The Pediatric Obesity Microbiome and Metabolism Study (POMMS): Methods, Baseline Data, and Early Insights

Abstract

Objective: The purpose of this study was to establish a biorepository of clinical, metabolomic, and microbiome samples from adolescents with obesity as they undergo lifestyle modification.

Methods: A total of 223 adolescents aged 10 to 18 years with BMI ≥95th percentile were enrolled, along with 71 healthy weight participants. Clinical data, fasting serum, and fecal samples were collected at repeated intervals over 6 months. Herein, the study design, data collection methods, and interim analysis-including targeted serum metabolite measurements and fecal 16S ribosomal RNA gene amplicon sequencing among adolescents with obesity (n = 27) and healthy weight controls (n = 27)-are presented.

Results: Adolescents with obesity have higher serum alanine aminotransferase, C-reactive protein, and glycated hemoglobin, and they have lower high-density lipoprotein cholesterol when compared with healthy weight controls. Metabolomics revealed differences in branched-chain amino acid-related metabolites. Also observed was a differential abundance of specific microbial taxa and lower species diversity among adolescents with obesity when compared with the healthy weight group.

Conclusions: The Pediatric Metabolism and Microbiome Study (POMMS) biorepository is available as a shared resource. Early findings suggest evidence of a metabolic signature of obesity unique to adolescents, along with confirmation of previously reported findings that describe metabolic and microbiome markers of obesity.

Figure 1.. POMMS study design.

Adolescents between 10 and 18 with either BMI >5^th %ile to < 85^th percentile (healthy weight controls, or HWC) or BMI equal to or over the 95^th percentile (adolescents with obesity, or OB) were recruited to join the study. Target numbers of recruits for each intervention are indicated, along with actual recruitment numbers. Age matched HWC recruits had clinical measurements of health as well as serum, stool, and PBMCs collected at a single timepoint, while OB recruits were evaluated and offered a treatment arm that was clinically relevant depending on the individual. OB recruits then had clinical measurements of health, blood, PBMC and stool samples taken at baseline, 3 months, and 6 months (or termination) of the study. Stool samples were also collected from OB patients at 1.5 and 4.5 months after the first visit. All samples are stored in replicates in the POMMS Biorepository managed within the Duke Children’s Biobank to be made available for research purposes.

Figure 2.. Clinical lab measurements of liver function and inflammation were significantly higher in OB v HWC.

Log transformed serum values of alanine transferase (ALT) and C-reactive protein (CRP) were compared at baseline between healthy weight control (HWC) and adolescents with obesity (OB). Error bars indicate standard deviation of the mean. *** = P< 0.001 following correction for multiple testing. See Methods for details on statistical analysis.

Figure 3.. A subset of adolescents with obesity have reduced gut microbial diversity and differences in abundance of specific microbial taxa when compared to their healthy weight counterparts.

(A) Shannon α-diversity and Bray Curtis β-diversity metrics between HWC and OB stool 16S rRNA gene sequences based on identified amplicon sequence variants. (B-C) The Linear discriminant analysis (LDA) effect size tool (LEfSe) was applied to taxonomic data resulting from 16S rRNA gene amplicon sequencing. (B) Relative abundance of taxa with that vary significantly by cohort are displayed. (C) Count data of each taxon with a significantly different abundance between HWC and OB cohorts in the LDA analysis. Each symbol represents abundance in an individual sample. (D) PhiLR Taxa identified by 16S rRNA gene sequencing that were present at a read count of > 3 across at least 10% of patient samples were retained for analysis. PhiLR results are displayed as log relative abundances of opposing clades in a phylogenetic tree and significant balances were chosen on the basis of a simple predictive model. A PhILR value greater than zero indicates greater abundance of the numerator component relative to the denominator component and a negative value indicates the reverse. These balances were most effective at predicting patient membership in either the HWC or OB cohort. See Methods section for details on statistical analyses and access to relevant R code.

Figure 4:. Phylogenetic clustering of gut microbial taxa suggest that genetic relationships predict presence or absence of taxa in OB cohorts.

(A) Taxa identified by 16S rRNA gene amplicon sequencing were subjected to unsupervised clustering into 5 taxonomic clusters and grouped by color and treatment status. Each terminal node of the tree represents results from an individual fecal sample. (B) Clusters were assigned a color and each fecal sample result was grouped by cluster in (A) and then divided by HWC or OB status in order of participant ID number. See methods for links to relevant R code and raw data.