Prediction of resting energy expenditure for adolescents with severe obesity: A multi-centre analysis.

BACKGROUND AND OBJECTIVES: Resting energy expenditure (REE) assessments can help inform clinical treatment decisions in adolescents with elevated body mass index (BMI), but current equations are suboptimal for severe obesity. We developed a predictive REE equation for youth with severe obesity and obesity-related comorbidities and compared results to previously published predictive equations. METHODS: Data from indirect calorimetry, clinical measures, and body composition per Dual x-ray absorptiometry (DXA) were collected from five sites. Data were randomly divided into development (N = 438) and validation (N = 118) cohorts. A predictive equation was developed using Elastic Net regression, using sex, race, ethnicity, weight, height, BMI percent of the 95th%ile (BMIp95), waist circumference, hip circumference, waist/hip ratio, age, Tanner stage, fat and fat-free mass. This equation was verified in the validation cohort and compared with 11 prior equations. RESULTS: Data from the total cohort (n = 556, age 15 ± 1.7 years, 77% female, BMIp95 3.3 ± 0.94) were utilized. The best fit equation was REE = -2048 + 18.17 × (Height in cm) - 2.57 × (Weight in kg) + 7.88 × (BMIp95) + 189 × (1 = male, 0 = female), R2 = 0.466, and mean bias of 23 kcal/day. CONCLUSION: This new equation provides an updated REE prediction that accounts for severe obesity and metabolic complications frequently observed in contemporary youth.

Effects of follicle-stimulating hormone on energy balance and tissue metabolic health after loss of ovarian function.

Loss of ovarian function imparts increased susceptibility to obesity and metabolic disease. These effects are largely attributed to decreased estradiol (E2), but the role of increased follicle-stimulating hormone (FSH) in modulating energy balance has not been fully investigated. Previous work that blocked FSH binding to its receptor in mice suggested this hormone may play a part in modulating body weight and energy expenditure after ovariectomy (OVX). We used an alternate approach to isolate the individual and combined contributions of FSH and E2 in mediating energy imbalance and changes in tissue-level metabolic health. Female Wistar rats were ovariectomized and given the gonadotropin releasing hormone (GnRH) antagonist degarelix to suppress FSH production. E2 and FSH were then added back individually and in combination for a period of 3 wk. Energy balance, body mass composition, and transcriptomic profiles of individual tissues were obtained. In contrast to previous studies, suppression and replacement of FSH in our paradigm had no effect on body weight, body composition, food intake, or energy expenditure. We did, however, observe organ-specific effects of FSH that produced unique transcriptomic signatures of FSH in retroperitoneal white adipose tissue. These included reductions in biological processes related to lipogenesis and carbohydrate transport. In addition, rats administered FSH had reduced liver triglyceride concentration (P < 0.001), which correlated with FSH-induced changes at the transcriptomic level. Although not appearing to modulate energy balance after loss of ovarian function in rats, FSH may still impart tissue-specific effects in the liver and white adipose tissue that might affect the metabolic health of those organs.NEW & NOTEWORTHY We find no effect of follicle-stimulating hormone (FSH) on energy balance using a novel model in which rats are ovariectomized, subjected to gonadotropin-releasing hormone antagonism, and systematically given back FSH by osmotic pump. However, tissue-specific effects of FSH on adipose tissue and liver were observed in this study. These include unique transcriptomic signatures induced by the hormone and a stark reduction in hepatic triglyceride accumulation.

Integrated image and sensor-based food intake detection in free-living.

The first step in any dietary monitoring system is the automatic detection of eating episodes. To detect eating episodes, either sensor data or images can be used, and either method can result in false-positive detection. This study aims to reduce the number of false positives in the detection of eating episodes by a wearable sensor, Automatic Ingestion Monitor v2 (AIM-2). Thirty participants wore the AIM-2 for two days each (pseudo-free-living and free-living). The eating episodes were detected by three methods: (1) recognition of solid foods and beverages in images captured by AIM-2; (2) recognition of chewing from the AIM-2 accelerometer sensor; and (3) hierarchical classification to combine confidence scores from image and accelerometer classifiers. The integration of image- and sensor-based methods achieved 94.59% sensitivity, 70.47% precision, and 80.77% F1-score in the free-living environment, which is significantly better than either of the original methods (8% higher sensitivity). The proposed method successfully reduces the number of false positives in the detection of eating episodes.

Distribution of dim light melatonin offset (DLMOff) and phase relationship to waketime in healthy adults and associations with chronotype.

OBJECTIVES: Dim light melatonin onset, or the rise in melatonin levels representing the beginning of the biological night, is the gold standard indicator of circadian phase. Considerably less is known about dim light melatonin offset, or the decrease in melatonin to low daytime levels representing the end of the biological night. In the context of insufficient sleep, morning circadian misalignment, or energy intake after waketime but before dim light melatonin offset, is linked to impaired insulin sensitivity, suggesting the need to characterize dim light melatonin offset and identify risk for morning circadian misalignment. METHODS: We examined the distributions of dim light melatonin offset clock hour and the phase relationship between dim light melatonin offset and waketime, and associations between dim light melatonin offset, phase relationship, and chronotype in healthy adults (N = 62) who completed baseline protocols measuring components of the circadian melatonin rhythm and chronotype. RESULTS: 74.4% demonstrated dim light melatonin offset after waketime, indicating most healthy adults wake up before the end of biological night. Later chronotype (morningness-eveningness, mid-sleep on free days corrected, and average mid-sleep) was associated with later dim light melatonin offset clock hour. Later chronotype was also associated with a larger, positive phase relationship between dim light melatonin offset and waketime, except for morningness-eveningness. CONCLUSIONS: These findings suggest morning circadian misalignment risk among healthy adults, which would not be detected if only dim light melatonin onset were assessed. Chronotype measured by sleep timing may better predict this risk in healthy adults keeping a consistent sleep schedule than morningness-eveningness preferences. Additional research is needed to develop circadian biomarkers to predict dim light melatonin offset and evaluate appropriate dim light melatonin offset timing to promote health.

Randomization to a Provided Higher-Complex-Carbohydrate Versus Conventional Diet in Gestational Diabetes Mellitus Results in Similar Newborn Adiposity.

OBJECTIVE: Nutrition therapy for gestational diabetes mellitus (GDM) has conventionally focused on carbohydrate restriction. In a randomized controlled trial (RCT), we tested the hypothesis that a diet (all meals provided) with liberalized complex carbohydrate (60%) and lower fat (25%) (CHOICE diet) could improve maternal insulin resistance and 24-h glycemia, resulting in reduced newborn adiposity (NB%fat; powered outcome) versus a conventional lower-carbohydrate (40%) and higher-fat (45%) (LC/CONV) diet. RESEARCH DESIGN AND METHODS: After diagnosis (at ∼28-30 weeks' gestation), 59 women with diet-controlled GDM (mean ± SEM; BMI 32 ± 1 kg/m2) were randomized to a provided LC/CONV or CHOICE diet (BMI-matched calories) through delivery. At 30-31 and 36-37 weeks of gestation, a 2-h, 75-g oral glucose tolerance test (OGTT) was performed and a continuous glucose monitor (CGM) was worn for 72 h. Cord blood samples were collected at delivery. NB%fat was measured by air displacement plethysmography (13.4 ± 0.4 days). RESULTS: There were 23 women per group (LC/CONV [214 g/day carbohydrate] and CHOICE [316 g/day carbohydrate]). For LC/CONV and CHOICE, respectively (mean ± SEM), NB%fat (10.1 ± 1 vs. 10.5 ± 1), birth weight (3,303 ± 98 vs. 3,293 ± 81 g), and cord C-peptide levels were not different. Weight gain, physical activity, and gestational age at delivery were similar. At 36-37 weeks of gestation, CGM fasting (86 ± 3 vs. 90 ± 3 mg/dL), 1-h postprandial (119 ± 3 vs. 117 ± 3 mg/dL), 2-h postprandial (106 ± 3 vs. 108 ± 3 mg/dL), percent time in range (%TIR; 92 ± 1 vs. 91 ± 1), and 24-h glucose area under the curve values were similar between diets. The %time >120 mg/dL was statistically higher (8%) in CHOICE, as was the nocturnal glucose AUC; however, nocturnal %TIR (63-100 mg/dL) was not different. There were no between-group differences in OGTT glucose and insulin levels at 36-37 weeks of gestation. CONCLUSIONS: A ∼100 g/day difference in carbohydrate intake did not result in between-group differences in NB%fat, cord C-peptide level, maternal 24-h glycemia, %TIR, or insulin resistance indices in diet-controlled GDM.

I2N: image to nutrients, a sensor guided semi-automated tool for annotation of images for nutrition analysis of eating episodes.

Introduction: Dietary assessment is important for understanding nutritional status. Traditional methods of monitoring food intake through self-report such as diet diaries, 24-hour dietary recall, and food frequency questionnaires may be subject to errors and can be time-consuming for the user. Methods: This paper presents a semi-automatic dietary assessment tool we developed - a desktop application called Image to Nutrients (I2N) - to process sensor-detected eating events and images captured during these eating events by a wearable sensor. I2N has the capacity to offer multiple food and nutrient databases (e.g., USDA-SR, FNDDS, USDA Global Branded Food Products Database) for annotating eating episodes and food items. I2N estimates energy intake, nutritional content, and the amount consumed. The components of I2N are three-fold: 1) sensor-guided image review, 2) annotation of food images for nutritional analysis, and 3) access to multiple food databases. Two studies were used to evaluate the feasibility and usefulness of I2N: 1) a US-based study with 30 participants and a total of 60 days of data and 2) a Ghana-based study with 41 participants and a total of 41 days of data). Results: In both studies, a total of 314 eating episodes were annotated using at least three food databases. Using I2N's sensor-guided image review, the number of images that needed to be reviewed was reduced by 93% and 85% for the two studies, respectively, compared to reviewing all the images. Discussion: I2N is a unique tool that allows for simultaneous viewing of food images, sensor-guided image review, and access to multiple databases in one tool, making nutritional analysis of food images efficient. The tool is flexible, allowing for nutritional analysis of images if sensor signals aren't available.

The spectrum of eating environments encountered in free living adults documented using a passive capture food intake wearable device.

Introduction: The aim of this feasibility and proof-of-concept study was to examine the use of a novel wearable device for automatic food intake detection to capture the full range of free-living eating environments of adults with overweight and obesity. In this paper, we document eating environments of individuals that have not been thoroughly described previously in nutrition software as current practices rely on participant self-report and methods with limited eating environment options. Methods: Data from 25 participants and 116 total days (7 men, 18 women, Mage = 44 ± 12 years, BMI 34.3 ± 5.2 kg/mm2), who wore the passive capture device for at least 7 consecutive days (≥12h waking hours/d) were analyzed. Data were analyzed at the participant level and stratified amongst meal type into breakfast, lunch, dinner, and snack categories. Out of 116 days, 68.1% included breakfast, 71.5% included lunch, 82.8% included dinner, and 86.2% included at least one snack. Results: The most prevalent eating environment among all eating occasions was at home and with one or more screens in use (breakfast: 48.1%, lunch: 42.2%, dinner: 50%, and snacks: 55%), eating alone (breakfast: 75.9%, lunch: 89.2%, dinner: 74.3%, snacks: 74.3%), in the dining room (breakfast: 36.7%, lunch: 30.1%, dinner: 45.8%) or living room (snacks: 28.0%), and in multiple locations (breakfast: 44.3%, lunch: 28.8%, dinner: 44.8%, snacks: 41.3%). Discussion: Results suggest a passive capture device can provide accurate detection of food intake in multiple eating environments. To our knowledge, this is the first study to classify eating occasions in multiple eating environments and may be a useful tool for future behavioral research studies to accurately codify eating environments.

Long-Term Retention of Young Adult Study Participants with Youth-Onset Type 2 Diabetes: Results from the TODAY2 Study.

INTRODUCTION: The Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) trial examined the effects of three treatment arms in a group of racially and ethnically diverse adolescents and youth with type 2 diabetes mellitus. TODAY2 was an observational follow-up study reporting outcomes and complications in these participants after having diabetes for approximately 13 years. Participant retention was essential to fulfill this objective. This report describes the motivations and problems participants self-reported related to continuing in this study. METHODS: The TODAY2 retention survey was administered to participants with a mean age of 27 years, 36% non-Hispanic black, 18% non-Hispanic white, 39% Hispanic, 52% public, and 35% private healthcare coverage, who completed the last study visit (63.8% of original TODAY cohort). The survey listed potential benefits and barriers to staying in the trial. Participants indicated agreement or disagreement with each statement using a four-point Likert-type scale. RESULTS: More than 93% of survey responders agreed with the benefits listed for staying in TODAY2. The most cited reason for staying in the study was related to the strong relationship that participants had with study staff. The common barriers to attending trial visits were tending to other medical problems, fear of disappointing study staff, and school/work scheduling conflicts. Participants with public healthcare coverage were more likely to endorse benefits related to diabetes care (e.g., getting the latest test results, staying motivated to care for my diabetes) and monetary compensation, whereas participants with poor glycemic control cited that a barrier to attending study visits was "fear of disappointing" study staff. CONCLUSION: In a racially and ethnically diverse population of youth-onset type 2 diabetes, benefits and barriers associated with long-term retention are described. These findings can be used to help inform future retention strategies for young adults in clinical trials.

Energy intake estimation using a novel wearable sensor and food images in a laboratory (pseudo-free-living) meal setting: quantification and contribution of sources of error.

OBJECTIVES: Dietary assessment methods not relying on self-report are needed. The Automatic Ingestion Monitor 2 (AIM-2) combines a wearable camera that captures food images with sensors that detect food intake. We compared energy intake (EI) estimates of meals derived from AIM-2 chewing sensor signals, AIM-2 images, and an internet-based diet diary, with researcher conducted weighed food records (WFR) as the gold standard. SUBJECTS/METHODS: Thirty adults wore the AIM-2 for meals self-selected from a university food court on one day in mixed laboratory and free-living conditions. Daily EI was determined from a sensor regression model, manual image analysis, and a diet diary and compared with that from WFR. A posteriori analysis identified sources of error for image analysis and WFR differences. RESULTS: Sensor-derived EI from regression modeling (R2 = 0.331) showed the closest agreement with EI from WFR, followed by diet diary estimates. EI from image analysis differed significantly from that by WFR. Bland-Altman analysis showed wide limits of agreement for all three test methods with WFR, with the sensor method overestimating at lower and underestimating at higher EI. Nutritionist error in portion size estimation and irreconcilable differences in portion size between food and nutrient databases used for WFR and image analyses were the greatest contributors to image analysis and WFR differences (44.4% and 44.8% of WFR EI, respectively). CONCLUSIONS: Estimation of daily EI from meals using sensor-derived features offers a promising alternative to overcome limitations of self-report. Image analysis may benefit from computerized analytical procedures to reduce identified sources of error.

A Naturalistic Actigraphic Assessment of Changes in Adolescent Sleep, Light Exposure, and Activity Before and During COVID-19.

The majority of high school-aged adolescents obtain less than the recommended amount of sleep per night, in part because of imposed early school start times. Utilizing a naturalistic design, the present study evaluated changes in objective measurements of sleep, light, and physical activity before (baseline) and during the first wave of the COVID-19 pandemic (during COVID-19) in a group of US adolescents. Sixteen adolescents (aged 15.9 ± 1.2 years, 68.8% female) wore an actigraphy monitor for 7 consecutive days during an in-person week of school before the pandemic (October 2018-February 2020) and again during the pandemic when instruction was performed virtually (May 2020). Delayed weekday sleep onset times of 1.66 ± 1.33 h (p < 0.001) and increased sleep duration of 1 ± 0.87 h (p < 0.001) were observed during COVID-19 compared with baseline. Average lux was significantly higher during COVID-19 compared with baseline (p < 0.001). Weekday physical activity parameters were not altered during COVID-19 compared with baseline, except for a delay in the midpoint of the least active 5 h (p value = 0.044). This analysis provides insight into how introducing flexibility into the traditional school schedule might influence sleep in adolescents.

Body mass index and variability in meal duration and association with rate of eating.

Background: A fast rate of eating is associated with a higher risk for obesity but existing studies are limited by reliance on self-report and the consistency of eating rate has not been examined across all meals in a day. The goal of the current analysis was to examine associations between meal duration, rate of eating, and body mass index (BMI) and to assess the variance of meal duration and eating rate across different meals during the day. Methods: Using an observational cross-sectional study design, non-smoking participants aged 18-45 years (N = 29) consumed all meals (breakfast, lunch, and dinner) on a single day in a pseudo free-living environment. Participants were allowed to choose any food and beverages from a University food court and consume their desired amount with no time restrictions. Weighed food records and a log of meal start and end times, to calculate duration, were obtained by a trained research assistant. Spearman's correlations and multiple linear regressions examined associations between BMI and meal duration and rate of eating. Results: Participants were 65% male and 48% white. A shorter meal duration was associated with a higher BMI at breakfast but not lunch or dinner, after adjusting for age and sex (p = 0.03). Faster rate of eating was associated with higher BMI across all meals (p = 0.04) and higher energy intake for all meals (p < 0.001). Intra-individual rates of eating were not significantly different across breakfast, lunch, and dinner (p = 0.96). Conclusion: Shorter beakfast and a faster rate of eating across all meals were associated with higher BMI in a pseudo free-living environment. An individual's rate of eating is constant over all meals in a day. These data support weight reduction interventions focusing on the rate of eating at all meals throughout the day and provide evidence for specifically directing attention to breakfast eating behaviors.

Improvement of Methodology for Manual Energy Intake Estimation From Passive Capture Devices.

Objective: To describe best practices for manual nutritional analyses of data from passive capture wearable devices in free-living conditions. Method: 18 participants (10 female) with a mean age of 45 ± 10 years and mean BMI of 34.2 ± 4.6 kg/m2 consumed usual diet for 3 days in a free-living environment while wearing an automated passive capture device. This wearable device facilitates capture of images without manual input from the user. Data from the first nine participants were used by two trained nutritionists to identify sources contributing to inter-nutritionist variance in nutritional analyses. The nutritionists implemented best practices to mitigate these sources of variance in the next nine participants. The three best practices to reduce variance in analysis of energy intake (EI) estimation were: (1) a priori standardized food selection, (2) standardized nutrient database selection, and (3) increased number of images captured around eating episodes. Results: Inter-rater repeatability for EI, using intraclass correlation coefficient (ICC), improved by 0.39 from pre-best practices to post-best practices (0.14 vs 0.85, 95% CI, respectively), Bland-Altman analysis indicated strongly improved agreement between nutritionists for limits of agreement (LOA) post-best practices. Conclusion: Significant improvement of ICC and LOA for estimation of EI following implementation of best practices demonstrates that these practices improve the reproducibility of dietary analysis from passive capture device images in free-living environments.

Preventing ovariectomy-induced weight gain decreases tumor burden in rodent models of obesity and postmenopausal breast cancer.

BACKGROUND: Obesity and adult weight gain are linked to increased breast cancer risk and poorer clinical outcomes in postmenopausal women, particularly for hormone-dependent tumors. Menopause is a time when significant weight gain occurs in many women, and clinical and preclinical studies have identified menopause (or ovariectomy) as a period of vulnerability for breast cancer development and promotion. METHODS: We hypothesized that preventing weight gain after ovariectomy (OVX) may be sufficient to prevent the formation of new tumors and decrease growth of existing mammary tumors. We tested this hypothesis in a rat model of obesity and carcinogen-induced postmenopausal mammary cancer and validated our findings in a murine xenograft model with implanted human tumors. RESULTS: In both models, preventing weight gain after OVX significantly decreased obesity-associated tumor development and growth. Importantly, we did not induce weight loss in these animals, but simply prevented weight gain. In both lean and obese rats, preventing weight gain reduced visceral fat accumulation and associated insulin resistance. Similarly, the intervention decreased circulating tumor-promoting growth factors and inflammatory cytokines (i.e., BDNF, TNFα, FGF-2), with greater effects in obese compared to lean rats. In obese rats, preventing weight gain decreased adipocyte size, adipose tissue macrophage infiltration, reduced expression of the tumor-promoting growth factor FGF-1 in mammary adipose, and reduced phosphorylated FGFR indicating reduced FGF signaling in tumors. CONCLUSIONS: Together, these findings suggest that the underlying mechanisms associated with the anti-tumor effects of weight maintenance are multi-factorial, and that weight maintenance during the peri-/postmenopausal period may be a viable strategy for reducing obesity-associated breast cancer risk and progression in women.

ZnT8 autoantibody prevalence is low in youth with type 2 diabetes and associated with higher insulin sensitivity, lower insulin secretion, and lower disposition index.

Aim: ZnT8 autoantibody positivity (ZnT8+) is associated with risk for type 1 diabetes and with metabolic complications in adults. Our aim was to assess prevalence of ZnT8 + in the Treatment of T2D in Adolescents and Youth (TODAY) cohort and describe associated phenotypic outcomes. Methods: TODAY participants were 13.98 ± 2.03 years with a confirmed diagnosis of T2D, BMI percentile of 97.69 ± 3.32 (64% female), and GAD- and IA2- at baseline. ZnT8 autoantibodies were measured at baseline and end of study. Results: 3 of 687 participants (0.29%) were ZnT8 + and there was one conversion (0.15%) from ZnT8- to ZnT8 + during the study. ZnT8A + individuals had higher HbA1c, HDL and LDL cholesterol, and IL-1ß concentrations, and lower BMI, IL-6, and triglyceride concentrations compared to the TODAY cohort and ZnT8A- individuals. They also had higher insulin sensitivity with lower insulin secretion and disposition index, metabolically resembling T1D. All ZnT8 + participants experienced loss of glycemic control on randomized treatment, but exhibited lower rates of diabetic complications than other groups. Conclusion: Given the low rate of complications in ZnT8 + individuals, ZnT8 likely does not impact the clinical course of the disease in this population.

Clinical research reactivation during the COVID-19 pandemic: An academic center process and lessons for the future.

Background: Clinical research is a central mission of the University of Colorado Anschutz Medical Campus (CU-Anschutz). On March 18, 2020, due to rising COVID-19 rates and personal protective equipment (PPE) shortages, an emergency approval process for critical research essential to the care and safety of patients, including COVID-19 trials, was enacted. All other clinical research studies requiring face-to-face visits were placed on hold to protect participant and staff safety. Methods: A clinical research TaskForce was rapidly assembled, consisting of a cross- section of campus clinical research operations leaders, including affiliate hospitals. This group developed a guidance document and process where the primary prioritization factor was positive therapeutic benefit/risk (Groups 2-5). A REDCap form demarcating items including research visit types and safety plans was designed. A separate Space Plan Committee approval was required to gauge environmental health and safety. Results: A total of 654 protocols were approved over 31 weeks using this process. Group 2 review and approvals occurred within 5 days of campus reactivation, and 65 days after original clinical research hold. Groups 3 through 5 were opened for submission and review in a phased approach. The majority proactively submitted IRB protocol amendments to minimize face-to-face participant/staff contact. There were no cases of COVID-19 outbreak in research participants. Conclusion: Clinical research reactivation was rapidly implemented in a transparent, collaborative, broadly supported, and efficient process of staged reactivation while prioritizing the health and safety of participants and staff at CU-Anschutz. This model is practical and easily generalizable to other medical research campuses.

An exercise intervention alters stool microbiota and metabolites among older, sedentary adults.

BACKGROUND: Physiologic aging has been associated with gut dysbiosis. Although short exercise interventions have been linked to beneficial changes in gut microbiota in younger adults, limited data are available from older populations. We hypothesized that exercise would produce beneficial shifts in microbiota and short-chain fatty acid (SCFA) levels in older persons. METHODS: Stool samples were collected before and at completion of a supervised 24-week cardiovascular and resistance exercise intervention among 50-75-year-old participants. SCFA levels were analyzed by gas chromatography and microbiome by 16S rRNA gene sequencing. Negative binomial regression models compared pre- and post-differences using false discovery rates for multiple comparison. RESULTS: A total of 22 participants provided pre-intervention samples; 15 provided samples at study completion. At baseline, the majority of participants were men (95%), mean age 58.0 (8.8) years, mean body mass index 27.4 (6.4) kg/m2. After 24 weeks of exercise, at the genus level, exercise was associated with significant increases in Bifidobacterium (and other unidentified genera within Bifidobacteriaceae), Oscillospira, Anaerostipes, and decreased Prevotella and Oribacterium (p < 0.001). Stool butyrate increased with exercise [5.44 (95% confidence interval 1.54, 9.24) mmol/g, p = 0.02], though no significant differences in acetate or propionate (p ⩾ 0.09) were seen. CONCLUSION: Our pilot study suggested that an exercise intervention is associated with changes in the microbiome of older adults and a key bacterial metabolite, butyrate. Although some of these changes could potentially reverse age-related dysbiosis, future studies are required to determine the contribution of changes to the microbiome in the beneficial effect of exercise on overall health of older adults. Clinical Trials NCT02404792.

Bone turnover marker responses to sleep restriction and weekend recovery sleep.

BACKGROUND: Prior data demonstrated three weeks of sleep restriction and concurrent circadian disruption uncoupled bone turnover markers (BTMs), indicating decreased bone formation and no change or increased bone resorption. The effect of insufficient sleep with or without ad libitum weekend recovery sleep on BTMs is unknown. METHODS: BTMs were measured in stored serum from 20 healthy adults randomized to one of three study groups consisting of a control group (N = 3 men; 9 h/night) or one of two nocturnal sleep restriction groups in an inpatient laboratory environment. One Sleep Restriction group ("SR"; N = 9; 4 women) had 5 h sleep opportunity per night for nine nights. The other sleep restriction group had an opportunity for ad libitum Weekend Recovery sleep ("WR"; N = 8; 4 women) after four nights of 5 h sleep opportunity per night. Food intake was energy balanced at baseline and ad libitum thereafter. Fasted morning BTM levels and hourly 24 h melatonin levels were obtained on study days 3 (baseline), 5 (after 1 night of sleep restriction for WR and SR), and 11 (after a sleep restricted workweek with weekend recovery sleep in WR or 7 nights of sleep restriction in SR). Linear mixed-effects modeling was used to examine the effect of study duration (e.g., change over time), study condition, age, and sex on BTMs. Pearson correlations were used to determine associations between changes in BTMs and changes in weight and morning circadian misalignment (i.e., duration of high melatonin levels after wake time). RESULTS: There was no significant difference between the three study groups in change over time (p ≥ 0.4 for interaction between assigned group and time for all BTMs), adjusted for age and sex. There was no significant change in N-terminal propeptide of procollagen type I (P1NP), osteocalcin, or C-telopeptide of type I collagen (CTX) from baseline to day 11 (all p ≥ 0.3). In women <25 years old, there was a non-significant decline in P1NP from day 3 to day 5 (= -15.74 ± 7.80 ng/mL; p = 0.06). Change in weight and morning circadian misalignment from baseline to day 11 were correlated with statistically non-significant changes in BTMs (all p ≤ 0.05). CONCLUSION: In this small secondary analysis, we showed that nine nights of prescribed sleep restriction with or without weekend recovery sleep and ad libitum food intake did not alter BTMs. It is possible that age, sex, weight change and morning circadian misalignment modify the effects of sleep restriction on bone metabolism.

Effects of ad libitum food intake, insufficient sleep and weekend recovery sleep on energy balance.

STUDY OBJECTIVES: Insufficient sleep is believed to promote positive energy balance (EB) and weight gain. Increasing weekend sleep duration to "recover" from weekday sleep loss is common, yet little is known regarding how weekend recovery sleep influences EB. We conducted a randomized controlled trial to assess how: (1) 2 days and 8 days of insufficient sleep and (2) ad libitum weekend recovery sleep impact EB (energy intake [EI] - energy expenditure [EE]). METHODS: Following ten baseline days with 9 h per night sleep opportunities, participants completed one of three 10-day experimental protocols with ad libitum EI: control (9 h sleep opportunities; n = 8; 23 ± 5 years [mean ± SD]); sleep restriction (SR; 5 h sleep opportunities; n = 14; 25 ± 5 years); sleep restriction with weekend recovery sleep (SR + WR; 5 days insufficient sleep, 2 days ad libitum weekend recovery sleep, 3 days recurrent insufficient sleep; n = 14; 27 ± 4 years). RESULTS: Twenty-four hour EB increased (p < 0.001; main effect) by an average of 797.7 ± 96.7 (±SEM) kcal during the 10-day experimental protocol versus baseline with no significant differences between groups. Percent change from baseline in 24 h-EE was higher (p < 0.05) on day 2 of insufficient sleep (SR and SR + WR groups; 10 ± 1%) versus adequate sleep (control group; 4 ± 3%). CONCLUSIONS: In this between-group study, the effects of adequate sleep and insufficient sleep, with or without or weekend recovery sleep, on 24 h-EB were similar. Examining EB and body weight changes using within-subject cross-over designs and "free-living" conditions outside the laboratory (e.g. sleep extension) are needed to advance our understanding of the links between insufficient sleep, weekend recovery sleep and weight-gain.

Systems Analysis of Gut Microbiome Influence on Metabolic Disease in HIV-Positive and High-Risk Populations.

Poor metabolic health, characterized by insulin resistance and dyslipidemia, is higher in people living with HIV and has been linked with inflammation, antiretroviral therapy (ART) drugs, and ART-associated lipodystrophy (LD). Metabolic disease is associated with gut microbiome composition outside the context of HIV but has not been deeply explored in HIV infection or in high-risk men who have sex with men (HR-MSM), who have a highly altered gut microbiome composition. Furthermore, the contribution of increased bacterial translocation and associated systemic inflammation that has been described in HIV-positive and HR-MSM individuals has not been explored. We used a multiomic approach to explore relationships between impaired metabolic health, defined using fasting blood markers, gut microbes, immune phenotypes, and diet. Our cohort included ART-treated HIV-positive MSM with or without LD, untreated HIV-positive MSM, and HR-MSM. For HIV-positive MSM on ART, we further explored associations with the plasma metabolome. We found that elevated plasma lipopolysaccharide binding protein (LBP) was the most important predictor of impaired metabolic health and network analysis showed that LBP formed a hub joining correlated microbial and immune predictors of metabolic disease. Taken together, our results suggest the role of inflammatory processes linked with bacterial translocation and interaction with the gut microbiome in metabolic disease among HIV-positive and -negative MSM.IMPORTANCE The gut microbiome in people living with HIV (PLWH) is of interest since chronic infection often results in long-term comorbidities. Metabolic disease is prevalent in PLWH even in well-controlled infection and has been linked with the gut microbiome in previous studies, but little attention has been given to PLWH. Furthermore, integrated analyses that consider gut microbiome, together with diet, systemic immune activation, metabolites, and demographics, have been lacking. In a systems-level analysis of predictors of metabolic disease in PLWH and men who are at high risk of acquiring HIV, we found that increased lipopolysaccharide-binding protein, an inflammatory marker indicative of compromised intestinal barrier function, was associated with worse metabolic health. We also found impaired metabolic health associated with specific dietary components, gut microbes, and host and microbial metabolites. This study lays the framework for mechanistic studies aimed at targeting the microbiome to prevent or treat metabolic endotoxemia in HIV-infected individuals.

Lipoprotein Lipase Overexpression in Skeletal Muscle Attenuates Weight Regain by Potentiating Energy Expenditure.

Moderate weight loss improves numerous risk factors for cardiometabolic disease; however, long-term weight loss maintenance (WLM) is often thwarted by metabolic adaptations that suppress energy expenditure and facilitate weight regain. Skeletal muscle has a prominent role in energy homeostasis; therefore, we investigated the effect of WLM and weight regain on skeletal muscle in rodents. In skeletal muscle of obesity-prone rats, WLM reduced fat oxidative capacity and downregulated genes involved in fat metabolism. Interestingly, even after weight was regained, genes involved in fat metabolism were also reduced. We then subjected mice with skeletal muscle lipoprotein lipase overexpression (mCK-hLPL), which augments fat metabolism, to WLM and weight regain and found that mCK-hLPL attenuates weight regain by potentiating energy expenditure. Irrespective of genotype, weight regain suppressed dietary fat oxidation and downregulated genes involved in fat metabolism in skeletal muscle. However, mCK-hLPL mice oxidized more fat throughout weight regain and had greater expression of genes involved in fat metabolism and lower expression of genes involved in carbohydrate metabolism during WLM and regain. In summary, these results suggest that skeletal muscle fat oxidation is reduced during WLM and regain, and therapies that improve skeletal muscle fat metabolism may attenuate rapid weight regain.