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. Author manuscript; available in PMC: 2020 Sep 1.
Published in final edited form as: Environ Int. 2019 Jun 22;130:104935. doi: 10.1016/j.envint.2019.104935

Table 5.

Associations between metabolomic principal component (PC) scores and body mass index (BMI) among 173 adolescents and young adults.

Independent Variables β6 p
Metabolomic PCs
 PC11 −1.21 <0.001
 PC22 0.30 0.42
 PC33 1.51 <0.001
 PC44 2.34 <0.001
 PC55 −1.01 0.001
Race/Ethnicity
 Non-Hispanic White ref
 Hispanic White 0.44 0.56
 Other 0.95 0.34
Sex
 Male ref
 Female −0.42 0.55
Age −0.01 0.96
Parental education
 Less than high school ref
 Completed high school −0.21 0.79
 Some college or higher −0.87 0.30
 Unknown −2.04 0.35
Ever used e-cigarette
 No ref
 Yes 0.87 0.25
Cigarette smoke in the last week
 No ref
 Yes −1.15 0.40
1.

Metabolomic principal component (PC) 1 represents a variety of short- and median-chain acylcarnitines and explains 26.3% variance of concentrations of all metabolites analyzed in the study samples. More details of the loadings of specific metabolites for each PC are described in Supplemental Table 4.

2.

PC2 represents non-esterified fatty acids (NEFA) and NEFA oxidation by-products including long-chain acylcarnitines, acetylcarnitine (C2) and 3-Hydroxybutyrylcarnitine (C4-OH), which explains 10.2% variance of concentrations of all metabolites analyzed in the study samples.

3.

PC3 represents metabolites involved in branched-chain amino-acid (BCAA) catabolism, which explains 7.2% variance of concentrations of all metabolites analyzed in the study samples.

4.

PC4 represents amino acids involved in general amino acid catabolism and the urea cycle, which explains 4.9% variance of concentrations of all metabolites analyzed in the study samples.

5.

PC5 represents amino acids involved in glycine metabolism, which explains 4.1% variance of concentrations of all metabolites analyzed in the study samples.

6.

Mixed effects model with all five PCs in one regression model and adjustment for socio-demographic confounders was used to estimate independent association of each metabolomic PC with BMI as a continuous outcome variable. Association estimates (β) and p-values are presented for each independent variable in the analysis model.