Metabolic Effects of Differential Organ Growth Rates

July 14, 2017 updated by: Dympna Gallagher, Columbia University
Young children have a high resting energy expenditure (REE) relative to their body weight and metabolically active compartment, fat-free mass (FFM). Both body weight and FFM are, however, metabolically heterogeneous and include organs and tissues varying widely in specific metabolic rate (i.e., organ REE/kg/d). One prevailing hypothesis is that most, if not all, of the higher REE observed in young animals and children compared to adults can be accounted for by a larger proportion of high metabolic rate components such as brain, liver, and heart..

Study Overview

Status

Completed

Detailed Description

FFM was the traditional and only means of adjusting REE for between-individual differences in metabolically active tissue components. The investigators seek to improve the understanding of variation in REE by developing new and improved rapid magnetic resonance imaging (MRI) methods of quantifying some of the major heat producing organs and tissues in children and adults. The long-term aim is to provide an improved understanding of human energy requirements. Specifically, the investigators propose to test whether: 1) a portion of the elevated daily REE adjusted for FFM observed in young children (Tanner Stage 1) could be accounted for by the relative fractions of body mass as high metabolic activity tissues (heart, liver, kidney, brain) and low metabolic activity tissues (skeletal muscle, adipose tissue), 2) a portion of the age-related decline in daily REE adjusted for FFM observed in children could be accounted for by changes in the relative fractions of body mass as high and low metabolic rate tissues during growth.

Study Type

Observational

Enrollment (Actual)

49

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • New York
      • New York, New York, United States, 10032
        • Dympna Gallagher

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

7 years to 11 years (Child)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Subjects will be healthy African-American, Asian (Chinese, Korean, Japanese), and Caucasian pre-pubertal females and males (ages 7-11 years) at baseline. Lean (Body mass index (BMI) < 85th by age and sex) and obese (BMI > 95th percentile by age and sex.

Description

Inclusion Criteria:

  • Healthy
  • Aged from 7-11 years
  • Pre-pubertal (based on Tanner staging)
  • Africa-American, Asian, and Caucasian (by self-report of all 4 grandparents of same race group)

Exclusion Criteria:

  • Actively involved in a weight management program
  • Have co-morbidities of obesity (Blounts disease, hypertension, diabetes; sleep apnea)
  • Have entered puberty
  • Precocious puberty
  • Have known metabolic abnormalities
  • Were born prematurely, or were small or large for gestational age
  • Lean individuals who have a family history (parents or siblings) of obesity or Type 2 diabetes
  • Current or previous significant use of any medication known to affect any of the variables being measured

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Prepubertal children
Healthy 7-11 year old girls and boys.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Resting energy expenditure in kilocalories
Time Frame: Day 1
REE is measured by indirect calorimetry over a 30 minute period and extrapolated to a 24 hour period
Day 1
Fat mass in kilograms
Time Frame: Day 1
Measured from a whole-body dual energy X-ray absorptiometry (DXA) scan
Day 1
Fat-free mass in kilograms
Time Frame: Day 1
Measured from a whole-body dual energy X-ray absorptiometry (DXA) scan
Day 1
Height in meters
Time Frame: Day 1
Measured using a stadiometer
Day 1
Weight in kilograms
Time Frame: Day 1
Measured using a calibrated scale
Day 1
Liver in kilograms
Time Frame: Day 1
Total volume measured by MRI
Day 1
Heart in kilogram
Time Frame: Day 1
Left ventricular mass measured by cardiac gated MRI
Day 1
Kidneys in kilogram
Time Frame: Day 1
Total volume measured by MRI
Day 1
Spleen in kilograms
Time Frame: Day 1
Total volume measured by MRI
Day 1
Trunk high metabolic rate organs in kilograms
Time Frame: Day 1
The sum of liver, kidneys, spleen, and heart
Day 1
Brain mass in kilogram
Time Frame: Day 1
Total volume measured by MRI
Day 1
Skeletal muscle mass in kilograms
Time Frame: Day 1
Skeletal muscle volume measured by MRI
Day 1
Residual fat-free mass in kilograms
Time Frame: Day 1
Fat-free mass minus the sum of kidneys, liver, spleen, heart, and skeletal muscle
Day 1
Total body adipose tissue mass in kilogram
Time Frame: Day 1
Represents the sum of visceral, subcutaneous, and intermuscular adipose tissue by MRI
Day 1
Body mass index in kg/m2
Time Frame: Day 1
Weight and height will be combined to report BMI
Day 1
Variability in resting energy expenditure
Time Frame: Day 1
The collected measures will be aggregated to statistically test the following question: How much of the variability in resting energy expenditure can be accounted for by the mass of the measured organs (liver, kidneys, spleen, heart) and tissues (fat, skeletal muscle, brain) and is the explained variance greater than the variance explained when predicting resting energy explained from a model using fat and fat-free mass alone.
Day 1

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change in resting energy expenditure in relation to changes in body composition and organ mass.
Time Frame: From baseline measure to follow-up, approximately 2 years
A portion of age-related decline (2-years) in daily REE adjusted for FFM observed in children is explainable in part by changes in the relative fractions of body mass as high (brain, heart, liver, kidney) and low (skeletal muscle, adipose tissue) metabolic activity tissues with growth and pubertal progress
From baseline measure to follow-up, approximately 2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Dympna Gallagher, Columbia University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 14, 2004

Primary Completion (Actual)

February 20, 2007

Study Completion (Actual)

February 20, 2007

Study Registration Dates

First Submitted

July 11, 2017

First Submitted That Met QC Criteria

July 13, 2017

First Posted (Actual)

July 17, 2017

Study Record Updates

Last Update Posted (Actual)

July 18, 2017

Last Update Submitted That Met QC Criteria

July 14, 2017

Last Verified

July 1, 2017

More Information

Terms related to this study

Other Study ID Numbers

  • AAAO3053

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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