Gut Microbiota Composition in Hispanic and Non-Hispanic Children.

Comparison of the Gut Microbiota Composition in Caucasian Hispanic and Caucasian Non-Hispanic Children With and Without Obesity

The human gastrointestinal (GI) tract is filled with millions of bacteria that can affect our health. These bacteria are linked with our overall health including obesity risk. In the United States the Hispanic population is one of the ethnic groups at higher risk of developing obesity. In this study the team will investigate differences in the GI bacterial composition between Hispanic and Caucasian children, and potentially demonstrate a correlation between the composition of metagenome and a higher risk to develop obesity. This will be done by collecting stool samples and comparing the bacteria found in the stool of Hispanic children (with and without obesity) and Caucasian children (with and without obesity.

Study Overview

• Status: Completed
• Conditions: Obesity
• Intervention / Treatment: Other: Fecal Sample Collection; Other: Physical Activity Questionnaire; Other: Food Frequency Questionnaire; Other: 24-hour dietary recall diary

Detailed Description

I. SPECIFIC AIMS There are a vast number of microbes in the human gastrointestinal tract (GI) including bacterial, fungal and protozoal microorganisms which all together make our microbiome. Over the last years evidence has shown that the GI microbiome is linked with our overall health including obesity risk. The GI microbiota can influence both sides of the energy balance that includes factors influencing energy utilization from the diet and factors that play a role in the regulation of energy expenditure and storage by influencing host genes (1, 2). Studies of demonstrated that overweight and obesity rates are among the highest for Hispanic children in the United States. It is estimated that in the US 47% of Hispanic children are overweight and 31% have obesity, compared to 35% and 21% respectively for Caucasian non-Hispanic children. Literature has shown environment factors are associated with childhood obesity in Hispanic children including: parental influences, screen time, physical activity behavior, socioeconomic status/food security, and sleep duration (3,4). Thus far there have been no studies having investigated if there are significant differences in the gut microbiome of Hispanic children; moreover, whether these differences (taxonomy or gene expression) puts them at higher risk to develop obesity compared other ethnic groups.

The investigators predict there are significant GI microbiome differences between Caucasian non-Hispanic children and Hispanic Children.

Aim: Confirm differences in microbiome between Caucasian non-Hispanic children (with and without obesity) and Hispanic children (with and without obesity) in this pilot study.

Hypothesis: Hispanic children will have a lower fecal bacterial diversity compared to Caucasian non-Hispanic children that is associated with more overall adiposity and impaired glucose homeostasis determined by:

A) Next generation metagenomic "whole genome/shotgun" sequencing of DNA from fecal samples of cohorts which includes Hispanic children with obesity, Hispanic children without obesity, Caucasian non-Hispanic children with obesity and Caucasian non-Hispanic children without obesity.

B) Bioinformatics computational analysis comparing the four groups to determine beta diversity (relative taxonomic) abundance.

II. BACKGROUND AND SIGNIFICANCE Obesity is a serious health risk in the United States. The prevalence of childhood obesity has increased over the last two decades. According the U.S. Department of health and Human Services, recent date showed that the prevalence of obesity higher among youth aged 6-11 year and adolescents aged 12-19 years compared with children aged 2-5 years of age. The Hispanic population is among the most affected ethnic groups in the United States. Approximately 47% of Hispanic children are overweight and 31% have obesity. Multiple factors have been found to play a role in the development of childhood obesity in Hispanic children, including: parental influences, screen time, physical activity behavior, socioeconomic status/food security, and sleep duration.

Over the last few years there has been a research interest in understanding the development and pathogenesis of obesity. Recent studies have found that the gut microbiota plays in an important role in the triggering and the development on obesity. The GI microbiota can influence both sides of the energy balance that includes factors influencing energy utilization from the diet and factors that play a role in the regulation of energy expenditure and storage by influencing host genes. In a study by Hou, they evaluated the 16S rRNA gene, the enterotypes and quantity of gut microbiota among obese children and a healthy control cohort. In this study they found that the composition of the gut microbiota showed significant differences between obese children and healthy controls. The results indicated that the phyla of Firmicutes and Bacteroidetes were the predominant fecal microbiome in both cohorts but the relative abundance ratio of Firmicutes and Bacteroidetes (F/B) in the obese cohort was significantly higher than that in the healthy controls. Firmicutes are associated with genes involved in carbohydrate catabolism and is rich in obese individuals, while Bacteroidetes are linked with diminished body mass.

At this time there have been no studies that have investigated if there are significant differences in the gut microbiome of Hispanic children; moreover, whether these differences (taxonomy or gene expression) puts them at higher risk to develop obesity compared other ethnic groups. The study team feels it is important to identify possible microbiome differences in the Hispanic population that may put them at a higher risk of developing childhood obesity.

III. RESEARCH DESIGN AND METHODS INCLUDING STATISTICAL ANALYSIS Study Subjects/Experimental Design The investigators will recruit and enroll 4 cohorts including 6 Hispanic children with obesity, 6 Hispanic children without obesity, 6 Caucasian non-Hispanic children with obesity and 6 Caucasian non-Hispanic children without obesity. Obesity will be defined as a BMI >95%. Enrollment age will be between 6-12 years of age. The investigators will obtain baseline characteristics at the time of enrollment, including anthropometric measures (weight, length, BMI), dietary history (including 24 hour recall diary and a food frequency questionnaire), and physical activity history (Physical activity questionnaire). The investigators will obtain medication history, including history of use antibiotics, steroids and probiotics.

Dietary and Physical activity measurement At fecal collection, investigators will obtain dietary information for the patient using a 30-food item food frequency questionnaire and a 24-hour food recall diary. Diet records will be analyzed using the Nutrient Data System for Research software (Minneapolis, MN). The investigators will determine intake of macro- and micronutrient intake as well as patterns of dietary intake using the latent class (person-centered approach) as well as factor (data-based approach) analyses.

The investigators will collect physical activity data on the patient using the Physical Activity Questionnaire for Older Children (PAQ-C) and will analyze with Spearman correlation coefficients. Clinical data management will be the responsibility of the principal investigator and GI fellow/co-investigator and will use a secure database, REDCap, through Nemours' REDCap system.

Fecal Sample Collection With permission from the parent/guardian, stool collected in a sterile container will be brought within 12 hours of defecation from home or the outpatient clinic to a separate clinical laboratory where feces will be collected through use of FLOQswab brush x 3 (Copan Diagnostics, Murrieta, CA) The swabs will be pre-labeled with a de-identified code reflecting patient number, sample number, and date and the sample will be placed into dry ice then transferred to a -80 degrees Celsius freezer until retrieval by the research staff for transfer to CHOP Microbiome Center.

Bacterial DNA Isolation DNA will be extracted from samples using the DNeasy PowerSoil kit using the manufacturer's instructions (Qiagen, Germantown, MD). Shotgun libraries will be generated from 1 ng of DNA using the NexteraXT kit (Illumina, San Diego, CA, USA). Libraries will be sequenced on an Illumina HiSeq 2500 using 2x125bp chemistry in High Output mode.

Bioinformatics processing and statistical analysis Differences in weight gain, HgbA1c, physical activity associated with nutritional diet records or other outcomes will be assessed using t-test or Mann Whitney U test, adjusting for covariates. The relationship between nutrition records and outcomes will be further examined using mixed effects models, adjusting for the effect of key physical activity or dietary variables.

FASTQ files will be analyzed using an established computational pipeline developed at Nemours.

• Study Type: Observational
• Enrollment (Actual): 17

Contacts and Locations

Study Locations

• United States
  • Delaware
    • Wilmington, Delaware, United States, 19803
      • Nemours/AI duPont Hospital for Children

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 6 years to 12 years (Child)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

The investigators will recruit and enroll 4 cohorts including 6 Hispanic children with obesity, 6 Hispanic children without obesity, 6 Caucasian non-Hispanic children with obesity and 6 Caucasian non-Hispanic children without obesity. Obesity will be defined as a BMI >95%. Enrollment age will be between 6-12 years of age.

Description

Inclusion Criteria:

• Caucasian non-Hispanic and Hispanic Children with and without obesity.

Exclusion Criteria:

• if the subject has a current or recent (within the past 14 days) gastrointestinal infection (viral, bacterial, or fungal)
• Known to have gastrointestinal mucosal disease or have clinically significant constipation.
• Children taking probiotics.
• History of antibiotic use within the last 6 months at the time of recruitment.

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Hispanic children with obesity	Other: Fecal Sample Collection; With permission from the parent/guardian, stool collected in a sterile container will be brought within 12 hours of defecation from home or the outpatient clinic to a separate clinical laboratory where feces will be collected through use of FLOQswab brush x 3 (Copan Diagnostics, Murrieta, CA) The swabs will be pre-labeled with a de-identified code reflecting patient number, sample number, and date and the sample will be placed into dry ice then transferred to a -80 degrees Celsius freezer until retrieval by the research staff for transfer to CHOP Microbiome Center.; Other: Physical Activity Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Physical Activity Questionnaire (Physical Activity Questionnaire for Older Children) with the subject and parent.; Other: Food Frequency Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Food Frequency Questionnaire with the subject and parent.; Other: 24-hour dietary recall diary; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the 24-hour dietary recall diary with the subject and parent.
Hispanic children without obesity	Other: Fecal Sample Collection; With permission from the parent/guardian, stool collected in a sterile container will be brought within 12 hours of defecation from home or the outpatient clinic to a separate clinical laboratory where feces will be collected through use of FLOQswab brush x 3 (Copan Diagnostics, Murrieta, CA) The swabs will be pre-labeled with a de-identified code reflecting patient number, sample number, and date and the sample will be placed into dry ice then transferred to a -80 degrees Celsius freezer until retrieval by the research staff for transfer to CHOP Microbiome Center.; Other: Physical Activity Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Physical Activity Questionnaire (Physical Activity Questionnaire for Older Children) with the subject and parent.; Other: Food Frequency Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Food Frequency Questionnaire with the subject and parent.; Other: 24-hour dietary recall diary; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the 24-hour dietary recall diary with the subject and parent.
Caucasian non-Hispanic children with obesity	Other: Fecal Sample Collection; With permission from the parent/guardian, stool collected in a sterile container will be brought within 12 hours of defecation from home or the outpatient clinic to a separate clinical laboratory where feces will be collected through use of FLOQswab brush x 3 (Copan Diagnostics, Murrieta, CA) The swabs will be pre-labeled with a de-identified code reflecting patient number, sample number, and date and the sample will be placed into dry ice then transferred to a -80 degrees Celsius freezer until retrieval by the research staff for transfer to CHOP Microbiome Center.; Other: Physical Activity Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Physical Activity Questionnaire (Physical Activity Questionnaire for Older Children) with the subject and parent.; Other: Food Frequency Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Food Frequency Questionnaire with the subject and parent.; Other: 24-hour dietary recall diary; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the 24-hour dietary recall diary with the subject and parent.
Caucasian non-Hispanic children without obesity	Other: Fecal Sample Collection; With permission from the parent/guardian, stool collected in a sterile container will be brought within 12 hours of defecation from home or the outpatient clinic to a separate clinical laboratory where feces will be collected through use of FLOQswab brush x 3 (Copan Diagnostics, Murrieta, CA) The swabs will be pre-labeled with a de-identified code reflecting patient number, sample number, and date and the sample will be placed into dry ice then transferred to a -80 degrees Celsius freezer until retrieval by the research staff for transfer to CHOP Microbiome Center.; Other: Physical Activity Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Physical Activity Questionnaire (Physical Activity Questionnaire for Older Children) with the subject and parent.; Other: Food Frequency Questionnaire; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the Food Frequency Questionnaire with the subject and parent.; Other: 24-hour dietary recall diary; At the initial encounter the co-investigator Dr. David Garcia, who is a certified Spanish translator will complete the 24-hour dietary recall diary with the subject and parent.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Metagenome of each patient's fecal sample	sequence of all bacterial DNA and other organism's DNA in a sample	through study completion, an average of 9 months
Physical Activity	Administer a validated physical activity questionnaire	through study completion, an average of 9 months
Food frequency questionnaire	Administer a validated food frequency questionnaire	through study completion, an average of 9 months

Collaborators and Investigators

• Sponsor: Nemours Children's Clinic
• Investigators: Principal Investigator: Matthew D Di Guglielmo, MD PhD, Nemours

Publications and helpful links

General Publications

• Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014 Aug 1;30(15):2114-20. doi: 10.1093/bioinformatics/btu170. Epub 2014 Apr 1.
• Davis CD. The Gut Microbiome and Its Role in Obesity. Nutr Today. 2016 Jul-Aug;51(4):167-174. doi: 10.1097/NT.0000000000000167.
• Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013 Jan 1;29(1):15-21. doi: 10.1093/bioinformatics/bts635. Epub 2012 Oct 25.
• Carrera-Quintanar L, Ortuno-Sahagun D, Franco-Arroyo NN, Viveros-Paredes JM, Zepeda-Morales AS, Lopez-Roa RI. The Human Microbiota and Obesity: A Literature Systematic Review of In Vivo Models and Technical Approaches. Int J Mol Sci. 2018 Nov 30;19(12):3827. doi: 10.3390/ijms19123827.
• Ochoa A, Berge JM. Home Environmental Influences on Childhood Obesity in the Latino Population: A Decade Review of Literature. J Immigr Minor Health. 2017 Apr;19(2):430-447. doi: 10.1007/s10903-016-0539-3.
• Lindsay AC, Wallington SF, Lees FD, Greaney ML. Exploring How the Home Environment Influences Eating and Physical Activity Habits of Low-Income, Latino Children of Predominantly Immigrant Families: A Qualitative Study. Int J Environ Res Public Health. 2018 May 14;15(5):978. doi: 10.3390/ijerph15050978.
• Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of Obesity Among Adults and Youth: United States, 2015-2016. NCHS Data Brief. 2017 Oct;(288):1-8.
• Del Chierico F, Abbatini F, Russo A, Quagliariello A, Reddel S, Capoccia D, Caccamo R, Ginanni Corradini S, Nobili V, De Peppo F, Dallapiccola B, Leonetti F, Silecchia G, Putignani L. Gut Microbiota Markers in Obese Adolescent and Adult Patients: Age-Dependent Differential Patterns. Front Microbiol. 2018 Jun 5;9:1210. doi: 10.3389/fmicb.2018.01210. eCollection 2018.
• Hou YP, He QQ, Ouyang HM, Peng HS, Wang Q, Li J, Lv XF, Zheng YN, Li SC, Liu HL, Yin AH. Human Gut Microbiota Associated with Obesity in Chinese Children and Adolescents. Biomed Res Int. 2017;2017:7585989. doi: 10.1155/2017/7585989. Epub 2017 Oct 29.
• Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 2014 Mar 3;15(3):R46. doi: 10.1186/gb-2014-15-3-r46.
• Pereira MB, Wallroth M, Jonsson V, Kristiansson E. Comparison of normalization methods for the analysis of metagenomic gene abundance data. BMC Genomics. 2018 Apr 20;19(1):274. doi: 10.1186/s12864-018-4637-6.
• Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015 May 15;31(10):1674-6. doi: 10.1093/bioinformatics/btv033. Epub 2015 Jan 20.
• Hyatt D, LoCascio PF, Hauser LJ, Uberbacher EC. Gene and translation initiation site prediction in metagenomic sequences. Bioinformatics. 2012 Sep 1;28(17):2223-30. doi: 10.1093/bioinformatics/bts429. Epub 2012 Jul 12.
• Tatusov RL, Koonin EV, Lipman DJ. A genomic perspective on protein families. Science. 1997 Oct 24;278(5338):631-7. doi: 10.1126/science.278.5338.631.
• Li B, Dewey CN. RSEM: Accurate transcript quantification from RNA-seq data with or without a reference genome. Bioinforma Impact Accurate Quantif Proteomic Genet Anal Res. 2014;41-74.
• Vera-Becerra LE, Lopez ML, Kaiser LL. Relative validity of a tool to measure food acculturation in children of Mexican descent. Appetite. 2016 Feb 1;97:87-93. doi: 10.1016/j.appet.2015.11.014. Epub 2015 Nov 19.

Study record dates

Study Major Dates

• Study Start (Actual): June 14, 2019
• Primary Completion (Actual): February 28, 2020
• Study Completion (Actual): June 15, 2020

Study Registration Dates

• First Submitted: May 16, 2019
• First Submitted That Met QC Criteria: June 17, 2019
• First Posted (Actual): June 18, 2019

Study Record Updates

• Last Update Posted (Actual): June 30, 2020
• Last Update Submitted That Met QC Criteria: June 26, 2020
• Last Verified: June 1, 2020

More Information

Terms related to this study

• Keywords: Gut Microbiome
• Additional Relevant MeSH Terms: Overnutrition; Nutrition Disorders; Overweight; Body Weight; Obesity
• Other Study ID Numbers: 1347478

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