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Meta-Analysis
. 2023 Feb;131(2):27005.
doi: 10.1289/EHP11372. Epub 2023 Feb 22.

Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study

Affiliations
Meta-Analysis

Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study

Jesse A Goodrich et al. Environ Health Perspect. 2023 Feb.

Abstract

Background: Exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous and has been associated with an increased risk of several cardiometabolic diseases. However, the metabolic pathways linking PFAS exposure and human disease are unclear.

Objective: We examined associations of PFAS mixtures with alterations in metabolic pathways in independent cohorts of adolescents and young adults.

Methods: Three hundred twelve overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) and 137 young adults from the Southern California Children's Health Study (CHS) were included in the analysis. Plasma PFAS and the metabolome were determined using liquid-chromatography/high-resolution mass spectrometry. A metabolome-wide association study was performed on log-transformed metabolites using Bayesian regression with a g-prior specification and g-computation for modeling exposure mixtures to estimate the impact of exposure to a mixture of six ubiquitous PFAS (PFOS, PFHxS, PFHpS, PFOA, PFNA, and PFDA). Pathway enrichment analysis was performed using Mummichog and Gene Set Enrichment Analysis. Significance across cohorts was determined using weighted Z-tests.

Results: In the SOLAR and CHS cohorts, PFAS exposure was associated with alterations in tyrosine metabolism (meta-analysis p=0.00002) and de novo fatty acid biosynthesis (p=0.03), among others. For example, when increasing all PFAS in the mixture from low (30th percentile) to high (70th percentile), thyroxine (T4), a thyroid hormone related to tyrosine metabolism, increased by 0.72 standard deviations (SDs; equivalent to a standardized mean difference) in the SOLAR cohort (95% Bayesian credible interval (BCI): 0.00, 1.20) and 1.60 SD in the CHS cohort (95% BCI: 0.39, 2.80). Similarly, when going from low to high PFAS exposure, arachidonic acid increased by 0.81 SD in the SOLAR cohort (95% BCI: 0.37, 1.30) and 0.67 SD in the CHS cohort (95% BCI: 0.00, 1.50). In general, no individual PFAS appeared to drive the observed associations.

Discussion: Exposure to PFAS is associated with alterations in amino acid metabolism and lipid metabolism in adolescents and young adults. https://doi.org/10.1289/EHP11372.

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Figures

Figure is a dot graph with three columns titled Study of Latino Adolescents at Risk, Children’s Health Study, and Meta-analysis. There are five groups of pathways, named Other, which includes Nitrogen metabolism and Drug metabolism-cytochrome P 450; Metabolism of cofactors and vitamins, including Vitamin B6 (pyridoxine) metabolism and Porphyrin metabolism; Lipid metabolism, including Linoleate metabolism, Fatty acid metabolism, anti-inflammatory metabolism from Eicosapentaenoic acid, Prostaglandin formation from Arachidonate, and De novo fatty acid biosynthesis; Nonaromatic amino acid metabolism, including Lysine metabolism, Arginine and Proline metabolism, Urea cycle or amino group metabolism, and Glutathione metabolism; and Aromatic amino acid metabolism, including Tyrosine metabolism (y-axis) across negative log uppercase p, ranging from 0 to 6 in increments of 2 (x-axis) for analysis, individual cohort analysis, and meta-analysis, respectively.
Figure 1.
Metabolic pathways associated with exposure to a mixture of six PFAS in adolescents from the SOLAR cohort (n=312) and young adults from the CHS cohort (n=137). Metabolic pathways are grouped into super pathways as indicated on the right of the plot. Meta-analysis p values are provided for pathways identified as being associated with PFAS in both cohorts. Dot size for the SOLAR and CHS cohorts are proportional to the number of significant metabolites associated with each pathway. Only pathways that were significant in either the SOLAR cohort, the CHS cohort, or the meta-analysis are presented here; for complete results see Table S3. Note: CHS, Children’s Health Study; EPA, eicosapentaenoic acid; PFAS, per- and polyfluoroalkyl substances; Sig, Significant; SOLAR, Study of Latino Adolescents at Risk.
Figure 2A is a coefficient plot titled Study of Latino Adolescents at Risk, plotting Thyroid hormone biosynthesis, including Thyroxine; Phenylalanine metabolism, including Phenylacetylglutamine, Phenylacetaldehyde, and Hippuric acid; Tyrosine metabolism and degradation, including Acetoacetic acid, 4-Hydroxyphenylacetaldehyde, Pyruvic acid, L-Glutamic acid, and Tyramine-O-sulfate; Catecholamine biosynthesis and degradation, including Homovanillin, Vanylglycol, 1,2-Dehydrosalsolinol, 3-O-Methyldopa, 3-Methoxytyramine, Norepinephrine, Norepinephrine sulfate, Metanephrine, and ascorbate (y-axis) across Per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 3 in unit increments (x-axis) for Same direction of association in Study of Latino Adolescents at Risk and Children’s Health Study, Only significant in one cohort, and Opposite direction of association in Study of Latino Adolescents at Risk versus Children’s Health Study. Figure 2B is a coefficient plot titled Children’s Health Study, plotting Melanin biosynthesis, including Dopaquinone; Thyroid hormone biosynthesis, including Thyroxine; Phenylalnine metabolism, including Hippuric acid; Tyrosine metabolism and degradation, including L-Glutamic acid and Acetoacetic acid; and Catecholamine biosynthesis and degradation, including Vanylglycol and Homovanillic acid (y-axis) across Per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 3 in unit increments (x-axis) for Same direction of association in Study of Latino Adolescents at Risk and Children’s Health Study, Only significant in one cohort, and Opposite direction of association in Study of Latino Adolescents at Risk versus Children’s Health Study.
Figure 2.
Associations between PFAS mixtures and metabolites associated with aromatic amino acid metabolism in (A) adolescents from the SOLAR cohort (n=312) and (B) young adults from the CHS cohort (n=137). Metabolites are grouped by tyrosine metabolism subpathways as indicated on the right of the plot. Effect estimates for PFAS mixture (ψ) and the 95% Bayesian credible interval (BCI) estimate the change in metabolite levels (SD of the log-transformed feature intensity) when increasing all PFAS in the mixture from the 30th percentile to the 70th percentile. This estimate is also equivalent to a standardized mean difference calculated between a hypothetical group of individuals with all PFAS at the 70th percentile vs. a hypothetical group of individuals with all PFAS at the 30th percentile. Corresponding p-values and q-values are presented in Table S4. Note: CHS, Children’s Health Study; PFAS, per- and polyfluoroalkyl substances; SD, standard deviation; SOLAR, Study of Latino Adolescents at Risk.
Figure 3A is a coefficient plot titled Study of Latino Adolescents at Risk, plotting Putative anti-inflammatory metabolites formation from Eicosapentaenoic acid, including Leukotriene C 5 and 15 Keto-prostaglandin E 2; Prostaglandin formation from Arachidonate, including Arachidonic acid and Prostaglandin E 2; Linoleate metabolism, including (E)-4-Hyfroxynon-2-enal, 12,13-Epoxy-9-alkoxy-10 E-octadecenoate, Lysophosphatidylcholines (18 to 1(9 Z)), Pelargonic acid, 13(S)-Hydroperoxyoctadecatrienoic acid, 13-Octadecanienoic acid, and Linoleic acid; Fatty acid metabolism, including Glycerol; and De novo fatty acid biosynthesis, including Elaidic acid and Dodecanoic acid (y-axis) across Per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 2 in unit increments (x-axis) for Same direction of association in Study of Latino Adolescents at Risk and Children’s Health Study and Only significant in one cohort. Figure 3B is a coefficient plot titled Children’s Health Study, plotting Prostaglandin formation from Arachidonate, including Arachidonic acid and 11-Hydroxyeicosatetraenoate glyceryl ester, and De novo fatty acid biosynthesis, including Docosahexaenoic acid and Behenic acid (y-axis) across per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 2 in unit increments (x-axis) for Same direction of association in Study of Latino Adolescents at Risk and Children’s Health Study and Only significant in one cohort.
Figure 3.
Associations between PFAS mixtures and metabolites associated with lipid metabolism in (A) adolescents from the SOLAR cohort (n=312) and (B) young adults from the CHS cohort (n=137). Effect estimates for PFAS mixture (ψ) and the 95% Bayesian credible interval (BCI) estimate the change in metabolite levels (SD of the log-transformed feature intensity) when increasing all PFAS in the mixture from the 30th percentile to the 70th percentile. This estimate is also equivalent to a standardized mean difference calculated between a hypothetical group of individuals with all PFAS at the 70th percentile vs. a hypothetical group of individuals with all PFAS at the 30th percentile. Corresponding p-values and q-values are presented in Table S4. Note: CHS, Children’s Health Study; EPA, eicosapentaenoic acid; HPOT, hydroperoxyoctadecatrienoic acid; LysoPC, lysophosphatidylcholines; OxoODE, Octadecanienoic acid; PFAS, per- and polyfluoroalkyl substances; SD, standard deviation; SOLAR, Study of Latino Adolescents at Risk.
Figure 4A is a coefficient plot titled Study of Latino Adolescents at Risk, plotting Urea cycle, including N-acetylornithine; Lysine metabolism, including L-Carnitine, Aminoadipic acid, 6-Amino-2-oxohexanoate; and Arginine and proline metabolism, including Aspartic acid, 5-Amino-2-oxopentanoic acid, Citrulline, and N-Acetylputrescine (y-axis) across Per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 2 in unit increments (x-axis) for Same direction of association in Study of Latino Adolescents at Risk and Children’s Health Study and Only significant in one cohort. Figure 4B is a coefficient plot titled Children’s Health Study, plotting Lysine metabolism, including 3-Dehydroxycarnitine and Aminoadipic acid; and Arginine and proline metabolism, including 5 prime-Methylthioadenosine (y-axis) across Per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 2 in unit increments (x-axis) for Same direction of association in Study of Latino Adolescents at Risk and Children’s Health Study and Only significant in one cohort.
Figure 4.
Associations between PFAS mixtures and metabolites associated with nonaromatic amino acid metabolism in (A) adolescents from the SOLAR cohort (n=312) and (B) young adults from the CHS cohort (n=137). Effect estimates for PFAS mixture (ψ) and the 95% Bayesian credible interval (BCI) estimate the change in metabolite levels (SD of the log-transformed feature intensity) when increasing all PFAS in the mixture from the 30th percentile to the 70th percentile. This estimate is also equivalent to a standardized mean difference calculated between a hypothetical group of individuals with all PFAS at the 70th percentile vs. a hypothetical group of individuals with all PFAS at the 30th percentile. Corresponding p-values and q-values are presented in Table S4. Note: CHS, Children’s Health Study; PFAS, per- and polyfluoroalkyl substances; SD, standard deviation; SOLAR, Study of Latino Adolescents at Risk.
Figure 5 is a coefficient plot, plotting Vitamin B 6 (pyridoxine) metabolism, including 4-Pyridoxic acid and Pyridoxamine and porphyrin metabolism, including Biliverdin and Bilirubin (y-axis) across Per- and polyfluoroalkyl substances mixture effect uppercase psi (95 percent Bayesian credible interval), ranging from negative 1 to 2 in unit increments (x-axis) for Only significant in one cohort.
Figure 5.
Associations between PFAS mixtures and metabolites associated with metabolism of cofactors in adolescents from the SOLAR cohort (n=312). No significant associations were observed in the CHS cohort. Effect estimates for PFAS mixture (ψ) and the 95% Bayesian credible interval (BCI) estimate the change in metabolite levels (SD of the log-transformed feature intensity) when increasing all PFAS in the mixture from the 30th percentile to the 70th percentile. This estimate is also equivalent to a standardized mean difference calculated between a hypothetical group of individuals with all PFAS at the 70th percentile vs. a hypothetical group of individuals with all PFAS at the 30th percentile. Corresponding p-values and q-values are presented in Table S4. Note: CHS, Children’s Health Study; PFAS, per- and polyfluoroalkyl substances; SD, standard deviation; SOLAR, Study of Latino Adolescents at Risk.

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