Covassin, Naima

Background Sleep fragmentation induced by repetitive arousals is a hallmark of obstructive sleep apnea (OSA). Sleep fragmentation has been linked to hypertension in community‐based studies, but it is unclear if this association is manifest in OSA. We aimed to explore whether frequent arousals from sleep modify the relationship between OSA and prevalent hypertension. Methods and Results A total of 10 102 patients with OSA and 1614 primary snorers were included in the study. Hypertension was defined on either direct blood pressure measures or diagnosis by a physician. Spontaneous, respiratory, and movement arousals were derived by polysomnography. Logistic regression models were used to estimate the associations between arousals and prevalent hypertension in patients with OSA and primary snorers. For every 10‐unit increase of total arousal index, odds of hypertension significantly increased in both the total sample (odds ratio [OR], 1.08; 95% CI, 1.03–1.14; P =0.002) and patients with OSA (OR, 1.10; 95% CI, 1.04–1.16; P <0.001), but not in the primary snoring group. Total arousal index was significantly associated with systolic blood pressure and diastolic blood pressure in the total sample (β=0.05 and β=0.06; P <0.001) and in patients with (β=0.05 and β=0.06; P <0.01), but not in primary snorers. In addition, a greater influence of respiratory events with arousals than respiratory events without arousals on blood pressure in OSA was also noted. Results were independent of confounders, including apnea‐hypopnea index and nocturnal hypoxemia. Conclusions We conclude that repetitive arousals from sleep are independently associated with prevalent hypertension in patients with OSA.

Abstract While the contribution of several physiological systems to arterial blood pressure regulation has been studied extensively, the role of normal and disrupted sleep as a modifiable determinant of blood pressure control, and in the pathophysiology of hypertension, has only recently emerged. Several sleep disorders, including sleep apnea and insomnia, are thought to contribute to the development of hypertension, although less attention is paid to the relationship between sleep duration and blood pressure independent of sleep disorders per se. Accordingly, this review focuses principally on the physiology of sleep and the consequences of abnormal sleep duration both experimentally and at the population level. Clinical implications for patients with insomnia who may or may not have abbreviated sleep duration are explored. As a corollary, we further review studies of the effects of sleep extension on blood pressure regulation. We also discuss epidemiological evidence suggesting that long sleep may also be associated with hypertension and describe the parabolic relationship between total sleep time and blood pressure. We conclude by highlighting gaps in the literature regarding the potential role of gut microbial health in the cross-communication of lifestyle patterns (exercise, diet, and sleep) with blood pressure regulation. Additionally, we discuss populations at increased risk of short sleep, and specifically the need to understand mechanisms and therapeutic opportunities in women, pregnancy, the elderly, and in African Americans.

Although insufficient sleep is associated with increased cardiovascular risk, evidence of a causal relationship is lacking. We investigated the effects of prolonged sleep restriction on 24-hour ambulatory blood pressure (BP) and other cardiovascular measures in 20 healthy young participants (aged 23.4±4.8 years, 9 females), who underwent a randomized, controlled, crossover, 16-day inpatient study consisting of 4 days of acclimation, 9 days of sleep restriction (4 hours of sleep/night) or control sleep (9 hours), and 3 days of recovery. Subjects consumed a weight maintenance diet with controlled nutrient composition throughout. A 24-hour BP (primary outcome) and cardiovascular biomarkers were measured repeatedly. Polysomnographic monitoring was continuous. Comparing sleep restriction versus control sleep, 24-hour mean BP was higher (adjusted mean difference, day 12: 2.1 mm Hg [95% CI, 0.6–3.6], corrected P =0.016), endothelial function was attenuated ( P <0.001), and plasma norepinephrine increased ( P =0.011). Despite increased deep sleep, BP was elevated while asleep during sleep restriction and recovery. Post hoc analysis revealed that 24-hour BP, wakefulness, and sleep BP increased during experimental and recovery phases of sleep restriction only in women, in whom 24-hour and sleep systolic BP increased by 8.0 (5.1–10.8) and 11.3 (5.9–16.7) mm Hg, respectively (both P <0.001). Shortened sleep causes persistent elevation in 24-hour and sleep-time BP. Pressor effects are evident despite closely controlled food intake and weight, suggesting that they are primarily driven by the shortened sleep duration. BP increases are especially striking and sustained in women, possibly suggesting lack of adaptation to sleep loss and thus greater vulnerability to its adverse cardiovascular effects.

Introduction: Obesity is linked with heightened vulnerability to cardiovascular diseases including hypertension. Nonetheless, mechanistic studies addressing the effects of experimental weight gain on blood pressure are lacking. We sought to examine whether experimental weight gain raises ambulatory blood pressure in healthy individuals and identify any relationship between changes in blood pressure and changes in regional fat distribution. Methods: Twenty-six normal weight subjects were randomized to a 8-week period of weight gain through overfeeding (N=16; age 30.4±6.6 years, BMI 23.5±3.5 kg/m 2 ) or weight maintenance (N=10; age 27.1±7.7 years, BMI 23.6±2.7 kg/m 2 ). Measurements of body composition by dual-energy X-ray absorptiometry and abdominal computed tomographic scans and 24-h ambulatory blood pressure monitoring were obtained at baseline and at follow-up. Results: Overfeeding resulted in an increase in body weight of 3.7±1.5 kg ( p <0.001) in weight gainers, with increments seen in total (21994±8247.4 to 25180.7±8563.1 gr, p <0.001), visceral (61.6±32.7 to 75.5±30.9 cm 2 , p =0.002) and subcutaneous fat (135.5±77.4 to 167.9±82.9 cm 2 , p <0.001). No changes occurred in the maintenance group. Weight gainers exhibited an increase in 24-h systolic blood pressure at follow-up (113.7±8 to 117.7±7.9 mmHg, p =0.009) and mean blood pressure (MAP) (85.1±4.9 to 86.8±5.1 mmHg, p =0.02), while blood pressure was unchanged in controls. Changes in MAP were positively correlated only with changes in visceral fat (rho=0.452, p =0.02) but not with changes in weight or any other body composition measure. Conclusion: Modest weight gain leads to marked elevation in 24-h blood pressure in lean healthy subjects. The association between increased MAP and abdominal visceral fat accumulation suggests that visceral deposition of adipose tissue may contribute specifically and mechanistically to the enhanced risk of hypertension associated with weight gain.

Introduction: An increasing number of healthy adults consume energy drinks to enhance their physical and mental performance. Energy drinks contain caffeine and multiple other “natural” stimulants and their combined effects on cardiac hemodynamics in healthy individuals are unclear. Hypothesis: We hypothesized that drinking a commercially available energy drink, Rockstar , compared to a placebo drink, increases resting blood pressure and heart rate in healthy adults, and these increases would be further accentuated by stress conditions. Methods: We enrolled 25 healthy, normotensive subjects (14 males), aged 29±1 years, with body mass index 24.5±1 kg/m 2 , in a randomized, double-blind, placebo-controlled, crossover study. Each subject consumed a placebo drink and a commercially available Rockstar energy drink (473 ml), in random order on two separate study days. Blood pressure and heart rate responses were recorded and compared before and 30 minutes after drink consumption, both at rest and then in response to physical, mental and cold stressors. Results: The Rockstar energy drink induced a 6±1% increase in resting systolic blood pressure, compared to 3±1% with the placebo drink (P=0.0078). Diastolic blood pressure increased by 7±1% vs 0±1% with the placebo drink (P=0.0007; Figure 1). Heart rate increased similarly in both groups, by 5±2% in the energy drink group vs. 7±2% in the placebo group. Blood pressure and heart rate increases during the stress stimuli (sustained handgrip, mental stress and cold stress) did not differ between energy drink and placebo. Conclusions: Drinking a commercially available Rockstar energy drink significantly increases resting blood pressure in young healthy adults. Blood pressure increases are not further accentuated by exercise, mental or cold pressor stress stimuli. These hemodynamic changes induced by energy drink consumption could predispose to cardiovascular events.

Background Despite strenuous public health efforts, obesity rates continue to rise globally, and contribute importantly to increased cardiometabolic morbidity and mortality. Dietary habits play a key role in the development and progression of obesity, and are the target of choice in preventative and therapeutic programs. Although preclinical studies have shown that caffeine may exert anti‐adipogenic effects, in humans the implications of coffee consumption on risks of excess adiposity are unclear. Objective The objective of this study was to investigate the association between habitual coffee consumption and indices of total and regional body fat in healthy adults. Methods Seventy‐eight subjects (46 males, mean age 27.3±6.1 years) who took part in research studies conducted at the Mayo Clinic Cardiovascular/Sleep Laboratory and underwent body composition assessment were selected. Absence of cardiovascular or metabolic diseases was ascertained by physical exam and review of medical charts. Height, weight, waist and hip circumference measures were collected for computation of body mass index (BMI, kg/m 2 ) and waist‐to‐hip ratio (WHR). Measurements of total body fat percentage, upper body fat (kg), and lower body fat (kg) were obtained from dual‐energy X‐ray absorptiometry (DXA). Abdominal computed tomography (CT) was used to quantify subcutaneous adipose tissue (SAT, cm 2 ) and visceral adipose tissue (VAT, cm 2 ). Habitual coffee consumption (cups/day; range 0–3) was self‐reported and coded as a binary variable (yes/no). Results Sixty percent of the subjects (n=47) reported habitual coffee consumption. Age and gender distribution were comparable between groups (P=0.52 and P=0.73, respectively). There was no significant difference between those who reported consuming coffee and those who did not in terms of BMI (23.6±2.7 kg/m 2 vs 24±2.8 kg/m 2 , P=0.56) and WHR (0.85±0.08 vs 0.85±0.07, P=0.7). Likewise, body composition and fat distribution indices were similar between groups: total body fat percentage (coffee drinkers vs non‐coffee drinkers: 30.5±7.2% vs 28.6±7.8%, P=0.27), upper body fat mass (6.6±2.4 kg vs 6.6±3.1 kg, P=0.99), lower body fat mass (9.4±5.2 kg vs 8.4±4.1 kg, P=0.39), SAT (143.4±61.3 cm 2 vs 135.9±63.7 cm 2 , P=0.6), and VAT (57.7±35.5 cm 2 vs 70.3±44 cm 2 , P=0.22). Analysis stratified by gender did not reveal any differential effect of regular coffee consumption on body fat (all Ps>0.26). Conclusion In healthy, young individuals moderate habitual coffee consumption is not associated with measures of total or regional adiposity. Whether the anti‐obesity effects of caffeine emerge only when it is consumed in larger quantities remains to be determined. Support or Funding Information Research support: 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 .

Background Osteoporosis, a condition associated with decreased bone density, contributes significantly to morbidity and mortality. Importantly, the incidence and economic burden of osteoporosis is rising partly due to increases in the aging population. Moreover, while the role of obesity on bone health is controversial, studies suggest that obesity alters bone density. Effects of obstructive sleep apnea (OSA), which is more prevalent in ageing and obesity, on any relationship between obesity and BMD are not well known. Objective To examine the effects of BMI and OSA on total and regional bone density. Methods A database of all research participants with nocturnal polysomnography and whole body dual energy X‐Ray absorptiometry scan (DEXA) was created. The study population included 72 subjects without OSA (AHI<5, Age: 29.1 ± 7.3 years, BMI: 24.3 ± 3.6 Kg/m 2 ) and 22 subjects with OSA (apnea hypopnea index, AHI>5; 4 females, Age: 43.3 ± 11.2 years, BMI: 30.8 ± 4.1 Kg/m 2 ). We examined the relationship between BMI and BMD in all our subjects. Linear regression models adjusted for age and BMI were used to assess changes in bone density in the presence of OSA. Additional analyses examining the effects of OSA in overweight and obese individuals (BMI>25 kg/m 2 ) and relationship between BMI and BMD in OSA subjects were also undertaken. Results Total body bone density in all our study subjects was positively correlated with BMI (Std Beta = 0.42, 95% CI 0.004 – 0.015, p < 0.001) but not age (Std Beta = 0.04, 95% CI −0.002 −0.003, p = 0.71) or presence of OSA (Std Beta = 0.042, −0.029 − 0.040, p = 0.75). Similarly, bone density in spine was increased with increases in BMI (Std Beta = 0.45, 95% CI 0.006 − 0.019, p = 0.0003) and not affected by age (Std Beta = 0.14, 95% CI −0.001 – 0.005, p = 0.23) or presence of OSA (Std Beta = 0.18, 95% CI −0.011 – 0.065, p = 0.16). Also, increases in BMD in pelvic region were only associated with BMI (Std Beta = 0.30, 0.001 – 0.019, p = 0.024). Age (Std Beta = −0.09, −0.005 – 0.002, p = 0.45) or presence of OSA (Std Beta = 0.19, −0.016 – 0.086, p = 0.17) did not alter BMD in pelvic area. Interestingly, overweight and obese subjects with OSA had a lower pelvic BMD compared to overweight and obese subjects without OSA (1.10 ± 0.12 g/cm 3 Vs. 1.19 ± 0.16 g/cm 3 , p = 0.043), even when OSA subjects had a higher BMI (31.4± 3.7 kg/m 2 Vs. 27.8± 3.2 Kg/m 2 , p = 0.001) and were older (43.4 ± 11.3 years Vs 30.6 ± 8.8 years, p<0.001). Also, the positive relationship between BMI and BMD was not present in OSA subjects in our study population (Total BMD: p = 0.73; Spine BMD: p = 0.94; Pelvic BMD: p=0.77). Conclusion A positive association between bone density and BMI was observed in our study population. However, this relationship was not evident in OSA subjects. Further, our study suggests that OSA may be accompanied by decreased bone density in the pelvic region. Cross‐sectional and longitudinal studies examining the effects of OSA on regional bone density, fractures, and frailty in BMI, age and gender matched populations are warranted. Support or Funding Information VKS and PS are supported by NIH grant HL65176 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 Compelling evidence links obstructive sleep apnea (OSA), a prevalent sleep disorder, to heightened morbidity and mortality. Individuals with family history (FH) of OSA exhibit increased risk of developing this sleep disorder, suggesting that genetics, in addition to demographic and lifestyle factors, are likely implicated in the pathogenesis of OSA. However, it is unclear whether a positive FH of OSA predisposes to other unfavorable health outcomes. In this regard, data on its impact on vulnerability to obesity, both a precursor and a consequence of OSA, are lacking. Objective We sought to assess the association between FH of OSA and risk of obesity. Methods The study population consisted of 612 individuals (66% male, age 48.1±17.3 years) who took part in research studies performed in the Cardiovascular/Sleep Laboratory at Mayo Clinic and had complete family history data. FH of OSA and obesity were determined from questionnaires. Demographics and medical comorbidities including OSA diagnosis were obtained from self‐reports. Body mass index (BMI, kg/m 2 ) was calculated from height and weight measures and used to determine obesity status as follows: normal weight (BMI <25 kg/m 2 ), overweight (BMI 25–29.9 kg/m 2 ), and obese (BMI ≥30 kg/m 2 ). Measurements of waist circumference were obtained to determine central obesity (defined as waist circumference ≥88 cm in women and ≥102 cm in men). Results FH of OSA was reported by twelve percent of the sample (n=72). Individuals with FH of OSA were younger and more likely to be female than those without (age: 40.8±12.6 years vs 49.1±17.6 years, P<0.0001; sex: 48.6% vs 32.2%, P=0.008). Those with positive FH had higher BMI (31.5±6.8 kg/m 2 vs 29.2±7 kg/m 2 , P=0.009), were more frequently obese (59.7% vs 39.8%, P=0.007), and had higher prevalence of central obesity (67.7% vs 53.8%, P=0.036). Multivariable regression models showed the FH of OSA was associated with 3.2‐times greater risk of obesity (95% CI 1.7–5.9, P=0.0002) and with 2.3‐times greater risk of central obesity (95% CI 1.2–4.5, P=0.011) after correcting for age, sex, OSA diagnosis, and FH of obesity. Conclusion Family history of OSA is accompanied by an increased likelihood of obesity, especially central obesity, even if subjects with FH of OSA are much younger. This relationship is independent of conventional risk factors, including OSA diagnosis, suggesting that comorbid OSA in the offspring is unlikely to be implicated. Research addressing the potential pathophysiological mechanisms underlying our findings is warranted. Support or Funding Information Research support: VKS and PS are supported by NIH HL65176. NC is supported by American Heart Association grant 16SDG27250156, and Mayo Clinic CCaTS 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 .

Background Increases in circulating free‐fatty acids (FFAs) contribute to obesity‐associated cardiometabolic pathology and may be considered a surrogate marker for adipose tissue dysfunction. However, alterations in FFA metabolism resulting from modest weight gain have not been previously evaluated. Objective Examine the changes in FFAs during modest weight gain in healthy individuals and to investigate the relationship between regional fat depots. Study Design We evaluated the effects of overfeeding in 8 healthy, non‐obese participants (4 men; age 29 ± 5.7 years; BMI: 25.1 ± 2.1 kg/m2). FFA concentrations were measured using liquid chromatography/mass spectrometry under fasting conditions and during oral‐glucose tolerance test (OGTT) at baseline and after 8 weeks of weight gain. Prior to the baseline and weight gain visits, subjects consumed isocaloric macro‐nutrient stable diet for three days (50% carbohydrate, 35% fat and 15% protein). Body composition and regional fat depots were assessed using dual‐energy X‐ray absorptiometry and abdominal computed tomography scans. Results Overfeeding was accompanied by 3.9 ± 1.6 kg weight gain (p=0.01) resulting from 2.9 ± 0.9 kg (p=0.01) increase in fat mass and 1.0 ± 0.9 kg (p=0.04) increase in fat‐free mass. Compared to baseline, fasting FFA (439 ± 162 μM vs. 368 ± 123 μM, p=0.55) and area under the curve (AUC) for FFA during OGTT (23319 ± 11686 μM. min−1 vs. 20495 ± 4847 μM.min−1, p=0.55) did not change with weight gain. However, at 120 min. of the OGTT FFA were significantly greater after weight gain (60 ± 18 μM vs. 77 ± 34 μM, p=0.04). We found a negative relationship between relative changes in visceral fat area and FFA at 120 min of glucose challenge (rho=−0.76, p=0.03). Furthermore, relative changes in fasting FFA and AUC for FFA during OGTT with weight gain were associated with baseline total fat mass (fasting FFA: rho=0.76, p=0.03; AUC FFA: rho=0.81; p=0.02) and baseline abdominal fat area (fasting FFA: rho=0.76, p=0.03; AUC FFA: rho=0.79; p=0.02). Conclusions Modest weight gain does not alter fasting FFA or overall FFA response to oral glucose challenge. However, our data suggest development of early stages of adipose tissue insulin resistance which is apparent via lesser suppression of FFA at 120 min. of OGTT. Furthermore, the relationships between fasting FFA, AUC‐FFA, and baseline fat mass suggest that individuals with high baseline adiposity may be more susceptible to develop adipose tissue insulin resistance with weight gain. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .