Covassin, Naima

Background The prevalence of excessive daytime sleepiness (EDS) in the general population is reported to be 9 to 28 percent. Various social and biological factors have been reported to contribute to the development of EDS, such as cardiovascular disease, metabolic disorders as well as socioeconomic status. Medically, EDS is associated with poorer prognosis in patients with sleep disorders. However, whether sleepiness is an independent negative prognostic indicator in patients without sleep apnea is poorly understood. Objective To evaluate the relationship between self‐reported excessive daytime sleepiness (assessed by Epworth Sleepiness Scale) and the risk of all‐cause mortality in patients without obstructive sleep apnea (OSA). Methods We performed a retrospective cohort study in a large registry of patients seen at the Mayo Clinic Center for Sleep Medicine between November 17 th , 2009 and April 15 th , 2017. All patients received a diagnostic polysomnography and had completed Epworth Sleepiness Scale (ESS). The primary outcome of all‐cause mortality risk was computed using the Kaplan‐Meier analysis and Cox‐proportional hazard model with age, sex, body mass index (BMI), baseline comorbidities and sleep measurements as confounders. Results A total of 2746 non‐OSA patients were identified. The overall median age (IQR) was computed as 53 (40, 63) with 45% of patients identifying as males. The median follow‐up time was approximately 2.3 years. In a univariate analysis, daytime sleepiness was associated with the female sex, younger age and higher BMI. No significant differences were observed in vascular related diseases between sleepy and non‐sleepy patients. EDS was not significantly associated with all‐cause mortality with an adjusted hazard ratio of 1.23 (95% CI 0.86, 1.76; p =0.257). In addition, there was no significant association of EDS and the risk of all‐cause mortality even after stratifying by sex, age and BMI in non‐OSA patients. Conclusion EDS is not associated with all‐cause mortality in non‐OSA patients. Further prospective studies are needed to confirm this finding. Support or Funding Information This research was supported by NIH HL65176 and NIH HL114024. Kaplan–Meier survival curve of 8 years all‐cause mortality of non‐OSA patients with and without excessive daytime sleepiness (EDS) at baseline. image Kaplan–Meier survival curve of 8 years all‐cause mortality of non‐OSA patients with and without excessive daytime sleepiness (EDS) at baseline. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Background Sleep disturbances are increasingly common and associated with adverse health outcomes. Inadequate sleep may also produce daytime symptoms, such as excessive sleepiness. Growing research identifies daytime sleepiness as a risk factor for morbidity and mortality. However, it is unclear whether these associations are independent of the presence of sleep disordered breathing, a primary cause of hypersomnolence. Objective In this study, we sought to assess the relation between daytime sleepiness and established cardiometabolic risk factors, independently of obstructive sleep apnea. Methods We compiled data from 456 individuals (69% male, age 51.3±15.7 years) who participated in research studies performed in the Cardiovascular/Sleep Laboratory at Mayo Clinic and had complete sleepiness data. Height and weight were measured to calculate body mass index (BMI, kg/m 2 ). Obesity was defined as BMI ≥30 kg/m 2 . Hypertension was determined as self‐reported diagnosis or taking antihypertensive medications. Diabetes mellitus was defined as patient‐reported diabetes or usage of insulin or antidiabetic drugs. Obstructive sleep apnea (OSA) was self‐reported or determined from polysomnography. Subjective daytime sleepiness was defined as an affirmative answer to the question “Are you usually sleepy during the daytime?”. Results Daytime sleepiness was reported by 51% of the subjects (n=231). Those with daytime sleepiness were more likely to be male (74.9% vs 62.3%, P=0.005), but the average age was similar between groups (51.6±17.3 years vs 51±14.1 years, P=0.67). BMI was greater among the subjects with perceived daytime sleepiness than in those without (32.2±7 kg/m 2 vs 28.9±6.8 kg/m 2 , P<0.0001), and obesity was more frequent in the former group (62.9% vs 35.4%, P<0.0001). Prevalence of hypertension (37% vs 27.5%, P=0.03), diabetes (14% vs 6.7%, P=0.01), and OSA (18.2% vs 10.4%, P=0.035) was also higher in individuals reporting sleepiness during the day. In multivariable analysis adjusted for age, sex, and OSA, daytime sleepiness was associated with increased risk of obesity (OR=2.88, 95% CI 1.84–4.49, P<0.0001), hypertension (OR=1.73, 95% CI 1.04–2.87, P=0.034), and diabetes (OR=2.58, 95% CI 1.18–5.61, P=0.017). Conclusion Daytime sleepiness is associated with greater risk of obesity, hypertension and diabetes independently of comorbid OSA. Daytime sleepiness may be a novel target for preventative and therapeutic strategies aimed at improving cardiometabolic health. Support or Funding Information NC is supported by American Heart Association grant 16SDG27250156, and Mayo Clinic Center for Clinical and Translational Science grant Marie Ingalls Cardiovascular Research Career Development Fund. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Objective Inadequate sleep is associated with an increased risk of hypertension. Exaggerated blood pressure (BP) reactivity to psychological stress is predictive of the development of hypertension. Following 24‐hours of total sleep deprivation, individuals exhibit an exaggerated BP response to mental stress (MS). The mechanisms contributing to this response and the generalizability to more prolonged exposure to restricted sleep are not clear. Thus we sought to examine the early hemodynamic response to MS in individuals before and during prolonged sleep restriction. We hypothesized the early rise in BP during MS would occur more slowly and would achieve a higher peak following 9 nights of restricted sleep when compared to control. We further hypothesized the contribution of total peripheral resistance (TPR) to the rise in BP would be greater following restricted sleep when compared to control. Methods Individuals completed two visits randomized to control sleep or experimental sleep restriction. Ten young (23±1 yrs) healthy, non‐obese (24±1 kg/m 2 ) men and women (5M/5F) completed the restriction visit and seven of the same individuals (23±1 yrs; 5M/2F; 24±1 kg/m 2 ) completed the control visit. Each visit consisted of 4 days of acclimation (9 hours of sleep per night) followed by 9 days of control (9 hours/night) or restricted (4 hours/night) sleep. For the purpose of this investigation, individuals were studied on days 2 and 13. Beat‐by‐beat heart rate (HR, electrocardiography) and BP (finger plethysmography) were measured continuously during 2 min of quiet rest followed by 5 min of mental arithmetic. Stroke volume (SV) was estimated from the pressure waveform and cardiac output (CO) and TPR were calculated. Peak change, time to peak, and rate of rise in BP were assessed during the initiation of mental stress (first 30‐s). Results BP increased during MS ( P <0.05) and the early peak BP did not differ between conditions ( P =0.35–0.84). However, following prolonged experimental sleep restriction, individuals achieved peak systolic BP earlier (Time to peak: 19±4 vs 9±3 s, P =0.04) and the rate of rise in diastolic BP at the onset of MS was significantly greater (0.7± 0.3 vs 2.3±0.7 mmHg/s, P =0.01) when compared to the acclimation period. No differences in time to peak BP or rate of rise at the onset of MS were observed on the control visit ( P =0.16–0.97). The peak change in SV (0.5±1.4 vs 6.3±2.1, P =0.03) and CO (1.1±0.2 vs 1.7±0.2 L/min, p=0.01) at the onset of MS were greater following prolonged sleep restriction when compared to the acclimation period. No differences in the change in SV or CO were observed on the control visit ( P =0.39–0.41) and no differences in the change in TPR were observed on either visit ( P =0.36–0.86). Conclusions Prolonged (9‐day) experimental sleep restriction (4 hours/night) results in a faster increase in BP in response to mental arithmetic. This rapid increase in BP at the onset of MS is achieved primarily via a greater increase in SV and CO when compared to the acclimation period. These data highlight an important role for CO in the BP response to stress in sleep restricted individuals and provide important insight into potential mechanisms which may contribute to the development of hypertension following inadequate sleep. Support or Funding Information NIH HL130339, NIH HL114676, NIH HL114024, NIH HL083947, APS UGSRF This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Background The prevalence of inadequate sleep in the general population is rising. While the detrimental health consequences of sleep disorders such as sleep‐disordered breathing are well established, little is known on the contributory role of perceived sleep quality on cardiometabolic risk profile. Importantly, poor sleep quality may be reported even in absence of objective findings of suboptimal sleep. We hypothesized that subjective poor sleep quality would be associated with markers of cardiometabolic risk in individuals without sleep disorders. Methods We compiled data from 667 research subjects (446 males, age 36.4±13.8 years) studied in the Cardiovascular/Sleep Laboratory at Mayo Clinic from 2000 to 2017. Subjects with history of sleep disorders and/or overt cardiovascular diseases, as determined from medical record or self‐report, were excluded from this study. Health status was further confirmed by physical exam. Supine systolic and diastolic blood pressure (SBP/DBP), height, weight, and waist and hip circumferences were collected. Body mass index (BMI, kg/m 2 ) was derived from height and weight. Presence of hypertension (SBP and/or DBP ≥140/80 mmHg) and obesity (BMI ≥30 kg/m 2 ) was recorded. Subjective sleep quality was self‐reported as either good or poor. Analysis of variance and Chi‐square tests were performed to examine differences in outcome measures according to sleep quality. Logistic regression models were run to examine the predictive value of poor sleep quality for hypertension and obesity risk. Results Poor subjective sleep quality was reported by 231 individuals out of 667 (34.6%). Subjects with perceived poor sleep were older (poor sleep vs good sleep: 42.3±12.9 years vs 33.2±13.3 years, p<0.0001), with greater BMI (31.4±7 kg/m 2 vs 26.5±6.3 kg/m 2 , p<0.0001), waist (104.6±17.8 kg/m 2 vs 89.7±14.8 kg/m 2 , p<0.0001) and hip (111.8±14.8 kg/m 2 vs 102.3±11.5 kg/m 2 , p<0.0001) circumference than good sleepers. Compared to the latter group, SBP and DBP values were also higher in self‐evaluated poor sleepers (poor sleep vs good sleep, SBP: 128.8±15.5 mmHg vs 122.9±14.4 mmHg, p<0.0001; DBP: 74.5±10.6 mmHg vs 71.8±11.4 mmHg, p=0.012). Obesity was more prevalent in those with subjective poor sleep quality than in good sleepers (53.3% vs 19.7%, p<0.0001). Similarly, 72.5% of patients with hypertension reported poor sleep quality while only 27.5% of them were good sleepers (p<0.0001). In comparison to good sleep quality, perceived poor sleep was associated with 3.6 times greater risk of obesity (95% CI 2.5, 5.2, p<0.0001) and 3.5 times greater risk of hypertension (95% CI 1.7, 6.9, p=0.0004) after correcting for conventional covariates. Significance was retained after further adjustment for reported snoring and witnessed apneas. Conclusions Poor perceived sleep quality is independently associated with elevated risk of high blood pressure and excess body weight in individuals without sleep disorders. These findings favor the concept that promoting adequate sleep quality, even subjectively, may benefit cardiometabolic health. Support or Funding Information American Heart Association grant 16SDG27250156; National Institutes of Health grants RO1 HL 065176 and HL 134808. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Background Increasing evidence suggests that insufficient sleep is associated with increased morbidity and mortality. Studies linking short sleep with metabolic derangements such as obesity, insulin resistance and dyslipidemia, are especially persuasive. Nevertheless, the vast majority of these data have been obtained from observational studies. We sought to evaluate the effects of 9 days of partial sleep deprivation compared to normal sleep on lipid profile in healthy subjects undergoing an in‐laboratory, experimental protocol. Methods Eight healthy, nonobese, normolipidemic subjects (4 males, age 25.4±6.8 years, body mass index 25.2±3.9 kg/m 2 ) completed a randomized, controlled, crossover, 16‐day in‐patient study. Each sequence consisted of a 4‐day acclimation period, followed by 9 days of experimental partial sleep deprivation (4 hours of sleep opportunity; 00:30 AM – 4:30 AM); or normal sleep (9 hours of sleep opportunity; 10:00 PM – 7:00 AM), and a subsequent 3‐day recovery segment. Subjects consumed a controlled, weight maintenance diet (15% protein, 55% carbohydrates, and 30% fat) during the study. Fasting blood samples for measures of total cholesterol, high‐density lipoprotein (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, and triglycerides were obtained in both study sequences on Days 4, 7, 10, 13, and 16. Results Compared to normal sleep, experimental partial sleep deprivation did not cause significant changes in total cholesterol (partial sleep deprivation vs normal sleep: 160.1±21.8 mg/dL vs 164.9±23.7 mg/dL, P=0.724), HDL cholesterol (54.1±14.7 mg/dL vs 52±12.8 mg/dL, P=0.75), LDL cholesterol (86.5±18.9 mg/dL vs 89.5±19.7 mg/dL, P=0.329), or triglycerides (97.7±26.6 mg/dL vs 96.6±38.3 mg/dL, P=0.633). Analysis of time course of lipid values across study days did not reveal appreciable patterns (all P>0.295). Likewise, body weight was similar during both study sequences (partial sleep deprivation vs normal sleep: 69.6±14.2 kg vs 69.2±13.5 kg, P=0.459). Conclusions Experimental sleep restriction does not alter circulating lipids or weight in healthy subjects. Aberrant metabolic effects of insufficient sleep may be mediated by dietary intake and occur when access to food is unrestricted, or may emerge only after longer exposure to sleep curtailment. Support or Funding Information American Heart Association grant 16SDG27250156; National Institutes of Health R01 grants HL114676 and HL114024; European Union project FNUSA‐ICRC no. CZ.1.05/1.1.00/02.0123. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Background Numerous studies have identified an association between frequency of breakfast consumption and body weight in children and adolescents, indicating that those who skip this meal are more likely to gain weight and develop obesity in adulthood. However, few studies have examined the implications of infrequent breakfast consumption for obesity risk in the adult population, and available data are mixed. The purpose of this study was to investigate the role of breakfast consumption on obesity indices and weight gain in a sample of healthy adults. Methods The study sample was drawn from a cohort of consecutive subjects who were recruited for research studies at the Cardiovascular/Sleep Laboratory at Mayo Clinic from 2005 to 2017 and consisted of 347 healthy adults (215 males, mean age 35.5±15.4 years, ranging from 18 to 87 years old). Physical examination and review of medical records were conducted to ensure absence of overt disease. Measures of height, weight, waist and hip circumference were obtained. Body mass index (BMI, kg/m 2 ) and waist‐to‐hip ratio (WHR) were computed. Obesity was defined as BMI ≥30 kg/m 2 . Weight gain over the past year was quantified from self‐report. Frequency of breakfast consumption (times/week, range 0 to 7) was collected from questionnaire and coded as “never” (0 times/week), “infrequent” (1 to 4 times/week), and “frequent” (5 to 7 times/week). Only those who reported the same breakfast routine for ≥2 years were included in the analysis. Results Four percent of the sample (n=15) reported never consuming breakfast and 24% (n=85) reported eating it infrequently. Compared to the individuals who consumed it frequently, those who never or infrequently had breakfast were predominately men (P=0.049) and older (P=0.001). Waist circumference was larger in those who skipped breakfast in comparison to those who consumed it 1–4 times/week or 5–7 times/week (97.5±17.9 cm vs. 85.6±11 cm vs. 87.7±15 cm, respectively; P=0.017). There were no significant differences in hip circumference, WHR, or BMI across breakfast eating patterns. Prevalence of obesity tended to be higher among those who skipped breakfast than in those who ate it frequently (26.7% vs. 10.9%, P=0.074). Individuals who did not consume breakfast reported the greatest weight gain, followed by those who consumed it 1–4 times/week, while the lowest weight gain was reported by those who had breakfast 5–7 times/week (3.6±6.9 kg vs. 2±2.3 kg vs. 1.3±2.2 kg; P=0.002). In a multivariable model, skipping breakfast predicted weight gain independently of age, gender, and BMI (P=0.004). Conclusions Infrequent breakfast consumption is associated with indices of central obesity and weight gain, with these associations being more evident in individuals who never eat breakfast. Our findings on healthy adults are consistent with prior observations in the young, corroborating the concept that regular consumption of this meal is an important and independent contributor of healthy weight at all ages. Support or Funding Information American Heart Association grant 16SDG27250156; National Institutes of Health grants RO1 HL 114676 and HL 114024; CCaTS Early Stage Investigator Award. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Background: Decreased testosterone (TTST) and sex hormone binding globin (SHBG) contribute to development of cardiometabolic disorders in obese men. We aimed to determine the effect of weight gain and weight loss on TTST and SHBG in healthy men and to examine their relationship with endothelial function. Method: 25 normal weight healthy men underwent an overfeeding protocol to gain 5% body weight over 8 weeks. Following weight gain, they underwent 8 weeks of weight loss. TTST, SHBG and endothelial function (brachial artery flow‐mediated dilation, FMD) were measured at baseline (T1), after weight gain (T2) and after weight loss (T3). Results: Volunteers gained 4 ± 1.3 kg and subsequently lost 3.2 ± 1.5 kg of body weight. TTST levels did not change (T1: 18.85 ± 6.2 nmol/L, T2: 19.3 ± 6.9 nmol/L, T3: 20.3 ± 7.6 nmol/L). However, SHBG decreased during weight gain (p=0.04) and increased during weight loss (p=0.0005) (T1: 22.8 ± 10.5 nmol/L, T2: 20.8 ± 11.1 nmol/L, T3: 25.58 ± 11.5 nmol/L). Furthermore, SHBG reduction during weight gain tended to correlate with decreases in FMD (p=0.06; R 2 =0.15). During weight loss, increases in SHBG correlate negatively with changes in FMD (p=0.008; R 2 =0.32). Conclusion : In normal weight healthy men, SHBG decreases with modest weight gain and increases with weight loss. TTST does not change. Changes in SHBG partly predict improvements in endothelial function with weight loss. Grant Funding Source : Supported by AHA 11SDG7260046, R21 DK81014, AHA 13POST16420009

Traditionally regarded as a consequence of sleep‐disordered breathing, excessive daytime sleepiness (EDS) is now recognized as an independent risk factor for cardiovascular disease. Evidence also links the shortening of telomeres, responsible for protecting DNA, with increased cardiovascular disease risk. Interestingly, recent data illustrate telomere lengthening in patients with obstructive sleep apnea (OSA); however, whether EDS is associated with telomere length independently of OSA remains unknown. To examine this potential relationship, we studied 169 subjects with polysomnography assessment who answered “yes” or “no” to experiencing EDS; 70 subjects (41%) reported EDS (59M, 44±12yrs, 30.3±5.5kg/m 2 ) whereas 99 did not (59%, 71M, 40±15yrs, 28.6±7.5kg/m 2 ). Telomere length was quantified via qPCR of genomic DNA isolated from peripheral blood samples and did not differ between individuals reporting EDS compared to those who did not (4,856±280 vs. 4,880±340bp, respectively, P =0.31). However, 50% of subjects reporting EDS had moderate‐to‐severe OSA (apnea‐hypopnea index ≥15events/hr) compared to 28% of the non‐EDS group ( P <0.01). To account for the confounding effects of OSA on telomere length, we conducted a series of subgroup analyses. Subjects without OSA who reported EDS (n=35, 27M, 39±11yrs, 27.4±5.0kg/m 2 ) had shorter telomeres (4,805±165 vs. 4,875±231bp, P =0.05) than those not reporting EDS (n=71, 47M, 35±11yrs, 26.8±5.4kg/m 2 ). Interestingly, within the OSA subgroup, there were no differences in telomere length (4,897±235 vs. 4,858±251bp, P =0.45) between those with (n=35, 32M, 48±11yrs, 33.2±4.5kg/m 2 ) and without EDS (n=28, 24M, 53±16yrs, 33.1±9.7kg/m 2 ). These effects do not appear to be influenced by subject demographics as no differences were found between compared groups (EDS‐OSA vs. nEDS‐OSA and OSA+EDS vs. OSA‐EDS). Collectively, our data suggest individuals reporting EDS may be at greater risk of developing cardiovascular disease due to accelerated telomere shortening. It also appears OSA and EDS exert differential effects on telomere length.