brain
areas are active during REM sleep; thus, the quiescence in
mailto:amita@mail.med.upenn.edu
http://dx.doi.org/10.1016/j.cell.2011.07.004
neural activity typically associated with sleep actually occurs
during NREM sleep.
Although the EEG definition of sleep, which is based upon
electrical activity patterns at the cortical level, precluded its
study in animals that do not have a well-defined cortex, pioneer-
ing efforts of a few researchers identified sleep-like states in
several species of fish, reptiles, amphibians, and even some
invertebrates, such as cockroach, bees, and octopus (Campbell
and Tobler, 1984). These researchers proposed specific behav-
ioral criteria to define sleep, but such practice was not widely
accepted. What eventually changed the field was the realization
that other fields hadmade rapid progress by using simple animal
models (Hendricks et al., 2000b). In particular, circadian biology
was often cited as an example of a field in which molecular
mechanisms identified in flies and fungi turned out to be
conserved in humans (Hendricks et al., 2000b). Thus, sleep
researchers developed simple animal models by using primarily
the criteria for a sleep-like state proposed originally by Campbell
and Tobler (1984). According to these criteria, a sleep-like state
is (1) a reversible state during which voluntary movements do not
occur; (2) controlled by a circadian clock; (3) accompanied by an
increase in arousal threshold, such that stronger sensory stimuli
are required to elicit a response from the animal; and (4)
controlled by a homeostatic system that ensures adequate
levels of the state. It is well known that sleep deprivation is
followed by a compensatory increase in sleep, or sleep rebound,
which reflects the essential nature
of sleep.
We now know that fish and fruit flies display periods of rest
at night, which satisfy behavioral and physiological criteria for
sleep (Hendricks et al., 2000a; Prober et al., 2006; Shaw
et al., 2000; Yokogawa et al.,
2007).
Likewise, criteria for sleep
are met by a quiescent state in worms—lethargus—although
this occurs during development in conjunction with larval molts
rather than as a 24 hr rhythm in adults (Raizen
et al., 2008).
Interestingly, the larval molts, and therefore lethargus, are
regulated by the worm ortholog of the circadian clock gene,
period (per), which regulates the timing of sleep in other organ-
isms. This raises the intriguing possibility that lethargus is
a primordial sleep state regulated by genes of the circadian
clock but occurring in a developmental context. Synapses
are formed during lethargus (Hallam and Jin, 1998; White
et al., 1978), which is also consistent with a proposed function
of sleep.
With genetic model systems now available, assays for sleep
have shifted from measuring cortical electrical activity (EEGs)
to directly monitoring rest and activity behavior. Video record-
ings can monitor many behavior states relatively easily, whereas
‘‘beam-break assays’’ canmonitor locomotor activity (Hendricks
et al., 2000a; Prober et al., 2006; Shaw et al., 2000; Yokogawa
et al., 2007). Electrophysiological recordings of fly brains have
revealed how the fly sleep state correlates with specific electro-
physiological characteristics (Nitz et al., 2002; van Swinderen
et al., 2004), but such recordings are clearly not practical
for high-throughput or even day-to-day experiments. Even in
the mouse (the preferred mammalian model for genetic
approaches), researchers are starting to rely upon measure-
ments of behavior to assay sleep instead of electrophysiological
measurements (Pack et al., 2007).
Importantly, these behavioral assays, used in different model
systems, are corroborating a role for sleep-regulating molecules
identified throughmore traditional approaches, and they are also
identifying new components. Here we review the major classes
of molecules identified thus far, focusing particularly on the find-
ings derived from the newer models for sleep—fish, flies, and
worms. For more details on the molecular analysis in mammals,
we direct the reader to two excellent Reviews (Andretic et al.,
2008a; Cirelli, 2009).
Neurotransmitter/Neuropeptide Systems
Regulation of sleep by various neurotransmitters was discov-
ered, before the advent of modern genetic technologies, through
pharmacological methods. Adenosine has long been touted
as a major sleep-promoting molecule that acts primarily in the
mammalian basal forebrain. Although there have been some
challenges to this idea, the hypothesis nonetheless prevails
(Bjorness and Greene, 2009). Wake-promoting effects of
caffeine are thought to be mediated by its antagonistic action
on adenosine receptors (Basheer et al., 2004). Indeed, mice
mutant for the A2A adenosine receptor show deficits in their
response to caffeine (Huang et al., 2005). However, mutants of
other adenosine receptors show limited effects on sleep. Bjor-
ness et al. (2009) found that disrupting the A1 receptor only in
the central nervous system reduces slow wave activity (an elec-
trophysiological measure thought to reflect sleep drive) in
response to sleep restriction, but it has no effect on baseline
sleep. These findings suggest that adenosine is one of many
neurotransmitters that regulate sleep, rather than being the
dominant regulator (Bjorness and Greene, 2009). Adenosine
and caffeine have similar effects on Drosophila sleep as they
do onmammalian sleep, and theDrosophila response to caffeine
is attenuated by decreased signaling through the dopamine D1
receptor or reduced protein kinase A (PKA) activity (Andretic
et al., 2008b; Wu et al., 2009). Surprisingly, the single known
adenosine receptor in Drosophila is not required for wake-
promoting effects of caffeine (Wu et al., 2009). Although this
may be indicative of different mechanisms driving the response
to caffeine (perhaps the inhibition of a phosphodiesterase,
another known target of caffeine), one cannot exclude the possi-
bility that other, unidentified adenosine receptors exist in
Drosophila.
Other neurotransmitters implicated in mammalian sleep are
histamine, dopamine, acetylcholine, norepinephrine, all of which
promote wakefulness, and GABA (gamma-aminobutyric acid),
which promotes sleep (Andretic et al., 2008a; Cirelli, 2009).
Effects of serotonin are somewhat complicated; although it
suppresses REM sleep, its effects on NREM are unclear and
may even be stimulatory (Crocker and Sehgal, 2010). Genetic
analysis in the mouse generally supports roles for these neuro-
transmitters in regulating sleep, although their effects are some-
times small and complicated, perhaps due to redundancy and
compensation.
In Drosophila, dopamine and octopamine, which acts similarly
to norepinephrine, have robust wake-promoting effects, where-
as GABA and serotonin promote sleep (Agosto et al., 2008; And-
retic et al., 2005; Crocker and Sehgal, 2008; Yuan
et al.,
2006).
Analysis of the cellular circuitry underlying these effects is start-
ing to reveal some interesting features. Dopamine invokes two
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 195
Figure 1. An Example of a Conserved Mechanism Underlying Sleep
In both Drosophila and mammals, an arousal-promoting peptide (PDF
and hypocretin, respectively) is secreted by cells within, or in the vicinity of,
the central clock network. In mammals, hypocretin-producing neurons in the
lateral hypothalamus receive circadian inputs from the central clock in the
suprachaismatic nucleus (SCN) via the dorsomedial hypothalamus (DMH).
(Circadian inputs are indicated in the lighter shaded box.) They are inhibited by
GABAergic inputs from the ventrolateral preoptic (VLPO) area. In Drosophila,
the large ventral lateral neurons (lLNvs) are part of the clock network although
they are not required for free-running circadian rhythms. Instead they mediate
light-driven arousal, at least in part through the release of PDF. As inmammals,
GABAergic inputs to these neurons promote sleep.
different types of arousal, a startle response and normal wakeful-
ness, and these are mediated by the same receptor but in
different cellular loci (Lebestky et al., 2009). Wake-promoting
octopamine is released by neurons in the dorsal part of the fly
brain, and it acts through the octopamine receptor OAMB
located in neuroendocrine cells that produce Drosophila
insulin-like-peptide (Dilp2) (Crocker et al., 2010). Many sleep-
related effects of serotonin and dopamine are mediated by
anatomical structures called the mushroom bodies, which are
also independently implicated in sleep (Joiner et al., 2006;
Pitman et al., 2006). Thus, the dopamine D1 receptor acts in
mushroom bodies to modulate the response to caffeine and to
prevent learning impairments induced by sleep deprivation,
whereas serotonin acts through the d5-HT1A receptor in mush-
room bodies to promote sleep (Andretic et al., 2008b; Seugnet
et al., 2008; Yuan et al., 2006). Finally, a major target of sleep-
promoting GABA is the large ventral lateral neurons (lLNvs)
(Parisky et al., 2008). These are best known for their expression
of circadian clock genes, although they do not appear to have
a function in free-running circadian rhythms (Nitabach and Ta-
ghert, 2008). Instead, the lLNvs promote arousal in response to
light (Shang et al., 2008; Sheeba et al., 2008). GABA signaling,
through the Resistance to dieldrin (Rdl) receptor, likely inhibits
these neurons, allowing sleep to occur.
Pharmacological studies in zebrafish have also implicated
many of the neurotransmitters that regulate sleep in flies and
mammals (Rihel et al., 2010). These studies highlight the power
of the fish system for identifying small molecules that affect sleep
via high-throughput screens. Small molecules can be added to
the water used to house the fish, allowing easy delivery and
access. In addition, many different populations of fish, each
treated with a different compound, can be assayed simulta-
neously through video recording. Through such a screen, Rihel
et al. identifiedwake-promoting effects of b-adrenergic agonists,
which is consistent with theDrosophila andmammalian data dis-
cussed above. Interestingly, as inDrosophila, selective serotonin
reuptake inhibitors (SSRIs) decreased wake in zebrafish. These
pharmacological approaches, together with the ease of high-
throughput screening in flies and fish, may allow for more
clear-cut answers regarding the role of individual sleep-regu-
lating components.
Neuropeptides also play a large role in regulating sleep, the
best known being the hypocretins/orexins (Sakurai, 2007). These
neuropeptides underlie the sleep disorder narcolepsy, as
described below in the section on human sleep genes. A
sleep-regulating role for hypocretins is conserved in zebrafish
(Faraco et al., 2006; Prober et al., 2006). Although orthologs of
these molecules have not been found in flies, a different neuro-
peptide may function in an analogous fashion (Parisky et al.,
2008). This peptide, pigment-dispersing factor (PDF), is secreted
by central clock cells, ventral lateral neurons, in the fly brain. The
small LNvs drive circadian rhythms in constant darkness, but the
lLNvs are required for light-mediated arousal, which appears to
depend upon PDF (Parisky et al., 2008). Thus, PDF may function
in flies as hypocretin does in mammals, as a wake-promoting
peptide secreted by neurons whose activity is suppressed
during sleep by inhibitory neurotransmitters such as GABA
(Figure 1).
196 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
Some molecules are required to regulate sleep under specific
conditions. For instance, Drosophila sex peptide, which is
secreted in the male seminal fluid, accounts for the decreased
sleep in females following copulation (Isaac
et al., 2010).
Whereas virgin females display a robust afternoon siesta, similar
to that seen in male flies, mated females have less daytime sleep
presumably because they need to perform more foraging and to
identify sites for egg-laying. As in flies, gender differences in
mammalian sleep depend upon gonad function (Zimmerman
et al., 2006).
Steroid hormones regulate many biological processes, and
sleep is no exception. TheDrosophila steroid hormone ecdysone
promotes sleep (Ishimoto and Kitamoto, 2010), as does the
naturally occurring neuroactive steroid 3alpha,5alpha-tetrahy-
drodeoxycorticosterone in mammals (Müller-Preuss et al.,
2002). Although the relevance of such regulation is not known,
the mechanism of action in mammals could involve stimulation
of GABA receptors (Müller-Preuss et al., 2002).
Intracellular Signaling Molecules
Given the important role for neuropeptides and neurotransmit-
ters, it is not surprising that signaling molecules acting down-
stream of neurotransmitters/neuropeptides also influence sleep.
For example, the protein kinase A (PKA)/CREB pathway pro-
motes wakefulness in Drosophila, and CREB promotes wake in
mammals (Graves et al., 2003; Hendricks et al.,
2001).
We
know that octopamine, and perhaps also PDF, acts through
PKA to increase wake (Crocker and Sehgal, 2008; Mertens et al.,
2005). In addition, some dopamine receptors signal through
cyclic adenosine monophosphate (cAMP), so PKA could also
contribute to wake-promoting effects of dopamine. It is impor-
tant to note that, although pan-neuronal expression of PKA
promotes wake, there are specific subsets of neurons in the fly
brain where PKA actually drives sleep (Joiner et al., 2006). In
these neurons, it may be activated by a sleep-promoting mole-
cule like serotonin.
The cyclic guanosine monophosphate (cGMP) kinase
promotes sleep in flies and worms (Raizen et al., 2008), and it
also regulates mammalian sleep (Langmesser et al., 2009).
Upstream signals of this kinase have not yet been identified,
but an intriguing possibility is that nitric oxide (NO) is involved
because NO is a known activator of cGMP and is independently
implicated in sleep regulation. The current model is that neuronal
NO, produced by inducible nitric oxide synthase, signals through
adenosine to promote recovery sleep following sleep deprivation
(Kalinchuk et al., 2010).
Another sleep-regulating pathway is the extracellular signal-
regulated kinases/mitogen-activated protein kinase (ERK/
MAPK) pathway, at least partly in response to epidermal growth
factor (EGF) signaling (Foltenyi et al., 2007). In Drosophila,
increased EGF signaling activates ERK to promote sleep. The
relevant EGF signals originate in the region of the pars intercer-
ebralis, close to the neuroendocrine cells that mediate wake-
promoting effects of octopamine. Thus, the pars intercerebralis
is a hypothalamus-like structure that contains sleep- and
wake-promoting cells in close proximity. The target of EGF
action, as measured by activated ERK signaling, is in the ventral
part of the fly brain. In addition, ATF-2, a transcription factor acti-
vated by MAPK in response to cellular stress, promotes sleep
through its action in lLNvs (Shimizu et al., 2008). Importantly,
a role for EGF signaling in rest:activity behavior is conserved
across species. LIN-3, an EGF-likemolecule in worms, promotes
behavioral quiescence by activating diacylglycerol and phos-
pholipase C-g (Van Buskirk and Sternberg, 2007). In mammals,
transforming growth factor alpha (TGF-a), which signals through
the EGF receptor, causes a cessation of locomotor activity
(Kramer et al., 2001).
Ion Channels and Channel-Regulating Proteins
Although a role for ion channels in sleep is predictable (because
channels are required to regulate neural activity), it is surprising
that channels and channel regulators are the most prominent
class of molecules identified through unbiased screens for
sleep-regulating genes. Of the channels, voltage-gated potas-
sium channels are turning out to have a major function in pro-
moting sleep. A genetic screen in Drosophila by Cirelli et al.
(2005) identified sleep-inhibiting effects of mutations in the
Shaker potassium channel. Cirelli and colleagues then showed
that Hyperkinetic, a regulatory subunit of Shaker, also influences
sleep levels in flies (Bushey et al., 2007). The rebound response
to sleep deprivation is intact in Shaker mutants, indicating that
the effects are specific for baseline sleep (Cirelli et al., 2005). In
an independent forward genetic screen, Koh et al. (2008) identi-
fied sleepless (sss) as another sleep-promoting gene. The sss
gene product is a small, GPI-anchored protein that regulates
levels and activity of the Shaker channel. SSS facilitates activa-
tion of Shaker and may also target Shaker to the appropriate
compartment in the cell (Wu et al., 2010). However, the reduction
in daily sleep is greater in the sss mutant than in Shaker and, in
addition, the sss mutation reduces the increased sleep (i.e.,
rebound) following sleep deprivation (Koh et al., 2008). It is
possible that misregulated Shaker in sssmutants has a stronger
effect than loss of Shaker in Shaker mutants (T. Dean, A.S., and
T. Hoshi, unpublished data). Alternatively, SSSmay also regulate
other sleep-relevant channels. The hypothesized structure for
SSS resembles that of some toxins, and so it could be an endog-
enous toxin-like molecule that regulates channel activity (Wu
et al., 2010).
The effects of Shaker channels on sleep are also conserved in
mammals (Douglas et al., 2007). A mammalian sss ortholog has
not been found yet in part because the limited coding region of
the small sss gene makes bioinformatic analyses quite difficult.
However, genes that share motifs with sss are found in the
mammalian genome, and the protein product of one such
gene, lynx1, also regulates a channel, the nicotinic acetylcholine
receptor (Miwa et al., 2006). Thus, it is likely that a SSS equivalent
exists in mammals.
Other studies have also pointed to the importance of channels
in sleep. The zebrafish screen described above found that
blockers of the ether-a-go-go-related gene (ERG) potassium
channel increase waking activity (Rihel et al., 2010). Interestingly,
a human syndrome that causes insomnia, in addition to other
pathologies, is associated with autoantibodies to voltage-gated
potassium channels (Josephs et al., 2004).
Circadian Clock Genes
It is well-known that the circadian clock regulates sleep, and
thus, one might expect clock mutants to exhibit sleep pheno-
types. On the other hand, circadian and homeostatic controls
may be, at least partially, independent, and thus, mutants could
be specific for one system or the other. For instance, the sss
mutants have normal clock function. Similarly, circadian clock
mutants may disrupt the consolidation of sleep (so that it does
not occur in amajor block of time at night), but they need not alter
the total amount of sleep, which is a measure of homeostatic
regulation.
The major known clock mechanism in eukaryotes consists of
cyclically expressed core clock proteins that negatively regulate
their own transcription in an autoregulatory loop (Zheng and
Sehgal, 2008). Typically, one of these negative regulators is crit-
ical for determining the circadian period. Transcriptional activa-
tion of the negative regulators requires two proteins that usually
function as a dimer and are essential for the amplitude of the
rhythm. InDrosophila, loss of the transcriptional activatorsClock
(Clk) and cycle (cyc) decreases total sleep time (Hendricks et al.,
2003). However, loss of the repressors period (per) and timeless
(tim) has little to no effect on sleep. In mammals, sleep pheno-
types have been reported for the activators Clock and BMAL1
and also for repressors Per and Cryptochrome (Cry) (Laposky
et al., 2005; Naylor et al., 2000; Wisor et al., 2002). In addition,
a circadian gene that acts as a corepressor in mammalian and
fly clocks alters total sleep time in humans (discussed below).
As to whether these effects of the clock genes are an output of
the circadian clock or represent functions independent of time-
keeping is not clear. It has been suggested that effects of the
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 197
Table 1. Signaling Mechanisms that Regulate Sleep across
Species
Molecule Drosophilaa Mammalsa
Dopamine [ Wake [ Wake
GABA [ Sleep [ Sleep
Norepinephrine (octopamine) [ Wake [ Wake
Serotonin [ Sleep [ REM sleep
NREM sleep?
cAMP/cAMP signaling [ Wake [ Wake
EGF signaling [ Sleep [ Sleep
Voltage-gated K+ channels (Shaker) [ Sleep [ Sleep
aWorms and fish are not included because many of these pathways have
not yet been investigated in these systems.
mammalian clock genes on sleep occur not in the central clock
(the suprachiasmatic nucleus) but rather in other parts of the
brain (Franken and Dijk, 2009). Definitive conclusions will require
selective rescue of the two phenotypes—circadian and sleep—
through tissue-specific expression. If both phenotypes are
rescued through expression in the same subset of cells, they
likely represent the same type of regulation.
Metabolic Factors
People with diabetes show a high incidence of sleep disorders,
and short sleep times have correlated with obesity, leading to
the notion that one physiological process influences the other
(Adamantidis and de Lecea, 2008). Little is known about this
connection on amolecular level, but it is actively under investiga-
tion in model systems.
When flies are starved, they forage for food, a response that
can be assayed in the laboratory as increased activity. Under
these starvation conditions, sleep is suppressed, but the drive
to sleep does not accumulate. In addition, learning deficits that
can be caused by sleep deprivation also do not accumulate
(Keene et al., 2010; Thimgan et al., 2010). Sleep suppression
occurs, at least in part, through the activity of the CLK and
CYC proteins. Thus, Clk and cycmutants show decreased sleep
during normal conditions but are unable to further suppress
sleep when starved (Keene et al., 2010). Whereas mutating Clk
and cyc causes sleep deficits in response to a metabolic stress,
brummer (bmm) and lipid storage droplet 2 (lsd2) appear to be
primarily metabolic mutants that also affect sleep (Thimgan
et al., 2010). The bmm mutants are resistant to starvation and
display an increased homeostatic response, measured as
increased rebound, to sleep deprivation; conversely, lsd2
mutants are sensitive to starvation and display decreased sleep
homeostasis. Based upon these findings, it is tempting to
propose models for the interaction between sleep and metabo-
lism, but that is premature at this point. It is entirely possible that
this apparent interaction reflects shared molecular pathways
between sleep and metabolism rather than mutual regulation.
Immune Genes
A long-standing hypothesis posits that immune genes promote
sleep (Imeri and Opp, 2009). The immune protein NF-kB is up-
regulated in sleep-deprived mammals (Chen et al., 1999), and
sleep is usually increased during illness (Imeri and Opp,
2009). Recent studies in Drosophila reveal that immune genes,
such as Relish (encoding the Drosophila NF-kB), and antibacte-
rial peptides are upregulated following sleep deprivation (Wil-
liams et al., 2007). Although Relish mutants show only minimal
changes in total sleep, it appears that Relish is required to
increase sleep in response to injury or infection (Kuo et al.,
2010). Thus, some immune genes may promote sleep under
pathological conditions, which could include prolonged sleep
deprivation. Increased sleep under injury or infection supports
a role for sleep in facilitating recovery (Imeri and Opp, 2009).
At the same time, mutating some immune genes, such as
TAK1 (TGF-b-activated kinase), alters baseline sleep in
Drosophila, and anti-inflammatory compounds, such as gluco-
corticoids and NSAIDs, increase daytime activity in zebrafish,
indicating that immune/inflammatory signaling also affects
baseline rest:activity levels (Rihel et al., 2010; Williams et al.,
2007).
198 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
Key Features to Emerge from Model Organism Studies
It is clear that mechanisms regulating sleep are conserved
across species (see Table 1 for a summary of the mechanisms
conserved in flies and mammals). Another striking observation
from these studies is that there do not appear to be dedicated
sleep genes. Even the most unbiased approaches have not, to
date, uncovered genes that function specifically to regulate
sleep. Thus, in contrast to circadian clocks, in which the key
components are proteins dedicated to timekeeping, sleep is
regulated by genes that are involved in normal neuronal function.
Many such genes are also important for circadian rhythms, but
they function downstream of the clock to relay time-of-day
signals.
In case of sleep, the homeostat itself—the component that
drives theneed to sleep—maybederived fromchanges in routine
neural function. Models for sleep homeostasis, which invoke
changes in adenosine or glycogen, fit with this idea, suggesting
that excess neural activity leads to altered levels of a molecule
that signals an energy imbalance and promotes sleep (Scharf
et al., 2008). These models naturally support energy-restoration
functions for sleep. On the other hand, the information gleaned
from the genetic analysis of sleep is also perfectly consistent
with a role for sleep in synaptic plasticity. Indeed, a synaptic func-
tion for sleep is supported by both the mutant Drosophila lines
discussed above and the molecular screens searching for genes
regulated as a function of sleep state. For example, molecules
and proteins that mediate recovery from neuronal hyperactivity
(e.g., Homer1) are upregulated by sleep loss (Maret et al., 2007;
Nelson et al., 2004). Presumably, this contributes to synaptic
scaling during sleep, as discussed below. Wewill return to spec-
ulating about sleep function after discussing genes implicated in
human sleep and sleep disorders.
Genetic Factors Underlying Circadian RhythmDisorders
It is now well-established that familial advanced
sleep phase
syndrome (FASPS) is caused by mutations in human clock-
related genes (Toh et al., 2001; Xu et al., 2005). Individuals with
this autosomal-dominant trait have normal sleep architecture
and a lifelong tendency to wake and sleep at very early times
(i.e., 1–3 a.m. and 6–8 p.m., respectively). Melatonin and temper-
ature rhythms are advanced by 4–6 hr, and the free-running
period (i.e., the period of rhythms observed in organisms in the
absence of any environment clues, thereby indicating endoge-
nous clock time) has been measured as 1 hr shorter than in
controls. Underlyingmutations in two pedigree populations point
to defects in phosphorylation of PER2 as the core issue, with
mutations identified in both PER2 and Casein Kinase 1 genes
(CK1d).
These findings correspond well with circadian mutations in
other organisms. For example, in Drosophila and the Syrian
hamster, mutations in the CK13 kinase (encoded by the
Drosophila doubletime [dbt] gene and Syrian hamster tau gene)
lead to deficient phosphorylation of PER and changes in circa-
dian period. Mouse modeling studies of the FASPS mutations
revealed a few surprises in the molecular pathways of these
components. These include the probable action of an unknown
kinase, complex interactions of phosphorylation with nuclear
entry and retention, and transcriptional and posttranscriptional
regulation of clock proteins (Mignot and Takahashi, 2007).
Diurnal preferences (i.e., a tendency to prefer mornings versus
evenings) are heritable (Drennan et al., 1991). Thus, genetic vari-
ants affecting circadian regulation are segregating in the general
population. Variable results have been obtained from genome-
wide or candidate gene association studies attempting to iden-
tify these variants, suggesting that the next step is to greatly
increase sample size (e.g., 100,000 individuals) for genome-
wide association studies (GWAS). Another option is to rese-
quence candidate loci in individuals or family clusters with
phenotypes at the extremes of the normal range. Further,
subjective diurnal preference scores are likely less amenable
to genetic analysis than more objective physiological measures
of circadian phase.
Genetic Factors Regulating EEG and the Sleep
Homeostat
Genetic analysis of selected EEG traits and the sleep homeostat
is an active field in model systems and in humans. In mice, spec-
tral features of the EEG are altered by a deficiency in a single
enzyme involved in short-chain fatty acid metabolism (ACADS)
(Tafti et al., 2003), as well as by Homer1a. The latter was identi-
fied through quantitative trait locus (QTL) analysis and mapping
studies in inbred mice (Maret et al., 2007). This illustrates the
strong effect that genetic background has on the effect size of
any identified gene, which complicates the extrapolation of loci
identified in model organisms to potential human phenotypes.
In humans, a variation in the PER3 gene was recently associ-
ated with differences in EEG markers of sleep homeostasis after
sleep deprivation and with behavioral consequences of this
deprivation (Viola et al., 2007). Although this polymorphism
was not implicated in related studies by other groups (Goel
et al., 2009), the original finding suggests that circadian genes
are involved in sleep homeostasis, consistent with studies in
mice and Drosophila (Mignot, 2008).
Average sleep duration at night is a poorly defined phenotype,
and so not surprisingly, GWAS have yielded neither significant
(�p < 10�8) nor reproducible signals in studies with limited
sample sizes (up to 10,000 individuals). However, a recent
screen for circadian gene mutations in pedigrees with habitual
short sleep duration identified a mutation in a critical basic
helix-loop-helix domain of DEC2 (a repressor of CLOCK/
BMAL1 activity) (He et al., 2009). Studies of this mutation in
animal models showed that it causes increased daily wakeful-
ness in transgenic mice, as well as dominant effects in trans-
genic flies. This again illustrates the role of circadian clock
proteins in the regulation of sleep and suggests that a viable
approach to identifying additional sleep-regulatory genes may
be systematic mutation screening, exome sequencing, or
whole-genome sequencing in subjects with extreme sleep
phenotypes segregating in pedigrees.
Genetics of Human Narcolepsy-Cataplexy
Narcolepsy affects the control of sleep and wakefulness, result-
ing in excessive daytime sleepiness, symptoms of dissociated
REM sleep (e.g., sleep paralysis and dream-like ‘‘hypnagogic’’
hallucinations at sleep onset), disrupted nocturnal sleep, and
cataplexy (i.e., brief episodes of muscle weakness triggered by
emotions). In animal models, the full disease can be produced
by disrupting hypocretin (orexin) neurotransmission by defects
in either the hypocretin receptor 2 or the hypocretin ligand
gene (Chemelli et al., 1999; Lin et al., 1999). By contrast, the
disease in humans is sporadic, resulting in the majority of cases
from a loss of �70,000 hypothalamic neurons producing hypo-
cretin, rather than single-gene mutations (Chabas et al., 2003).
Concordance is low (35%) in monozygotic twins, but recurrence
risk in first degree relatives is increased by 20- to 40-fold,
although still low overall (0.9%–2.3%), suggesting that the
disease results from an interaction of environmental factors on
a susceptible genetic background.
The destruction of hypocretin cells is almost certainly an auto-
immune event, as both Human Leukocyte Antigen (HLA) and
T cell receptor (TCR) variants have strong effects on predisposi-
tion. Expressed on immune cells, HLA class II antigens present
processed foreign peptides to T cells by engaging the TCR.
Nearly all narcolepsy/hypocretin deficiency cases carry two
specific and tightly linked class II gene alleles: DQA1*01:02
and DQB1*06:02. (HLA genes are extremely polymorphic, and
alleles are grouped in broader subtypes based on sequence
similarities, as noted by the first two digits; the next two digits
represent minor amino acid variations among these broader
families.) However, these are also common alleles across ethnic
groups (12%–38%) and thus are not sufficient to cause disease
(Mignot et al., 2001). Other HLA class II alleles also modulate
susceptibility, notably DQB1*03:01 (susceptibility) and
DQB1*06:01, DQB1*05:01, and DQA1*01 (non-DQA1*01:02)
(protective). Analysis of the binding pockets and dimerization
activities of these variants indicates that even minor changes in
the peptide-binding pockets may determine risk and that some
protective alleles may act by reducing the availability of the
disease-associated DQA1*01:02/DQB1*06:02 heterodimer
(Hong et al., 2007; Mignot et al., 2001).
The TCR alpha gene (TCRA) is also an important susceptibility
factor for narcolepsy. TCR initiates an immune response when it
interacts with peptide-bound HLA antigens. Like the immuno-
globulin loci, the TCRA locus undergoes somatic cell recombina-
tion between 46 functional variable (V) and 49 functional joining
(J) segments. A single-nucleotide polymorphism (SNP) variant
(rs1154155C) in the J segment region of the locus shows sig-
nificant association in Caucasians and other ethnic groups
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 199
(Hallmayer et al., 2009), and this association has been replicated
in multiple
studies.
We hypothesize that the DQB1*0602/
DQA1*0102 HLA heterodimer interacts with a TCR idiotype in
which a specific VJ recombinant is associated with the presence
of rs1154155 (directly or indirectly). In the context of a selected
antigenic trigger, this could then lead to further immune reaction
ending in the destruction of hypocretin-producing cells.
Most autoimmune diseases have an array of strong HLA
susceptibility factors. Thus, perhaps one of the most intriguing
aspects of the autoimmune process in narcolepsy is the remark-
able specificity of both the susceptibility loci and the autoim-
mune target, as destruction appears highly selective toward
hypocretin cells. In addition, typical markers of an autoimmune
process disappear rapidly after the disease destroys hyocretin
cells, if they are ever present at all (Overeem et al., 2008).
Increased autoantibodies against Tribbles homolog 2 (TRIB2)
near disease onset were recently suggested by several groups
(Lim and Scammell, 2010) but not confirmed in samples
collected later (Dauvilliers et al., 2010). Upper airway infections,
such as strep throat and flu, have been implicated as environ-
mental triggers of narcolepsy. Higher rates of diagnosed strep
throat infections and high titers of anti-streptolysin O (marking
strep infections) near disease onset have been reported (Long-
streth et al., 2009). Additionally, H1N1 vaccines containing the
AS03 adjuvant and H1N1 infections are also implicated as rare
triggers of narcolepsy (Dauvilliers et al., 2010). These triggers
may act either directly by contributing important epitopes or
nonspecifically through reactivation of dormant T cell clones,
superantigen activity, or permeabilizing the blood brain barrier
(for example by fever) and thereby facilitating immune cell entry
(Dauvilliers et al., 2010).
Additional narcolepsy susceptibility loci have been identified
through GWAS. A SNP marker located between and decreasing
expression of carnitine palmitoyltransferase 1B (CPT1B) and
Choline Kinase B (CHKB) was associated with narcolepsy in
a Japanese sample, and the association was replicated in
a second sample of Japanese but not in Caucasians (Miyagawa
et al., 2008). Both genes are plausible REM sleep regulatory
candidates. CHKB metabolizes choline, the precursor of acetyl-
choline, a regulator of REM sleep. Likewise, CPT1B is part of
the carnitine shuttle, transporting long-chain fatty acyl-CoAs
from the cytoplasm into the mitochondria. CPT1B is also a rate-
controlling enzyme of the beta-oxidation pathway in mitochon-
dria, a pathway involved in the regulation of theta-oscillations
during REMsleep (Tafti et al., 2003). The possibility that this poly-
morphismmodulatesREMsleep independently of hypocretin cell
loss was recently bolstered by the finding of an
association in
essential hypersomnia, a milder form of narcolepsy typically not
associated with hypocretin deficiency (Miyagawa et al., 2009).
A direct effect of this polymorphismonREMsleepwould suggest
that decreased mitochondrial beta-oxidation (a process that
occurs primarily in the periphery) is associated with increased
REM, linking REM sleep with energy homeostasis.
A role for purinergic receptors in narcolepsy was identified by
a GWAS in Caucasians, followed by fine mapping in multiple
ethnic groups (Kornum et al., 2011). Purinergic signaling plays
a key role in immune regulation. The SNP rs2305795, located
in the 30 untranslated region of the purinergic receptor gene
200 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
P2Y11, decreases the receptor’s expression in peripheral mono-
nuclear cells and is significantly associated with narcolepsy
susceptibility. The P2Y11 receptor also modulates immune cell
chemotaxis and cell death induced by ATP, suggesting immune
modulatory effects.
Genetics of Other Sleep Disorders
Restless Leg Syndrome
Restless leg syndrome (RLS) is a common disorder character-
ized by an uncomfortable and intrusive urge to move the lower
limbs. Symptoms manifest during rest, are worse in the evening,
and improve with movement. Periodic leg movements in sleep
are often also present. Numerous studies have shown that iron
deficiency in the brain and reduced dopaminergic neuronal
activity are critical pathophysiological factors (Salas et al., 2010).
RLS has a strong genetic component, with up to 60% of
cases reporting affected family members and high concor-
dance (83%) reported in monozygotic twins. Attempts to iden-
tify RLS genes through linkage analysis in families have identi-
fied neither specific mutations nor specific genes, although
three linked genomic regions have been replicated (reviewed
in Trenkwalder et al., 2009). By contrast, studies using a
GWA design have been fruitful (Stefansson et al., 2007; Winkel-
mann et al., 2007, 2011), revealing a surprising role for develop-
mental regulatory factors. These transcription factors likely
affect spinal cord regulation of sensory perception and loco-
motor pattern generation and may also interact with brain
iron homeostastis.
The MEIS1 locus is the most important RLS susceptibility
gene. Variants near exon 9, a region with high interspecies
conservation, have shown the strongest association with RLS,
displaying odds ratio greater than 2 (Winkelmann et al., 2007).
More recently, an extended study also found an additional, inde-
pendent association 1.9 MB away from MEIS1, in a region likely
to also regulate MEIS1 expression (Winkelmann et al., 2011)
(Table 2). MEIS1 is strongly expressed in dopaminergic neurons
of the substantia nigra (where studies have reported lower iron
levels in RLS cases), in the spinal cord, and in the red nucleus,
a region that regulates coordination of limb movement and that
also contains lower iron levels in RLS. MEIS1 is part of a Hox
transcriptional regulatory network that specifies motor neuron
pool identity and thus the pattern of target-muscle connectivity,
suggesting a key link to the pathophysiology of RLS within the
spinal cord.
Variants in BTBD9 (BTB [POZ] domain containing 9) have also
repeatedly shown association with RLS, with allelic odds ratios
between 1.5–1.8. Notably, in an Icelandic cohort (Stefansson
et al., 2007), SNP associations were strongly tied to the presence
of periodic limb movements (i.e., the repetitive cramping or jerk-
ing of the legs during sleep), implying that this locus confers risk
specifically for themotor component of RLS. Serum ferritin levels
were also found to vary by genotype, potentially underlying the
iron deficiency associated with RLS. Little is known of the func-
tion of BTBD9 in mammals; however, in Drosophila, proteins
containing the BTB (POZ) domain have important roles in meta-
morphosis and limb pattern formation. These proteins have
wide-ranging functions, making assignment of a specific func-
tion to BTBD9 difficult.
A third RLS locus surrounds the MAP2K5 and
SKOR1
(LBXCOR1) genes, but linkage disequilibrium has prevented
identification of the relevant gene (Winkelmann et al., 2007).
SKOR1 (SKI family transcriptional corepressor 1) has appealing
links to RLS, as it is expressed selectively in a subset of dorsal
horn interneurons in the developing spinal cord, which relay
pain and touch. The SKOR1/Lbx1 pathway is essential to the
generation of a GABAergic versus glutamatergic phenotype in
these cells (Cheng et al., 2005), and this locus may contribute
to the sensory component of the phenotype by affecting modu-
lation of sensory and pain inputs.
Extended fine mapping and GWA studies have identified
two additional loci (Table 2). The PTPRD (protein tyrosine
phosphatase receptor type delta) locus emerged through fine
mapping of a suggestive GWA signal in a linkage region on
chromosome 9p (Schormair et al., 2008). Although no muta-
tions were identified among patients, this is still an excellent
candidate, with established roles in axon guidance and termi-
nation of motor neurons during embryonic development in the
mouse. Most recently, a large linkage disequilibrium block
containing TOX3 (a breast cancer susceptibility locus) and
untranslated BC034767 was associated with susceptibility in
an extended RLS sample, although a role for these two tran-
scripts in RLS pathogenesis is not yet known (Winkelmann
et al., 2011).
A role for neuronal nitric oxide synthase (NOS1) in RLS was
also suggested through fine mapping of a region on chromo-
some 12q, which was first identified through linkage analysis in
population-based RLS cases and controls (Winkelmann et al.,
2008), although no mutations were detected in RLS1-linked
family members. The NOS1 gene is an appealing candidate for
underlying specific symptoms of the syndrome because nitric
oxide acts as an atypical neurotransmitter in the central nervous
systemwith roles in pain perception, control of sleep-wake regu-
lation, and modulation of dopaminergic activity (Winkelmann
et al., 2008).
Taken together, results to date suggest that RLS is character-
ized by an imbalance of the spinal circuitry gating sensory inte-
gration and controlling locomotor outputs. This imbalance may
be developmental and is mostly the result of genetic polymor-
phisms in transcription factors. Descending influences, for
example descending dopaminergic projections, cognitive influ-
ences, and the effect of iron deficiency further destabilize the
circuitry.
Hypersomnias, Insomnia, and Parasomnias
Table 2 provides a summary of the various sleep disorders for
which some genetic data are available. Many additional sleep
disorders and parasomnias (i.e., sleep disorders that involve
abnormal and unnatural movements or behaviors) show genetic
effects or familial clustering, but no specific genes are yet
implicated. Insomnia runs in families and has higher concor-
dance in monozygotic twins, but this heterogeneous phenotype
will require large samples and potentially EEG-based endophe-
notypes for genetic mapping. Individuals with Morvan’s
syndrome, a disorder associated with insomnia, have autoanti-
bodies to potassium channels suggesting a potentially con-
served mechanism, given the role of these channels in sleep in
model organisms.
In the general population, idiopathic hypersomnia, or isolated
sleepiness, is another poorly defined and heterogeneous pheno-
type. Candidate loci identified (Gottlieb et al., 2007) in a low-
density GWAS await confirmation. The distinction between
narcolepsy without cataplexy and idiopathic hypersomnia is
difficult. These may lie on a continuum with narcolepsy-cata-
plexy, as the frequency of DQB1*0602 (40%) in patients with
idiopathic hypersomnia is intermediate between that in the
general population (12%–38%) and that in narcolepsy-cataplexy
(70%–100%). Although measurements of hypocretin in cerebro-
spinal fluid are typically within the normal range for narcolepsy
without cataplexy, some patients show low levels in the narco-
lepsy-cataplexy range in association with DQB1*0602 (Mignot
et al., 2002). Hypocretin levels are within normal range for idio-
pathic hypersomnia, with rare exceptions. As mentioned above,
a narcolepsy polymorphism located between CPT1B and CHKB
may be associated with both narcolepsy and hypersomnia in
Japanese cohorts.
Kleine Levin syndrome (KLS) is a rare disorder primarily
affecting adolescent males. Characterized by recurring episodes
of profound hypersomnia and cognitive and behavioral changes,
it typically attenuates and disappears in adulthood. Recent
studies suggest that genetic factors confer susceptibility. Ashke-
nazi Jewish heritage is often reported, suggesting a potential
founder effect. Furthermore, 5 out of 105 KLS patients reported
an affected family member. This suggests the action of a major
susceptibility gene that potentially controls the response after
exposure to an unknown environmental trigger, such as an
infection. An HLA association with KLS was suggested, but
this finding has not been replicated in subsequent studies (Arnulf
et al., 2008).
Features of dissociated REM sleep, such as sleep paralysis
and hypnagogic hallucinations, are highly heritable and frequent
in the general population, particularly with insufficient sleep.
Sleep paralysis shows high concordance in monozygotic twins,
and autosomal-dominant transmission has been reported (re-
viewed in Mignot, 1997). In REM sleep behavior disorder, inhibi-
tion of motor pathways in REM sleep is lost, allowing robust and
potentially dangerous motor activity in response to dream con-
tent. As with other features of dysregulated REM sleep, REM
sleep behavior disorder is common in narcolepsy, but it also
occurs in the population and in Parkinson’s disease. REM sleep
behavior disorder is often an early sign of neurodegenerative
disorders, particularly Parkinson’s disease (Massicotte-Mar-
quez et al., 2008). The extent of heredity in REM sleep behavior
disorder has not been established, but a variety of single-
gene
defects and HLA-DR/DQ are implicated in the development of
Parkinson’s disease.
NREM sleep parasomnias, including sleepwalking, sleep
talking, and night terrors, typically occur during slow wave
sleep. Prevalence is high in children but rarely requires medical
intervention and typically disappears during adulthood. Sleep-
walking may be present in up to 20% of children and is present
in up to 3% of adults. Sleepwalking, sleep talking, enuresis
(i.e., bed-wetting), bruxism (i.e., grinding teeth), and night
terrors have substantial genetic effects and also co-occur, sug-
gesting some common genetic susceptibilities (Hublin et al.,
2001).
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 201
Table 2. Human Susceptibility Loci for Sleep and Sleep Disorders
Genes Pathology
Experimental
Design
Associated SNP,
Allele, or Mutation
Allelic Odds
Ratio Comments
DQB1 and DQA1
(forming the DQ
heterodimer)
Narcolepsy/
hypocertin
deficiency
Candidate
gene
Main predisposing effect is
DQB1*06:02–DQA1*01:02;
Secondary predisposing effects:
DQB1*03:01; Secondary
protective effects: DQA1*01,
DQB1*05, or DQB1*06 that are
not DQA1*01:02, DQB1*06:02.
OR0602 = 8.8
(Caucasians)
Effects conserved across African
Americans, Asians, andCaucasians.
Most effects in these loci are
dominant mediated by DQ01*06:02;
very few cases are DQB1*06:02
negative. Almost all subjects are
DQ1*0:102, an allele in tight
linkage with DQB1*06:02.
CPT1B/CHKB Narcolepsy/
hypocrerin
deficiency
Essential
hypersomnia
GWAS rs5770917C
(affect expression)
OR = 1.8
(Japanese only)
Association is still tentative.
Identified in Japanese narcolepsy
patients, replicated in Koreans. The
association is not significant in
European populations or those of
African descent. Did not replicate in
a Chinese narcolepsy sample. Also
associated with hypersomnia in
Japan. Loci have roles in
beta-oxidation and acetylcholine
synthesis, potentially modulating
rapid eye movement (REM) sleep.
TCRA Narcolepsy/
hypocretin
deficiency
GWAS rs1154155C
(may modify TCRJ
usage or sequence)
OR = 1.7
(all ethnic
groups)
Identified in Caucasian narcolepsy
patients and replicated across
ethnic groups (Asians and African
Americans). Independently
replicated in European and Chinese
narcolepsy patients and in Japanese
cases with HLA (human leukocyte
antigen)-positive essential
hypersomnia. This suggests the
involvement of a specific T cell
receptor on narcolepsy patients,
possibly interacting with the
DQ locus.
P2RY11 Narcolepsy/
hypocretin
deficiency
GWAS rs2305795A
(affect expression)
OR = 1.3 Identified in Caucasians, with
replication across ethnic groups;
not yet replicated independently;
immunomodulatory function or
reduced ATP-induced apoptosis
of immune cells.
HPER2 Familial advanced
sleep phase
syndrome
Candidate gene
sequencing
S662G (removal
of a functional
phosphorylation site)
n.a.
(fully penetrant)
Autosomal-dominant transmission;
validation in in vitro and mice
models.
CK1d Familial advanced
sleep phase
syndrome
Candidate gene
sequencing
T44A (reduced kinase
activity of the enzyme)
n.a.
(fully penetrant)
Autosomal-dominant transmission;
validation in in vitro and mice
models.
DEC2 Familial
short sleep
Candidate gene
sequencing
P385R (reduced
Clk/Bmal1-mediated
transactivation by DEC2)
n.a.
(fully penetrant)
Autosomal-dominant transmission
(allele dosage model); validation
in fly and mice models.
MEIS1(a)
Restless leg
syndrome
GWAS rs6710341A- rs12469063G
haplotype
OR = 2.0
(Caucasians)
Identified in Caucasians; replicated
by multiple studies in Caucasians;
decreased expression in restless
leg syndrome (RLS); function still
unknown in mice. MEIS1 functions
in CNS and motor neuron
development.
202 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
Table 2. Continued
Genes Pathology
Experimental
Design
Associated SNP,
Allele, or Mutation
Allelic Odds
Ratio Comments
MEIS1/
ETAA1(b)
Restless leg
syndrome
GWAS rs6747972A OR = 1.2
(Caucasians)
Independent association; intergenic
region on chromosome 2p14
located 1.3 MB dowstream of
MEIS1; likely regulates MES1
or ETAA1 expression.
BTBD9 Restless leg
syndrome
GWAS rs9296249T OR = 1.7
(Caucasians)
Replicated by multiple studies in
Caucasians; also associated with
periodic leg movements during
sleep independent of RLS; risk allele
may be associated with decreased
ferritin (more prominent in women
than in men); allele dosage model;
involvement
in RLS unknown.
MAP2K5/
SKOR1
(LBXCOR1)
Restless leg
syndrome
GWAS rs1026732G OR = 1.5
(Caucasians)
Most likely LBXCOR1 (SKOR1);
recessive effect; allele dosage
model; gene has a function in
the development of the CNS/spinal
cord/dorsal horn; involvement
in RLS unknown.
PTPRD Restless leg
syndrome
GWAS rs4626664T,
rs1975197A
OR = 1.4
(Caucasians)
Replicated independently in
Caucasian populations; allele
dosage model; involvement in RLS
unknown. In principle, it functions
during the development of the CNS/
motorneuron and in axon guidance.
TOX3,
noncoding
BC034767
RNA
Restless leg
syndrome
rs3104767G OR = 1.3
(Caucasians)
TOX3 is a well-known breast cancer
susceptibility gene, but it associates
with a different SNP. Genome-wide
significant but no clear functional
data or independent replication.
NOS1 Restless leg
syndrome
Case-control
association in
RLS linkage region
rs7977109A OR = 0.76
(Caucasians)
Not yet replicated; involvement
in RLS unknown; suggested to
modulate dopaminergic
neurotransmission; different
variants across the gene were
associated in two case-control
studies.
Sleep-Disordered Breathing and Obstructive Sleep
Apnea
Obstructive sleep apnea is a highly prevalent disorder character-
ized by intermittent upper-airway collapse, which impairs
ventilation and disrupts sleep (White, 2005). Numerous geneti-
cally influenced or physiologic factors can contribute to upper-
airway collapse, including anatomical features (e.g., craniofacial
features), reduced dilator muscle activity during sleep,
decreased end-expiratory lung volume, ventilatory control insta-
bility, and sleep-state instability, although obesity may outweigh
these other predispositions.
Candidate gene and small GWA studies of this complex
phenotype (which use the apnea hypopnea index as phenotype)
have not led to consistently replicated findings apart from an
association with Apolipoprotein E allele e4 (APOE e4), which
has been variably replicated (for example, Gottlieb et al.,
2004). APOE e4 is well known to be associated with Alzheimer’s
disease. The association with sleep apnea remains controver-
sial, as samples differed by age, ethnicity, and body mass index,
as well as screening methodology. The association may also be
confounded by interactions with cognitive decline, which affects
symptom reporting. However, APOE e4 could predispose an
individual to sleep apnea through multiple mechanisms,
including lowering levels of choline acetyltransferase and
reducing neuromuscular activation of the upper-airway dilator
muscles. Furthermore, differential lipid binding to b-amyloid or
Tau proteins could lead to plaque formation in respiratory
centers. Based on the range of interacting physiologic traits
that contribute to susceptibility to sleep apnea, future studies
will likely need to use endophenotypes to reduce heterogeneity
in order to identify underlying loci.
Overlap between Human Sleep Genes and Those Found
in Model Organisms
Studies of sleep in humans have focused on specific sleep dis-
orders rather than variations in amount of sleep. To the extent
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 203
that these disorders can be modeled in animals, mechanisms
appear to be conserved, as highlighted by narcolepsy symptoms
resulting from hypocretin system defects in humans, dogs, or
rodents. Animal models do not exist for many other human
sleep-related behaviors (RLS, parasomnias, etc.) and thus
comparisons cannot be made; however, conserved effects of
the circadian genes are well documented. For instance, alleles
of per in flies, which shorten the circadian period, result in a
phase advance in light-dark cycles, similar to that seen in hu-
mans with ASPS (Marrus et al., 1996). In addition, Dec2 is asso-
ciated with sleep phenotypes in humans, mice, and flies (He
et al., 2009). Finally, sleep-modulatory drugs used in humans
act through many of the neurotransmitter systems discussed in
the section on animal models, and they typically have similar
behavioral effects in these animals, including flies.
Sleep Function: Insights from Model Organisms
Studies in model organisms suggest a role for sleep in support-
ing cognitive function (Diekelmann and Born, 2010; Poe et al.,
2010) through the promotion of synaptic plasticity. As noted
above, the wormmodel for sleep is based upon a developmental
stage associated with neural changes, and many of the identi-
fied sleep-regulatory genes function in plasticity. Several
sleep-regulating loci, including PKA and CREB, are among the
major components required for learning and memory (Bailey
et al., 1996). In addition, their effects on sleep are mediated in
tissues important for the consolidation of memory. Thus, effects
of PKA on Drosophila sleep are exerted largely, although not
entirely, in the Drosophila mushroom bodies, well-known for
their function in learning and memory (Joiner et al., 2006). More-
over, the sleep-consolidating effects of serotonin, involved in
synaptic facilitation in Aplysia (Bailey et al., 1996), are mediated
by the 5-HT1A receptor in the mushroom bodies (Yuan et al.,
2006).
Although sleep is regulated by brain structures important for
learning and memory, the reverse is also true: sleep deprivation
impacts memory and the sites of memory formation. Learning
impairments induced by sleep deprivation of Drosophila can be
rescued by the expression of the dopamine D1 receptor inmush-
room bodies (Seugnet et al., 2008). Similarly, sleep deprivation of
mice impairs learning by impacting gene expression in the
hippocampus (Vecsey et al., 2009), most notably through
increases in phosphodiesterase 4 (PDE4). Thus, thesemolecules
that regulate both sleep and plasticity may well provide the
mechanistic link between these two processes.
The critical question then is, how does sleep promote the
consolidation of memory, or what specifically is its role in syn-
aptic plasticity? Whereas some argue that sleep promotes
synaptic potentiation, others suggest that sleep is required for
synaptic depression. In support of the latter, molecular markers
of potentiation appear to be high in rats during wake and low
during sleep (Vyazovskiy et al., 2008). A similar study conducted
in Drosophila also reported that levels of key synaptic proteins
increase with wake and decline with sleep (Gilestro et al.,
2009). This model for sleep function postulates that increased
synaptic activity during wake is followed by increased sleep in
order to downscale and thereby normalize neural connectivity.
Indeed, flies maintained in social conditions, which presumably
204 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
increase potentiation, sleep more than those kept in isolation
(Ganguly-Fitzgerald et al., 2006). The effect of social experience
on sleep ismediated by specific genes in circadian clock neurons
(Donlea et al., 2009).
Although the emphasis is definitely on synaptic plasticity, hints
of other functions for sleep have also arisen from studies on
model organisms. The induction of chaperone proteins can
abrogate the lethal effects of sleep loss, suggesting that sleep
normally promotes activity of such chaperones (Shaw et al.,
2002). A general function for sleep in curbing stress is supported
by the effects of sleep deprivation on endoplasmic reticulum (ER)
stress, as BiP (a marker of ER stress) increases during sleep
deprivation in mice and flies (Naidoo et al., 2007; Naidoo et al.,
2005). BiP levels also determine the extent of recovery sleep in
Drosophila, suggesting that cellular stress influences the need
for sleep (Naidoo et al., 2007). As noted above, sleep is also
implicated in recovery from injury and infection.
Regardless of which hypothesis turns out to be correct and
which sleep function stands the test of time, it is clear that model
organisms are blazing a trail in the sleep field. In contrast, human
genetic studies have made strides in our understanding of a few
selected neurological sleep disorders, such as narcolepsy and
restless leg syndrome, but have not yet shed light on the genetic
basis of sleep homeostasis or the need for sleep, the two most
burning questions in sleep research today. This is likely to
change once a large sample of subjects, each phenotyped for
sleep variables, has been subjected to genetic analysis that
could include whole-genome sequencing. Combined genetic
and EEG analyses in large samples are also likely to assist in
this search as they may offer more objective and discrete
sleep-related phenotypes. We do not expect that all aspects of
sleep regulation will be conserved across evolution, or that sleep
functions will be exactly the same in all species. However, we
predict that some unifying principles will emerge (Mignot,
2008); indeed, we believe that they have already started to
make an appearance.
ACKNOWLEDGMENTS
We would like to thank laboratory members for helpful discussions, Juliette
Faraco for assistance in writing this Review, and Julie Williams for comments
on the role of immune genes. Our work on sleep is supported by P01
AG017628 (Sehgal laboratory) and NS23724 (Mignot laboratory).
REFERENCES
Adamantidis, A., and de Lecea, L. (2008). Sleep and metabolism: shared
circuits, new connections. Trends Endocrinol. Metab. 19, 362–370.
Agosto, J., Choi, J.C., Parisky, K.M., Stilwell, G., Rosbash, M., and Griffith,
L.C. (2008). Modulation of GABAA receptor desensitization uncouples sleep
onset and maintenance in Drosophila. Nat. Neurosci. 11, 354–359.
Allada, R., and Siegel, J.M. (2008). Unearthing the phylogenetic roots of sleep.
Curr. Biol. 18, R670–R679.
Ambrosius, U., Lietzenmaier, S., Wehrle, R., Wichniak, A., Kalus, S., Winkel-
mann, J., Bettecken, T., Holsboer, F., Yassouridis, A., and Friess, E. (2008).
Heritability of sleep electroencephalogram. Biol. Psychiatry 64, 344–348.
Andretic, R., van Swinderen, B., and Greenspan, R.J. (2005). Dopaminergic
modulation of arousal in Drosophila. Curr. Biol. 15, 1165–1175.
Andretic, R., Franken, P., and Tafti, M. (2008a). Genetics of sleep. Annu. Rev.
Genet. 42, 361–388.
Andretic, R., Kim, Y.C., Jones, F.S., Han, K.A., and Greenspan, R.J. (2008b).
Drosophila D1 dopamine receptor mediates caffeine-induced arousal. Proc.
Natl. Acad. Sci. USA 105, 20392–20397.
Arnulf, I., Lin, L., Gadoth, N., File, J., Lecendreux, M., Franco, P., Zeitzer, J., Lo,
B., Faraco, J.H., and Mignot, E. (2008). Kleine-Levin syndrome: a systematic
study of 108 patients. Ann. Neurol. 63, 482–493.
Bailey, C.H., Bartsch, D., and Kandel, E.R. (1996). Toward a molecular
definition of long-term memory storage. Proc. Natl. Acad. Sci. USA 93,
13445–13452.
Basheer, R., Strecker, R.E., Thakkar, M.M., and McCarley, R.W. (2004). Aden-
osine and sleep-wake regulation. Prog. Neurobiol. 73, 379–396.
Bjorness, T.E., and Greene, R.W. (2009). Adenosine and sleep. Curr. Neuro-
pharmacol. 7, 238–245.
Bjorness, T.E., Kelly, C.L., Gao, T., Poffenberger, V., and Greene, R.W. (2009).
Control and function of the homeostatic sleep response by adenosine A1
receptors. J. Neurosci. 29, 1267–1276.
Bushey, D., Huber, R., Tononi, G., and Cirelli, C. (2007). Drosophila Hyperki-
netic mutants have reduced sleep and impaired memory. J. Neurosci. 27,
5384–5393.
Campbell, S.S., and Tobler, I. (1984). Animal sleep: a review of sleep duration
across phylogeny. Neurosci. Biobehav. Rev. 8, 269–300.
Chabas, D., Taheri, S., Renier, C., and Mignot, E. (2003). The genetics of
narcolepsy. Annu. Rev. Genomics Hum. Genet. 4, 459–483.
Chemelli, R.M., Willie, J.T., Sinton, C.M., Elmquist, J.K., Scammell, T., Lee, C.,
Richardson, J.A., Williams, S.C., Xiong, Y., Kisanuki, Y., et al. (1999). Narco-
lepsy in orexin knockout mice: molecular genetics of sleep regulation. Cell
98, 437–451.
Chen, Z., Gardi, J., Kushikata, T., Fang, J., and Krueger, J.M. (1999). Nuclear
factor-kappaB-like activity increases in murine cerebral cortex after sleep
deprivation. Am. J. Physiol. 276, R1812–R1818.
Cheng, L., Samad, O.A., Xu, Y., Mizuguchi, R., Luo, P., Shirasawa, S., Gould-
ing,M., andMa, Q. (2005). Lbx1 and Tlx3 are opposing switches in determining
GABAergic versus glutamatergic transmitter phenotypes. Nat. Neurosci. 8,
1510–1515.
Cirelli, C. (2009). The genetic and molecular regulation of sleep: from fruit flies
to humans. Nat. Rev. Neurosci. 10, 549–560.
Cirelli, C., Bushey, D., Hill, S., Huber, R., Kreber, R., Ganetzky, B., and Tononi,
G. (2005). Reduced sleep in Drosophila Shaker mutants. Nature 434, 1087–
1092.
Crocker, A., and Sehgal, A. (2008). Octopamine regulates sleep in drosophila
through protein kinase A-dependent mechanisms. J. Neurosci. 28, 9377–
9385.
Crocker, A., and Sehgal, A. (2010). Genetic analysis of sleep. Genes Dev. 24,
1220–1235.
Crocker, A., Shahidullah, M., Levitan, I.B., and Sehgal, A. (2010). Identification
of a neural circuit that underlies the effects of octopamine on sleep:wake
behavior. Neuron 65, 670–681.
Dauvilliers, Y., Montplaisir, J., Cochen, V., Desautels, A., Einen, M., Lin, L.,
Kawashima, M., Bayard, S., Monaca, C., Tiberge, M., et al. (2010). Post-
H1N1 narcolepsy-cataplexy. Sleep 33, 1428–1430.
DeGennaro, L., Marzano, C., Fratello, F., Moroni, F., Pellicciari, M.C., Ferlazzo,
F., Costa, S., Couyoumdjian, A., Curcio, G., Sforza, E., et al. (2008). The
electroencephalographic fingerprint of sleep is genetically determined:
a twin study. Ann. Neurol. 64, 455–460.
Diekelmann, S., and Born, J. (2010). The memory function of sleep. Nat. Rev.
Neurosci. 11, 114–126.
Donlea, J.M., Ramanan, N., and Shaw, P.J. (2009). Use-dependent plasticity in
clock neurons regulates sleep need in Drosophila. Science 324, 105–108.
Douglas, C.L., Vyazovskiy, V., Southard, T., Chiu, S.Y., Messing, A., Tononi,
G., and Cirelli, C. (2007). Sleep in Kcna2 knockout mice. BMC Biol. 5, 42.
Drennan, M.D., Klauber, M.R., Kripke, D.F., and Goyette, L.M. (1991). The
effects of depression and age on the Horne-Ostberg morningness-evening-
ness score. J. Affect. Disord. 23, 93–98.
Faraco, J.H., Appelbaum, L., Marin, W., Gaus, S.E., Mourrain, P., and Mignot,
E. (2006). Regulation of hypocretin (orexin) expression in embryonic zebrafish.
J. Biol. Chem. 281, 29753–29761.
Foltenyi, K., Greenspan, R.J., and Newport, J.W. (2007). Activation of EGFR
and ERK by rhomboid signaling regulates the consolidation and maintenance
of sleep in Drosophila. Nat. Neurosci. 10, 1160–1167.
Frank, M.G. (2006). The mystery of sleep function: current perspectives and
future directions. Rev. Neurosci. 17, 375–392.
Franken, P., and Dijk, D.J. (2009). Circadian clock genes and sleep homeo-
stasis. Eur. J. Neurosci. 29, 1820–1829.
Ganguly-Fitzgerald, I., Donlea, J., and Shaw, P.J. (2006). Waking experience
affects sleep need in Drosophila. Science 313, 1775–1781.
Gilestro, G.F., Tononi, G., and Cirelli, C. (2009). Widespread changes in
synaptic markers as a function of sleep and wakefulness in Drosophila.
Science 324, 109–112.
Goel, N., Banks, S., Mignot, E., and Dinges, D.F. (2009). PER3 polymorphism
predicts cumulative sleep homeostatic but not neurobehavioral changes to
chronic partial sleep deprivation. PLoS ONE 4, e5874.
Gottlieb, D.J., DeStefano, A.L., Foley, D.J., Mignot, E., Redline, S., Givelber,
R.J., and Young, T. (2004). APOE epsilon4 is associated with obstructive sleep
apnea/hypopnea: the Sleep Heart Health Study. Neurology 63, 664–668.
Gottlieb, D.J., O’Connor, G.T., and Wilk, J.B. (2007). Genome-wide associa-
tion of sleep and circadian phenotypes. BMC Med. Genet. 8 (Suppl 1), S9.
Graves, L.A., Hellman, K., Veasey, S., Blendy, J.A., Pack, A.I., and Abel, T.
(2003). Genetic evidence for a role of CREB in sustained cortical arousal. J.
Neurophysiol. 90, 1152–1159.
Hallam, S.J., and Jin, Y. (1998). lin-14 regulates the timing of synaptic remod-
elling in Caenorhabditis elegans. Nature 395, 78–82.
Hallmayer, J., Faraco, J., Lin, L., Hesselson, S., Winkelmann, J., Kawashima,
M., Mayer, G., Plazzi, G., Nevsimalova, S., Bourgin, P., et al. (2009). Narco-
lepsy is strongly associated with the T-cell receptor alpha locus. Nat. Genet.
41, 708–711.
He, Y., Jones, C.R., Fujiki, N., Xu, Y., Guo, B., Holder, J.L., Jr., Rossner, M.J.,
Nishino, S., and Fu, Y.H. (2009). The transcriptional repressor DEC2 regulates
sleep length in mammals. Science 325, 866–870.
Hendricks, J.C., Finn, S.M., Panckeri, K.A., Chavkin, J., Williams, J.A., Sehgal,
A., and Pack, A.I. (2000a). Rest in Drosophila is a sleep-like state. Neuron 25,
129–138.
Hendricks, J.C., Sehgal, A., and Pack, A.I. (2000b). The need for a simple
animal model to understand sleep. Prog. Neurobiol. 61, 339–351.
Hendricks, J.C., Williams, J.A., Panckeri, K., Kirk, D., Tello, M., Yin, J.C., and
Sehgal, A. (2001). A non-circadian role for cAMP signaling and CREB activity in
Drosophila rest homeostasis. Nat. Neurosci. 4, 1108–1115.
Hendricks, J.C., Lu, S., Kume, K., Yin, J.C., Yang, Z., and Sehgal, A. (2003).
Gender dimorphism in the role of cycle (BMAL1) in rest, rest regulation, and
longevity in Drosophila melanogaster. J. Biol. Rhythms 18, 12–25.
Hong, S.C., Lin, L., Lo, B., Jeong, J.H., Shin, Y.K., Kim, S.Y., Kweon, Y., Zhang,
J., Einen, M., Smith, A., et al. (2007). DQB1*0301 and DQB1*0601 modulate
narcolepsy susceptibility in Koreans. Hum. Immunol. 68, 59–68.
Huang, Z.L., Qu,W.M., Eguchi, N., Chen, J.F., Schwarzschild, M.A., Fredholm,
B.B., Urade, Y., and Hayaishi, O. (2005). Adenosine A2A, but not A1, receptors
mediate the arousal effect of caffeine. Nat. Neurosci. 8, 858–859.
Hublin, C., Kaprio, J., Partinen, M., and Koskenvu, M. (2001). Parasomnias:
co-occurrence and genetics. Psychiatr. Genet. 11, 65–70.
Imeri, L., and Opp, M.R. (2009). How (and why) the immune system makes us
sleep. Nat. Rev. Neurosci. 10, 199–210.
Isaac, R.E., Li, C., Leedale, A.E., and Shirras, A.D. (2010). Drosophila male sex
peptide inhibits siesta sleep and promotes locomotor activity in the post-
mated female. Proc. Biol. Sci. 277, 65–70.
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 205
Ishimoto, H., and Kitamoto, T. (2010). The steroid molting hormone Ecdysone
regulates sleep in adult Drosophila melanogaster. Genetics 185, 269–281.
Joiner, W.J., Crocker, A., White, B.H., and Sehgal, A. (2006). Sleep in
Drosophila is regulated by adult mushroom bodies. Nature 441, 757–760.
Josephs, K.A., Silber, M.H., Fealey, R.D., Nippoldt, T.B., Auger, R.G., and
Vernino, S. (2004). Neurophysiologic studies in Morvan syndrome. J. Clin.
Neurophysiol. 21, 440–445.
Kalinchuk, A.V., McCarley, R.W., Porkka-Heiskanen, T., and Basheer, R.
(2010). Sleep deprivation triggers inducible nitric oxide-dependent nitric oxide
production in wake-active basal forebrain neurons. J. Neurosci. 30, 13254–
13264.
Keene, A.C., Duboué, E.R., McDonald, D.M., Dus, M., Suh, G.S., Waddell, S.,
and Blau, J. (2010). Clock and cycle limit starvation-induced sleep loss in
Drosophila. Curr. Biol. 20, 1209–1215.
Koh, K., Joiner, W.J., Wu, M.N., Yue, Z., Smith, C.J., and Sehgal, A. (2008).
Identification of SLEEPLESS, a sleep-promoting factor. Science 321,
372–376.
Kornum, B.R., Kawashima, M., Faraco, J., Lin, L., Rico, T.J., Hesselson, S.,
Axtell, R.C., Kuipers, H., Weiner, K., Hamacher, A., et al. (2011). Common
variants in P2RY11 are associated with narcolepsy. Nat. Genet. 43, 66–71.
Kramer, A., Yang, F.C., Snodgrass, P., Li, X., Scammell, T.E., Davis, F.C., and
Weitz, C.J. (2001). Regulation of daily locomotor activity and sleep by hypotha-
lamic EGF receptor signaling. Science 294, 2511–2515.
Kuo, T.H., Pike, D.H., Beizaeipour, Z., and Williams, J.A. (2010). Sleep trig-
gered by an immune response in Drosophila is regulated by the circadian clock
and requires the NFkappaB Relish. BMC Neurosci. 11, 17.
Langmesser, S., Franken, P., Feil, S., Emmenegger, Y., Albrecht, U., and Feil,
R. (2009). cGMP-dependent protein kinase type I is implicated in the regulation
of the timing and quality of sleep and wakefulness. PLoS ONE 4, e4238.
Laposky, A., Easton, A., Dugovic, C., Walisser, J., Bradfield, C., and Turek, F.
(2005). Deletion of the mammalian circadian clock gene BMAL1/Mop3 alters
baseline sleep architecture and the response to sleep deprivation. Sleep 28,
395–409.
Lebestky, T., Chang, J.S., Dankert, H., Zelnik, L., Kim, Y.C., Han, K.A., Wolf,
F.W., Perona, P., and Anderson, D.J. (2009). Two different forms of arousal
in Drosophila are oppositely regulated by the dopamine D1 receptor ortholog
DopR via distinct neural circuits. Neuron 64, 522–536.
Lim, A.S., and Scammell, T.E. (2010). The trouble with Tribbles: do antibodies
against TRIB2 cause narcolepsy? Sleep 33, 857–858.
Lin, L., Faraco, J., Li, R., Kadotani, H., Rogers, W., Lin, X., Qiu, X., de Jong,
P.J., Nishino, S., and Mignot, E. (1999). The sleep disorder canine narcolepsy
is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98,
365–376.
Longstreth, W.T., Jr., Ton, T.G., and Koepsell, T.D. (2009). Narcolepsy and
streptococcal infections. Sleep 32, 1548.
Maret, S., Franken, P., Dauvilliers, Y., Ghyselinck, N.B., Chambon, P., and
Tafti, M. (2005). Retinoic acid signaling affects cortical synchrony during sleep.
Science 310, 111–113.
Maret, S., Dorsaz, S., Gurcel, L., Pradervand, S., Petit, B., Pfister, C., Hagen-
buchle, O., O’Hara, B.F., Franken, P., and Tafti, M. (2007). Homer1a is a core
brain molecular correlate of sleep loss. Proc. Natl. Acad. Sci. USA 104, 20090–
20095.
Marrus, S.B., Zeng, H., and Rosbash, M. (1996). Effect of constant light and
circadian entrainment of perS flies: evidence for light-mediated delay of the
negative feedback loop in Drosophila. EMBO J. 15, 6877–6886.
Massicotte-Marquez, J., Décary, A., Gagnon, J.F., Vendette, M., Mathieu, A.,
Postuma, R.B., Carrier, J., and Montplaisir, J. (2008). Executive dysfunction
andmemory impairment in idiopathic REM sleep behavior disorder. Neurology
70, 1250–1257.
Mertens, I., Vandingenen, A., Johnson, E.C., Shafer, O.T., Li, W., Trigg, J.S.,
De Loof, A., Schoofs, L., and Taghert, P.H. (2005). PDF receptor signaling in
Drosophila contributes to both circadian and geotactic behaviors. Neuron
48, 213–219.
206 Cell 146, July 22, 2011 ª2011 Elsevier Inc.
Mignot, E. (1997). Genetics of narcolepsy and other sleep disorders. Am. J.
Hum. Genet. 60, 1289–1302.
Mignot, E. (2008). Why we sleep: the temporal organization of recovery. PLoS
Biol. 6, e106.
Mignot, E., and Takahashi, J.S. (2007). A circadian sleep disorder reveals
a complex clock. Cell 128, 22–23.
Mignot, E., Lin, L., Rogers,W., Honda, Y., Qiu, X., Lin, X., Okun, M., Hohjoh, H.,
Miki, T., Hsu, S., et al. (2001). Complex HLA-DR and -DQ interactions confer
risk of narcolepsy-cataplexy in three ethnic groups. Am. J. Hum. Genet. 68,
686–699.
Mignot, E., Lammers, G.J., Ripley, B., Okun, M., Nevsimalova, S., Overeem,
S., Vankova, J., Black, J., Harsh, J., Bassetti, C., et al. (2002). The role of
cerebrospinal fluid hypocretin measurement in the diagnosis of narcolepsy
and other hypersomnias. Arch. Neurol. 59, 1553–1562.
Miwa, J.M., Stevens, T.R., King, S.L., Caldarone, B.J., Ibanez-Tallon, I., Xiao,
C., Fitzsimonds, R.M., Pavlides, C., Lester, H.A., Picciotto, M.R., and Heintz,
N. (2006). The prototoxin lynx1 acts on nicotinic acetylcholine receptors to
balance neuronal activity and survival in vivo. Neuron 51, 587–600.
Miyagawa, T., Kawashima, M., Nishida, N., Ohashi, J., Kimura, R., Fujimoto,
A., Shimada,M., Morishita, S., Shigeta, T., Lin, L., et al. (2008). Variant between
CPT1B and CHKB associated with susceptibility to narcolepsy. Nat. Genet.
40, 1324–1328.
Miyagawa, T., Honda, M., Kawashima, M., Shimada, M., Tanaka, S., Honda,
Y., and Tokunaga, K. (2009). Polymorphism located between CPT1B and
CHKB, and HLA-DRB1*1501-DQB1*0602 haplotype confer susceptibility to
CNS hypersomnias (essential hypersomnia). PLoS ONE 4, e5394.
Müller-Preuss, P., Rupprecht, R., and Lancel, M. (2002). The effects of the
neuroactive steroid 3 alpha,5 alpha-THDOC on sleep in the rat. Neuroreport
13, 487–490.
Naidoo, N., Giang, W., Galante, R.J., and Pack, A.I. (2005). Sleep deprivation
induces the unfolded protein response in mouse cerebral cortex. J. Neuro-
chem. 92, 1150–1157.
Naidoo, N., Casiano, V., Cater, J., Zimmerman, J., and Pack, A.I. (2007). A role
for the molecular chaperone protein BiP/GRP78 in Drosophila sleep homeo-
stasis. Sleep 30, 557–565.
Naylor, E., Bergmann, B.M., Krauski, K., Zee, P.C., Takahashi, J.S., Vitaterna,
M.H., and Turek, F.W. (2000). The circadian clock mutation alters sleep
homeostasis in the mouse. J. Neurosci. 20, 8138–8143.
Nelson, S.E., Duricka, D.L., Campbell, K., Churchill, L., and Krueger, J.M.
(2004). Homer1a and 1bc levels in the rat somatosensory cortex vary with
the time of day and sleep loss. Neurosci. Lett. 367, 105–108.
Nitabach, M.N., and Taghert, P.H. (2008). Organization of theDrosophila circa-
dian control circuit. Curr. Biol. 18, R84–R93.
Nitz, D.A., van Swinderen, B., Tononi, G., and Greenspan, R.J. (2002). Electro-
physiological correlates of rest and activity in Drosophila melanogaster. Curr.
Biol. 12, 1934–1940.
Overeem, S., Black, J.L., 3rd, and Lammers, G.J. (2008). Narcolepsy: immuno-
logical aspects. Sleep Med. Rev. 12, 95–107.
Pack, A.I., Galante, R.J., Maislin, G., Cater, J., Metaxas, D., Lu, S., Zhang, L.,
Von Smith, R., Kay, T., Lian, J., et al. (2007). Novel method for high-throughput
phenotyping of sleep in mice. Physiol. Genomics 28, 232–238.
Parisky, K.M., Agosto, J., Pulver, S.R., Shang, Y., Kuklin, E., Hodge, J.J., Kang,
K., Liu, X., Garrity, P.A., Rosbash, M., and Griffith, L.C. (2008). PDF cells are
a GABA-responsive wake-promoting component of the Drosophila sleep
circuit. Neuron 60, 672–682.
Pitman, J.L., McGill, J.J., Keegan, K.P., and Allada, R. (2006). A dynamic
role for the mushroom bodies in promoting sleep in Drosophila. Nature 441,
753–756.
Poe, G.R., Walsh, C.M., and Bjorness, T.E. (2010). Cognitive neuroscience of
sleep. Prog. Brain Res. 185, 1–19.
Prober, D.A., Rihel, J., Onah, A.A., Sung, R.J., and Schier, A.F. (2006).
Hypocretin/orexin overexpression induces an insomnia-like phenotype in
zebrafish. J. Neurosci. 26, 13400–13410.
Raizen, D.M., Zimmerman, J.E., Maycock, M.H., Ta, U.D., You, Y.J.,
Sundaram, M.V., and Pack, A.I. (2008). Lethargus is a Caenorhabditis elegans
sleep-like state. Nature 451, 569–572.
Rihel, J., Prober, D.A., Arvanites, A., Lam, K., Zimmerman, S., Jang, S.,
Haggarty, S.J., Kokel, D., Rubin, L.L., Peterson, R.T., and Schier, A.F.
(2010). Zebrafish behavioral profiling links drugs to biological targets and
rest/wake regulation. Science 327, 348–351.
Sakurai, T. (2007). The neural circuit of orexin (hypocretin): maintaining sleep
and wakefulness. Nat. Rev. Neurosci. 8, 171–181.
Salas, R.E., Gamaldo, C.E., and Allen, R.P. (2010). Update in restless legs
syndrome. Curr. Opin. Neurol. 23, 401–406.
Scharf, M.T., Naidoo, N., Zimmerman, J.E., and Pack, A.I. (2008). The energy
hypothesis of sleep revisited. Prog. Neurobiol. 86, 264–280.
Schormair, B., Kemlink, D., Roeske, D., Eckstein, G., Xiong, L., Lichtner, P.,
Ripke, S., Trenkwalder, C., Zimprich, A., Stiasny-Kolster, K., et al. (2008).
PTPRD (protein tyrosine phosphatase receptor type delta) is associated with
restless legs syndrome. Nat. Genet. 40, 946–948.
Seugnet, L., Suzuki, Y., Vine, L., Gottschalk, L., and Shaw, P.J. (2008). D1
receptor activation in the mushroom bodies rescues sleep-loss-induced
learning impairments in Drosophila. Curr. Biol. 18, 1110–1117.
Shang, Y., Griffith, L.C., and Rosbash, M. (2008). Light-arousal and circadian
photoreception circuits intersect at the large PDF cells of the Drosophila brain.
Proc. Natl. Acad. Sci. USA 105, 19587–19594.
Shaw, P.J., Cirelli, C., Greenspan, R.J., and Tononi, G. (2000). Correlates of
sleep and waking in Drosophila melanogaster. Science 287, 1834–1837.
Shaw, P.J., Tononi, G., Greenspan, R.J., and Robinson, D.F. (2002). Stress
response genes protect against lethal effects of sleep deprivation in
Drosophila. Nature 417, 287–291.
Sheeba, V., Fogle, K.J., Kaneko, M., Rashid, S., Chou, Y.T., Sharma, V.K., and
Holmes, T.C. (2008). Large ventral lateral neurons modulate arousal and sleep
in Drosophila. Curr. Biol. 18, 1537–1545.
Shimizu, H., Shimoda, M., Yamaguchi, T., Seong, K.H., Okamura, T., and Ishii,
S. (2008). Drosophila ATF-2 regulates sleep and locomotor activity in pace-
maker neurons. Mol. Cell. Biol. 28, 6278–6289.
Stefansson, H., Rye, D.B., Hicks, A., Petursson, H., Ingason, A., Thorgeirsson,
T.E., Palsson, S., Sigmundsson, T., Sigurdsson, A.P., Eiriksdottir, I., et al.
(2007). A genetic risk factor for periodic limb movements in sleep. N. Engl. J.
Med. 357, 639–647.
Tafti, M., Petit, B., Chollet, D., Neidhart, E., de Bilbao, F., Kiss, J.Z., Wood,
P.A., and Franken, P. (2003). Deficiency in short-chain fatty acid beta-oxida-
tion affects theta oscillations during sleep. Nat. Genet. 34, 320–325.
Thimgan, M.S., Suzuki, Y., Seugnet, L., Gottschalk, L., and Shaw, P.J. (2010).
The perilipin homologue, lipid storage droplet 2, regulates sleep homeostasis
and prevents learning impairments following sleep loss. PLoS Biol. 8, 8.
Toh, K.L., Jones, C.R., He, Y., Eide, E.J., Hinz, W.A., Virshup, D.M., Ptácek,
L.J., and Fu, Y.H. (2001). An hPer2 phosphorylation site mutation in familial
advanced sleep phase syndrome. Science 291, 1040–1043.
Trenkwalder, C., Högl, B., and Winkelmann, J. (2009). Recent advances in the
diagnosis, genetics and treatment of restless legs syndrome. J. Neurol. 256,
539–553.
Van Buskirk, C., and Sternberg, P.W. (2007). Epidermal growth factor signaling
induces behavioral quiescence in Caenorhabditis elegans. Nat. Neurosci. 10,
1300–1307.
van Swinderen, B., Nitz, D.A., and Greenspan, R.J. (2004). Uncoupling of brain
activity from movement defines arousal States in Drosophila. Curr. Biol. 14,
81–87.
Vecsey, C.G., Baillie, G.S., Jaganath, D., Havekes, R., Daniels, A., Wimmer,
M., Huang, T., Brown, K.M., Li, X.Y., Descalzi, G., et al. (2009). Sleep depriva-
tion impairs cAMP signalling in the hippocampus. Nature 461, 1122–1125.
Viola, A.U., Archer, S.N., James, L.M., Groeger, J.A., Lo, J.C., Skene, D.J., von
Schantz, M., and Dijk, D.J. (2007). PER3 polymorphism predicts sleep
structure and waking performance. Curr. Biol. 17, 613–618.
Vyazovskiy, V.V., Cirelli, C., Pfister-Genskow,M., Faraguna, U., and Tononi, G.
(2008). Molecular and electrophysiological evidence for net synaptic potentia-
tion in wake and depression in sleep. Nat. Neurosci. 11, 200–208.
White, D.P. (2005). Pathogenesis of obstructive and central sleep apnea. Am.
J. Respir. Crit. Care Med. 172, 1363–1370.
White, J.G., Albertson, D.G., and Anness,M.A. (1978). Connectivity changes in
a class of motoneurone during the development of a nematode. Nature 271,
764–766.
Williams, J.A., Sathyanarayanan, S., Hendricks, J.C., and Sehgal, A. (2007).
Interaction between sleep and the immune response in Drosophila: a role for
the NFkappaB relish. Sleep 30, 389–400.
Winkelmann, J., Schormair, B., Lichtner, P., Ripke, S., Xiong, L., Jalilzadeh, S.,
Fulda, S., Pütz, B., Eckstein, G., Hauk, S., et al. (2007). Genome-wide associ-
ation study of restless legs syndrome identifies common variants in three
genomic regions. Nat. Genet. 39, 1000–1006.
Winkelmann, J., Lichtner, P., Schormair, B., Uhr, M., Hauk, S., Stiasny-Kolster,
K., Trenkwalder, C., Paulus, W., Peglau, I., Eisensehr, I., et al. (2008). Variants
in the neuronal nitric oxide synthase (nNOS, NOS1) gene are associated with
restless legs syndrome. Mov. Disord. 23, 350–358.
Winkelmann, J., Czamara, D., Schormair, B., Knauf, F., Schulte, E.C., Trenk-
walder, C., Dauvilliers, Y., Polo, O., Högl, B., et al. (2011). Genome-wide asso-
ciation study identifies novel restless legs syndrome susceptibility loci on 2p14
and 16q12.1. PLoS Genet. 7, e1002171. 10.1371/journal.pgen.1002171.
Wisor, J.P., O’Hara, B.F., Terao, A., Selby, C.P., Kilduff, T.S., Sancar, A.,
Edgar, D.M., and Franken, P. (2002). A role for cryptochromes in sleep regula-
tion. BMC Neurosci. 3, 20.
Wu, M.N., Ho, K., Crocker, A., Yue, Z., Koh, K., and Sehgal, A. (2009). The
effects of caffeine on sleep in Drosophila require PKA activity, but not the
adenosine receptor. J. Neurosci. 29, 11029–11037.
Wu, M.N., Joiner, W.J., Dean, T., Yue, Z., Smith, C.J., Chen, D., Hoshi, T.,
Sehgal, A., and Koh, K. (2010). SLEEPLESS, a Ly-6/neurotoxin family member,
regulates the levels, localization and activity of Shaker. Nat. Neurosci. 13,
69–75.
Xu, Y., Padiath, Q.S., Shapiro, R.E., Jones, C.R., Wu, S.C., Saigoh, N., Saigoh,
K., Ptácek, L.J., and Fu, Y.H. (2005). Functional consequences of a CKIdelta
mutation causing familial advanced sleep phase syndrome. Nature 434,
640–644.
Yokogawa, T., Marin, W., Faraco, J., Pézeron, G., Appelbaum, L., Zhang, J.,
Rosa, F., Mourrain, P., and Mignot, E. (2007). Characterization of sleep in
zebrafish and insomnia in hypocretin receptor mutants. PLoS Biol. 5, e277.
Yuan, Q., Joiner, W.J., and Sehgal, A. (2006). A sleep-promoting role for the
Drosophila serotonin receptor 1A. Curr. Biol. 16, 1051–1062.
Zheng, X., and Sehgal, A. (2008). Probing the relative importance of molecular
oscillations in the circadian clock. Genetics 178, 1147–1155.
Zimmerman, J.E., Rizzo, W., Shockley, K.R., Raizen, D.M., Naidoo, N.,
Mackiewicz, M., Churchill, G.A., and Pack, A.I. (2006). Multiple mechanisms
limit the duration of wakefulness in Drosophila brain. Physiol. Genomics 27,
337–350.
Cell 146, July 22, 2011 ª2011 Elsevier Inc. 207
- Genetics of Sleep and Sleep Disorders
Molecular Insights from Animal Models
Neurotransmitter/Neuropeptide Systems
Intracellular Signaling Molecules
Ion Channels and Channel-Regulating Proteins
Circadian Clock Genes
Metabolic Factors
Immune Genes
Key Features to Emerge from Model Organism Studies
Genetic Factors Underlying Circadian Rhythm Disorders
Genetic Factors Regulating EEG and the Sleep Homeostat
Genetics of Human Narcolepsy-Cataplexy
Genetics of Other Sleep Disorders
Restless Leg Syndrome
Hypersomnias, Insomnia, and Parasomnias
Sleep-Disordered Breathing and Obstructive Sleep Apnea
Overlap between Human Sleep Genes and Those Found in Model Organisms
Sleep Function: Insights from Model Organisms
Acknowledgments
References
In 1-2 pages, summarize the journal article. Describe the research/study conducted. Summarize the results/key findings. Explain future implications of the findings.
Need this article in in less than 8 hours.
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
