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Robert J. McCaffreyf, Qian Wuc, Kurunthachalam Kannanb,c, Edward F. Fitzgeralda,b,∗ ...... McIntosh, L.J., Ajilore, O.A., Brooke, S.M., Sapolsky, R.M., 1996.
International Journal of Hygiene and Environmental Health 220 (2017) 679–685

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International Journal of Hygiene and Environmental Health journal homepage: www.elsevier.com/locate/ijheh

Perfluoroalkyl substances, thyroid hormones, and neuropsychological status in older adults Srishti Shrestha a , Michael S. Bloom a,b , Recai Yucel a , Richard F. Seegal b,c , Robert Rej d,e , Robert J. McCaffrey f , Qian Wu c , Kurunthachalam Kannan b,c , Edward F. Fitzgerald a,b,∗ a Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, One University Place, Rensselaer, NY 12144, United States b Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, One University Place, Rensselaer, NY 12144, United States c Division of Environmental Health Sciences, Wadsworth Center, New York State Department of Health, Empire State Plaza, P.O. Box 509, Albany, NY 12201, United States d Division of Translational Medicine, Wadsworth Center, New York State Department of Health, Empire State Plaza, P.O. Box 509, Albany, NY 12201, United States e Department of Biomedical Sciences, School of Public Health, University at Albany, State University of New York, One University Place, Rensselaer, NY 12144, United States f Department of Psychology, University at Albany, State University of New York, Albany, NY, 12222, United States

a r t i c l e

i n f o

Article history: Received 24 September 2016 Received in revised form 8 December 2016 Accepted 21 December 2016 Keywords: Perfluoroalkyl substances Thyroid hormones Neuropsychological status Older adults

a b s t r a c t Minimal data exist regarding the neurotoxicity of perfluoroalkyl substances (PFASs) in aging populations and the possible mediating effects of thyroid hormones (THs). Hence, the aims of this study were to: (i) assess associations between PFASs and neuropsychological function, and (ii) determine if such associations are mediated by changes in circulating THs in an aging population. We measured perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), total thyroxine (T4) and free thyroxine (fT4) in serum and performed neuropsychological tests in 126 men and women aged 55–74 years and living in upper Hudson River communities. Multivariable linear regressions were conducted to assess associations between PFASs and neuropsychological test scores. Mediation analyses were performed in a subset of 87 participants for whom information was available on both PFASs and THs. We calculated THmediated, non-TH mediated, and total effects of PFASs on neuropsychological test scores. Higher PFOA was associated with better performance in tasks of the California Verbal Learning Test and the Wisconsin Card Sorting Test. Higher PFOS was associated with improved performance in a Wechsler Memory Scale subtest and Block Design Subtest (BDT) total scores. There was no evidence of mediation by THs for PFOA-neuropsychological function associations. However, T4 and fT4 partially mediated the protective effect of PFOS on BDT total scores. Our findings do not suggest that PFASs are associated with poor neuropsychological function. There was some evidence of mediation for the association between PFASs and neuropsychological functions by THs, although some other modes of action also appear likely. © 2016 Elsevier GmbH. All rights reserved.

1. Introduction Perfluoroalkyl substances (PFASs) are a class of persistent, bioaccumulative, and toxic compounds, which have been widely used in a variety of consumer products and industrial applications (Agency for Toxic Substances and Disease Registry, 2009), and have become pervasive in the environment (Giesy and Kannan, 2001). Perfluo-

∗ Corresponding author at: Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, One University Place, Room 105, Rensselaer, NY 12144, United States. E-mail address: efi[email protected] (E.F. Fitzgerald). http://dx.doi.org/10.1016/j.ijheh.2016.12.013 1438-4639/© 2016 Elsevier GmbH. All rights reserved.

rooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are the two most predominant PFASs in the environment. Toxicological studies suggest that PFASs induce neurotoxicity (Viberg and Mariussen, 2015). Few studies have investigated PFASs in relation to their neurotoxic effects in humans, and the majority were focused on children (Chen et al., 2013; Gump et al., 2011; Hoffman et al., 2010; Liew et al., 2015; Stein and Savitz, 2011; Stein et al., 2013). However, results from children studies are inconclusive, with PFASs associated with improved as well as with deficits in neurodevelopmental outcomes. To date, only two studies have examined the association of PFASs with cognition in aging adults (Gallo et al., 2013; Power et al., 2013), and the findings suggested that PFASs may be neuroprotective. Further studies using more sen-

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sitive neurocognitive endpoints may help to better elucidate and characterize the associations between PFASs and neuropsychological status in adults. Optimal function of the hypothalamus-pituitary-thyroid system is important to maintain proper neuropsychological function (Bauer et al., 2008). Previous studies have shown that PFASs may also alter levels of circulating thyroid hormones (THs) in human adults (Knox et al., 2011; Wen et al., 2013). It is possible that PFASs may alter neuropsychological function via disruption of thyroid homeostasis, a mechanism by which other persistent organic pollutants are suspected to cause neurotoxicity (Kodavanti, 2005). Yet, the role of thyroid function in mediating PFASneuropsychological function associations has not been evaluated in prior research. To help address these research gaps, we performed a crosssectional study among men and women in New York State (NYS). We previously reported positive associations for PFOA and PFOS, two of the most common PFASs, with total thyroxine (T4) and free thyroxine (fT4) in this population (Shrestha et al., 2015). We also reported associations between T4 and fT4 and tests of visuo-spatial function and memory and learning (Shrestha et al., 2016). Here, we evaluate overall associations for PFOA and PFOS with neuropsychological status in the same study population and whether these associations are mediated by T4 and fT4.

2.2. Neuropsychological assessment The neuropsychological testing protocol was previously described in detail (Fitzgerald et al., 2008). Briefly, memory and learning were assessed using the California Verbal Learning Test (CVLT) (Delis et al., 2000) and the Wechsler Memory Scale (WMS) Form I-Russell’s Revision tests (Russell, 1975). The Trail Making Test (TMT) – Part A was used to assess measures of attention (Reitan and Wolfson, 1993). Executive function was assessed using the Stroop Color-Word Test (SCWT) (Trenerry et al., 1989), the Wisconsin Card Sorting Test (WCST) (Heaton, 1981) and the TMT − Part B (Reitan and Wolfson, 1993). The Digit Symbol Substitution Test (DSST) and the Block Design Subtest (BDT) were used to assess visual and spatial functions (Wechsler, 1981). Cognitive processing time was measured using the Simple Reaction Time Test. The presence and severity of depression and anxiety were assessed by the Beck Depression Inventory (BDI) and the State-Trait Anxiety Inventory (STAI), respectively (Beck et al., 1961; Speilberger et al., 1970). Motor function was assessed using the Static Motor Steadiness Test (SMST) (Lezak et al., 2004), the Grooved Pegboard Test (GPT) (Klove, 1963) and the Finger Tapping Test (FTT) (Reitan and Wolfson, 1993).

2.3. Serum chemical analysis 2. Methods 2.1. Sample selection The current analysis was conducted in a sub-sample of study participants that were recruited for a larger parent project designed to examine associations between polychlorinated biphenyls (PCBs) and neuropsychological function. Details including study population and participant recruitment procedures have been described elsewhere (Fitzgerald et al., 2008). Briefly, the source population consisted of men and women, aged 55–74 years, who lived in three NYS communities with similar demographics and adjacent to the Hudson River: Fort Edward, Hudson Falls, and Glens Falls. These areas were selected for the study because General Electric plants in the area used PCBs to manufacture electric capacitors from 1947 until 1977 and discharged more than 450,000 kg of untreated PCBs into the upper Hudson River (U.S. EPA, 2011). We contacted 2704 men and women aged 55–74 years and living in one of the three study communities and screened them for eligibility. Of those who were eligible and invited, 253 (40%) agreed to participate. Individuals were excluded if: i) they had not lived in their respective areas for at least 25 years, ii) they had been involved in a PCB-related job for ≥ 1 year, or iii) they had certain medical conditions, including a history of stroke, severe head injury, Parkinson’s disease, Alzheimer’s disease, or severe cognitive impairment. Structured in-person interviews and neuropsychological testing were administered between 2000 and 2002. Serum samples were collected at the same time to measure levels of PCBs, and residual samples were archived at −20 ◦ C. In 2005, THs were measured in those samples with volume ≥ 1.0 mL (n = 143) and, in 2010, PFASs were measured in those samples with volume ≥ 0.2 mL (n = 157). We further excluded 31 participants with clinically diagnosed thyroid disease, who were taking any thyroid-related medications or those under sex hormone therapy, given their potential to alter THs (Surks and Sievert, 1995; Tahboub and Arafah, 2009), leaving 126 participants with data on PFASs and 87 participants with data on both PFASs and THs. The study protocol was approved by the Institutional Review Boards of the University at Albany, State University of New York and the NYS Department of Health (NYSDOH).

All biomarker determinations, inclusive of PCBs, PFASs, THs, and lipids were performed by the Wadsworth Center at the NYSDOH (Albany, NY). The analytical and quality control/assurance procedures for the serum PCB analyses have been detailed previously (Fitzgerald et al., 2007; Fitzgerald et al., 2008). Thirty PCB congeners (IUPAC numbers 28, 52, 60, 66, 74, 99, 101, 105, 110, 118, 130, 138, 146, 153, 156, 167, 170, 172, 177, 178, 180, 183, 187, 193, 194, 199, 201, 203, 206, and 209) that constitute more than 95% of total PCB residue in human serum were analyzed and summed to obtain total PCBs (Humphrey et al., 2000). The analytical procedures for PFOA and PFOS are described in detail elsewhere (Kannan et al., 2004). Briefly, the chemicals were initially extracted from serum using an ion-pairing method and subsequently analyzed by high performance liquid chromatograph-tandem mass spectrometer. Isotopically labeled internal standards were spiked into each sample and quantification was done by an isotope dilution method. Limits of quantitation (LOQ) were determined based on the linear range of the calibration curve prepared at concentrations of 0.5 ng/mL to 100 ng/mL, and ranged from 0.5 to 1 ng/mL. One observation for PFOA was below the LOQ, for which the machine-read value (0.58n g/ml) was assigned to prevent bias that may accompany traditional imputation procedures (Schisterman et al., 2006).

2.4. Thyroid function and lipid analysis Given limited evidence for associations between thyroid stimulating hormone (TSH) and total triiodothyronine (T3) with either neuropsychological test scores or PFASs in this population (Shrestha et al., 2015; Shrestha et al., 2016), we only focused on T4 and fT4 as potential mediators in this analysis. Concentrations in serum were measured using an immunoelectrochemiluminometric assay (Roche Elecsys 1010 system, Roche Diagnostics, U.S.A). The average inter-run coefficients of variation for T4 and fT4 were 4.5% and 2.2%, respectively. The laboratory reference intervals were 5.1–14.1 ␮g/dL for T4 and 0.9–1.7 ng/dL for fT4. Serum cholesterol and triglycerides were determined enzymatically using a Hitachi 911 analyzer (Roche Diagnostics, Indianapolis, IN) (Allain et al., 1974).

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2.5. Statistical analysis Total serum lipids (g/L) were estimated as 2.27 × cholesterol (g/L) + triglycerides (g/L) + 0.623 (Phillips et al., 1989) and serum total PCBs was expressed on a lipid basis (ng of PCBs per g of serum total lipids). All neuropsychological test scores were continuous in nature, and therefore multivariable linear regressions were performed to assess associations between PFASs and neuropsychological test scores adjusting for age, sex, education, and serum total PCBs (lipid basis) (Fitzgerald et al., 2008; Kato et al., 2011; Lezak et al., 2004) using data from the 126 person subset. Serum PFOA, PFOS, and some of the neuropsychological test scores were natural log-transformed (ln) to normalize residual distributions. Here, we reported the difference in a neuropsychological test score per one interquartile range (IQR) higher ln PFAS for all regression models. We used the SAS Macro developed by Valeri and Vanderweele (2013) to assess if associations between PFASs and neuropsychological test scores were mediated by THs in the 87 person subset. In order for a variable to be a mediator, two conditions have to be met: (i) the exposure must be associated with the mediator; and (ii) the mediator must be associated with the outcome. Therefore, we first examined associations between PFASs and THs, and THs and neuropsychological test scores using linear regression models. For those with evidence of associations, we built linear regression models: (i) with an exposure predicting a mediator (E (M|X = x, C = c) = ␤0 + ␤1x + ␤2c + ␧); and ii) with both the exposure and the mediator predicting an outcome (E (Y|X = x, M = m, C = c) = ␪0 + ␪1x + ␪2 m + ␪3c + ␧). Here X, Y, M, and C indicate exposure (i.e., PFAS), outcome (i.e., neuropsychological test score), potential mediator (i.e., TH) and the vector of covariates, respectively. We report a non-TH-mediated or direct effect (obtained from ␪1) expressed as an average change in test score per one IQR higher ln PFAS level at the mean TH value; a TH-mediated or indirect effect expressed (obtained from product of ␪2 and ␤1) as a change in test score associated with TH changes resulting from a one IQR change in ln PFAS for individuals with ln PFAS level fixed at the third quartile; and a total effect (sum of direct and indirect) as a change in test score per one IQR higher ln PFAS. We considered age (Kato et al., 2011; Lezak et al., 2004; Peeters, 2008), sex (Brann et al., 2007; Kato et al., 2011; Lezak et al., 2004; Tahboub and Arafah, 2009), education (Ardila et al., 2000; Lezak et al., 2004), serum total PCBs (Bloom et al., 2014; Fitzgerald et al., 2008), and cigarette smoking (Bertelsen and Hegedus, 1994; Lezak et al., 2004) as sufficient sets of covariates to adjust for confounding of associations among PFASs, THs, and neuropsychological tests. We obtained the 95 percentile confidence intervals (CIs) for the direct, indirect, and total effects using 1000 bootstrap samples. We also performed mediation analysis allowing an interaction between PFAS and TH, but did not detect evidence of statistical interaction. The traditional lipid standardization procedure for PCBs may produce biased effect estimates from regression models (Schisterman et al., 2005). Therefore, we repeated our analysis using serum total PCBs on a wet-weight basis while adjusting for total lipids as an additional covariate. Statistical tests were twotailed, and considered statistically significant at p < 0.05. All of the analyses were performed using SAS version 9.3 (SAS Institute, Cary, NC).

3. Results ¨ Table 1 presents background characteristics of the participants. Mean age (standard deviation (SD)) was 63.8 (6.1) years. The geometric means (SDs) of serum PFOA and PFOS were 8.2 (1.7) ng/mL and 35.5 (1.8) ng/mL, respectively. The IQR (first quartile–third quartile) was 6 (5.9–11.9) ng/mL for PFOA and 27.5

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(23.3–50.8) ng/mL for PFOS. Descriptive statistics for the neuropsychological test scores are presented in the Supplemental Table. The multivariable results for the overall association between PFAS concentrations and neuropsychological status are presented in Table 2. After adjusting for age, sex, education, and serum total PCBs (lipid basis), higher PFOA was significantly associated with better performance on t-score of CVLT (␤ = 2.63, 95% CI = 0.20, 5.06), which correspond to 6% higher mean score. Higher PFOA was also associated with two subtests of the WCST, that is, there were fewer perseverative errors (␤ = −0.18, 95% CI = −0.34, −0.01) and fewer perseverative responses (␤ = −0.20, 95% CI = −0.38, −0.0). These effects correspond to 16%–18% lower mean scores. We detected significant association between PFOS and visual reproduction delayed recall score of WMS (␤ = 0.79, 95% CI = 0.03, 1.55) and total score of BDT (␤ = 2.10, 95% CI = −0.02, 4.22) which correspond to about 11% and 8% higher respective mean scores. The geometric means (SDs) for serum T4 and fT4 were 8.6 (1.2) ␮g/dL and 1.2 (1.2) ng/dL, respectively, for the 87person sub-sample. The IQR (first quartile–third quartile) was 2.3 (7.6–9.8) ␮g/dL for T4 and 0.2 (1.1–1.4) ng/dL for fT4. The values of T4 and fT4 were within laboratory reference ranges, with the exception one borderline low fT4 observation. In the analyses that assessed associations between PFASs and THs (i.e., between the exposures and the mediators) in the 87-person sub-sample (details presented elsewhere (Shrestha et al. 2015)), PFOA was positively associated with T4 (␤ = 0.38, 95% CI = −0.07, 0.83), and PFOS was positively associated with both T4 (␤ = 0.77, 95% CI = 0.33, 1.21) and fT4 (␤ = 0.05, 95% CI = 0.00, 0.11); the beta estimates here represent differences in THs associated with one IQR higher ln PFASs. Likewise, key findings in previous analyses that assessed associations between THs and neuropsychological tests (i.e., mediator-outcome relationships) in the 87-person sub-sample were: (i) significant association between increasing T4 and improved BDT total scores (␤ = 4.82, 95% CI = 1.97, 7.67); (ii) significant associations between increasing fT4 and poor performance in short delay free recall scores (␤ = −0.95, 95% CI = −1.80, −0.10) and long delay free recall scores (␤ = −0.92 , 95% CI = −1.80, −0.05) of the CVLT; and (iii) significant association between higher fT4 and improved BDT total scores (␤ = 4.65, 95% CI = 2.16, 7.13); the beta estimates here represent differences in test scores associated with one IQR higher THs. Although not statistically significant, higher THs were also associated with poor performance in other CVLT subtests and improved digit symbol coding total score (data not shown). For the mediation analysis, we specifically focused on CVLT subtests and BDT scores. We did not detect evidence of any significant mediation by T4 for the effect of PFOA on neuropsychological test scores (data not shown), but detected evidence of mediation by THs for the effects of PFOS on some neuropsychological test scores, which are presented in Table 3. Specifically, we detected mediation by fT4 for the effects of PFOS on both the CVLT short and long delay free recall scores. In each case, the fT4-mediated effects were in the opposite direction of the non-fT4 mediated effects, reducing overall association or total effect. For example, fT4-mediated and non-fT4 mediated effects for short delay free recall were −0.24 (95 percentile CI = −0.63, 0.02) and 0.39 (95 percentile CI = −0.71, 1.44), respectively, and the total effect was 0.15 (95 percentile CI = −0.85, 1.11). We also found that the association between PFOS and BDT total scores was partially mediated by THs. The estimates for T4-mediated, and non-T4 mediated and total effects were 1.55 (95 percentile CI = 0.26, 3.20), 1.34 (95 percentile CI = −1.98, 4.65) and 2.89 (95 percentile CI = 0.02, 6.20), respectively (proportion mediated = 1.55/2.89 = 53%). The estimates for fT4 mediated, nonfT4 mediated, and total effects were 0.98 (95 percentile CI = −0.01, 2.42), 1.91 (95 percentile CI = −1.14, 5.06), and 2.89 (95 percentile CI = 0.02, 6.20), respectively (proportion mediated = 34%).

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Table 1 Background characteristics of study participants (n = 126). Characteristics

n

AM (SD)

Median

Q1, Q3

Range

GM (SD)

Age at interview (years) Number of drinks over past year (among drinkers) a , b Total packs in last year (among smokers)c Years of education Serum total PCB (ng/g of total lipids) Serum PFOA (ng/mL) Serum PFOS (ng/mL)

126 108

63.8 (6.1) 317.7 (372)

64 208

58, 69 51, 420

55, 74 1, 2184

– –

23

295.3 (211.4)

365

146, 365

0.7, 730

–

126 124

13.7 (2.6) 517.2 (250.3)

13 461.6

12, 16 348.6, 594.3

6, 20 139.3, 1638.2

– 467.8 (1.6)

126 126

9.5 (5.4) 42.1 (28.9)

8.1 33.7

5.9, 11.9 23.3, 50.8

0.6, 42.7 5.3, 217

8.2 (1.7) 35.5 (1.8)

Categories

n

%

Sex Women Men

50 76

39.68 60.32

Income $30,000 to $45,000 >$45,000 to $60,000 >$60,000 to $75,000 >$75,000

8 26 30 24 17 15

6.67 21.67 25 20 14.17 12.5

Abbreviations: AM, Arithmetic Mean; GM, Geometric Mean; PCB, Polychlorinated Biphenyls; PFOA, Perfluorooctanoic Acid; PFOS, Perfluorooctane Sulfonate; Q1, Quartile 1; Q3, Quartile 3; Range, Minimum-Maximum; SD, Standard Deviation. a One drink is defined as 12 oz. of beer, 4 oz. of wine, or 1.5 oz. of liquor. b n = 108 were drinkers, and 18 were non-drinkers. c n = 23 were smokers, and 103 were non-smokers.

We repeated the analyses entering total PCBs on a wet weight basis and serum total lipids as covariates in regression models. The results were similar to those using total PCBs expressed on a lipid basis (data not shown).

4. Discussion In this study of men and women aged 55 to 74 years and living in upper Hudson River NYS communities, higher levels of PFOA were significantly associated with improved performance in CVLT t-score in the memory and learning domain and certain WCST tasks in the executive function domain. In addition, higher PFOS was significantly associated with improved performance in WMS visual reproduction delayed recall score in the memory and learning domain and BDT total scores in the visuospatial function domain. We did not find significant associations with neuropsychological test scores in other domains including attention, reaction time, affective state, and motor function. To the best of our knowledge, this is the first study to evaluate associations of PFASs using wide-ranging neuropsychological tests in older adults. Clinically, poor performances on the CVLT tasks, including tscore, short and long delay free recall scores, have been linked with impairments in frontal cortex and medial temporal lobe, and poor performances on the WCST tasks have been detected mainly among individuals with impairments in the prefrontal cortex or frontal lobe (Mitrushina et al., 2005). In contrast, improved CVLT t-score, detected in relation to elevated PFOA, may indicate better memory formation, and low perseverative responses and errors may indicate better concept formation and an improved ability to shift cognitive strategies. Likewise, improved BDT scores in relation to elevated PFOS suggest improved ability to analyze and synthesize spatial relationship (Lezak et al., 2004). We detected some evidence of mediation by THs for PFOS but not for PFOA. THs may affect neurocognitive function via interaction with neurotransmitters (Bauer et al., 2008) and may regulate adult neurogenesis as shown in experimental animal stud-

ies (Remaud et al., 2014). On the other hand, experimental as well as human studies suggest that THs may cause neurotoxicity via oxidative stress (Marcocci et al., 2012) and augment necrotic neuronal death (Chan et al., 1996). Thus, alteration in THs level has long been suspected to be a mechanism by which some chemical pollutants affect neurocognitive function (Kodavanti, 2005). In our population, we detected that higher PFOS was positively associated with T4 and fT4; higher fT4 was associated with poor performance in CVLT short and long delay free recall scores; and both higher T4 and fT4 were associated with improved BDT total scores. Furthermore, our mediation analysis showed that PFOS may positively affect performance in these CVLT subtests via pathways not mediated by fT4 and negatively via fT4-mediated pathways, possibly resulting in a reduced impact overall. On other hand, PFOS positively affected performance in BDT via both T4- and fT4-mediated and non-TH mediated pathways in our data, resulting in better performance overall. We do not know the reasons for such contrasting domainspecific mediation by THs, and the existing literature regarding how THs may affect neuropsychological domains in euthyroid individuals is controversial (Begin et al., 2008). Pathways by which THs affect the central nervous system may differ by regions due to the non-uniform distribution of TH receptors (Whybrow and Bauer, 2005). This may also be a chance finding. Our finding that PFASs may improve neurocognitive function in an aging population is consistent with the findings from two previous studies (Gallo et al., 2013; Power et al., 2013). In National Health and Nutrition Examination Survey (NHANES) participants 60 to 85 years of age in 1999–2000 and 2003–2008, high levels of PFOS but not PFOA was associated with lower odds of self-reported cognitive limitations among diabetics; the association was stronger among non-medicated diabetics (Power et al., 2013). Another study was performed among 21,024 adults, aged >50 years who lived in contaminated water districts near a chemical plant that used PFOA in the manufacture of fluoropolymers (the C8 cohort); higher levels of both PFOS and PFOA were associated with lower odds of selfreported short term memory impairment (Gallo et al., 2013). PFOA

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Table 2 Associations between perfluoroalkyl substances and neuropsychological test scores, restricted to individuals not under sex hormone or thyroid hormone therapy and individuals without thyroid disease (n = 126). PFOA

PFOS

Neuropsychological test

␤ (95% CI)a

p-value

␤ (95% CI)a

p-value

Memory and learning CVLT, t-scoreb CVLT, trial 1 scoreb CVLT, short delay free recallb CVLT, long delay free recallb CVLT, semantic cluster ratiob CVLT, learning slopeb CVLT, perseverationsb , d WMS, logical memory immediate recall scoreb WMS, logical memory delayed recall scoreb WMS, visual reproduction immediate recall scoreb WMS, visual reproduction delayed recall scoreb

2.63 (0.20, 5.06) 0.23 (−0.18, 0.64) 0.46 (−0.18, 1.11) 0.40 (−0.27, 1.06) 0.05 (−0.12, 0.23) 0.01 (−0.11, 0.14) 0.08 (−0.12, 0.28) 0.28 (−0.85, 1.42) 0.09 (−0.98, 1.15) −0.11 (−0.79, 0.56) −0.12 (−0.83, 0.59)

0.03 0.27 0.16 0.24 0.53 0.82 0.42 0.62 0.87 0.74 0.74

0.92 (−1.77, 3.61) −0.14 (−0.59, 0.31) 0.09 (−0.61, 0.80) −4.1 × 10−3 (−0.73, 0.73) 0.06 (−0.13, 0.25) −0.03 (−0.17, 0.11) −0.02 (−0.24, 0.20) −0.70 (−1.92, 0.52) −0.14 (−1.29, 1.01) 0.56 (−0.16, 1.29) 0.79 (0.03, 1.55)

0.50 0.54 0.79 0.99 0.53 0.67 0.86 0.26 0.81 0.13 0.04

Measures of attention Trail making test, Part A-time to completec , d

0.01 (−0.05, 0.07)

0.77

−0.05 (−0.12, 0.02)

0.13

Executive function Stroop color word test, t-scoreb Trail making test, Part B-time to completec , d WCST, perseverative errorc , d WCST, perseverative responsec , d

−1.37 (−2.94, 0.20) 0.02 (−0.05, 0.10) −0.18 (−0.34, −0.01) −0.20 (−0.38, −0.02)

0.09 0.54 0.04 0.03

−0.34 (−2.07, 1.38) 0.02 (−0.06, 0.10) −0.14 (−0.30, 0.02) −0.16 (−0.34, 0.01)

0.69 0.67 0.09 0.07

Visual and spatial function BDT, total scoreb Digit symbol coding, total scoreb

−0.44 (−2.42, 1.55) 0.50 (−1.60, 2.60)

0.66 0.64

2.10 (−0.02, 4.22) −0.39 (−2.67, 1.89)

0.05 0.73

Reaction time Reaction time (dominant hand)c

−0.01 (−0.05, 0.03)

0.54

0.02 (−0.02, 0.07)

0.31

Affective state BDI, total scorec STAI, state anxiety t-scorec STAI, trait anxiety t-scorec , d

0.08 (−0.85, 1.02) 0.11 (−1.90, 2.13) −0.02 (−0.06, 0.02)

0.86 0.91 0.35

0.25 (−0.77, 1.26) −0.80 (−2.99, 1.38) −0.01 (−0.05, 0.04)

0.63 0.47 0.74

Motor function FTT (dominant hand), average scoreb FTT (non-dominant hand), average scoreb GPT (dominant hand), time to completionc , d GPT (non-dominant hand), time to completionc,d SMST (dominant hand), total number of contactsc , d SMST (dominant hand), total time touchingc , d SMST (non-dominant hand), total number of contactsc , d SMST (non-dominant hand), total time touchingc , d

−0.54 (−1.90, 0.81) −0.08 (−1.17, 1.00) −0.01 (−0.06, 0.03) −0.03 (−0.07, 0.02) −0.03 (−0.21, 0.15) −0.07 (−0.21, 0.07) −0.12 (−0.31, 0.06) −0.18 (−0.43, 0.06)

0.43 0.88 0.47 0.24 0.75 0.35 0.19 0.15

−0.44 (−1.90, 1.03) −0.32 (−1.49, 0.85) −0.03 (−0.07, 0.02) −0.04 (−0.09, 0.01) −0.12 (−0.32, 0.07) −0.15 (−0.30, 0.00) 0.02 (−0.17, 0.21) −0.06 (−0.30, 0.19)

0.56 0.59 0.21 0.12 0.22 0.06 0.84 0.64

Note: Bold typeface indicates p < 0.05. Abbreviations: BDI, Beck Depression Inventory; BDT, Block Design Subtest; CI, Confidence Intervals; CVLT, California Verbal Learning Test; FTT, Finger Tapping Test; GPT, Grooved Pegboard Test; PFOA, Perfluorooctanoic acid; PFOS, Perfluorooctane Sulfonate; SMST, Static Motor Steadiness Test; STAI, State-Trait Anxiety Inventory; WCST, Wisconsin Card Sorting Test; WMS, Wechsler Memory Scale. a Adjusting for age, sex, education, and serum total PCB (lipid basis). b Low Score = Impairment. c High Score = Impairment. d Natural log-transformed. Table 3 Mediation of the associations between perfluorooctane sulfonate and neuropsychological test scores by thyroid hormones (n = 87). Domain and Test

TH

TH effect (95 percentile CI)a

Non-TH effect (95 percentile CI)a

Total effect (95 percentile CI)a

Memory and learning CVLT, short delay free recallb CVLT, long delay free recallb

fT4 fT4

−0.24 (−0.63, 0.02) −0.24 (−0.63, 0.01)

0.39 (−0.71, 1.44) 0.35 (−0.86, 1.50)

0.15 (−0.85, 1.11) 0.11 (−1.08, 1.27)

T4 fT4

1.55 (0.26, 3.20) 0.98 (−0.01, 2.42)

1.34 (−1.98, 4.65) 1.91 (−1.14, 5.06)

2.89 (0.02, 6.20) 2.89 (0.02, 6.20)

Visual and spatial function BDT, total scoreb

Abbreviations;: BDT, Block Design Subtest; CI, Confidence Intervals; CVLT, California Verbal Learning Test; fT4, Free Thyroxine; T4, Total Thyroxine; TH, Thyroid Hormone. Note: Bold typeface indicates that 95% percentile CIs exclude null. a Adjusted for age, sex, education, cigarette smoking, and serum total PCB (lipid basis). b Low Score = Impairment.

levels in the C8 cohort were 10 to 13 fold higher than reported here, whereas C8 cohort PFOS levels were comparable to ours. Overall, few published studies have investigated associations between PFASs and neurocognition, and potential mechanisms for

such associations are unknown. The investigators of the prior epidemiologic studies in adults (Gallo et al., 2013; Power et al., 2013) postulated that protective associations could be due to the ability of PFASs to activate peroxisome proliferator activated receptors

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(PPARs), ligand-activated transcription factors that regulate genes involved in lipid metabolism and inflammation (Vanden Heuvel et al., 2006). The hypothesis was based on the findings from human and animal studies that PPAR-␥ agonists, including thiazolidinediones, elicit neuroprotection via their anti-inflammatory property (Kaundal and Sharma, 2010). A recent experimental study indicated that PFOS upregulates the activity PPAR-␥, providing further support to this hypothesis (Wan Ibrahim et al., 2013). On the other hand, toxicological evidence that PFASs may be neurotoxic is growing as well (Lee et al., 2012; Reistad et al., 2013; Viberg and Mariussen, 2015). We also explored the hypothesis that PFASneurotoxicity may be mediated by THs. Overall, it appears that the effects mediated via pathways leading to toxicity are comparatively small relative to the effects mediated by pathways leading to neuroprotection, resulting in a protective effect overall. In addition, studies of PFASs and neurocognitive function in children and adolescents reported mixed findings, with higher PFOA and PFOS associated with improved (Stein and Savitz, 2011; Stein et al., 2013) as well as poorer neurocognitive outcomes (Hoffman et al. 2010). So it is possible that the timing of exposure may also determine the chemodynamics of PFASs, producing divergent associations across populations as suggested by a previous study (Gallo et al., 2013). The results of this study should be interpreted carefully due to several limitations. We made multiple statistical comparisons, which increased the likelihood of spurious results due to inflation of the Type I error rate, and leading to chance findings. The small sample size limited our statistical power to detect modest effects, especially for the mediation analysis. Further, it is possible that PCBs may modify associations between PFAS and neuropsychological function, but the evaluation of potential interaction between PFAS and PCBs in mediation analysis is beyond the scope of this study given the small sample size. In addition, given the cross-sectional nature of study, we could not determine the temporal order of exposure, mediator, and outcome; it is possible that the detected associations could be due to reverse causation. Further, our mediation analyses assumed that there was no confounding of the associations among exposure, mediator, and outcome. Although we adjusted for factors such as age, sex, and education, it is possible that there were other unmeasured confounders. Additionally, we performed our analysis in subsamples of 126 and 87 persons from the original 253 person parent study cohort, raising the possibility of selection bias. However, inclusion in the current analysis was based solely on the availability of sufficient archived serum to allow for the determination of PFASs and THs, so self-selection was not involved. Supporting this argument is the fact that the distributions of socio-demographic factors for the 126 participants included in this study were similar to those for the 127 persons in the original parent study who were excluded, with the exception of reported alcohol consumption (86% vs. 73%, respectively, p < 0.05). The current study has several strengths which include the sensitive and objective biomarker measures of environmental exposures and TH mediators. We also addressed the limitations of selfreported neurocognitive outcomes used by previous studies (Gallo et al., 2013; Power et al., 2013); we employed batteries of wellknown and widely accepted tests to assess neuropsychological status in clinical populations and general populations exposed to various neurotoxicants (Fitzgerald et al., 2008; Schantz et al., 2001). In addition, our comprehensive evaluation of the wide-ranging domains of neuropsychological function allowed for us to identify specific PFAS-associated effects. Furthermore, ours is the first study to assess mediating effects of THs for the associations between PFASs and neuropsychological function.

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