Ncbi Early Life Exposure to Per- and Polyfluoroalkyl Substances (Pfass) a Critical Review

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Environ Int. Author manuscript; available in PMC 2019 Feb one.

Published in final edited form as:

PMCID: PMC5801004

NIHMSID: NIHMS921809

Early life exposure to per- and polyfluoroalkyl substances and mid-childhood lipid and alanine aminotransferase levels

Ana M. Mora,^{a, b} Abby F. Fleisch,^{c, d} Sheryl Fifty. Rifas-Shiman,^eastward Jennifer Due west. Baidal,^f Larissa Pardo,^b Thomas F. Webster,^g Antonia One thousand. Calafat,^h Xiaoyun Ye,^h Emily Oken,^{due east, i} and Sharon K. Sagiv^{a, j}

Ana Grand. Mora

^aCenter for Environmental Research and Children'south Health (CERCH), School of Public Wellness, University of California, Berkeley, Berkeley, California, The states

^bFundamental American Institute for Studies on Toxic Substances, Universidad Nacional, Heredia, Costa rica

Abby F. Fleisch

^cPediatric Endocrinology and Diabetes, Maine Medical Middle, Portland, Maine, U.s.a.

^dCenter for Outcomes Research and Evaluation, Maine Medical Centre Enquiry Institute, Portland, Maine, USA

Sheryl 50. Rifas-Shiman

^eDivision of Chronic Disease Enquiry Across the Lifecourse, Section of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA

Jennifer W. Baidal

^fPartition of Pediatric Gastroenterology, Hepatology, and Nutrition, Columbia University Medical Centre, New York, New York, USA

Larissa Pardo

^bCentral American Institute for Studies on Toxic Substances, Universidad Nacional, Heredia, Costa rica

Thomas F. Webster

^gDepartment of Ecology Health, Boston University School of Public Wellness, Boston, Massachusetts, USA

Antonia M. Calafat

^hDivision of Laboratory Sciences, National Center for Ecology Wellness, Centers for Disease Command and Prevention, Atlanta, Georgia, United states of america

Xiaoyun Ye

^hPartitioning of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Emily Oken

^eDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, U.s.

ⁱDepartment of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA

Sharon K. Sagiv

^aCenter for Environmental Research and Children's Health (CERCH), School of Public Wellness, University of California, Berkeley, Berkeley, California, U.s.a.

^jSectionalisation of Epidemiology, School of Public Wellness, University of California, Berkeley, Berkeley, California, USA

Abstruse

Groundwork

Growing show suggests that exposure to per- and polyfluoroalkyl substances (PFASs) may disrupt lipid homeostasis and liver part, but data in children are express.

Objective

Nosotros examined the association of prenatal and mid-childhood PFAS exposure with lipids and alanine aminotransferase (ALT) levels in children.

Methods

Nosotros studied 682 female parent-kid pairs from a Boston-surface area pre-birth cohort. Nosotros quantified PFASs in maternal plasma collected in pregnancy (median 9.vii weeks gestation, 1999–2002) and in child plasma collected in mid-childhood (median age 7.7 years, 2007–2010). In mid-childhood we also measured fasting full (TC), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and ALT. Nosotros then derived low-density lipoprotein cholesterol (LDL-C) from TC, HDL-C, and TG using the Friedewald formula.

Results

Median (interquartile range, IQR) perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), and perfluorodecanoate (PFDeA) concentrations in kid plasma were 6.two (5.v), 4.3 (three.0), and 0.3 (0.3) ng/mL, respectively. Among girls, higher child PFOS, PFOA, and PFDeA concentrations were associated with detrimental changes in the lipid contour, including higher TC and/or LDL-C [e.g., β per IQR increment in PFOS = 4.0 mg/dL (95% CI: 0.three, seven.eight) for TC and 2.six mg/dL (−0.5, 5.8) for LDL-C]. Withal, amongst both boys and girls, higher plasma concentrations of these child PFASs were also associated with higher HDL-C, which predicts better cardiovascular wellness, and slightly lower ALT, which may indicate meliorate liver function. Prenatal PFAS concentrations were too modestly associated with improved childhood lipid and ALT levels.

Conclusions

Our data suggest that prenatal and mid-childhood PFAS exposure may be associated with modest, simply somewhat conflicting changes in the lipid profile and ALT levels in children.

Keywords: per- and polyfluoroalkyl substances, lipids, liver function, pregnancy, babyhood

1. Introduction ^ane

Per- and polyfluoroalkyl substances (PFASs) – synthetic compounds used in a broad range of industrial and consumer products, including stain-resistant coatings for upholstery and fabrics, pesticide additives, coatings for nutrient packaging, and fire-retardant foams (Lindstrom et al. 2011) – have structural homology with fat acids (Fletcher et al. 2013) and may have endocrine-disrupting properties (Braun 2017). Evidence suggests that PFAS exposure may contribute to lipid- and liver enzyme-related metabolic disturbances (Steenland et al. 2010) through activation of the peroxisome proliferator-activated receptors (PPAR) alpha (α) (Wolf et al. 2008) and gamma (γ) (Vanden Heuvel et al. 2006), and/or altered expression of lipid transport- and metabolism-related genes (Fletcher et al. 2013).

Most animate being studies have shown that PFAS exposure can induce beneficial changes in circulating lipids, including lower total cholesterol (TC) and triglycerides (TG) (Kennedy et al. 2004; Lau et al. 2007; White et al. 2011). Human studies accept reported conflicting associations of PFASs with lipids, with cross-sectional studies in adults and children reporting associations of higher PFASs concentrations with detrimental [i.east., higher circulating TC, low-density lipoprotein cholesterol (LDL-C), and TG] (Costa et al. 2009; Eriksen et al. 2013; Fitz-Simon et al. 2013; Geiger et al. 2014; Nelson et al. 2010; Sakr et al. 2007a; Sakr et al. 2007b; Starling et al. 2014; Steenland et al. 2009; Zeng et al. 2015) and beneficial changes in lipid profile [i.eastward., higher high-density lipoprotein cholesterol (HDL-C)] (Chateau-Degat et al. 2010; Starling et al. 2014). One of two published studies that explored associations of prenatal PFASs with mid-babyhood lipids observed not-linear associations of perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) (ii of the most prevalent and ordinarily studied PFASs) with serum lipids (TC and LDL-C): at depression PFAS concentrations (lower tertile), PFAS-related associations with lipids were beneficial and at high PFAS concentrations (middle and upper tertiles), PFAS-related associations with lipids were detrimental (Maisonet et al. 2015). The other study observed beneficial associations of prenatal perfluorohexane sulfonate (PFHxS) plasma concentrations with TG z-scores measured in early babyhood (Manzano-Salgado et al. 2017). These studies did not examine the association betwixt postnatal PFAS exposure and childhood lipids.

Contempo cross-sectional and cohort studies in adults accept investigated the clan betwixt PFASs and liver enzymes – markers of hepatocellular dysfunction – with inconsistent results (Alexander et al. 2007; Costa et al. 2009; Darrow et al. 2016; Emmett et al. 2006; Gallo et al. 2012; Gleason et al. 2015; Lin et al. 2009; Sakr et al. 2007a; Sakr et al. 2007b). For instance, PFAS concentrations accept been positively associated with alanine aminotransferase (ALT) levels in some population-based (Darrow et al. 2016; Gallo et al. 2012; Gleason et al. 2015) and occupational studies (Alexander and Olsen 2007; Lin et al. 2009; Sakr et al. 2007a), simply not in others (Costa et al. 2009; Sakr et al. 2007b). To our cognition, no study has examined the clan of prenatal or postnatal PFAS exposure with liver enzymes in children.

Projection Viva is a prospective pre-birth accomplice designed to report the extent to which events during early development affect health outcomes over the lifespan. In previous analyses of PFASs in Project Viva, nosotros observed pocket-sized associations with increased adiposity and risk of obesity in girls, just non boys, in mid-childhood (Mora et al. 2017). However, we found no adverse furnishings of early-life PFAS exposure on leptin, adiponectin, or homeostatic assessment of insulin resistance (HOMA-IR) in mid-childhood; in fact, children with college plasma concentrations of some PFASs had lower insulin resistance (Fleisch et al. 2017). In light of these findings, and given that animal data have shown that early-life exposure to PFASs may disrupt lipid metabolism and induce hepatotoxic effects (Kennedy et al. 2004; Lau et al. 2007; White et al. 2011), we evaluated the extent to which PFAS concentrations in prenatal and mid-childhood plasma were associated with childhood lipids and ALT in Project Viva.

2. Methods

2.1. Study population

Significant women were enrolled in Project Viva from 1999 to 2002 during their first prenatal visit to Atrius Harvard Vanguard Medical Associates, a multi-specialty group practice in Eastern Massachusetts (Oken et al. 2015). Of 2,128 live singleton offspring, 1,776 (84%) children had PFAS concentrations measured in maternal non-fasting plasma collected in early on pregnancy [median (range) ix.7 (four.8–21.4) weeks gestation, n = 1,645] or in kid fasting plasma nerveless in mid-childhood [median historic period (range) 7.7 (6.7–11.0) years, north = 653]. Of these i,776 children, 682 (38%) had lipids or ALT measured in fasting mid-childhood plasma samples (aforementioned samples used to mensurate PFAS; see Figure A.1).

Institutional Review Boards of participating sites approved all study protocols. All mothers provided written informed consent at each written report visit and children provided verbal assent at the mid-childhood visit. The involvement of the Centers for Disease Command and Prevention (CDC) laboratory did not constitute engagement in human subjects research.

2.ii. Prenatal and child PFAS measurements

Maternal and kid plasma samples were shipped to the Segmentation of Laboratory Sciences at the CDC and analyzed for concentrations of eight PFAS analytes: PFOS, PFOA, PFHxS, perfluorononanoate (PFNA), two-(N-ethyl-perfluorooctane sulfonamido) acetate (Et-PFOSA-AcOH; also known equally EtFOSAA), 2-(N-methyl-perfluorooctane sulfonamido) acetate (Me-PFOSA-AcOH; also known as MeFOSAA), perfluorodecanoate (PFDeA), and perfluorooctane sulfonamide (PFOSA; likewise known every bit FOSA). Child plasma samples were also analyzed for concentrations of linear and branched isomers of PFOS and PFOA (we did not measure out linear and branched isomers in our maternal samples because they were analyzed earlier): n-perfluorooctane sulfonate (n-PFOS), perfluoromethylheptane sulfonates (Sm-PFOS), perfluorodimethylhexane sulfonates (Sm2-PFOS), n-perfluorooctanoate (n-PFOA), and branched perfluorooctanoates (Sb-PFOA). All samples were analyzed using online solid-phase extraction coupled with isotope dilution high-operation liquid chromatography-tandem mass spectrometry, as previously described (Fleisch et al. 2017; Harris et al. 2017; Sagiv et al. 2015). Limits of detection (LOD) were 0.1 ng/mL for all PFASs except for PFOS concentrations in prenatal plasma (0.2 ng/mL). Values below the LOD were replaced with LOD divided past the square root of 2.

ii.3. Lipids and ALT levels in mid-babyhood

We measured fasting TC, HDL-C, TG, and ALT using enzymatic assays, in the same plasma samples used for quantification of mid-babyhood PFASs. We and so calculated LDL-C using the Friedewald formula: TC-(HDL-C)-(TG × 0.2) (Friedewald et al. 1972). We also calculated the ratio of TC to HDL-C, an indicator of the detrimental portion of the lipid contour (Millan et al. 2009).

2.4. Potential confounders and predictors of lipids and ALT levels

Nosotros collected information on maternal age, marital condition, education, parity, smoking habits, and household income using in-person interviews at written report enrollment. We besides assessed maternal albumin concentrations and glomerular filtration rate (GFR), 2 markers of pregnancy hemodynamics that have been hypothesized as potential confounders of PFAS-outcomes associations (Savitz 2014; Verner et al. 2015). We measured albumin and creatinine concentrations in the same early pregnancy plasma specimens used for PFASs quantification and then calculated GFR using the Cockroft-Gault formula [GFR-CG = (140-age) × weight (kg) × 1.04/serum creatinine (μmol/L)] (Cockcroft et al. 1976). Albumin is the master binding poly peptide for PFASs (D'Eon J et al. 2010) and besides an indicator for plasma volume expansion during pregnancy.

Nosotros abstracted engagement of delivery from medical records. We collected information on child sex, race/ethnicity, breastfeeding duration, fast food and soda intake, physical activity, and screen time using mailed questionnaires and in-person interviews throughout childhood. Lastly, nosotros measured child height and weight at the mid-childhood visit and calculated body mass index (BMI) as weight (kg)/elevation (k)ⁱⁱ.

two.5. Statistical analyses

We decided a priori to include in our analyses only PFASs with a detection frequency of 70% or more (Lubin et al. 2004), which included six prenatal (PFOS, PFOA, PFNA, PFHxS, EtFOSAA, and MeFOSAA) and five mid-childhood PFASs (PFOS, PFOA, PFNA, PFHxS, and PFDeA).

Nosotros examined associations of prenatal and mid-babyhood PFAS plasma concentrations with lipids and ALT in mid-childhood using multivariable linear regression models. Nosotros modeled PFAS concentrations as continuous variables, with signal estimates representing the change in outcome per interquartile range (IQR) increment in exposure in order to facilitate comparisons across PFAS analytes with different distributions within our study population. To evaluate nonlinearity, we fitted generalized additive models (GAM) with penalized spline polish terms for the exposures (all p _GAM > 0.05); we besides modeled PFAS concentrations in quartiles to limit the influence of extreme values. Nosotros interpreted effect estimates based on their magnitude and precision.

We identified potential confounders and known predictors of the outcomes of interest (i.e. maternal education, smoking during pregnancy, gestational age at blood draw, and kid's sex, race/ethnicity, and age at lipids/ALT measurements) using directed acyclic graphs. These covariates were included a priori in regression models. We assessed other covariates reported in the literature [household income, maternal marital status, maternal plasma albumin concentrations and GFR during pregnancy (only for prenatal PFASs), breastfeeding duration; and child's concrete activity, screen fourth dimension, and fast food and soda consumption (only for mid-childhood PFASs)] by adding them, one at a time, to the last models, but none of them materially changed the PFAS coefficients. Missing values (< ten%) for covariates (i.due east., marital status, maternal education, annual household income, smoking status, and kid race/ethnicity) were imputed past randomly selecting a value from the dataset (Lubin et al. 2004). Because we were missing data on child race/ethnicity for nigh 10% of the study participants, we also created a divide variable for which nosotros substituted the missing values with maternal race/ethnicity. We constitute minimal differences betwixt the randomly imputed and substitution variables, then we decided to adjust our models for the former in club to exist consequent with our imputation method.

Considering previous studies take observed sexual practice-specific associations between PFASs and lipids (Eriksen et al. 2013; Frisbee et al. 2010), we examined whether child sex activity modified the exposure-outcome associations using a product interaction term between kid sexual activity and prenatal or mid-childhood PFAS IQRs (or quartiles) and also stratifying by sex.

We conducted several sensitivity analyses to assess the robustness of our results. First, given that a few studies have linked specific PFAS isomers to health outcomes (Bao et al. 2017; Yu et al. 2015), we examined the extent to which different isomers of mid-childhood PFASs were associated with lipids and ALT. We considered all isomer concentrations with a detection frequency of 70% or more than [due north-PFOS, Sm-PFOS, and n-PFOA (all with 99.5% detectable values) (CDC 2015; Fleisch et al. 2017)]. 2nd, we included all prenatal PFASs in the prenatal covariate-adapted models and all mid-childhood PFASs in the mid-childhood models to examine co-pollutant confounding. Finally, because prenatal PFAS concentrations have been positively associated with adiposity (Mora et al. 2017) and adiposity is an important determinant of lipids in childhood (Dai et al. 2009; Plourde 2002), we included mid-childhood BMI (kg/m²) in both combined and sex activity-stratified models to explore its potential effect every bit mediator of the PFAS-lipids associations.

3. Results

3.1. Participants' characteristics

On boilerplate, meaning women included in the present analyses were 32.four years old at enrollment [standard deviation (SD) = v.6]. Approximately ninety% were married or cohabitating with their partners, 58% were multiparous, 65% had a college degree or greater, 62% had an annual household income higher than $70,000, and 69% had never smoked (Table 1). L-two percent of children were boys and 59% were white. Maternal and child characteristics were similar among boys and girls (Table 1).

Table 1

Characteristics [n (%) or median (P25-P75)] of Projection Viva study participants included in present analyses.

	All children (n = 682)	Boys (due north = 356)	Girls (n = 326)	p-valuea
Maternal/family characteristics
Age at enrollment (years)
<20	27 (four.0)	14 (iii.9)	13 (4.0)	0.99
20-<35	434 (63.6)	226 (63.v)	208 (63.8)
≥35	221 (32.4)	116 (32.6)	105 (32.ii)
Married/cohabitatingb
No	73 (10.vii)	35 (nine.eight)	38 (11.7)	0.44
Yes	609 (89.iii)	321 (90.two)	288 (88.3)
Parity
0	287 (42.1)	152 (42.7)	135 (41.iv)	0.85
1	254 (37.ii)	129 (36.ii)	125 (38.iii)
≥2	141 (20.7)	75 (21.1)	66 (xx.3)
Pedagogyb
<College graduate	242 (35.v)	133 (37.iv)	109 (33.4)	0.56
College graduate	245 (35.9)	124 (34.8)	121 (37.1)
Graduate school	195 (28.six)	99 (27.8)	96 (29.5)
Annual household income (USD $)a
<40,000	120 (17.six)	58 (16.iii)	62 (19.0)	0.64
40,000–70,000	141 (20.seven)	74 (20.8)	67 (20.half dozen)
>70,000	421 (61.seven)	224 (62.9)	197 (60.4)
Smoking statusb
Never smoked	473 (69.four)	241 (67.7)	232 (71.ii)	0.62
Former smoker	133 (19.v)	73 (20.5)	60 (18.4)
Smoked during pregnancy	76 (eleven.1)	42 (11.8)	34 (ten.4)
Gestational age at prenatal PFAS measurements (weeks)c	9.6 (8.half-dozen–10.7)	9.six (8.seven–10.7)	9.seven (8.four–10.7)	0.75
Child characteristics
Race/ethnicityb
Black	159 (23.iii)	84 (23.vi)	75 (23.0)	0.93
White	403 (59.i)	208 (58.iv)	195 (59.8)
Other	120 (17.6)	64 (18.0)	56 (17.two)
BMI in mid-childhood (kg/yard2)	16.6 (fifteen.4–18.iv)	sixteen.4 (15.four–17.ix)	16.7 (15.3–18.8)	0.08
Age at mid-childhood PFAS and lipids/ALT measurements (years)	vii.vii (7.iv–8.iv)	7.7 (7.4–eight.five)	7.7 (7.3–8.ii)	0.16

Mid-babyhood PFOS, PFOA, PFNA, and PFHxS concentrations were lower than prenatal concentrations quantified in maternal samples (Table 2). Spearman correlation coefficients of PFAS concentrations measured in prenatal plasma ranged between 0.20 and 0.72 and in mid-childhood plasma ranged betwixt 0.14 and 0.79 (strongest correlation for PFOS and PFOA; encounter Tabular array A.i). Correlations of the same PFASs measured in prenatal versus mid-babyhood plasma ranged between 0.08 and 0.40 (see Tabular array A.1). Prenatal and mid-childhood PFAS concentrations did not vary by child sexual practice (Tabular array 2).

Table 2

Distribution of prenatal PFAS concentrations and mid-childhood PFAS (ng/mL), lipid (mg/dL) and ALT (U/L) concentrations in the study population.

	All childrena			Boysa	Girlsa
	%>LODb	Range	Median (P25-P75)	Median (P25-P75)	Median (P25-P75)	p-valuec
Exposures
Prenatal PFAS
PFOS	100.0	4.6–168.0	24.6 (17.9–34)	24.3 (17.8–34.iv)	24.vii (xviii.two–32.9)	0.92
PFOA	100.0	0.ix–22.4	v.4 (3.9–vii.half dozen)	5.five (iv.0–7.3)	5.iv (3.viii–7.9)	0.53
PFNA	99.0	0.1–2.6	0.6 (0.v–0.9)	0.6 (0.v–0.9)	0.6 (0.5–0.9)	0.56
PFHxS	99.seven	0.one–43.ii	ii.4 (1.vi–3.eight)	ii.5 (1.vi–three.8)	2.two (i.iv–iii.9)	0.22
EtFOSAA	99.6	0.i–21.ii	1.2 (0.i–21.2)	1.i (0.7–one.8)	i.2 (0.vii–1.9)	0.72
MeFOSAA	100.0	0.1–29.vii	2.0 (1.3–three.two)	2.0 (ane.3–3.1)	two.0 (1.three–three.2)	0.96
Mid-babyhood PFAS
PFOS	99.5	0.1–51.iv	6.2 (four.2–9.7)	6.3 (four.2–nine.8)	6.1 (iv.1–nine.6)	0.49
due north-PFOS	99.5	0.one–34.2	4.4 (three.0–vii.0)	4.iv (3.0–seven.one)	4.5 (2.nine–half dozen.9)	0.57
sm-PFOS	99.5	0.i–xvi.eight	1.7 (1.1–2.8)	1.8 (ane.2–2.9)	1.7 (1.ane–two.vii)	0.33
sm2-PFOS	1.4	0.1–0.4	0.1 (0.1–0.one)	0.1 (0.1–0.1)	0.1 (0.1–0.1)	0.86
PFOA	99.5	0.ane–fourteen.iii	four.3 (three.0–6.0)	iv.4 (three.ane–6.0)	4.2 (three.0–6.one)	0.69
n-PFOA	99.5	0.i–13.viii	four.1 (iii.0–5.vii)	iv.one (3.0–five.seven)	4.0 (ii.viii–five.7)	0.56
sb-PFOA	57.three	0.1–2.4	0.two (0.1–0.4)	0.two (0.ane–0.four)	0.two (0.1–0.iv)	0.71
PFNA	99.5	0.one–25.seven	ane.5 (1.one–2.3)	1.5 (1.one–two.two)	1.5 (1.one–2.3)	0.83
PFHxS	99.5	0.1–56.eight	i.ix (1.2–3.4)	1.9 (i.2–iii.eight)	1.9 (1.ii–3.2)	0.16
PFDeA	88.1	0.1–ane.9	0.3 (0.ii–0.5)	0.3 (0.2–0.5)	0.4 (0.2–0.5)	0.26
Mid-childhood outcomes d
Lipids
Full cholesterol		78.0–288.0	160.0 (141.0–176.0)	160.0 (140.0–178.0)	159.0 (144.0–175.0)	0.ninety
LDL-C		10.1–183.0	90.6 (76.v–103.9)	89.4 (74.five–103.ix)	92.1 (79.ix–104.vi)	0.11
HDL-C		24.seven–144.iv	55.eight (47.7–64.five)	57.5 (49.8–66.three)	54.3 (46.5–62.3)	<0.01
Total/HDL-C × 100		135.half-dozen–753.0	281.5 (243.i–332.6)	277.4 (236.three–314.one)	289.3 (250.0–346.8)	<0.01
Triglycerides		xiii.0–756.0	52.0 (41.0–68.0)	51.0 (41.0–67.0)	54.0 (42.0–70.0)	0.13
Liver enzyme
ALT		eight.0–76.0	nineteen.0 (sixteen.0–23.0)	19.0 (16.0–24.0)	19.0 (16.0–23.0)	0.93

Overall, median (IQR) TC in mid-childhood was 160.0 (35.0) mg/dL, LDL-C 90.vi (27.four) mg/dL, HDL-C 55.8 (sixteen.viii) mg/dL, TC/HDL-C ratio (× 100) 281.5 (89.v), TG 52.0 (27.0) mg/dL, and ALT xix.0 (7.0) U/L (Tabular array 2). About 17%, 13%, and 15% of children had high TC (≥ 200 mg/dL), LDL-C (≥ 130 mg/dL), and TG (≥ 100 mg/dL), whereas 8% had low HDL-C (<40 mg/dL) (NIH 2012). Amidst boys, we observed higher HDL-C [median (IQR) 57.5 (16.five)] than amid girls [54.3 (xv.8); p < 0.05; Table ii]. Among girls, we found higher TC/HDL-C ratios [289.two (96.8)] than among boys [277.4 (77.8); p < 0.05].

Compared to mothers of children included in the present analysis (northward = 682; Table 1), mothers from the initial cohort (n = 2,128) were more likely to be nulliparous (48%), have an annual household income of forty,000–70,000 USD$ (23%), and had slightly higher plasma PFAS concentrations [e.thou., median (interquartile range, IQR) PFOS and PFOA concentrations in mothers with PFAS measurements during pregnancy (northward = 1,645) 25.vii (16.0) and 5.8 (iii.eight) ng/mL]; their children were as well more likely to be white (67%) or have other race/ethnicity (20%; information not shown).

3.2. Associations of prenatal PFAS with lipids and ALT in mid-childhood

We did not detect strong associations of prenatal plasma PFAS concentrations with lipids and ALT measured in mid-babyhood in analyses of boys and girls combined (Table 3). Yet, among girls, we found that college prenatal PFOS and PFOA concentrations were associated with a beneficial lipoprotein profile, including lower TG and TC/HDL-C ratio (× 100) [e.grand., β per IQR increment in PFOS = −iv.2 mg/dL (95% conviction interval (CI): −9.2, 0.viii) for TG, p _INT = 0.04; and −7.vii (95% CI: −16.0, 0.half-dozen) for TC/HDL-C, p _INT = 0.08; Table 3]. Prenatal PFOA plasma concentrations were besides associated with college HDL-C, a predictor of better cardiovascular health, among girls [β per IQR increment = ane.2 mg/dL (95% CI: −0.8, −3.two), p _INT = 0.03; Table three]. In quartile analyses, we institute overall, but non strictly monotonic, lower TG and TC/HDL-C ratio (× 100) and college HDL-C beyond higher quartiles (Q3 and/or Q4) of PFOS and/or PFOA concentrations amongst girls (versus Q1; data not shown). Lastly, most all prenatal PFAS exposures were negatively associated with ALT levels among girls [due east.g., β per IQR increment in MeFOSAA = −ane.two U/L (95% CI: −i.9, −0.five); p _INT = 0.05; Tabular array 3].

Table 3

Adjusted linear regression coefficients for associations of prenatal PFAS concentrations with lipid and ALT levels in mid-childhood among all children and stratified past child sexual activity.

	All childrena	Boysb	Girlsc
	β (95% CI)	β (95% CI)	β (95% CI)	p int
Lipids
Total cholesterol (mg/dL)
PFOS	0.8 (−1.6, 3.3)	1.4 (−1.9, iv.viii)	−0.4 (−iii.v, ii.7)	0.24
PFOA	0.5 (−2.three, 3.4)	ane.4 (−2.8, v.7)	0.0 (−3.8, 3.nine)	0.63
PFNA	0.2 (−two.4, 2.eight)	2.0 (−2.3, half dozen.2)	−ane.iv (−4.8, 1.nine)	0.23
PFHxS	0.5 (−one.1, two.2)	0.half dozen (−2.4, 3.6)	0.four (−i.3, ii.2)	0.99
EtFOSAA	0.1 (−1.2, 1.4)	0.0 (−ane.9, 1.ix)	0.0 (−1.vi, one.6)	0.68
MeFOSAA	−0.ane (−2.1, 2.0)	0.three (−two.1, 2.8)	−0.i (−3.two, 2.9)	0.46
LDL cholesterol (mg/dL)
PFOS	0.5 (−1.5, 2.6)	0.vi (−ii.two, 3.5)	−0.1 (−2.eight, two.5)	0.38
PFOA	0.7 (−1.8, 3.1)	2.2 (−1.5, v.eight)	−0.vii (−4.0, 2.half-dozen)	0.eighteen
PFNA	0.five (−1.8, 2.8)	2.3 (−1.3, 6.0)	−1.two (−iv.0, ane.7)	0.12
PFHxS	0.5 (−0.9, 1.ix)	0.4 (−2.3, iii.2)	0.5 (−0.9, ane.viii)	0.98
EtFOSAA	0.5 (−0.5, 1.6)	0.2 (−i.2, one.7)	0.7 (−0.seven, 2.one)	0.86
MeFOSAA	0.i (−1.eight, two.0)	0.6 (−1.vii, ii.ix)	−0.iii (−3.0, 2.4)	0.38
HDL cholesterol (mg/dL)
PFOS	0.six (−0.five, one.7)	0.6 (−0.8, 2.0)	0.6 (−0.9, two.1)	0.93
PFOA	−0.2 (−i.vi, 1.2)	−1.ii (−3.i, 0.half dozen)	1.two (−0.8, 3.2)	0.03
PFNA	0.2 (−1.2, 1.6)	−0.i (−2.0, one.8)	0.3 (−1.7, ii.3)	0.41
PFHxS	0.ane (−0.5, 0.7)	0.0 (−one.0, 1.0)	0.2 (−0.5, 0.eight)	0.48
EtFOSAA	−0.ii (−0.9, 0.5)	−0.two (−1.0, 0.7)	−0.4 (−i.6, 0.9)	0.89
MeFOSAA	−0.2 (−1.0, 0.vi)	−0.4 (−1.2, 0.5)	0.4 (−one.2, 2.0)	0.65
Total/HDL-C × 100
PFOS	−3.iv (−nine.one, 2.four)	−0.8 (−8.8, vii.three)	−7.7 (−16.0, 0.6)	0.08
PFOA	−1.0 (−8.7, 6.8)	half dozen.ix (−iii.6, 17.5)	−10.4 (−21.1, 0.two)	0.01
PFNA	−one.8 (−8.9, five.3)	five.2 (−4.8, 15.3)	−7.8 (−17.4, one.seven)	0.02
PFHxS	−0.1 (−3.4, 3.1)	1.iii (−5.2, 7.viii)	−1.0 (−4.6, 2.7)	0.37
EtFOSAA	0.1 (−iii.ane, iii.iii)	0.one (−4.0, 4.2)	−0.0 (−4.9, four.ix)	0.59
MeFOSAA	−0.6 (−6.ane, 5.0)	i.6 (−4.two, vii.4)	−four.8 (−14.5, 4.nine)	0.22
Triglycerides (mg/dL)
PFOS	−i.4 (−iv.6, 1.8)	1.0 (−2.2, 4.2)	−iv.2 (−9.2, 0.8)	0.04
PFOA	0.2 (−three.3, 3.viii)	two.five (−2.0, 6.9)	−ii.iv (−viii.1, 3.iii)	0.13
PFNA	−two.5 (−v.viii, 0.8)	−1.5 (−iv.nine, 1.9)	−2.9 (−8.1, 2.4)	0.35
PFHxS	−0.6 (−2.0, 0.eight)	0.6 (−1.9, 3.1)	−ane.one (−3.1, i.0)	0.22
EtFOSAA	−1.0 (−2.4, 0.4)	−0.three (−2.1, one.5)	−1.6 (−3.three, 0.1)	0.43
MeFOSAA	−0.1 (−ii.ane, 2.0)	0.five (−1.2, ii.one)	−i.3 (−seven.7, v.0)	0.55
Liver enzymes
ALT (U/L)
PFOS	−0.four (−1.1, 0.2)	−0.two (−1.ii, 0.8)	−0.7 (−1.iv, 0.1)	0.71
PFOA	−0.5 (−one.3, 0.ii)	−0.5 (−1.6, 0.6)	−0.7 (−1.7, 0.4)	0.96
PFNA	−0.1 (−0.ix, 0.6)	0.3 (−1.0, one.6)	−0.six (−1.4, 0.2)	0.32
PFHxS	−0.ane (−0.four, 0.ii)	−0.0 (−0.six, 0.half-dozen)	−0.i (−0.4, 0.2)	0.75
EtFOSAA	−0.1 (−0.5, 0.2)	0.1 (−0.4, 0.6)	−0.4 (−0.8, 0.0)	0.35
MeFOSAA	−0.2 (−1.ane, 0.seven)	0.2 (−0.7, 1.ane)	−ane.ii (−ane.9, −0.v)	0.05

iii.3. Associations of child PFAS with lipids and ALT in mid-babyhood

Mid-babyhood PFAS plasma concentrations were associated with both detrimental (increased TC and LDL-C) and beneficial (increased HDL-C and decreased TG) changes in circulating lipid profile in combined (all children) and sex activity-stratified analyses (Table 4). Specifically, among girls, college mid-childhood PFOS, PFOA, and PFDeA concentrations were associated with a higher TC and LDL-C [e.chiliad., β per IQR increment in PFOS = iv.0 mg/dL (95% CI: 0.3, 7.viii) for TC, p _INT = 0.xix; and ii.six mg/dL (95% CI: −0.five, 5.viii) for LDL-C, p _INT = 0.twenty; Tabular array 4]. While not strictly monotonic, we institute overall college TC and LDL-C across higher quartiles of PFOS, PFOA, and PFDeA among girls (come across Figure A.2).

Table four

Adapted linear regression coefficients for associations of mid-babyhood PFAS concentrations with lipid and ALT levels in mid-childhood amidst all children and stratified by kid sex.

	All childrena	Boysb	Girlsc
	β (95% CI)	β (95% CI)	β (95% CI)	p int
Lipids
Full cholesterol (mg/dL)
PFOS	1.8 (−0.2, 3.7)	0.5 (−ane.8, 2.9)	4.0 (0.3, 7.8)	0.19
PFOA	2.half-dozen (−0.v, five.7)	one.2 (−iii.0, v.4)	5.2 (0.four, 9.9)	0.26
PFNA	0.six (−0.vii, 1.9)	0.4 (−1.two, i.9)	1.0 (−1.4, iii.4)	0.72
PFHxS	−0.3 (−1.0, 0.5)	−0.five (−1.v, 0.4)	0.2 (−ane.0, 1.3)	0.38
PFDeA	6.8 (3.6, 10.ane)	5.iii (0.viii, 9.8)	ix.2 (four.iii, fourteen.1)	0.25
LDL cholesterol (mg/dL)
PFOS	0.viii (−0.9, two.5)	−0.2 (−2.2, ane.9)	2.6 (−0.5, 5.viii)	0.xx
PFOA	0.9 (−1.8, 3.half-dozen)	−0.3 (−3.nine, 3.iv)	3.0 (−one.0, vii.0)	0.27
PFNA	0.2 (−0.8, 1.3)	0.1 (−1.0, 1.two)	0.iv (−i.vii, 2.5)	0.86
PFHxS	−0.2 (−0.nine, 0.4)	−0.5 (−1.4, 0.3)	0.3 (−0.6, 1.3)	0.17
PFDeA	iii.2 (0.6, 5.eight)	ane.9 (−1.7, 5.4)	5.iii (1.ii, 9.four)	0.21
HDL cholesterol (mg/dL)
PFOS	1.five (0.4, 2.5)	ane.2 (0.0, 2.3)	2.0 (0.0, 4.0)	0.37
PFOA	1.5 (0.one, 2.nine)	i.v (−0.4, 3.3)	1.eight (−0.4, four.0)	0.54
PFNA	0.2 (−0.three, 0.vii)	0.ane (−0.six, 0.7)	0.5 (−0.iv, 1.3)	0.52
PFHxS	0.0 (−0.3, 0.four)	0.one (−0.iii, 0.5)	−0.1 (−0.5, 0.iv)	0.83
PFDeA	iv.three (2.six, 6.0)	iii.7 (1.2, 6.2)	v.two (3.0, vii.iii)	0.34
Total/HDL-C × 100
PFOS	−four.4 (−9.4, 0.6)	−five.0 (−x.3, 0.3)	−3.ix (−xiv.seven, 6.8)	0.87
PFOA	−2.seven (−10.1, 4.7)	−5.four (−14.1, 3.3)	0.6 (−12.four, 13.5)	0.80
PFNA	0.1 (−two.0, 2.iii)	0.7 (−2.ane, three.five)	−0.9 (−4.5, 2.7)	0.51
PFHxS	−0.6 (−2.2, 1.0)	−ane.one (−3.i, 0.9)	0.2 (−2.5, 3.0)	0.56
PFDeA	−x.i (−18.2, −two.one)	−viii.0 (−18.0, 1.9)	−12.iii (−25.3, 0.vii)	0.53
Triglycerides (mg/dL)
PFOS	−2.5 (−4.3, −0.6)	−2.three (−four.3, −0.3)	−3.1 (−7.0, 0.ix)	0.34
PFOA	1.0 (−2.4, 4.5)	−0.2 (−3.4, 3.0)	2.0 (−4.5, eight.4)	0.74
PFNA	0.9 (−0.2, 2.0)	1.one (−0.1, 2.3)	0.8 (−ane.7, 3.iii)	0.87
PFHxS	−0.4 (−1.0, 0.3)	−0.three (−1.2, 0.vi)	−0.v (−1.3, 0.three)	0.42
PFDeA	−iii.half-dozen (−8.2, i.0)	−i.3 (−4.6, 2.0)	−half-dozen.3 (−fifteen.v, 2.ix)	0.31
Liver enzymes
ALT (U/50)
PFOS	−0.3 (−0.9, 0.2)	−0.3 (−1.2, 0.5)	−0.4 (−1.0, 0.3)	0.74
PFOA	−0.7 (−ane.4, 0.0)	−0.half dozen (−1.half dozen, 0.4)	−0.ix (−1.viii, 0.0)	0.42
PFNA	−0.3 (−0.five, −0.1)	−0.four (−0.6, −0.2)	−0.two (−0.5, 0.1)	0.39
PFHxS	0.0 (−0.2, 0.two)	−0.1 (−0.4, 0.2)	0.1 (−0.1, 0.4)	0.30
PFDeA	−0.3 (−1.2, 0.5)	0.1 (−1.3, ane.4)	−0.9 (−one.8, −0.i)	0.xvi

Paradoxically, among boys and girls combined, higher mid-babyhood PFOS, PFOA, and PFDeA plasma concentrations were associated with higher HDL-C and/or lower TG [eastward.yard., β per IQR increment in PFOS = ane.5 mg/dL (95% CI: 0.4, 2.5) for HDL-C and −two.5 mg/dL (95% CI: −4.three, −0.half-dozen) for TG; Table 4]. Child PFDeA plasma concentrations were also associated with a lower TC/HDL-C ratio (× 100) [β per IQR increase = −10.1 (95% CI: −18.2, −two.1); Table 4], with consistently larger effect estimates in children in college quartiles (Q3 and/or Q4) of PFDeA plasma concentrations (versus Q1; meet Figure A.2).

Nosotros found that higher child PFOA and PFNA concentrations were associated with slightly lower ALT [adjusted β per IQR increase = −0.7 U/L (95% CI: −ane.4, 0) for PFOA, and −0.three U/L (95% CI: −0.5, −0.i) for PFNA] among boys and girls combined (p _INT > 0.20; Table iv). In add-on, college mid-childhood PFDeA concentrations were associated with modestly lower ALT amid girls [adjusted β per IQR increment = −0.9 U/L (95% CI: −one.viii, −0.i), p _INT = 0.16; Table 4]. PFHxS concentrations were not associated with consistent changes in lipids or ALT (Table iv).

iii.4. Sensitivity analyses

Linear and branched isomers of PFOS and PFOA measured in mid-childhood plasma had like patterns of association with lipids and ALT as full concentrations of PFOS and PFOA in analyses of boys and girls combined [due east.thousand., β per IQR increment in n-PFOS = ane.4 (95% CI: 0.4, 2.five) for HDL-C, and −two.half dozen mg/dL (95% CI: −four.four, −0.8) for TG], with stronger associations amidst girls than among boys (run across Table A.two). When nosotros included all prenatal PFASs in the same prenatal models, nosotros continued to discover mostly null PFAS-outcome associations (data not shown). However, when we included all mid-childhood PFASs in the same mid-childhood models, associations of PFDeA concentrations with lipids marginally strengthened while associations with PFOS and PFOA tended to weaken (see Table A.3; all variance inflation factors <ten). Nosotros likewise observed an association betwixt PFOA concentrations and TG [β per IQR increment = eleven.i mg/dL (95% CI: 2.ane, twenty.i)], after adjusting for all mid-childhood PFASs in the same model. The inclusion of mid-childhood BMI in the models did not change the main event estimates (data non shown).

4. Discussion

In this prospective Boston-area pre-nascency cohort, we observed that higher mid-babyhood PFOA, PFOS, and PFDeA plasma concentrations were associated with detrimental changes in the lipid profile, including higher TC and LDL-C, and peculiarly among girls. We besides plant that higher prenatal and mid-babyhood PFOS, PFOA, and/or PFDeA concentrations were associated with some beneficial changes in the lipid profile, including slightly higher HDL-C, lower TG, and/or lower TC/HDL-C ratio, once again mainly among girls. Higher prenatal and mid-childhood PFAS concentrations were also associated with potentially improve liver role in children, indicated by slight decreases in ALT.

Conflicting findings from these analyses as well as previous analyses of PFASs in Project Viva (Fleisch et al. 2017; Mora et al. 2017) make it challenging to draw whatsoever firm conclusions about the impact of prenatal and early life PFAS exposure on babyhood metabolic function. However, at that place are a some notable parallels, including stronger associations of PFASs with higher adiposity (Mora et al. 2017) and poorer lipid profiles among girls. In addition, we establish notable beneficial effects of PFASs with insulin resistance (Fleisch et al. 2017) and some lipids also among girls. Diverging directions of PFAS-related associations with metabolic function may be biologically plausible given that these chemicals accept multiple mechanisms of activity. For instance, PFOS and PFOA have been shown to be associated with contradistinct expression of lipid transport- and metabolism-related genes in humans (Fletcher et al. 2013), which may result in increased cholesterol. On the other hand, growing testify suggests that PFASs activate the peroxisome proliferator-activated receptor (PPAR) alpha (α) (Wolf et al. 2008), and like fibric acid derivatives which likewise piece of work through this mechanism, may raise HDL-C and lower TG and LDL-C (Derosa et al. 2017; Pawlak et al. 2015). Additionally, PPAR gamma (γ) activation may explain the changed association of PFASs with liver enzymes (Pawlak et al. 2015; Ratziu et al. 2016) and insulin sensitivity (Janani et al. 2015). Further inquiry on the biological mechanisms underlying the associations of PFAS exposure with lipids, liver enzymes, and other cardiometabolic outcomes would help to disentangle these complex relationships. In addition, it is of import to note that it remains unclear whether fauna-based prove can be extrapolated to humans, as differences in toxicokinetics (Hundley et al. 2006) and PPAR-α ligand specificities (Oswal et al. 2013) between rodents and humans accept been documented.

Regardless of the mechanistic underpinnings, most studies that have examined the associations of PFAS exposure and lipids (measured in fasting or non-fasting samples) in children and adolescents have reported agin relationships (Frisbee et al. 2010; Geiger et al. 2014; Lin et al. 2009; Maisonet et al. 2015; Manzano-Salgado et al. 2017; Timmermann et al. 2014; Zeng et al. 2015). Higher child PFOS and PFOA serum concentrations were associated with higher TC and LDL-C at ages 12–15 years in Taiwan (Zeng et al. 2015) and ages 12–eighteen years across the United States (Geiger et al. 2014). Higher child PFNA and perfluorobutane sulfonate serum concentrations were also associated with college TC and/or LDL-C in Taiwanese adolescents ages 12–fifteen years (Zeng et al. 2015). Less consistent associations have been reported for PFASs and TG (Frisbee et al. 2010; Geiger et al. 2014; Maisonet et al. 2015; Manzano-Salgado et al. 2017; Timmermann et al. 2014; Zeng et al. 2015), and nothing associations were observed for HDL in most studies (Frisbee et al. 2010; Geiger et al. 2014; Lin et al. 2009; Maisonet et al. 2015; Zeng et al. 2015). One of two studies that have examined the association of prenatal PFAS exposure with lipids to date found that higher prenatal PFHxS plasma concentrations were associated with higher TG measured at iv years in Spanish boys and girls combined (Manzano-Salgado et al. 2017). This study besides observed that higher prenatal PFOA plasma concentrations were associated with higher HDL-C in girls, but lower HDL-C in boys. In a British birth cohort study of girls, higher prenatal PFOS and PFOA serum concentrations were associated with higher TC and LDL-C (measured at vii–xv years) at lower PFAS concentrations, just modestly lower TC and LDL-C at college PFAS concentrations (Maisonet et al. 2015). Similar nonlinear exposure-response relationships with TC and LDL-C were reported in a cross-exclusive written report of children and adolescents ages one–eighteen years from a highly PFAS-exposed community in the Mid-Ohio Valley, United States (Frisbee et al. 2010).

Given that in that location is suggestive epidemiological evidence for nonlinear associations of PFASs with lipids (Frisbee et al. 2010; Maisonet et al. 2015; Steenland et al. 2010), we hypothesize that inconsistencies between these studies and ours could exist due to (ane) differences in prenatal and mid-childhood PFAS concentrations between written report populations and across time periods and (two) how the directionality of the PFAS-outcome associations may vary depending on these PFAS concentrations. For example, prenatal PFOS and PFOA plasma concentrations in our written report population, measured when concentrations peaked in the U.South. population (1999–2002) and before they declined due to industry's voluntary phase out of these compounds (Sagiv et al. 2015), were college than serum concentrations reported in the prospective written report of British girls, which was conducted ~10 years before (1990–1992) (Maisonet et al. 2015). PFAS concentrations in the current study were besides higher than prenatal plasma concentrations measured in the INMA birth cohort study (2003–2008) (Manzano-Salgado et al. 2017). In contrast, mid-childhood PFOS and PFOA plasma concentrations in Project Viva participants (2007–2010) were like to serum concentrations reported in children (12–xix years old) from the 2007–2008 NHANES cycle (CDC 2015) and other U.S. children and adolescents (1999–2008) (Frisbee et al. 2010; Geiger et al. 2014), but lower than plasma concentrations observed in Danish children (1997) (Timmermann et al. 2014). Mid-childhood PFDeA plasma concentrations in our study population were lower than serum concentrations measured in Taiwanese adolescents (2009–2010) (Zeng et al. 2015).

Although no published study has examined the effects of prenatal or childhood PFAS exposure on liver enzymes in children, numerous studies in adults have investigated these associations with inconsistent results (Alexander and Olsen 2007; Costa et al. 2009; Darrow et al. 2016; Emmett et al. 2006; Gallo et al. 2012; Gleason et al. 2015; Lin et al. 2009; Sakr et al. 2007a; Sakr et al. 2007b). Higher PFAS concentrations accept been associated with college ALT, a marker of hepatocellular dysfunction unremarkably used to screen for pediatric nonalcoholic fat liver disease (NAFLD) (Vos et al. 2017), in most cross-sectional studies (Alexander and Olsen 2007; Darrow et al. 2016; Gallo et al. 2012; Gleason et al. 2015; Lin et al. 2009; Sakr et al. 2007a), whereas prospective studies have reported generally null associations (Costa et al. 2009; Sakr et al. 2007b). In our analyses, we constitute that higher prenatal and mid-babyhood PFASs were associated with small, and probable clinically insignificant, decreases in ALT in children. Farther studies in children would benefit from using more comprehensive assessments of liver function, including measurement of other liver enzymes (e.chiliad., aspartate aminotransferase, albumin, alkaline phosphatase, and full bilirubin), and/or liver imaging technologies.

To our noesis, no studies accept observed sex differences in the associations between PFASs and liver enzymes (Darrow et al. 2016), just a few studies accept found differences in PFAS-lipids associations between males and females from different historic period groups (Eriksen et al. 2013; Frisbee et al. 2010; Maisonet et al. 2015; Manzano-Salgado et al. 2017). In previous analyses of Project Viva, associations of early on-life PFAS exposure with greater adiposity (Mora et al. 2017) and lower insulin resistance (Fleisch et al. 2017) were stronger amidst girls. It is possible that there is a sex-specific susceptibility to PFASs (Eriksen et al. 2013) or that sex differences occur in the expression of lipid transport- or metabolism-related genes (Fletcher et al. 2013). In addition, PFASs could interfere with androgen and/or estrogen action by disturbing the expression of genes associated with steroid hormone metabolism (Du et al. 2013) and, consequently, touch plasma lipid homeostasis in different means for males and females (Wang et al. 2011).

Our study has several limitations: (1) we cannot rule out the possibility that selection bias could have arisen due to loss to follow-up because we did not collect data on metabolic outcomes from children excluded from our analyses. (2) We conducted multiple comparisons and this could take led to statistically significant associations past risk. We were conscientious not to highlight isolated findings, but rather expect for patterns in our results. (iii) Remainder misreckoning from factors associated with both PFAS exposure and lipids or ALT levels, such as nutrition and socioeconomic status, could have biased our findings either towards or abroad from the zip. (iv) PFASs were modestly to strongly correlated in our study population and including them all in the same model may have compromised the precision of our upshot estimates and limited our ability to appraise co-pollutant confounding. (5) We cannot dismiss the possibility that the cross-sectional associations of mid-childhood PFAS concentrations with lipids and ALT levels that we observed could exist due to reverse causation (Dhingra et al. 2017). (6) While several studies have shown that PFAS concentrations in maternal plasma and serum during pregnancy correlate well with cord blood PFAS concentrations (Manzano-Salgado et al. 2015), suggesting that maternal blood can be used every bit proxy for fetal exposure to PFASs, the extent to which each PFAS analyte in maternal plasma is transferred to the fetus remains unclear (Pan et al. 2017). (7) Given the large number of prenatal PFDeA plasma concentrations below the LOD and relatively narrow range of mid-childhood PFDeA concentrations, our PFDeA findings should be interpreted charily. Additional enquiry is needed to meliorate our understanding of the potential function of PFDeA on lipids, liver function tests, and other wellness outcomes.

Our analyses contribute to the existing literature by examining PFAS exposure both during pregnancy and in childhood, ii developmental stages during which individuals are potentially more vulnerable to endocrine disruptors (Schug et al. 2011), such as PFASs. Additional strengths of this study include its large sample size and the availability of detailed data on potential confounding variables, mediators and result modifiers, such as markers of pregnancy hemodynamics, child fast food intake and physical activity, and child BMI.

5. Conclusion

In this Boston-expanse pre-nativity cohort, we found that plasma concentrations of select PFASs during pregnancy and mid-childhood were associated with small-scale detrimental and/or beneficial changes in circulating lipid profile and ALT levels in children, particularly among girls. Our results are biologically plausible, given the multiple mechanisms of action identified for these chemicals, and are, to some caste, consistent with the existing literature in adults. These findings provide additional evidence supporting a physiologic effect of PFASs and are important due to these toxicants' persistence in the environs and in humans.

​

Highlights

• Measured PFASs in maternal plasma in pregnancy and child plasma in mid-childhood

• Measured fasting lipids and ALT in mid-childhood

• Kid PFAS associated with college TC and LDL-C among girls

• Maternal and child PFAS associated with higher HDL-C and lower TG among girls

• Maternal and child PFAS associated with decreased ALT levels

Acknowledgments

We give thanks the participants and staff of Projection Viva; One thousand. Kato, A. Patel, and T. Jia for their contribution with PFAS measurements; and Due south. de Ferranti for her insights on the potential mechanisms of PFAS effects on lipids. This work was supported past the National Institutes of Health (R01ES021447, K24HD069408, P30DK092924, R01HD034568, UG3OD023286, P01ES009605, R25DK096944, and K23ES024803), U.S. Ecology Protection Agency (R82670901 and RD83451301), and Academic Pediatric Association. The findings and conclusions in this written report are those of the authors and exercise non necessarily stand for the official position of the NIH, EPA, or CDC. Use of trade names is for identification merely and does not imply endorsement by the CDC, the Public Health Service, or the U.S. Department of Wellness and Human Services.

Appendices

Effigy A.1

Projection Viva cohort sample size and participation. A total of 682 participants had data available for at least i exposure and one outcome examined in the present analyses.

Effigy A.2

Adjusted linear regression coefficients for associations of mid-babyhood PFAS quartiles with lipid and ALT levels in mid-childhood among boys^a and girls.^b

Abbreviations: PFAS, per- and polyfluoroalkyl substances; LDL, low-density lipoprotein; HDL, high-density lipoprotein; ALT, alanine aminotransferase; PFOS, perfluorooctane sulfonate; PFOA, perfluorooctanoate; PFNA, perfluorononanoate; PFHxS, perfluorohexane sulfonate; PFDeA, perfluorodecanoate.

Estimates are presented as modify (95% conviction intervals) in outcome for each quartile increment in exposure (exposure quartiles ii–4 vs. quartile 1). Models were adjusted for maternal education, prenatal smoking, and kid's race/ethnicity, and age at lipids/ALT measurements.

^aBoys with lipid measurements and PFOS concentrations: quartile 1 (Q1) = 81, quartile 2 (Q2) = 76, quartile 3 (Q3) = 81, and quartile 4 (Q4) = 76; with lipid measurements and PFOA concentrations: Q1 = 76, Q2 = 74, Q3 = 87, and Q4 = 77; with lipid measurements and PFNA concentrations: Q1 = 98, Q2 = 65, Q3 = 74, and Q4 = 77; with lipid measurements and PFHxS concentrations: Q1 = 91, Q2 = seventy, Q3 = 67, and Q4 = 86; with lipid measurements and PFDeA concentrations: Q1 = xc, Q2 = 84, Q3 = 100, and Q4 = xl. Boys with ALT measurements and PFOS concentrations: Q1 = 87, Q2 = 76, Q3 = 85, and Q4 = 84; with ALT measurements and PFOA concentrations: Q1 = 80, Q2 = 81, Q3 = 89, and Q4 = 82; with ALT measurements and PFNA concentrations: Q1 = 102, Q2 = 73, Q3 = 81, and Q4 = 76; with ALT measurements and PFHxS concentrations: Q1 = 89, Q2 = 75, Q3 = 73, and Q4 = 95; with ALT measurements and PFDeA concentrations: Q1 = 93, Q2 = 89, Q3 = 105, and Q4 = 45.

^bGirls with lipid measurements and PFOS concentrations: Q1 = 75, Q2 = 73, Q3 = 70, and Q4 = 64; with lipid measurements and PFOA concentrations: Q1 = 72, Q2 = 75, Q3 = 63, and Q4 = 72; with lipid measurements and PFNA concentrations: Q1 = 83, Q2 = 66, Q3 = 62, and Q4 = 71; with lipid measurements and PFHxS concentrations: Q1 = 84, Q2 = 67, Q3 = 75, and Q4 = 56; with lipid measurements and PFDeA concentrations: Q1 = 73, Q2 = 68, Q3 = 93, and Q4 = 48. Girls with ALT measurements and PFOS concentrations: Q1 = 77, Q2 = 74, Q3 = 74, and Q4 = 73; with ALT measurements and PFOA concentrations: Q1 = 74, Q2 = 78, Q3 = lxx, and Q4 = 76; with ALT measurements and PFNA concentrations: Q1 = 86, Q2 = 74, Q3 = 65, and Q4 = 73; with ALT measurements and PFHxS concentrations: Q1 = 87, Q2 = 69, Q3 = 78, and Q4 = 64; with ALT measurements and PFDeA concentrations: Q1 = 74, Q2 = 72, Q3 = 101, and Q4 = 51.

Wald test p-values for almost interaction terms between child sex and mid-childhood PFAS quartiles were not significant [PFOS: for total cholesterol (p = 0.20), for HDL cholesterol (p = 0.88), for total/HDL cholesterol × 100 (p = 0.87), triglycerides (p = 0.75), and ALT (p = 0.62)]; PFOA: for total cholesterol (p = 0.53), for LDL cholesterol (p = 0.67), for HDL cholesterol (p = 0.87), for total/HDL cholesterol × 100 (p = 0.92), triglycerides (p = 0.57), and ALT (p = 0.59); PFNA: for total cholesterol (p = 0.25), for HDL cholesterol (p = 0.99), for full/HDL cholesterol × 100 (p = 0.79), triglycerides (p = 0.94), and ALT (p = 0.72); PFHxS: for total cholesterol (p = 0.67), for HDL cholesterol (p = 0.56), for total/HDL cholesterol × 100 (p = 0.47), triglycerides (p = 0.63); PFDeA: for total cholesterol (p = 0.66), for LDL cholesterol (p = 0.61), for HDL cholesterol (p = 0.65), for total/HDL cholesterol × 100 (p = 0.89), triglycerides (p = 0.71), and ALT (p = 0.30)]. The only exceptions were some interaction terms between child sex and mid-childhood PFOS [for LDL cholesterol (p = 0.10)], PFNA [for LDL cholesterol (p = 0.sixteen)], and PFHxS quartiles [for LDL cholesterol (p = 0.12) and ALT (p = 0.10)].

Tabular array A.1

Spearman correlation coefficients for prenatal and mid-babyhood PFAS concentrations (ng/mL) in the study population (n = 518).

	Prenatal PFAS						Mid-babyhood PFAS
Exposures	PFOS	PFOA	PFNA	PFHxS	EtFOSAA	MeFOSAA	PFOS	due north-PFOS	sm-PFOS	PFOA	n-PFOA	PFNA	PFHxS	PFDeA
Prenatal PFAS
PFOS	1.00
PFOA	0.72	1.00
PFNA	0.67	0.56	i.00
PFHxS	0.54	0.55	0.44	1.00
EtFOSAA	0.52	0.38	0.xx	0.21	one.00
MeFOSAA	0.46	0.41	0.24	0.28	0.49	ane.00
Mid-childhood PFAS
PFOS	0.12	0.09	0.11	0.fifteen	0.05	0.18	ane.00
north-PFOS	0.13	0.x	0.12	0.xiv	0.05	0.18	one.00	1.00
sm-PFOS	0.11	0.09	0.10	0.16	0.06	0.16	0.97	0.94	1.00
PFOA	0.10	0.15	0.08	0.18	0.06	0.18	0.79	0.77	0.81	1.00
n-PFOA	0.11	0.15	0.08	0.18	0.05	0.18	0.79	0.77	0.81	1.00	1.00
PFNA	0.11	0.11	0.08	0.07	−0.01	0.08	0.32	0.33	0.29	0.40	0.42	ane.00
PFHxS	0.12	0.12	0.08	0.40	0.05	0.17	0.68	0.66	0.70	0.61	0.61	0.14	1.00
PFDeA	0.13	0.10	0.11	0.08	0.06	0.11	0.60	0.61	0.55	0.70	0.72	0.54	0.37	1.00

Table A.two

Adjusted linear regression coefficients for associations of mid-childhood linear and branched isomers of PFOS and PFOA concentrations with lipid and ALT levels in mid-childhood amidst all children and stratified past child sex.

	All childrena	Boysb	Girlsc
	β (95% CI)	β (95% CI)	β (95% CI)	p int
Lipids
Total cholesterol (mg/dL)
n-PFOS	one.8 (−0.2, iii.vii)	0.5 (−ane.nine, 2.9)	iv.two (0.5, 7.9)	0.15
sm-PFOS	1.8 (−0.4, 3.9)	0.7 (−i.9, 3.iv)	iii.6 (−0.3, 7.5)	0.36
due north-PFOA	2.9 (−0.2, half-dozen.1)	1.four (−ii.8, v.6)	5.6 (0.8, 10.3)	0.24
LDL cholesterol (mg/dL)
n-PFOS	0.viii (−0.8, ii.5)	−0.2 (−two.2, 1.viii)	2.8 (−0.3, 6.0)	0.15
sm-PFOS	0.vii (−one.two, 2.6)	−0.i (−2.5, 2.3)	2.1 (−1.2, 5.4)	0.43
n-PFOA	1.0 (−1.7, 3.seven)	−0.2 (−3.9, 3.4)	three.2 (−0.7, 7.1)	0.25
HDL cholesterol (mg/dL)
due north-PFOS	ane.four (0.4, two.5)	1.two (0.1, two.3)	2.0 (0.0, 4.0)	0.38
sm-PFOS	1.6 (0.4, 2.7)	1.iii (0.0, 2.6)	ii.1 (−0.ane, 4.2)	0.38
n-PFOA	1.8 (0.4, 3.3)	i.7 (−0.2, 3.half-dozen)	ii.2 (−0.0, 4.5)	0.47
Total/HDL-C × 100
north-PFOS	−4.3 (−9.ii, 0.7)	−five.0 (−10.2, 0.2)	−3.5 (−14.4, 7.5)	0.96
sm-PFOS	−four.9 (−x.5, 0.seven)	−five.0 (−11.1, one.0)	−five.four (−xvi.half dozen, 5.ix)	0.63
n-PFOA	−3.half dozen (−10.9, 3.7)	−5.eight (−14.v, 2.9)	−1.one (−xiii.7, 11.6)	0.90
Triglycerides (mg/dL)
n-PFOS	−2.six (−4.4, −0.8)	−2.3 (−iv.two, −0.4)	−three.3 (−7.1, 0.5)	0.33
sm-PFOS	−two.two (−4.6, 0.two)	−2.three (−iv.7, 0.1)	−2.7 (−seven.5, 2.1)	0.35
northward-PFOA	0.four (−2.vi, 3.5)	−0.3 (−3.5, two.nine)	0.8 (−5.0, 6.v)	0.59
Liver enzymes
ALT (U/Fifty)
n-PFOS	−0.3 (−0.9, 0.3)	−0.3 (−1.2, 0.6)	−0.iv (−one.1, 0.3)	0.68
sm-PFOS	−0.4 (−0.9, 0.1)	−0.five (−1.2, 0.3)	−0.4 (−1.0, 0.3)	0.94
n-PFOA	−0.seven (−ane.4, 0.0)	−0.half-dozen (−one.half-dozen, 0.iv)	−0.9 (−one.eight, −0.1)	0.41

Table A.3

Adjusted linear regression coefficients for associations of mid-babyhood PFAS concentrations with lipid and ALT levels in mid-babyhood amongst all children and stratified past child sex (models adjusted for all mid-childhood PFAS simultaneously).

	All childrena	Boysb	Girlsc
	β (95% CI)	β (95% CI)	β (95% CI)	p int
Lipids
Total cholesterol (mg/dL)
PFOS	0.nine (−one.9, 3.8)	1.0 (−2.7, 4.viii)	0.0 (−5.ane, 5.ane)	0.63
PFOA	−3.v (−8.three, 1.3)	−4.four (−11.4, 2.5)	−1.2 (−8.iv, 6.0)	0.64
PFNA	0.i (−1.three, ane.4)	0.0 (−1.half-dozen, ane.6)	0.0 (−2.5, 2.5)	0.99
PFHxS	−0.3 (−1.3, 0.6)	−0.6 (−1.7, 0.5)	0.2 (−ane.iii, ane.seven)	0.38
PFDeA	eight.7 (4.6, 12.nine)	8.3 (two.4, 14.3)	x.0 (3.7, sixteen.2)	0.60
LDL cholesterol (mg/dL)
PFOS	0.9 (−ane.4, 3.2)	0.9 (−2.i, three.viii)	0.3 (−4.0, 4.six)	0.74
PFOA	−two.v (−6.viii, ane.8)	−2.vii (−9.0, 3.vi)	−i.2 (−7.v, 5.1)	0.86
PFNA	0.0 (−1.1, 1.0)	−0.one (−1.3, one.1)	−0.2 (−2.five, 2.ane)	0.92
PFHxS	−0.3 (−one.0, 0.5)	−0.6 (−1.5, 0.4)	0.3 (−0.eight, one.5)	0.19
PFDeA	4.5 (one.0, eight.0)	3.7 (−1.1, 8.half dozen)	half-dozen.0 (0.4, 11.seven)	0.46
HDL cholesterol (mg/dL)
PFOS	one.2 (−0.2, ii.7)	1.2 (−0.5, 2.nine)	1.ane (−i.9, 4.1)	0.86
PFOA	−3.two (−5.4, −one.one)	−2.8 (−5.6, 0.0)	−3.2 (−6.7, 0.3)	0.90
PFNA	−0.two (−0.6, 0.three)	−0.ii (−0.9, 0.4)	−0.i (−0.8, 0.seven)	0.fourscore
PFHxS	0.0 (−0.4, 0.iv)	−0.one (−0.half-dozen, 0.5)	0.0 (−0.vi, 0.6)	0.86
PFDeA	five.9 (iii.seven, eight.1)	five.3 (2.one, 8.5)	6.5 (3.4, 9.vii)	0.63
Total/HDL-C × 100
PFOS	−v.3 (−xi.9, i.4)	−four.9 (−12.half-dozen, 2.7)	−6.9 (−22.i, 8.3)	0.82
PFOA	eleven.8 (−0.ii, 23.viii)	4.3 (−9.9, xviii.vi)	xix.0 (−1.one, 39.2)	0.41
PFNA	i.i (−one.4, 3.5)	i.6 (−ane.7, 4.ix)	0.i (−4.1, iv.3)	0.66
PFHxS	−0.4 (−two.2, 1.three)	−0.3 (−2.7, 2.1)	−0.1 (−3.0, 2.8)	0.91
PFDeA	−xv.vii (−26.6, −four.viii)	−9.1 (−22.v, iv.2)	−20.0 (−37.7, −2.3)	0.42
Triglycerides (mg/dL)
PFOS	−half-dozen.1 (−9.0, −3.two)	−5.iii (−8.7, −one.9)	−7.1 (−thirteen.0, −1.1)	0.62
PFOA	eleven.1 (2.ane, 20.ane)	five.iv (0.ii, 10.7)	fifteen.ix (1.vi, xxx.2)	0.22
PFNA	ane.four (0.1, 2.6)	1.v (0.2, 2.8)	one.3 (−1.9, four.5)	0.99
PFHxS	−0.i (−0.8, 0.6)	0.3 (−0.7, 1.3)	−0.7 (−1.9, 0.6)	0.21
PFDeA	−eight.4 (−17.9, one.0)	−3.2 (−vii.vii, 1.2)	−12.9 (−31.seven, 5.8)	0.35
Liver enzymes
ALT (U/Fifty)
PFOS	0.0 (−0.8, 0.9)	0.3 (−1.0, one.five)	0.ane (−0.8, 1.0)	0.93
PFOA	−0.ix (−ii.ii, 0.5)	−1.i (−three.0, 0.8)	−1.0 (−2.5, 0.6)	0.87
PFNA	−0.3 (−0.5, −0.ane)	−0.iv (−0.half-dozen, −0.2)	−0.ane (−0.iv, 0.three)	0.12
PFHxS	0.one (−0.2, 0.three)	−0.1 (−0.4, 0.ii)	0.ii (−0.1, 0.v)	0.22
PFDeA	0.4 (−0.viii, 1.6)	i.0 (−0.9, 2.9)	−0.3 (−one.5, 0.8)	0.26

Footnotes

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^ane Abbreviations: ALT, alanine aminotransferase; BMI, body mass alphabetize; CDC, Centers for Disease Control and Prevention; CI, confidence interval; EtFOSAA, 2-(N-ethyl-perfluorooctane sulfonamido) acetate; GAM, generalized additive models; GFR, glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; IQR, interquartile range; LDL-C, low-density lipoprotein cholesterol; LOD, limit of detection; MeFOSAA, two-(North-methyl-perfluorooctane sulfonamido) acetate; n-PFOA, north-perfluorooctanoate; n-PFOS, n-perfluorooctane sulfonate; NAFLD, nonalcoholic fatty liver illness; PFAS, per- and polyfluoroalkyl substances; PFDeA, perfluorodecanoate; PFHxS, perfluorohexane sulfonate; PFNA, perfluorononanoate; PFOA, perfluorooctanoate; PFOS, perfluorooctane sulfonate; PFOSA, perfluorooctane sulfonamide; PPAR, peroxisome proliferator-activated receptor; TC, full cholesterol; TG, triglycerides; Sb-PFOA, branched perfluorooctanoates; Sm-PFOS, perfluoromethylheptane sulfonates; Sm2-PFOS, perfluorodimethylhexane sulfonates.

Competing financial interests

None of the other authors declares any actual or potential competing financial interests.

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801004/

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