Sleep architecture and EEG power spectra in recently detoxified alcohol dependent patients

Highlights

• Compares polysomnography data between ‘recently detoxified’ chronic alcohol dependence patients and healthy controls.

• Both conventional sleep architectural and power spectral analyses were conducted.

• Patients showed significantly disturbed sleep architecture.

• Aberrant high frequency spectral power during REM sleep.

Abstract

Objectives

Persistent sleep abnormalities during abstinence are a harbinger for relapse in patients with chronic alcohol dependence. The present study aimed to compare polysomnography (PSG) data between ‘recently detoxified’ patients with chronic alcohol dependence and healthy controls.

Methods

Both conventional sleep architectural and power spectral analyses were conducted. Twenty subjects in each of the groups were enrolled. A 2 nights’ sleep (first-habituation and second-experimental) PSG data was collected. Computer assisted scoring supplemented by manual method using the Rechtschaffen and Kales criteria were used for sleep staging. Twenty eight channels were used for the EEG recording. Spectral power across early NREM (Non-rapid-eye-movement), Slow Wave Sleep and REM was computed using the Welch's averaged periodogram method.

Results

Results on conventional sleep staging showed that patients had significantly lesser total sleep time, sleep efficiency and stage shifts and longer sleep onset latency; while duration of each NREM stages were significantly lower, and latency of stage 2 NREM was significantly longer in patients. After controlling for multiple comparisons, spectral power analysis revealed significant differences only during REM sleep and specifically in high frequency (beta and gamma) bands.

Conclusions

Stating the mutually complementary role of conventional and spectral analyses of polysomnography EEG data, we conclude that sleep abnormalities are fairly evident in recently detoxified alcohol dependent patients.

Introduction

Global prevalence rates of alcohol use disorders range upto 16% (WHO, 2004). In India, the average prevalence of alcohol dependence has been found to be 4% (Murthy et al., 2010). Both clinical and subclinical forms of alcohol use are associated with sleep related problems (Brower, 2001). Evidence from both animal and human studies suggests that the relationship between alcohol use and circadian rhythm disturbances is bidirectional (Logan et al., 2014). While disrupted sleep rhythms are exhibited by individuals with alcohol use disorders, these disruptions in turn increase the subsequent risk of relapse (Stein and Friedmann, 2005).

Broadly, opposing sleep related outcomes during withdrawal and during acute intoxication have been found. While there is reduced sleep onset latency (SOL), longer total sleep time (TST) during acute intoxication (Mello and Mendelson, 1970), withdrawal phase is characterized by increased SOL, reduced TST, reduced sleep efficiency (SE), reduced rapid eye movement (REM) sleep latency, enhanced REM% and decreased slow-wave sleep (SWS) (Conroy and Arnedt, 2014). Even though not well characterized, sleep outcomes in acute and subacute withdrawal phase may differ. Thompson et al. (1995) found less TST and REM% during acute withdrawal than during subacute withdrawal.

Generally it is accepted that such patterns of sleep architecture tend to return to baseline with prolonged abstinence (Hasler et al., 2012). However, there is evidence that has shown that although sleep architecture improves gradually over the first year of abstinence, some characteristics were found to remain abnormal even after 2 years of abstinence (Drummond et al., 1998).

Early recovery from alcohol dependence i.e. soon after detoxification, is a phase that is still farther than being asymptomatic, and is characterized by physiological and psychic symptoms like irritability, autonomic dysfunction and insomnia (Bayard et al., 2004, de Zambotti et al., 2014). This phase of treatment is unique, in the sense that it is free from the acute intoxication effects of alcohol as well as from the effects of acute withdrawal. This group, being subjected to benzodiazepines for detoxification, might have residual effects of benzodiazepine receptor agonism, as well.

A very few studies have focused on this subset of alcohol dependent population. Perney et al. (2012) showed that treatment with acamprosate in recently-detoxified patients, not only increases the duration of abstinence but also improves sleep disturbances. Le Bon et al. (1997) reported recently-detoxified patients to have longer SOL, shorter TST, reduced sleep efficiency, longer stage 1 NREM, shorter slow wave sleep and greater number of awakenings. Apart from the longer stage 1 NREM, Snyder and Karacan (1985) also had reported similar findings. An increase of “REM sleep pressure”, a combined index of REM latency, REM density, and REM sleep percent, has been reported in this sub-population by Gann et al. (2001) besides decreased SWS.

A more sophisticated approach such as spectral power analysis could provide better understanding the sleep architecture (Feige et al., 2013). An increased beta power during NREM and REM sleep, although with less consistency, in patients with primary insomnia (Perlis et al., 2001, Spiegelhalder et al., 2012) that correspond to the general architectural changes, has been reported.

Very few studies, however, assessed cortical distribution of spectral power in various frequency bands across various scalp topographies. More significantly, far few studies, with varied populations and alcohol doses, have assessed electroencephalography (EEG) spectral power in alcohol dependent individuals. While, Dijk et al. (1992) found increased delta power, corresponding to prolonged SWS, following single dose ethanol ingestion, Van Reen et al. (2006), after single administration of a moderate dose of alcohol, found increased delta and alpha spectral power localized to fronto-central leads during NREM sleep. Colrain et al. (2009) found reduced spectral power in theta and delta frequencies, corresponding to shorter SWS, in frontal regions in patients dependent on alcohol. More importantly, Feige et al. (2007), studying the recently detoxified patients with alcohol dependence, found enhanced high-beta spectral power during REM sleep, limited to the adaptation night.

All in all, a very few studies have quantitative analysis on sleep EEG in alcohol dependent patients- while Colrain et al. (2009) do focus on various cortical topographical regions, they do not specifically include a particular phase of dependence; and Feige et al. (2007) focusing on newly detoxified patients, do not consider topographical differences and analyze a single channel. Perhaps, no study has so far, described regional-hemispheric characteristics in alcohol dependence. With this literature backup, the present study aimed at comparing sleep architecture and EEG spectral power (in various brain topographical areas across various frequency bands in different stages of sleep) in recently detoxified patients with chronic alcohol dependence and healthy controls.