No effect of circulating leptin on energy metabolism in normal weight or overweight/obese lactating mothers: The case-control Breastmilk and the Link to Overweight/Obesity and Maternal diet (BLOOM) study.

BACKGROUND & AIMS: Pregnancy and lactation are associated with metabolic changes, including alterations in energy metabolism, which are closely linked to body mass and composition due to hormonal status. Therefore, the objective of this study was to investigate the energy metabolism in exclusively or predominantly breastfeeding mothers with normal weight (NW) and overweight/obesity (OW/OB) and evaluate its associations with fasting serum leptin. METHODS: This cross-sectional BLOOM study was conducted among 39 mothers (n = 19 NW, n = 20 OW/OB) in 15.5 ± 1.2 weeks of lactation. The leptin was analyzed in a blood sample using an enzyme-linked immunosorbent assay, body composition was analyzed by dual-energy X-ray absorptiometry, and resting metabolic rate (RMR) was measured by indirect calorimetry method. RESULTS: The average RMR for all groups was 1747.5 ± 281.9 kcal/d, with a statistically significant difference between groups (1932.7 ± 222.6 vs. 1550.5 ± 190.6, p < 0.001, respectively in the OW/OB and NW group). The OW/OB mothers had higher oxygen uptake (VO2) and exhaled carbon dioxide (VCO2), but not respiratory quotient (RQ), carbohydrate (CHO%) and lipid oxidation (FAT%). When analyzing correlations stratified by BMI category, we found that serum leptin was correlated with CHO% negatively, and with FAT% positively in the NW but not in OW/OB mothers. Additionally, serum leptin was a significant predictor of RMR, VCO2, VO2, CHO%, and RMR/kg of total body weight. However, after adjusting for confounders, the observed associations were no longer statistically significant (RMR: ß = 0.113, 95% CI -0.354-0.319; VO2: ß = 0.141, 95% CI -0.462-0.744; VCO2: ß = 0.238, 95% CI -0.411-0.888; CHO%: ß = -0.146, 95% CI -0.151-0.444; RMR/kg of total body weight: ß = -0.294, 95% CI -0.831-0.244). CONCLUSIONS: Our results did not support the hypothesis that leptin plays a role in regulating energy homeostasis during lactation.

Effect of Menstrual Cycle Phase and Hormonal Contraceptives on Resting Metabolic Rate and Body Composition.

The cyclical changes in sex hormones across the menstrual cycle (MC) are associated with various biological changes that may alter resting metabolic rate (RMR) and body composition estimates. Hormonal contraceptive (HC) use must also be considered given their impact on endogenous sex hormone concentrations and synchronous exogenous profiles. The purpose of this study was to determine if RMR and dual-energy X-ray absorptiometry body composition estimates change across the MC and differ compared with HC users. This was accomplished during a 5-week training camp involving naturally cycling athletes (n = 11) and HC users (n = 7 subdermal progestin implant, n = 4 combined monophasic oral contraceptive pill, n = 1 injection) from the National Rugby League Indigenous Women's Academy. MC phase was retrospectively confirmed via serum estradiol and progesterone concentrations and a positive ovulation test. HC users had serum estradiol and progesterone concentrations assessed at the time point of testing. Results were analyzed using general linear mixed model. There was no effect of MC phase on absolute RMR (p = .877), relative RMR (p = .957), or dual-energy X-ray absorptiometry body composition estimates (p > .05). There was no effect of HC use on absolute RMR (p = .069), relative RMR (p = .679), or fat mass estimates (p = .766), but HC users had a greater fat-free mass and lean body mass than naturally cycling athletes (p = .028). Our findings suggest that RMR and dual-energy X-ray absorptiometry body composition estimates do not significantly differ due to changes in sex hormones in a group of athletes, and measurements can be compared between MC phases or with HC usage without variations in sex hormones causing additional noise.

Metabolic and microbial changes in light-vented bulbul during recent northward range expansion.

Endotherms recently expanding to cold environments generally exhibit strong physiological acclimation to sustain high body temperature. During this process, gut microbes likely play a considerable role in host physiological functions, including digestion and thermogenesis. The light-vented bulbul Pycnonotus sinensis represents one such species. It used to be restricted to the Oriental realm but expanded its distribution range north to the Palearctic areas during the past few decades. Here, we explored the seasonal dynamics of the resting metabolic rate (RMR) and microbiota for local and newly colonized populations of the species. Our results showed that the mass-adjusted RMR and body mass were positively correlated with latitude variations in both seasons. Consistently, the gut microbiota showed a corresponding variation to the northern cold environments. In the two northern populations, the alpha diversity decreased compared with those of the two southern populations. Significant differences were detected in dominant phyla, such as Firmicutes, Bacteroidetes, Proteobacteria, and Desulfobacterota in both seasons. The core microbiota showed geographic differences in the winter, including the elevated relative abundance of 5 species in northern populations. Finally, to explore the link between microbial communities and host metabolic thermogenesis, we conducted a correlation analysis between microbiota and mass-adjusted RMR. We found that more genera were significantly correlated with mass-adjusted RMR in the wintering season compared to the breeding season (71 vs. 23). These results suggest that microbiota of the lighted-vented bulbul linked with thermogenesis in diversity and abundance under northward expansion.

Resting Metabolic Rate and Substrate Utilization during Energy and Protein Availability in Male and Female Athletes.

Active athletes frequently develop low energy (LEA) and protein availabilities (LPA) with consequent changes in the vital metabolic processes, especially resting metabolic rate (RMR) and substrate utilization. This study investigated the association of energy and protein intakes with RMR and substrate utilization in male and female athletes and those with LEA and LPA. Sixty athletes (35% female, 26.83 ± 7.12 y) were enrolled in this study. Anthropometric measurements and body composition analysis were reported to estimate fat-free mass (eFFM). Dietary intakes were recorded by two-day multiple-pass 24 h recall records and three-day food records and then analyzed by food processor software to calculate protein intake (PI) and energy intake (EI). Indirect calorimetry was used to measure RMR and percentages of substrate utilization. Activity-energy expenditure (AEE) was assessed by using an Actighrphy sensor for three days. Energy availability was calculated using the following formula (EA = EI - AEE/eFFM). The correlation of EI and PI with RMR and substrate utilization was tested with Pearson correlation. In the LEA group, both EI and PI correlated positively with RMR (r = 0.308, 0.355, respectively, p < 0.05). In addition, EI showed a positive correlation with the percentage of fat utilization. In the male and sufficient-PA groups, PI correlated positively with the RMR and negatively with the percentage of protein utilization. In conclusion, the percentage of LEA is markedly prevalent in our sample, with a higher prevalence among males. Athletes with LEA had lower fat utilization and lower RMR, while those with sufficient PA showed lower protein utilization with excessive PI. These findings may explain the metabolic responses in the cases of LEA and LPA.

The Power of the Heterogeneous Stock Rat Founder Strains in Modeling Metabolic Disease.

Metabolic diseases are a host of complex conditions, including obesity, diabetes mellitus, and metabolic syndrome. Endocrine control systems (eg, adrenals, thyroid, gonads) are causally linked to metabolic health outcomes. N/NIH Heterogeneous Stock (HS) rats are a genetically heterogeneous outbred population developed for genetic studies of complex traits. Genetic mapping studies in adult HS rats identified loci associated with cardiometabolic risks, such as glucose intolerance, insulin resistance, and increased body mass index. This study determined underappreciated metabolic health traits and the associated endocrine glands within available substrains of the HS rat founders. We hypothesize that the genetic diversity of the HS rat founder strains causes a range of endocrine health conditions contributing to the diversity of cardiometabolic disease risks. ACI/EurMcwi, BN/NHsdMcwi, BUF/MnaMcwi, F344/StmMcwi, M520/NRrrcMcwi, and WKY/NCrl rats of both sexes were studied from birth until 13 weeks of age. Birth weight was recorded, body weight was measured weekly, metabolic characteristics were assessed, and blood and tissues were collected. Our data show wide variation in endocrine traits and metabolic health states in ACI, BN, BUF, F344, M520, and WKY rat strains. This is the first report to compare birth weight, resting metabolic rate, endocrine gland weight, hypothalamic-pituitary-thyroid axis hormones, and brown adipose tissue weight in these rat strains. Importantly, this work unveils new potential for the HS rat population to model early life adversity and adrenal and thyroid pathophysiology. The HS population likely inherited risk alleles for these strain-specific traits, making the HS rat a powerful model to investigate interventions on endocrine and metabolic health.

Gene regulation of RMR-related DNAJC6 on adipogenesis and mitochondria function in 3T3-L1 preadipocytes.

In the pilot GWAS of children obesity, DNAJC6 gene was found as a regulator for resting metabolic rate (RMR) and obesity in children aged 8-9 years. To investigate whether DNAJC6 gene regulated obesity and energy metabolism, the physiological mechanisms during adipogenesis of 3T3-L1 preadipocytes were confirmed after DNAJC6 gene was overexpressed or inhibited. Overexpressing DNAJC6 gene maintained a 3T3-L1 preadipocyte status during cell differentiation (MTT, ORO, DAPI/BODIPY). It suppressed adipogenesis and adipokine production (leptin, adiponectin), insulin signaling with IRS-GLUT4 system (RT-PCR, Western blotting), and mitochondrial function (Mito Stress Test). DNAJC6 overexpressed cells inhibited mTOR expression, but maintained LC3 expression at a high level, indicating that autophagy occurred and energy was obtained. However, when DNAJC6 gene was inhibited, fat synthesis factor was highly expressed during differentiation (PPARr, C/EBPa, aP2, etc) and the intracellular stress level increased accordingly, which affected the reduction of reserve respiratory capacity during mitochondrial respiration. Our study confirmed gene regulation of DNAJC6, overexpression or inhibition, affects adipogenesis with energy metabolism and mitochondrial functions. This basic data can be used for clinic obesity studies to control an energy imbalance.

Development and validation of new predictive equations for the resting metabolic rate of older adults aged ≥65 y.

BACKGROUND: The aging process alters the resting metabolic rate (RMR), but it still accounts for 50%-70% of the total energy needs. The rising proportion of older adults, especially those over 80 y of age, underpins the need for a simple, rapid method to estimate the energy needs of older adults. OBJECTIVES: This research aimed to generate and validate new RMR equations specifically for older adults and to report their performance and accuracy. METHODS: Data were sourced to form an international dataset of adults aged ≥65 y (n = 1686, 38.5% male) where RMR was measured using the reference method of indirect calorimetry. Multiple regression was used to predict RMR from age (y), sex, weight (kg), and height (cm). Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split and leave one out cross-validation were performed. The newly generated prediction equations were compared with the existing commonly used equations. RESULTS: The new prediction equation for males and females aged ≥65 y had an overall improved performance, albeit marginally, when compared with the existing equations. It is described as follows: RMR (kJ/d) = 31.524 × W (kg) + 25.851 × H (cm) - 24.432 × Age (y) + 486.268 × Sex (M = 1, F = 0) + 530.557. Equations stratified by age (65-79.9 y and >80 y) and sex are also provided. The newly created equation estimates RMR within a population mean prediction bias of ∼50 kJ/d (∼1%) for those aged ≥65 y. Accuracy was reduced in adults aged ≥80 y (∼100 kJ/d, ∼2%) but was still within the clinically acceptable range for both males and females. Limits of agreement indicated a poorer performance at an individual level with 1.96-SD limits of approximately ±25%. CONCLUSIONS: The new equations, using simple measures of weight, height, and age, improved the accuracy in the prediction of RMR in populations in clinical practice. However, no equation performs optimally at the individual level.

Trends in measuring BMR and RMR after spinal cord injury: a comprehensive review.

Studying factors that contribute to our understanding of maintaining normal energy balance are of paramount significance following spinal cord injury (SCI). Accurate determination of energy needs is crucial for providing nutritional guidance and managing the increasing prevalence of malnutrition or obesity after SCI. BMR represents 75-80 % of the total energy expenditure in persons with SCI. Accurately measuring BMR is an important component for calculating total energetic needs in this population. Indirect calorimetry is considered the gold-standard technique for measuring BMR. However, technical challenges may limit its applications in large cohort studies and alternatively rely on prediction equations. Previous work has shown that BMR changes in response to disuse and exercise in the range of 15-120 %. Factors including sex, level of injury and type of assistive devices may influence BMR after SCI. RMR is erroneously used interchangeably for BMR, which may result in overestimation of energetic intake when developing nutritional plans. To address this concern, we comprehensively reviewed studies that conducted BMR (n=15) and RMR (n=22) in persons with SCI. The results indicated that RMR is 9 % greater than BMR in persons with SCI. Furthermore, the SCI-specific prediction equations that incorporated measures of fat-free mass appeared to accurately predict BMR. Overall, the current findings highlighted the significance of measuring BMR as well as encouraging the research and clinical community to effectively establish countermeasures to combat obesity after SCI.

Longitudinal Changes in Body Composition and Resting Metabolic Rate in Male Professional Flat Jockeys: Preliminary Outcomes and Implications for Future Research Directions.

Jockeys are unique given that they make weight daily and, therefore, often resort to fasting and dehydration. Through increasing daily food frequency (during energy deficit), we have reported short-term improvements in jockey's body composition. While these changes were observed over 6-12 weeks with food provided, it is unclear whether such improvements can be maintained over an extended period during free-living conditions. We, therefore, assessed jockeys over 5 years using dual X-ray absorptiometry, resting metabolic rate, and hydration measurements. Following dietary and exercise advice, jockeys reduced fat mass from baseline of 7.1 ± 1.4 kg to 6.1 ± 0.7 kg and 6.1 ± 0.6 kg (p < .001) at Years 1 and 5, respectively. In addition, fat-free mass was maintained with resting metabolic rate increasing significantly from 1,500 ± 51 kcal/day at baseline to 1,612 ± 95 kcal/day and 1,620 ± 92 kcal/day (p < .001) at Years 1 and 5, respectively. Urine osmolality reduced from 816 ± 236 mOsmol/L at baseline to 564 ± 175 mOsmol/L and 524 ± 156 mOsmol/L (p < .001) at Years 1 and 5, respectively. The percent of jockeys consuming a regular breakfast significantly increased from 48% at baseline to 83% (p = .009) and 87% (p = .003) at Years 1 and 5, alongside regular lunch from 35% to 92% (p < .001) and 96% (p < .001) from baseline to Years 1 and 5, respectively. In conclusion, we report that improved body composition can be maintained in free-living jockeys over a 5-year period when appropriate guidance has been provided.

Revised Harris-Benedict Equation: New Human Resting Metabolic Rate Equation.

This paper contains a revision of the Harris-Benedict equations through the development and validation of new equations for the estimation of resting metabolic rate (RMR) in normal, overweight, and obese adult subjects, taking into account the same anthropometric parameters. A total of 722 adult Caucasian subjects were enrolled in this analysis. After taking a detailed medical history, the study enrolled non-hospitalized subjects with medically and nutritionally controlled diseases such as diabetes mellitus, cardiovascular disease, and thyroid disease, excluding subjects with active infections and pregnant or lactating women. Measurement of somatometric characteristics and indirect calorimetry were performed. The values obtained from RMR measurement were compared with the values of the new equations and the Harris-Benedict, Mifflin-St Jeor, FAO/WHO/UNU, and Owen equations. New predictive RMR equations were developed using age, body weight, height, and sex parameters. RMR males: (9.65 × weight in kg) + (573 × height in m) - (5.08 × age in years) + 260; RMR females: (7.38 × weight in kg) + (607 × height in m) - (2.31 × age in years) + 43; RMR males: (4.38 × weight in pounds) + (14.55 × height in inches) - (5.08 × age in years) + 260; RMR females: (3.35 × weight in pounds) + (15.42 × height in inches) - (2.31 × age in years) + 43. The accuracy of the new equations was tested in the test group in both groups, in accordance with the resting metabolic rate measurements. The new equations showed more accurate results than the other equations, with the equation for men (R-squared: 0.95) showing better prediction than the equation for women (R-squared: 0.86). The new equations showed good accuracy at both group and individual levels, and better reliability compared to other equations using the same anthropometric variables as predictors of RMR. The new equations were created under modern obesogenic conditions, and do not exclude individuals with regulated (dietary or pharmacological) Westernized diseases (e.g., cardiovascular disease, diabetes, and thyroid disease).