Sleep disorders in myotonic dystrophy type 2: a controlled polysomnographic study and self-reported questionnaires.

BACKGROUND AND PURPOSE: There is a paucity of data available regarding the occurrence of sleep disorders in myotonic dystrophy type 2 (DM2). In this study the sleep-wake cycle and daytime sleepiness were investigated in DM2 patients and compared with results from healthy subjects and myotonic dystrophy type 1 (DM1) patients. METHODS: Twelve DM2 outpatients, 12 age- and sex-matched healthy controls and 18 DM1 patients were recruited. Subjective quality of sleep was assessed by means of the Pittsburgh Sleep Quality Index (PSQI). Both the Epworth Sleepiness Scale and the Daytime Sleepiness Scale were performed in order to evaluate excessive daytime sleepiness (EDS). All participants underwent polysomnographic monitoring over 48 h as well as the Multiple Sleep Latency Test. RESULTS: Sleep efficiency was < 90% in 12/12 DM2 patients, and significantly reduced when compared with controls or with DM1. Decreased sleep efficiency was associated with sleep-disordered breathing in seven out of 12 DM2 patients and/or periodic limbs movements of sleep (PLMS) in three out of eight patients. Six DM2 patients showed REM sleep without atonia, whereas none of the controls or DM1 patients showed REM sleep dysregulation. The global PSQI score was higher in DM2 patients than in controls and DM1 patients. CONCLUSIONS: Sleep quality in DM2 patients is poorer than in DM1 patients and controls. Sleep apnea is the most common sleep disorder in DM2 patients. Obstructive sleep apnea and sleep fragmentation may represent the main cause of EDS, whereas PLMS is a frequent finding in DM1.

Muscle atonia index during multiple sleep latency test: A possible marker to differentiate narcolepsy from other hypersomnias.

OBJECTIVE: The complexity and delay of the diagnosis of narcolepsy require several diagnostic tests and invasive procedures such as lumbar puncture. Our study aimed to determine the changes in muscle tone (atonia index, AI) at different levels of vigilance during the entire multiple sleep latency test (MSLT) and each nap in people with narcolepsy type 1 (NT1) and 2 (NT2) compared with other hypersomnias and its potential diagnostic value. METHODS: Twenty-nine patients with NT1 (11 M 18F, mean age 34.9 years, SD 16.8) and sixteen with NT2 (10 M 6F, mean age 39 years, SD 11.8) and 20 controls with other hypersomnias (10 M, 10F mean age 45.1 years, SD 15.1) were recruited. AI was evaluated at different levels of vigilance (Wake and REM sleep) in each nap and throughout the MSLT of each group. The validity of AI in identifying patients with narcolepsy (NT1 and NT2) was analyzed using receiver operating characteristic (ROC) curves. RESULTS: AI during wakefulness (WAI) was significantly higher in the narcolepsy groups (NT1 and NT2 p < 0.001) compared to the hypersomniac group. AI during REM sleep (RAI) (p = 0.03) and WAI in nap with sudden onsets of REM sleep periods (SOREMP) (p = 0.001) were lower in NT1 than in NT2. The ROC curves showed high AUC values for WAI (NT1 0.88; Best Cut-off > 0.57, Sensitivity 79.3 % Specificity 90 %; NT2 0.89 Best Cut-off > 0.67 Sensitivity 87.5 % Specificity 95 %; NT1 and NT2 0.88 Best Cut-off > 0.57 Sensitivity 82.2 % Specificity 90 %) in discriminating subjects suffering from other hypersomnias. RAI and WAI in nap with SOREMP showed a poor AUC value (RAI AUC: 0.7 Best cutoff 0.7 Sensitivity 50 % Specificity 87.5 %; WAI in nap before SOREMP AUC: 0.66, Best cut-off < 0.82 sensitivity 61.9 % and specificity 67.35 %) differentiating NT1 and NT2. CONCLUSIONS: WAI may represent an encouraging electrophysiological marker of narcolepsy and suggests a vulnerable tendency to dissociative wake / sleep dysregulation lacking in other forms of hypersomnia. SIGNIFICANCE: AI during wakefulness may help distinguish between narcolepsy and other hypersomnias.

Sleep disorders in adult-onset myotonic dystrophy type 1: a controlled polysomnographic study.

BACKGROUND: Sleep disturbances and excessive daytime somnolence are common and disabling features in adult-onset myotonic dystrophy type 1 (DM1). METHODS: Our study used questionnaires, ambulatory polysomnography and the multiple sleep latency test to evaluate sleep-wake cycle and daytime sleepiness in unselected adult-onset DM1 patients. We recruited 18 patients affected by adult-onset DM1 and 18 matched controls. RESULTS: Sleep efficiency was <90% in 16/18 patients, and it was significantly reduced when compared with controls. Reduced sleep efficiency was associated with abnormal respiratory events (5/18 patients) and/or periodic limb movements (11/18 patients). The Periodic Limb Movement Index was significantly increased in DM1 versus controls. A significantly lower mean MSLT sleep latency was detected in DM1 versus controls, but it did not reach pathological levels. CONCLUSIONS: Our controlled study demonstrated sleep alterations in unselected consecutive DM1 patients. Periodic limb movements in sleep are commonly associated with sleep disturbance in adult-onset DM1, and it may represent a marker of CNS neurodegenerative processes in DM1.

Improvements in metabolic abnormalities among overweight schizophrenia and bipolar disorder patients.

PURPOSE: As weight-gain and metabolic abnormalities during treatment with psychotropic drugs are of great concern, we evaluated effects of psycho-education and medical monitoring on metabolic changes among severely mentally ill patients. MATERIALS AND METHODS: During repeated, systematic psycho-education about general health among 66 consecutive patients diagnosed with DSM-IV-TR schizophrenia (n=33) or type-I bipolar disorder (n=33), we evaluated (at intake 1, 2, 3, and 6 months) clinical psychiatric status, treatments and doses, recorded physiological parameters, and assessed attitudes about medication. RESULTS: At intake, patients with schizophrenia vs bipolar disorder were receiving 3-7 times more psychotropic medication, with 14% higher initial body-mass index (BMI: 29.1 vs 25.6 kg/m²), 12 times more obesity, and significantly higher serum lipid concentrations. During 6-months follow-up, among bipolar disorder patients, polytherapy and serum lipid concentrations declined more than among schizophrenia patients (e.g., total cholesterol+triglycerides, by 3.21 vs 1.75%/month). BMI remained stable. Declining lipid levels were associated with older age, bipolar disorder, being unemployed, higher antipsychotic doses, and lower initial BPRS scores (all P ≤ 0.001). CONCLUSIONS: Psychotropic treatments were more complex, and metabolic measures more abnormal among bipolar disorder than schizophrenia patients. Intensive psycho-education, clinical monitoring, and encouragement of weight-control for six months were associated with improvements in metabolic measures (but not to BMI), and more realistic attitudes about medication.

Uso de cannabis y desarrollo de esquizofrenia: ¿cuáles son los vínculos? / Cannabis use and schizophrenia development: which are the links?

El cannabis es la droga más utilizada por personas con esquizofrenia. Sin embargo, la relación entre el consumo de cannabis y el desarrollo de esquizofrenia aún no ha sido completamente aclarada. Esta comunicación corta pretende destacar algunos vínculos estudiados entre el consumo de cannabis y el desarrollo de esquizofrenia. Los autores resumen algunos de los principales hallazgos de varias investigaciones realizadas sobre este tema, incluyendo estudios sobre la sustancia blanca del cerebro, el circuito de recompensa cerebral, la fisiopatología del hipocampo, el volumen cerebral, la edad de inicio de la psicosis, las características del uso de cannabis y los rasgos de personalidad, la genética, la neuroquímica, así como la respuesta al estrés. Los autores concuerdan con la noción de que hay dos hipótesis más convincentes sobre el vínculo entre el cannabis y la esquizofrenia: 1. Cannabis como causa contribuyente y, 2. Vulnerabilidad compartida. Los autores hacen hincapié en que el consumo de cannabis no provoca por sí mismo un trastorno psicótico; sin embargo, tanto el uso temprano como el uso intensivo del mismo son más probables en individuos con una vulnerabilidad a la psicosis. El uso del cannabis es posiblemente el factor de riesgo medioambiental más modificable de la esquizofrenia, por lo que es necesaria una advertencia de salud pública de que el consumo de cannabis puede aumentar el riesgo de trastornos psicóticos.

Cannabis is the drug most often used by persons with schizophrenia. However, the relationship between cannabis use and schizophrenia development has not yet been fully clarified. This short communication aims to highlight some studied links between cannabis use and schizophrenia development. The authors summarize some of the main findings of several investigations done on this topic, including studies on brain white matter, brain reward circuit, hippocampal pathophysiology, brain volume, age of psychosis onset, and characteristics of cannabis use, personality traits, genetics, neurochemistry, and stress response. The authors agree with the notion that there are two most convincing hypotheses regarding the link between cannabis and schizophrenia: 1. Cannabis as a contributing cause and, 2. Shared vulnerability. The authors stress that cannabis use does not in itself cause a psychotic disorder; however, both early use and heavy use of it are more likely in individuals with a vulnerability to psychosis. The use of cannabis is arguably the most modifiable environmental risk factor for schizophrenia, so it is necessary to ensure a public health warning that cannabis use can increase the risk of psychotic disorders.