Elsevier

Frontiers in Neuroendocrinology

Volume 44, January 2017, Pages 27-34
Frontiers in Neuroendocrinology

Review article
Sleep & metabolism: The multitasking ability of lateral hypothalamic inhibitory circuitries

https://doi.org/10.1016/j.yfrne.2016.11.002Get rights and content

Highlights

  • Hypothalamus circuits support physiological regulation of homeostatic processes.

  • Both peptidergic and GABA/glutamate neurons from the lateral hypothalamus regulate metabolism and sleep-wake states.

  • How single hypothalamic circuit controls sleep and metabolism remains unclear.

  • The functional connectivity of sleep and metabolic circuits awaits further investigation.

Abstract

The anatomical and functional mapping of lateral hypothalamic circuits has been limited by the numerous cell types and complex, yet unclear, connectivity. Recent advances in functional dissection of input-output neurons in the lateral hypothalamus have identified subset of inhibitory cells as crucial modulators of both sleep-wake states and metabolism. Here, we summarize these recent studies and discuss the multi-tasking functions of hypothalamic circuitries in integrating sleep and metabolism in the mammalian brain.

Introduction

Sleep and wakefulness are two mutually exclusive behaviors. Sleep is “a rapidly reversible state of (behavioral) immobility and greatly reduced sensory responsiveness to environmental stimuli” (Siegel, 2008). Sleep-like states occur in lower vertebrates and throughout the animal kingdom, suggesting an ancient and strongly conserved mechanism necessary for primary and essential biological needs (but see (Siegel, 2008)). Sleep is important for brain maturation, cognitive processing and metabolite clearance in the brain. Sleep strongly depends on previous activity during wakefulness and prepares the brain and the body for future actions, yet our understanding of the neurobiological mechanisms underlying brain control of sleep-wake states is limited.

Here, we briefly summarize neuronal circuits underlying sleep-wake states with an emphasis on hypothalamic circuits. Other excellent reviews have recently summarized brain substrates of sleep-wake cycle (Brown et al., 2012, Fort et al., 2009) and food intake or metabolism (Sternson, 2013, Waterson and Horvath, 2015).

The control of sleep-wake state alternation is supported by distinct cellular networks (neuronal and non-neuronal cells) distributed across the central nervous system. The “stability” of this cycle is important for the proper functioning and the survival of the organism/species. In mammals, states of wakefulness, non-rapid eye movement (non-REM, or slow wave sleep) and rapid eye movement (REM, sometimes called paradoxical sleep) sleep are characterized by distinct electroencephalogram (EEG), electromyogram (EMG) and electrooculogram (EOG) signal features and cycle with both ultradian and circadian periods (Brown et al., 2012, Saper et al., 2010). Wakefulness is characterized by high-frequency/low-amplitude cortical EEG oscillations (4–300 Hz), muscle activity and ocular movements.

After prolonged period of wakefulness, sleep pressure – which reflects a process called sleep homeostasis – increases and leads to the onset of NREM sleep. Cortical oscillations show both global and local oscillations composed of slow waves (<1 Hz), high-amplitude delta oscillations (0.5–4 Hz), and spindles (9–15 Hz) accompanied by low muscle activity and the absence of ocular movement. REM sleep is a singular sleep state signalled by predominant EEG theta (6–9 Hz), and a complete disappearance of postural muscle tone (only muscle twitches persist), and fluctuation of the heart and breathing rates accompanied by rapid eye movements are frequently observed during that state. While each of these states is mutually exclusive, sign of intertwined states occur under homeostatic challenge (e.g., sleep pressure or after learning) in local part of the cortex (Funk et al., 2016, Huber et al., 2004, Vyazovskiy et al., 2011).

Although the neurobiological mechanisms controlling the recurrence of these states across a 24 h-period remain unclear, lesion, pharmacological and (opto)genetic studies strongly suggest that the onset, maintenance and termination of wake, NREM and REM sleep states rely on excitation/inhibition between distinct circuits distributed across the entire central nervous system (Fort et al., 2009, Luppi et al., 2016). In particular, unit recording in head-restrained animals revealed that wakefulness is associated with increased activity of the hypocretin/orexin (Hcrt/ox)-expressing neurons in the lateral hypothalamus, the noradrenergic locus coeruleus (LC)-expressing neurons in the brainstem, the serotoninergic dorsal raphe nuclei (DRN) in the brainstem, the histaminergic tuberomammilary nucleus (TMN) in the posterior hypothalamus, the cholinergic pedunculopontine (PPT) and laterodorsal tegmental (LDT) nuclei in the midbrain, as well as cholinergic neurons in the basal forebrain (reviewed in Brown et al., 2012). During NREM sleep, the activity of thalamo-cortico-thalamic circuits is highly synchronized and generates slow EEG oscillations as shown from in vivo recording of freely-moving animals. Similarly, inhibitory neurons in anterior hypothalamic (Alam et al., 1995, Zhang et al., 2015) and brainstem (Anaclet et al., 2014) structures are strongly active, however, their functional link to thalamo-cortical and cortical networks remains unclear. During REM sleep, inhibitory cells from the anterior (Lu et al., 2002) and the lateral (Clement et al., 2012, Jego et al., 2013, Verret et al., 2003) hypothalamus, as well as glutamatergic and GABAergic neurons from the brainstem (Luppi et al., 2006) were found to be strongly active using immediate early gene detection and in vivo recordings.

Amassing literature highlighted a dual role for sleep-wake circuits in the brain. For instance, norepinephrine neurons from the locus coeruleus represent a major hub for wakefulness, but also control stress response and attention during cognitive processing (Aston-Jones and Bloom, 1981, Bouret and Sara, 2005). Similarly, sleep and sedation circuits located in the anterior hypothalamus (VLPO, LPOA, etc.) concomitantly regulate body temperature (Schmidt, 2014, Szymusiak and Satinoff, 1981, Zhang et al., 2015). More caudally, neurons in the lateral hypothalamus (LH) expressing hcrt/ox, MCH, GABA and glutamate possess both sensing and controlling modalities, as their firing activity is strongly modulated by metabolic products both in vitro and in vivo (amino acids, glucose, etc.) (Burdakov et al., 2005, Karnani et al., 2011). Furthermore, the same cell types are also involved in the hypothalamic control of wakefulness, including Hcrt neurons and a subset of LH cells expressing VGAT, and both NREM and REM sleep, as exemplified by MCH cells (see below). These findings are discussed below and support the hypothesis that lateral hypothalamic circuits control both sleep and metabolism through multi-tasking networks. In a translational aspect, clinical and experimental studies report a high prevalence of metabolic syndrome associated with sleep disorders and vice versa. Patients with chronic sleep restriction, fragmented sleep or short sleep night present an increased risk for metabolic pathologies including diabetes and obesity, cardio-vascular risks, mood disorders and hormonal imbalances (Brown et al., 2015, Van Cauter et al., 2008).

This association suggests the existence of underlying circuitries that regulating both sleep/wake states and metabolism, as previously proposed (Adamantidis and de Lecea, 2008). How sleep-wake circuit shares food intake or metabolic functions? Both cellular/molecular and recent circuit evidence support these integrative properties amongst hypothalamic circuits. Here, we summarize recent findings linking sleep-wake state and metabolism and discuss lateral hypothalamic mechanisms underlying this patho-physiological associated symptom and point some future direction for the investigation for circuit multi-tasking properties.

Section snippets

Lateral hypothalamic (LH) circuitries in sleep-wake control

The LH is a homeostasis center that orchestrate food intake, metabolism balance, behaviors directed towards natural- (food, sex) and artificial- (drug) rewards (Bernardis and Bellinger, 1993, Saper et al., 2005, Stuber and Wise, 2016), and sleep-wake states (Brown et al., 2012, Saper et al., 2010). It contains multiple cell types with unique neurochemical profiles, vesicular transporter (s) (Collin et al., 2003, Rosin et al., 2003, Ziegler et al., 2002), connectivity (Ekstrand et al., 2014),

LH circuitries: multitasking sleep/arousal and metabolism?

Interestingly, while acute optogenetic stimulation of LHVGAT cells during NREM sleep provoked rapid arousal (Herrera et al., 2015), their chronic optical activation during wakefulness induced a sustained food intake response (Jennings et al., 2015). These findings provide a causal evidence for a dual role of these cells in sleep and metabolism (see Fig. 3).

Appetite is regulated by the interaction between metabolic and hormonal signals and the central nervous system. The hypothalamus regulates

A circuit perspective on multi-tasking circuits

As summarized above, many circuits of the brain shared one, two or more functions, as do LH neurons control both arousal and food intake, as possibly other unknown functions, in the mammalian brain (Table 1). Although there is likely an anatomical and functional disparity between LHGAD and LHVGAT neurons, in the following section, we will refer to LHGABA cells in general for clarity of our speculation, despite obvious diversity amongst those cells.

Perspectives

The LHGABA cells provide a working model to study multi-tasking amongst neural circuit in the mammalian brain. Although our understanding of LHGABA cell control of sleep and metabolism has progressed over the last years, several challenges remain. One of them is to define whether shared functions are integrated within the same cellular network, or whether it relies on separate subsets of strongly connected neurons within the LH. Equally important is to assess the importance of inputs-outputs

Acknowledgments

We thank members of our respective laboratories for their technical help and comments on a previous version of the manuscript. C.G.H. was supported by a Strauss Clinical Fellowship. A.A., T.K. and D.B. were supported by the Human Frontier Science Program (RGY0076/2012). A.A. was supported by the Douglas Foundation, McGill University, Canadian Fund for Innovation (CFI), Canadian Research Chair (CRC Tier 2), Canadian Institute for Health Research (CIHR) and the Natural Science and Engineering

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