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NCT Number: NCT05121935

MAL-ED Metabolic: A Follow-Up of Chronic Disease at Puberty

The concept that the roots of cardiometabolic disease start in early life was established by Dr. David Barker, who documented relationships between low birthweight (as a marker for challenges during gestation) and later cardiovascular disease (CVD). Later work has suggested that post-natal challenges (similar to prenatal ones) may also exhibit links to later cardiometabolic disease, with the strongest links appearing to be between low weight in early childhood and later hypertension and high waist circumference (WC). However, assessments for the relationship between early childhood challenges and insulin resistance and glucose regulation have been lacking and long-term cohort studies are few. In this project, we aim to assess children initially followed as part of The Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health (MAL-ED) study, where they received frequent measures of anthropometry and laboratory assessments for intestinal pathogens. These children are now of peri-pubertal age--a time period associated with metabolic shifts. We will assess for glucose dysregulation and findings associated with the metabolic syndrome, and we will analyze potential associations between current chronic disease risk findings with early life poor growth and intestinal pathogen carriage rate. As such, we hope to uncover potential targets in early life health to reduce later chronic disease risk.

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Key information

About this study

The relationship between prenatal challenges and later risk for chronic disease has been well established. Our group previously assessed the hypothesis that post-natal challenges (similar to prenatal ones) would exhibit links to later cardiometabolic disease. This was performed using retrospective data from a long-term cohort of children in Guatemala, demonstrating novel findings that higher degrees of diarrhea burden in the first 6 months of life (as a marker of nutritional and/or inflammatory stressors) were associated with a greater risk of metabolic syndrome as adults The causes of these findings are not known, though postulated mechanisms include epigenetic reprograming of metabolic rate, hormonal regulation and vascular tone. Unfortunately, long-term cohort studies are few, limiting opportunities to evaluate these links prospectively.

The Haydom Global Health Research Center in north central Tanzania represents an important rural setting for performing high-quality medical research in sub-Saharan Africa (5). The region around Haydom has a high degree of stunting and enteric pathogen carriage among a cohort of children followed in the area from 2009-2013 as part of the multi-country study "The Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health (MAL-ED)."

These children followed in Haydom during MAL-ED had monthly anthropometry and stool pathogen analysis, as well as extensive demographic data. This provides an opportunity to follow up on these children to assess for potential links between early life challenges (both enteric disease, infections and nutritional deficiencies) and later chronic disease risk, including lipid abnormalities, glucose intolerance and blood pressure elevations. The current proposal is to follow up on these children at the age of typical entry into puberty, as this is a common shift in metabolism when many children begin to exhibit metabolic abnormalities. We will assess these children for multiple measures:

  • Anthropometry (height, weight, BMI, waist circumference)
  • Assessment of pubertal stage by exam or questionnaire
  • Blood pressure
  • Lipids (LDL, HDL, triglycerides)
  • CRP
  • Oral glucose tolerance test (OGTT)
  • Fasting insulin
  • Metabolic syndrome (MetS) severity score
  • Blood saved for future epigenetic testing

We will use linear and and logistic regression to determine associations between 1) mean number of monthly pathogens (individual pathogens and in aggregate) and 2) reported symptoms (fever, cough, diarrhea), with multiple MetS-related outcomes: BMI percentile, WC, fasting insulin, 2-hour glucose following OGTT, triglycerides, HDL cholesterol, normalized BP and a MetS diagnosis.

The underlying hypothesis is that there will be consistent links between features of MetS (in particular blood pressure, waist circumference and insulin resistance) with 1) enteric pathogen burden (overall and for particularly virulent pathogens such as Enterotoxigenic E.coli) and 2) poor early life growth.

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Participated in original MAL-ED cohort

Exclusion criteria

  • Did not participate in original MAL-ED cohort

Treatment and study plan

Primary outcomes

  1. Current Systolic BP--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current systolic BP z-score vs. number enteric pathogens by age 2 years (from MAL-ED)

Secondary outcomes

  1. Current Systolic BP--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current systolic BP z-score vs. BMI z-score at age 2 years (from MAL-ED), adjusted for current BMI z-score

  2. Current Diastolic BP--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current diastolic BP z-score vs. number enteric pathogens by age 2 years (from MAL-ED)

  3. Current Diastolic BP--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current diastolic BP z-score vs. BMI z-score at age 2 years (from MAL-ED), adjusted for current BMI z-score

  4. Current BMI z-score--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current BMI z-score vs. number enteric pathogens by age 2 years (from MAL-ED)

  5. Current waist circumference--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current waist circumference vs. number enteric pathogens by age 2 years (from MAL-ED)

  6. Metabolic syndrome (MetS) severity score--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current MetS severity z-score vs. number enteric pathogens by age 2 years (from MAL-ED)

  7. Current metabolic syndrome (MetS) severity score--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current MetS severity z-score vs. number enteric pathogens by age 2 years (from MAL-ED), adjusted by current waist circumference

  8. Current glucose from oral glucose tolerance test (OGTT) at 2 hours--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current 2-hour OGTT glucose vs. number enteric pathogens by age 2 years (from MAL-ED)

  9. Current glucose from oral glucose tolerance test (OGTT) at 2 hours--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current 2-hour OGTT glucose vs. BMI z-score at age 2 years (from MAL-ED), adjusted by current BMI z-score

  10. Current fasting triglycerides--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current ln(triglycerides) vs. number enteric pathogens by age 2 years (from MAL-ED)

  11. Current fasting triglycerides--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current ln(triglycerides) vs. BMI z-score at age 2 years (from MAL-ED), adjusted by current BMI z-score

  12. Current HDL cholesterol--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current HDL cholesterol vs. number enteric pathogens by age 2 years (from MAL-ED)

  13. Current HDL cholesterol--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current HDL cholesterol vs. BMI z-score at age 2 years (from MAL-ED), adjusted by current BMI z-score

  14. Current fasting glucose--relationship to number of enteric pathogens by age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current fasting glucose vs. number enteric pathogens by age 2 years (from MAL-ED)

  15. Current fasting glucose--relationship to BMI z-score at age 2 years

    Time frame: Measured during current study (1 year +/- 3 months)

    Regression analysis of current fasting glucose vs. BMI z-score at age 2 years (from MAL-ED), adjusted by current BMI z-score

Study contacts

Contact information is provided by the study sponsor or research team.

Mark D DeBoer, MD

CONTACT

[email protected]

14349245956

Sponsors and collaborators

Lead sponsor

University of Virginia

Other

Collaborators

  • Haydom Lutheran Hospital

Registry information

Important dates

Study start
2022
Primary completion
2023
Study completion
2031
First posted
Nov 16, 2021
Registry last updated
Nov 16, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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