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Mount Pearl, Canada

Carskadon M.A.,Brown University | Carskadon M.A.,Sleep Research Laboratory | Sharkey K.M.,Brown University | Knopik V.S.,Brown University | And 2 more authors.
Sleep | Year: 2012

Objectives: This study examined whether the 5-HTTLPR polymorphism in the SLC6A4 gene is associated with self-reported symptoms of depressed mood in first-year university students with a persistent pattern of short sleep. Design: Students provided DNA samples and completed on-line sleep diaries and a mood scale during the first semester. A priori phenotypes for nocturnal sleep and mood scores were compared for the distribution of genotypes. Setting: Brown University, Providence, Rhode Island. Participants: A sample of 135 first-year students, 54 male, 71 Caucasian, mean age 18.1 (± 0.5) yr. Interventions: None. Measurements: Students completed on-line sleep diaries daily across the first term (21-64 days; mean = 51 days ± 11) and Center for Epidemiologic Studies-Depression (CES-D) mood scale after 8 wk. DNA was genotyped for the triallelic 5-HTTLPR polymorphism. Low-expressing S and L G polymorphisms were designated S′, and high-expressing L A was designated L′. Phenotype groups were identified from a combination of CES-D (median split: high > 12; low < 13) and mean nocturnal total sleep time (TST) from diaries: (shorter ≤ 7 hr; longer ≥ 7.5 hr). Three genotypes were identified (S′S′, S′L′, L′L′); the S′S′ genotype was present in a higher proportion of Asian than non-Asian students. Results: Four phenotype groups were compared: 40 students with shorter TST/high CES-D; 34 with shorter TST/low CES-D; 29 with longer TST/ high CES-D; 32 with longer TST/low CES-D. Female:male distribution did not vary across phenotype groups (chi-square = 1.39; df = 3; P = 0.71). S′S′ participants (n = 23) were overrepresented in the shorter TST/high CES-D group (chi- square = 15.04; df = 6; P < 0.02). This association was sustained after removing participants with preexisting evidence of depressed mood (chi-square = 12.90; df = 6; P = 0.045). Conclusion: These data indicate that young adults who reported shorter nocturnal sleep and higher depressed mood are more likely than others to carry a variant of the SLC6A4 gene associated with low expression of the serotonin transporter. Source

Kish S.J.,University of Toronto | Lerch J.,University of Toronto | Furukawa Y.,University of Toronto | Furukawa Y.,Juntendo Tokyo Koto Geriatric Medical Center | And 15 more authors.
Brain | Year: 2010

Animal data indicate that the recreational drug ecstasy (3,4-methylenedioxymethamphetamine) can damage brain serotonin neurons. However, human neuroimaging measurements of serotonin transporter binding, a serotonin neuron marker, remain contradictory, especially regarding brain areas affected; and the possibility that structural brain differences might account for serotonin transporter binding changes has not been explored. We measured brain serotonin transporter binding using [11C] N,N-dimethyl-2-(2-amino-4- cyanophenylthio) benzylamine in 50 control subjects and in 49 chronic (mean 4 years) ecstasy users (typically one to two tablets bi-monthly) withdrawn from the drug (mean 45 days). A magnetic resonance image for positron emission tomography image co-registration and structural analyses was acquired. Hair toxicology confirmed group allocation but also indicated use of other psychoactive drugs in most users. Serotonin transporter binding in ecstasy users was significantly decreased throughout all cerebral cortices (range-19 to-46) and hippocampus (-21) and related to the extent of drug use (years, maximum dose), but was normal in basal ganglia and midbrain. Substantial overlap was observed between control and user values except for insular cortex, in which 51 of ecstasy user values fell below the lower limit of the control range. Voxel-based analyses confirmed a caudorostral gradient of cortical serotonin transporter binding loss with occipital cortex most severely affected. Magnetic resonance image measurement revealed no overall regional volume differences between groups; however, a slight left-hemispheric biased cortical thinning was detected in methamphetamine-using ecstasy users. The serotonin transporter binding loss was not related to structural changes or partial volume effect, use of other stimulant drugs, blood testosterone or oestradiol levels, major serotonin transporter gene promoter polymorphisms, gender, psychiatric status, or self-reported hyperthermia or tolerance. The ecstasy group, although 'grossly behaviourally normal', reported subnormal mood and demonstrated generally modest deficits on some tests of attention, executive function and memory, with the latter associated with serotonin transporter decrease. Our findings suggest that the 'typical'/low dose (one to two tablets/session) chronic ecstasy-polydrug user might display a highly selective mild to marked loss of serotonin transporter in cerebral cortex/hippocampus in the range of that observed in Parkinson's disease, which is not gender-specific or completely accounted for by structural brain changes, recent use of other drugs (as assessed by hair analyses) or other potential confounds that we could address. The striking sparing of serotonin transporter-rich striatum (although possibly affected in 'heavier' users) suggests that serotonergic neurons innervating cerebral cortex are more susceptible, for unknown reasons, to ecstasy than those innervating subcortical regions and that behavioural problems in some ecstasy users during abstinence might be related to serotonin transporter changes limited to cortical regions. © The Author (2010). Source

Alshaer H.,Sleep Research Laboratory | Alshaer H.,University of Toronto | Garcia M.,Ibero-American University of Mexico | Radfar M.H.,University of Toronto | And 3 more authors.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2011

The similarities between unvoiced speech sounds and turbulent breath sounds were used to detect change in sound characteristics caused by narrowing of the upper airway (UA), similar to that occurring in obstructive sleep apnea (OSA). In 18 awake subjects, UA resistance (RAU), an index of UA narrowing, was measured simultaneously with breath sounds recording. Linear Prediction Coding was applied on turbulent inspiratory sounds drawn from low and high RAU conditions and K-means was used to cluster the resulting coefficients. The resulting 2 clusters were tested for agreement with the underlying RAU status. Distinct clusters were formed when R UA increased relatively high but not in cases with lower rise in RUA (P<0.01 for all indicators.) This is the first work to show the utility of LPC in breath sounds analysis confirmed by an objective indicator or UA narrowing. © 2011 IEEE. Source

Hummel R.,Sleep Research Laboratory | Bradley T.D.,Sleep Research Laboratory | Fernie G.R.,Sleep Research Laboratory | Chang S.J.I.,University of Toronto | Alshaer H.,Sleep Research Laboratory
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2015

Polysomnography is a comprehensive modality for diagnosing sleep apnea (SA), but it is expensive and not widely available. Several technologies have been developed for portable diagnosis of SA in the home, most of which lack the ability to detect sleep status. Wrist actigraphy (accelerometry) has been adopted to cover this limitation. However, head actigraphy has not been systematically evaluated for this purpose. Therefore, the aim of this study was to evaluate the ability of head actigraphy to detect sleep/wake status. We obtained full overnight 3-axis head accelerometry data from 75 sleep apnea patient recordings. These were split into training and validation groups (2/1). Data were preprocessed and 5 features were extracted. Different feature combinations were fed into 3 different classifiers, namely support vector machine, logistic regression, and random forests, each of which was trained and validated on a different subgroup. The random forest algorithm yielded the highest performance, with an area under the receiver operating characteristic (ROC) curve of 0.81 for detection of sleep status. This shows that this technique has a very good performance in detecting sleep status in SA patients despite the specificities in this population, such as respiration related movements. © 2015 IEEE. Source

Plante D.T.,University of Wisconsin - Madison | Plante D.T.,001 Research Park Boulevard | Trksak G.H.,Behavioral Psychopharmacology Research Laboratory | Trksak G.H.,Brain Imaging Center | And 21 more authors.
Sleep | Year: 2014

Study Objectives: A principal function of sleep may be restoration of brain energy metabolism caused by the energetic demands of wakefulness. Because energetic demands in the brain are greater in gray than white matter, this study used linear mixed-effects models to examine tissue-type specific changes in high-energy phosphates derived using 31P magnetic resonance spectroscopy (MRS) after sleep deprivation and recovery sleep. Design: Experimental laboratory study. Setting: Outpatient neuroimaging center at a private psychiatric hospital. Participants: A total of 32 MRS scans performed in eight healthy individuals (mean age 35 y; range 23-51 y). Interventions: Phosphocreatine (PCr) and β-nucleoside triphosphate (NTP) were measured using 31P MRS three dimensional-chemical shift imaging at high field (4 Tesla) after a baseline night of sleep, acute sleep deprivation, and 2 nights of recovery sleep. Novel linear mixed-effects models were constructed using spectral and tissue segmentation data to examine changes in bioenergetics in gray and white matter. Measurements and Results: PCr increased in gray matter after 2 nights of recovery sleep relative to sleep deprivation with no significant changes in white matter. Exploratory analyses also demonstrated that increases in PCr were associated with increases in electroencephalographic slow wave activity during recovery sleep. No significant changes in β-NTP were observed. Conclusions: These results demonstrate that sleep deprivation and subsequent recovery-induced changes in high-energy phosphates primarily occur in gray matter, and increases in phosphocreatine after recovery sleep may be related to sleep homeostasis. Source

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