1
|
Griffith GJ, Wang AP, Liem RI, Carr MR, Corson T, Ward K. A Reference Equation for Peak Oxygen Uptake for Pediatric Patients Who Undergo Treadmill Cardiopulmonary Exercise Testing. Am J Cardiol 2024; 212:41-47. [PMID: 38042265 DOI: 10.1016/j.amjcard.2023.11.061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/02/2023] [Accepted: 11/21/2023] [Indexed: 12/04/2023]
Abstract
Pediatric patients are often referred to cardiopulmonary exercise testing (CPET) laboratories for assessment of exercise-related symptoms. For clinicians to understand results in the context of performance relative to peers, adequate fitness-based prediction equations must be available. However, reference equations for prediction of peak oxygen uptake (VO2peak) in pediatrics are largely developed from field-based testing, and equations derived from CPET are primarily developed using adult data. Our objective was to develop a pediatric reference equation for VO2peak. Clinical CPET data from a validation cohort of 1,383 pediatric patients aged 6 to 18 years who achieved a peak respiratory exchange ratio ≥1.00 were analyzed to identify clinical and exercise testing factors that contributed to the prediction of VO2peak from tests performed using the Bruce protocol. The resultant prediction equation was applied to a cross-validation cohort of 1,367 pediatric patients. Exercise duration, gender, weight, and age contributed to the prediction of VO2peak, generating the following prediction equation: (R2 = 0.645, p <0.001, standard error of the estimate = 6.19 ml/kg/min): VO2peak (ml/kg/min) =16.411+ 3.423 (exercise duration [minutes]) - 5.145 (gender [0 = male, 1 = female]) - 0.121 (weight [kg]) + 0.179 (age [years]). This equation was stable across the age range included in the present study, with differences ≤0.5 ml/kg/min between mean measured and predicted VO2peak in all age groups. In conclusion, this study represents what we believe is the largest pediatric CPET-derived VO2peak prediction effort to date, and this VO2peak prediction equation provides clinicians who perform and interpret exercise tests in pediatric patients with a resource with which to better quantify fitness when CPET is not available.
Collapse
Affiliation(s)
- Garett J Griffith
- Northwestern University Feinberg School of Medicine, Chicago, Illinois.
| | - Alan P Wang
- Northwestern University Feinberg School of Medicine, Chicago, Illinois; Division of Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois
| | - Robert I Liem
- Northwestern University Feinberg School of Medicine, Chicago, Illinois; Division of Hematology, Oncology, and Stem Cell Transplantation, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois
| | - Michael R Carr
- Northwestern University Feinberg School of Medicine, Chicago, Illinois; Division of Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois
| | - Tyler Corson
- Rush University College of Health Sciences, Chicago, Illinois
| | - Kendra Ward
- Northwestern University Feinberg School of Medicine, Chicago, Illinois; Division of Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois
| |
Collapse
|
2
|
Vargas-Molina S, Bonilla DA, Petro JL, Carbone L, García-Sillero M, Jurado-Castro JM, Schoenfeld BJ, Benítez-Porres J. Efficacy of progressive versus severe energy restriction on body composition and strength in concurrent trained women. Eur J Appl Physiol 2023; 123:1311-1321. [PMID: 36802029 DOI: 10.1007/s00421-023-05158-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 01/25/2023] [Indexed: 02/19/2023]
Abstract
PURPOSE This study evaluated the concurrent training (CT) effect in combination with either progressive energy restriction (PER) or severe energy restriction (SER) on body composition and strength-related variables in resistance-trained women. METHODS Fourteen women (29.5 ± 3.8 years; 23.8 ± 2.8 kg·m-2) were randomly assigned to a PER (n = 7) or SER (n = 7) group. Participants performed an 8-week CT program. Pre- and post-intervention measures of fat mass (FM) and fat-free mass (FFM) were assessed by dual-energy X-ray absorptiometry and strength-related variables were assessed through 1-repetition maximum (in the squat and bench press) and countermovement jump. RESULTS Significant reductions in FM were observed in PER and SER (Δ = - 1.7 ± 0.4 kg; P = < 0.001; ES = - 0.39 and Δ = - 1.2 ± 0.6 kg; P = 0.002; ES = - 0.20, respectively). After correcting FFM for fat-free adipose tissue (FFAT), no significant differences for this variable were found either in PER (Δ = - 0.3 ± 0.1; P = 0.071; ES = - 0.06) or in SER (Δ = - 0.2 ± 0.1; P = 0.578; ES = - 0.04). There were no significant changes in the strength-related variables. No between-group differences were found in any of the variables. CONCLUSION A PER has similar effects to a SER on body composition and strength in resistance-trained women performing a CT program. Given that PER is more flexible and thus may enhance dietary adherence, it might be a better alternative for FM reduction compared to SER.
Collapse
Affiliation(s)
- Salvador Vargas-Molina
- Physical Education and Sports Area, Faculty of Medicine, University of Málaga, Bulevar Louis Pasteur, 25, 29010, Málaga, Spain.,EADE-University of Wales Trinity Saint David, Málaga, Spain
| | - Diego A Bonilla
- Research Division, Dynamical Business and Science Society-DBSS International SAS, Bogotá, Colombia.,Research Group in Physical Activity, Sports and Health Sciences, Universidad de Córdoba, Montería, Colombia.,Sport Genomics Research Group, Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), 48940, Leioa, Spain
| | - Jorge L Petro
- Research Division, Dynamical Business and Science Society-DBSS International SAS, Bogotá, Colombia.,Research Group in Physical Activity, Sports and Health Sciences, Universidad de Córdoba, Montería, Colombia
| | | | | | - José Manuel Jurado-Castro
- Metabolism and Investigation Unit, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004, Córdoba, Spain.,CIBERobn Physiopathology of Obesity and Nutrition, Centre of Biomedical Research Network, Institute of Health Carlos III, 28029, Madrid, Spain.,Osuna University School, Teaching Center Attached to the University of Seville, 41640, Seville, Spain
| | | | - Javier Benítez-Porres
- Physical Education and Sports Area, Faculty of Medicine, University of Málaga, Bulevar Louis Pasteur, 25, 29010, Málaga, Spain.
| |
Collapse
|
3
|
Sun Y, Cao X, Cao D, Cui Y, Su K, Jia Z, Wu Y, Jiang J. Genetic estimation of correlations and causalities between multifaceted modifiable factors and gastro-oesophageal reflux disease. Front Nutr 2022; 9:1009122. [PMID: 36386930 PMCID: PMC9663808 DOI: 10.3389/fnut.2022.1009122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 10/17/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Gastro-oesophageal reflux disease (GORD) is a common gastrointestinal dysfunction that significantly affects the quality of daily life, and health interventions are challenging to prevent the risk of GORD. In this study, we used Mendelian randomization framework to genetically determine the causal associations between multifaceted modifiable factors and the risk of GORD. MATERIALS AND METHODS Sixty-six exposures with available instrumental variables (IVs) across 6 modifiable pathways were included in the univariable MR analysis (UVMR). Summary-level genome-wide association studies (GWAS) datasets for GORD were retrieved from the Neale Lab (GORD Neale , Ncases = 29975, Ncontrols = 390556) and FinnGen (GORD Finn , Ncases = 13141, Ncontrols = 89695). Using the METAL software, meta-analysis for single nucleotide polymorphisms (SNPs) from GORD Neale and GORD Finn was conducted with an inverse variance weighted (IVW) fixed-effect model. Moreover, we leveraged partition around medoids (PAM) clustering algorithm to cluster genetic correlation subtypes, whose hub exposures were conditioned for multivariable MR (MVMR) analyses. P-values were adjusted with Bonferroni multiple comparisons. RESULTS Significant causal associations were identified between 26 exposures (15 risk exposures and 11 protective exposures) and the risk of GORD. Among them, 13 risk exposures [lifetime smoking, cigarette consumption, insomnia, short sleep, leisure sedentary behavior (TV watching), body mass index (BMI), body fat percentage, whole body fat mass, visceral adipose tissue, waist circumference, hip circumference, major depressive disorder, and anxious feeling], and 10 protective exposures (leisure sedentary behavior (computer use), sitting height, hand grip strength (left and right), birth weight, life satisfaction, positive affect, income, educational attainment, and intelligence) showed novel significant causal associations with the risk of GORD. Moreover, 13 exposures still demonstrated independent associations with the risk of GORD following MVMR analyses conditioned for hub exposures (educational attainment, smoking initiation and BMI). In addition, 12 exposures showed suggestive causal associations with the risk of GORD. CONCLUSION This study systematically elucidated the modifiable factors causally associated with the risk of GORD from multifaceted perspectives, which provided implications for prevention and treatment of GORD.
Collapse
Affiliation(s)
- Yuanlin Sun
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Xueyuan Cao
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Donghui Cao
- Department of Clinical Epidemiology, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Yingnan Cui
- Department of Gastric and Colorectal Surgery, General Surgery Center, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Kaisheng Su
- Department of Clinical Epidemiology, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Zhifang Jia
- Department of Clinical Epidemiology, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Yanhua Wu
- Department of Clinical Epidemiology, The First Hospital of Jilin University, Changchun, Jilin, China
| | - Jing Jiang
- Department of Clinical Epidemiology, The First Hospital of Jilin University, Changchun, Jilin, China,*Correspondence: Jing Jiang,
| |
Collapse
|
4
|
A Systematic Review of the Associations of Adiposity and Cardiorespiratory Fitness With Arterial Structure and Function in Nonclinical Children and Adolescents. Pediatr Exerc Sci 2022:1-12. [PMID: 36150705 DOI: 10.1123/pes.2022-0029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 08/02/2022] [Accepted: 08/07/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE To summarize the evidence on associations of adiposity and cardiorespiratory fitness (CRF) with arterial structure and function in nonclinical children and adolescents. METHODS Two researchers conducted a search in 5 electronic databases in April 2022 to find studies in nonclinical youth (age 5-17.9 y) reporting multivariable associations. Studies were eligible if adiposity and/or CRF were used as the predictor and arterial structure and/or function was the outcome. The Quality Assessment Tool for Quantitative Studies was used to assess methodological quality for experimental studies, and a modified version was used for observational studies. RESULTS Ninety-nine studies (72.7% cross-sectional) were included. Ninety-four assessed associations between adiposity and arterial outcomes, most using overall body proportion (n = 71), abdominal (n = 52), or whole-body adiposity (n = 40). Most evidence was inconsistent or nonsignificant, but 59 studies suggested higher abdominal adiposity and worse body proportion were associated with adverse arterial outcomes. Twenty-one assessed associations between CRF and arterial outcomes, with findings inconsistent. Most evidence was rated weak in quality. CONCLUSION While high adiposity may contribute to poor arterial outcomes, evidence is limited regarding CRF. Future studies should disentangle these associations by studying youth with healthy adiposity but poor CRF, or vice versa, using longitudinal or experimental study designs.
Collapse
|
5
|
Xin Z, Huang J, Cao Q, Wang J, He R, Hou T, Ding Y, Lu J, Xu M, Wang T, Zhao Z, Wang W, Ning G, Bi Y, Xu Y, Li M. Nonalcoholic fatty liver disease in relation to the remission and progression along the glycemic continuum. J Diabetes 2022; 14:606-619. [PMID: 36163589 PMCID: PMC9512772 DOI: 10.1111/1753-0407.13314] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 08/01/2022] [Accepted: 08/27/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The study aimed to explore the associations of nonalcoholic fatty liver disease (NAFLD) with the remission and progression along the glycemic continuum. METHODS This prospective cohort study was performed among the general population in 2010-2015. NAFLD was defined as ultrasound-detected hepatic steatosis with absence of excessive alcohol consumption and other hepatic diseases. Remission of type 2 diabetes referred to glycated hemoglobin <6.5% without hypoglycemic agents for ≥3 months. Prediabetes remission referred to normalization of blood glucose. Multivariable logistic analysis was applied to identify the risk of glycemic metabolic transition. RESULTS During a median follow-up of 4.3 years, participants with NAFLD had a significantly higher risk of progressing from normal glucose tolerance to diabetes (3.36 [1.60-7.07]) and lower likelihood of diabetes remission (0.48 [0.30-0.78]). Associations in participants with overweight or obesity and higher probability of hepatic fibrosis remained consistent. Results related to the effect of NAFLD on the specific glucose parameters were generally in line with the changes of glycemic status. NAFLD improvement decreased the risk of prediabetes progressing to diabetes (0.50 [0.32-0.80]) and increased the probability of prediabetes remission (2.67 [1.49-4.79]). NAFLD tended to show the most significant association with glycemic progression and decreased the likelihood in remission of prediabetes and diabetes. CONCLUSIONS Presence of NAFLD increased risk of glycemic progression and decreased likelihood of remission. NAFLD improvement mitigated glycemic deterioration, whereas NAFLD progression impeded the chance of remission. The results emphasized joint management of NAFLD and diabetes and further focused on liver-specific subgroups of diabetes to tailor early intervention.
Collapse
Affiliation(s)
- Zhuojun Xin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Jiaojiao Huang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Qiuyu Cao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Jialu Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Ruixin He
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Tianzhichao Hou
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yi Ding
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic DiseasesRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical GenomicsRuijin Hospital, Shanghai Jiao Tong University School of MedicineShanghaiChina
| |
Collapse
|
6
|
Assessment of aerobic exercise capacity in obesity, which expression of oxygen uptake is the best? SPORTS MEDICINE AND HEALTH SCIENCE 2021; 3:138-147. [PMID: 35784518 PMCID: PMC9219259 DOI: 10.1016/j.smhs.2021.01.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 01/27/2021] [Accepted: 01/30/2021] [Indexed: 11/24/2022] Open
|
7
|
Abe T, Thiebaud RS, Loenneke JP. The Fat Fraction Percentage of White Adipose Tissue at various Ages in Humans: An Updated Review. J Clin Densitom 2021; 24:369-373. [PMID: 33563512 DOI: 10.1016/j.jocd.2021.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/20/2021] [Accepted: 01/26/2021] [Indexed: 11/30/2022]
Abstract
We recently reported the fat fraction percentage of white adipose tissue in adolescents and adults measured by the water-fat separation method, but there was limited discussion about the change in adipose tissue fat fraction with growth. The purpose of this updated review was to examine the fat content of white (subcutaneous) adipose tissue during the process from birth to adulthood by adding the latest available data. A relevant database was searched through November 2020. Nineteen studies were included. We found that calculated mean values of fat fraction percentage in white adipose tissue were 72.2% in neonates, 87.2% in children, and 87.4% in adults. In contrast, fat fraction percentage of truncal white adipose tissue in the fetuses was from 10% to 24% (29 and 34 wk of gestational age, respectively). Our results suggest that the fat fraction percentage of white adipose tissue may not undergo large changes during the process from birth to adulthood (neonates = 72.2%, children = 87.2%, adults = 87.4%), which was different from the results of a study utilizing a biopsy. The mean value and range of fat fraction percentages for children over 7 years old were especially similar to adults. Further, the fat fraction percentage for neonates was relatively close to the results of children and adults. At the moment, the characteristics of the changes in fat fraction percentage of adipose tissue from birth to preschool children are unclear and future research is needed to clarify this issue.
Collapse
Affiliation(s)
- Takashi Abe
- Department of Health, Exercise Science, and Recreation Management, Kevser Ermin Applied Physiology Laboratory, The University of Mississippi, University, MS, USA.
| | - Robert S Thiebaud
- Department of Human Performance and Recreation, Brigham Young University - Idaho, Rexburg, ID, USA
| | - Jeremy P Loenneke
- Department of Health, Exercise Science, and Recreation Management, Kevser Ermin Applied Physiology Laboratory, The University of Mississippi, University, MS, USA
| |
Collapse
|
8
|
Robbins JM, Peterson B, Schranner D, Tahir UA, Rienmüller T, Deng S, Keyes MJ, Katz DH, Beltran PMJ, Barber JL, Baumgartner C, Carr SA, Ghosh S, Shen C, Jennings LL, Ross R, Sarzynski MA, Bouchard C, Gerszten RE. Human plasma proteomic profiles indicative of cardiorespiratory fitness. Nat Metab 2021; 3:786-797. [PMID: 34045743 PMCID: PMC9216203 DOI: 10.1038/s42255-021-00400-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 04/26/2021] [Indexed: 12/16/2022]
Abstract
Maximal oxygen uptake (VO2max) is a direct measure of human cardiorespiratory fitness and is associated with health. However, the molecular determinants of interindividual differences in baseline (intrinsic) VO2max, and of increases of VO2max in response to exercise training (ΔVO2max), are largely unknown. Here, we measure ~5,000 plasma proteins using an affinity-based platform in over 650 sedentary adults before and after a 20-week endurance-exercise intervention and identify 147 proteins and 102 proteins whose plasma levels are associated with baseline VO2max and ΔVO2max, respectively. Addition of a protein biomarker score derived from these proteins to a score based on clinical traits improves the prediction of an individual's ΔVO2max. We validate findings in a separate exercise cohort, further link 21 proteins to incident all-cause mortality in a community-based cohort and reproduce the specificity of ~75% of our key findings using antibody-based assays. Taken together, our data shed light on biological pathways relevant to cardiorespiratory fitness and highlight the potential additive value of protein biomarkers in identifying exercise responsiveness in humans.
Collapse
Affiliation(s)
- Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Bennet Peterson
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniela Schranner
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Exercise Biology Group, Faculty of Sports and Health Sciences, Technical University of Munich, Munich, Germany
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Theresa Rienmüller
- Institute of Health Care Engineering with Testing Center of Medical Devices, Graz University of Technology, Graz, Austria
| | - Shuliang Deng
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michelle J Keyes
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Daniel H Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Jacob L Barber
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Christian Baumgartner
- Institute of Health Care Engineering with Testing Center of Medical Devices, Graz University of Technology, Graz, Austria
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sujoy Ghosh
- Cardiovascular & Metabolic Disorders Program and Center for Computational Biology, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Changyu Shen
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Robert Ross
- School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada
| | - Mark A Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
9
|
Abe T, Wong V, Dankel SJ, Bell ZW, Spitz RW, Viana RB, Loenneke JP. Skeletal muscle mass in female athletes: The average and the extremes. Am J Hum Biol 2019; 32:e23333. [DOI: 10.1002/ajhb.23333] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 01/28/2023] Open
Affiliation(s)
- Takashi Abe
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology LaboratoryThe University of Mississippi University Mississippi
| | - Vickie Wong
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology LaboratoryThe University of Mississippi University Mississippi
| | - Scott J. Dankel
- Department of Health and Exercise ScienceRowan University Glassboro New Jersey
| | - Zachary W. Bell
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology LaboratoryThe University of Mississippi University Mississippi
| | - Robert W. Spitz
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology LaboratoryThe University of Mississippi University Mississippi
| | - Ricardo B. Viana
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology LaboratoryThe University of Mississippi University Mississippi
- Faculty of Physical Education and DanceFederal University of Goiás Goiânia Brazil
| | - Jeremy P. Loenneke
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology LaboratoryThe University of Mississippi University Mississippi
| |
Collapse
|
10
|
Abe T, Dankel SJ, Loenneke JP. Body Fat Loss Automatically Reduces Lean Mass by Changing the Fat-Free Component of Adipose Tissue. Obesity (Silver Spring) 2019; 27:357-358. [PMID: 30706656 DOI: 10.1002/oby.22393] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 11/21/2018] [Indexed: 12/14/2022]
Abstract
Fat-free mass or lean tissue mass includes nonskeletal muscle components such as the fat-free component of adipose tissue fat cells. This fat-free component of adipose tissue may need to be taken into consideration when large changes in body fat occur following a weight loss intervention. It is not uncommon to see a loss of lean mass with interventions designed to promote the loss of large amounts of fat mass. However, after eliminating the influence of the fat-free component of adipose tissue on dual-energy x-ray absorptiometry (DXA)-derived lean mass, the original loss of lean mass is no longer observed or is markedly reduced. This suggests that the majority of the lean mass lost with dieting may be the fat-free component of adipose tissue. To accurately estimate the change in lean tissue, eliminating the fat-free adipose tissue from DXA-derived lean mass is needed when large changes in body fat occur following an intervention.
Collapse
Affiliation(s)
- Takashi Abe
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology Laboratory, The University of Mississippi, Oxford, Mississippi, USA
| | - Scott J Dankel
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology Laboratory, The University of Mississippi, Oxford, Mississippi, USA
| | - Jeremy P Loenneke
- Department of Health, Exercise Science, & Recreation Management, Kevser Ermin Applied Physiology Laboratory, The University of Mississippi, Oxford, Mississippi, USA
| |
Collapse
|