# Associations of plasma persistent organic pollutants with brain atrophy, cognitive decline and risk of dementia in older adults

Sophie Lefèvre-Arbogast, Pierre Scala, Aurore Zorilla, Catherine Helmer, Jade Chaker, Arthur David, Fabien Mercier, Cécilia Samieri

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## To cite this version:

Sophie Lefèvre-Arbogast, Pierre Scala, Aurore Zorilla, Catherine Helmer, Jade Chaker, et al. Associations of plasma persistent organic pollutants with brain atrophy, cognitive decline and risk of dementia in older adults. Environment International, 2025, 203, pp.109756. 10.1016/j.envint.2025.109756. hal-05237240

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Submitted on 3 Sep 2025

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# Associations of plasma persistent organic pollutants with brain atrophy, cognitive decline and risk of dementia in older adults

Sophie Lefèvre-Arbogast<sup>a,b,*</sup>, Pierre Scala<sup>a,●</sup>, Aurore Zorilla<sup>a</sup>, Catherine Helmer<sup>a,●</sup>,
Jade Chaker<sup>b</sup>, Arthur David<sup>b</sup>, Fabien Mercier<sup>b,●</sup>, Cécilia Samieri<sup>a</sup>

ARTICLE INFO

Keywords:

Persistent organic pollutants

Polychlorinated biphenyls

Organochlorine compounds

Alzheimer's disease

Dementia

Cohort study

A B S T R A C T

**Background:** Persistent Organic Pollutants (POP), including polychlorinated biphenyls (PCBs) and organochlorine pesticides, are established neurotoxicants in experimental models; yet it remains uncertain whether exposures in the general population increase the risk to develop brain aging pathologies. We assessed the prospective associations of plasma POP concentrations with three dementia-related outcomes in a population-based cohort of older adults.

**Methods:** Analyses included 515 participants from the Three-City Study, free of dementia at baseline at the time of blood measurements (1999–2000, mean age 72.5), who underwent up to 8 repeated assessments of cognitive function and dementia over 17 years and up to 3 neuroimaging examinations over 10 years. Plasma concentrations of 15 PCBs, 12 organochlorine pesticides and 1 brominated flame retardant were measured by gas chromatography coupled with tandem mass spectrometry (detection rate ≥5 %), and a POP score summarizing overall exposure was derived via factorial analysis. Associations with dementia risk, longitudinal changes in cognitive function (composite measure of four tests) and in brain volume (medial temporal lobe) were analyzed using Cox and linear mixed models, adjusted for baseline age, sex, education, apolipoprotein E (APOE) genotype, body mass index and total lipid concentrations.

**Results:** In multivariable-adjusted models, neither individual POPs nor the total POP score were significantly and consistently associated with dementia-related outcomes. Significant interactions were observed between APOE genotype and highly-chlorinated PCBs (congeners 180, 194, and 196–203) across all outcomes (p for interaction ≤0.05), whereby adverse associations were seen in carriers of the APOE-ε4 allele, whereas opposing trends were observed in non-carriers.

**Conclusion:** Overall, this prospective study does not provide robust evidence to support an adverse association between exposure to POPs in the general population and the risk of all-cause dementia, cognitive decline, or brain atrophy in older adults.

1. Introduction

With the aging of the population, dementia and its main cause, the sporadic form of Alzheimer's disease (AD), have become a major concern worldwide. AD is a neurodegenerative disease characterized by typical neuropathological hallmarks and neuronal cell death in specific brain areas, causing progressive decline in cognitive function up to impacting daily life activities. Dementia arises from a complex interplay between genetic and non-genetic risk factors. The most important

susceptibility gene for AD dementia is the ε4 allele of the gene coding for the apolipoprotein E (ApoE), a protein involved in lipid transport and homeostasis. Women also have a higher risk of developing dementia than men, which may partly reflect differences in lifespan, educational attainment, and hormonal changes after menopause (Livingston et al., 2024). As for non-genetic factors, the role of the level of education, cardiometabolic risk factors, lifestyle habits and air pollution is well-recognized (Livingston et al., 2024). However, a large part of the environmental etiology remains unknown and the contribution of chemical

<footnote><sup>a</sup> Univ. Bordeaux, Inserm, BPH, U1219, F-33000 Bordeaux, France</footnote>

<footnote><sup>b</sup> Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) – UMR_S 1085, F-35000 Rennes, France</footnote>

<footnote>* Corresponding author at: Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail), UMR_S 1085, 9 Avenue du Professeur Léon Bernard, 35000, Rennes, France.</footnote>

<footnote>E-mail address: Sophie.Lefèvre-Arbogast@univ-rennes.fr (S. Lefèvre-Arbogast).</footnote>
exposures to brain aging pathologies is still unclear, especially at levels observed in the general population (from non-occupational sources) (Livingston et al., 2020; Lefèvre-Arbogast et al., 2024).

Persistent Organic Pollutants (POPs) encompass a range of ubiquitous synthetic compounds once used in agriculture, vector control (for which use is still authorized in certain countries) and industrial processes, including organochlorine pesticides (OCPs) used as insecticides, polychlorinated biphenyls (PCBs) used as electrical insulators, and brominated flame retardants (BFRs) added to manufactured materials to prevent fire propagation. POPs are characterized by their high persistence in the environment, wide distribution across the globe, bioaccumulation along the food chain and toxicity that led to international restrictions on their production and use since the late 1970s. Despite their ban decades ago in most parts of the world (e.g. PCBs production was phased out in 1977 in the US and 1987 in France), POPs are still widely found in human biomonitoring studies (SPF, 2021a,b). Indeed, due to their high lipophilicity and low degradation (i.e., half-life of about a decade in humans (Wolff et al., 2007)), POP are stored in adipose tissue during long periods of time with continuous release into the bloodstream, especially during periods of weight change (Wolff et al., 2007; Lee et al., 2020). There are also continuing sources of exposure, the main one being the consumption of contaminated foods, such as fatty fish (fish, with an estimated contamination of 5263 pg/g fresh weight by the six indicator PCBs in the French Total Diet Study, account for 37 % of total dietary exposure, followed by dairy products, especially butter and cheese, and meat) (Second French Total Diet Study, 2011; Lefèvre-Arbogast et al., 2024).

Most POPs have been detected in the human brain from infancy to aging (Mitchell et al., 2012; Richardson et al., 2014), and some evidence suggest they may be involved in development of AD and related cognitive impairment. POPs are recognized neurotoxicants, especially during developmental periods, with documented mechanisms of action comprising the disruption in neurotransmitter (particularly dopaminergic) systems, Ca2+ dyshomeostasis, oxidative stress, and amyloidogenesis (specifically dichlorodiphenyltrichloroethane [DDT] and its metabolite dichlorodiphenyldichloroethylene [DDE] (Richardson et al., 2014; Eid et al., 2022)) (Lefèvre-Arbogast et al., 2024; Pessah et al., 2019; Richardson et al., 2019). Primary epidemiological evidence of their influence on brain aging was provided by studies of highly exposed individuals, including a large agricultural community in the United States where the occupational exposure to OCPs was associated with increased risk of AD (Hayden et al., 2010), and Taiwanese victims of a major rice oil poisoning incident with PCBs who experienced learning and memory impairments 25 years later (Lin et al., 2008). Beyond occupational and incidental exposures, several studies reported that environmental exposures to OCPs and PCBs in the general population may also be linked to adverse cognitive outcomes (Richardson et al., 2014; Singh et al., 2013; Kim et al., 2015; Schantz et al., 2001; Fitzgerald et al., 2008; Haase et al., 2009; Bouchard et al., 2014; Przybyla et al., 2017; Medehouenou et al., 2014; Raffetti et al., 2020; Lee et al., 2016; Parada et al., 2024; Tanner et al., 2020; Medehouenou et al., 2019), although results have been inconsistent, especially among the few prospective studies that have investigated dementia risk or cognitive decline (Raffetti et al., 2020; Lee et al., 2016; Parada et al., 2024; Tanner et al., 2020; Medehouenou et al., 2019). For example, higher circulating PCBs have been related to higher risk of dementia and steeper cognitive decline over a mean period of 7–9 years in two studies (Raffetti et al., 2020; Parada et al., 2024), but null or opposite associations have also been reported (Lee et al., 2016; Tanner et al., 2020; Medehouenou et al., 2019).

In the present study, we aimed to evaluate in a French population of older adults the prospective associations of plasma POPs with three complementary measures of brain aging over a period of up to 17 years, including the incidence of dementia, cognitive decline and atrophy of the medial temporal lobe (MTL) – an established imaging biomarker of AD (Dubois et al., 2016).

## 2. Methods

### 2.1. Study population

The Three-City (3C)-Bordeaux study is a French population-based cohort initiated in 1999–2000, which enrolled 2104 noninstitutionalized community dwellers aged 65 years or older from the electoral rolls of Bordeaux (3C Study Group, 2003). Baseline data were collected during face-to-face interviews and included sociodemographic, lifestyle and medical information, anthropometric and blood pressure measurements, neuropsychological testing and blood sampling for assessment of standard biology (blood lipids and glucose), apolipoprotein E genotyping and constitution of a biobank. Face-to-face follow-up visits were performed every 2 to 3 years, including repeated neuropsychological testing carried out at home by a trained psychologist. As part of an ancillary brain imaging study, three magnetic resonance imaging (MRI) examinations were performed in 2000–2001, 2004–2006, and 2010–2011.

In 3C-Bordeaux, an ancillary project on the chemical exposome of brain aging was built, leveraging the biobank and clinical and subclinical markers from the neuroimaging study. Among the 630 3C-Bordeaux participants who participated in the neuroimaging study and had no major brain pathologies detected, 518 had available plasma samples in the biobank at baseline that were used for POP measurements (Supplementary Fig. 1). Among them, we excluded one participant with non-valid POP measures and 2 with prevalent dementia based on neurological examination, leaving 515 participants for analyses of cognitive function and decline (68 % had ≥5 cognitive assessments). Of them, 492 were followed-up over time and included in analyses of incident dementia. After excluding participants with MRI segmentation failure, 490 were included for analysis of brain atrophy (63 % had ≥2 MRI exam).

The Consultative Committee for the Protection of Persons participating in Biomedical Research of the Kremlin-Bicêtre University Hospital (Paris, France) and Sud-Méditerranée III approved the 3C study protocol, and all participants provided a written informed consent.

### 2.2. Outcomes

#### 2.2.1. Assessment of incident dementia

Incident dementia was assessed at each follow-up visit through a 3-step procedure. First, all participants were administered a battery of neuropsychological tests at home by trained psychologists. Then, all participants suspected of dementia based on their performances to neuropsychological tests were examined by a neurologist to set up a provisional diagnosis. Finally, an independent committee of neurologists reviewed all potential cases of dementia to obtain a consensus on the diagnosis based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders (4th edition).

#### 2.2.2. Assessment of cognitive function

Cognitive function was assessed at each follow-up visit using a battery of neuropsychological tests assessing various cognitive domains. For the present work, we used a latent score of cognition that jointly considered 4 tests assessing different domains: (1) global cognition (the Mini-Mental State Examination (Folstein et al., 1975); theoretical range 0–30); (2) visual working memory and attention (the Benton Visual Retention Test (Benton, 1953); theoretical range 0–15); (3) verbal semantic fluency (the Isaacs' Set Test at 15 s (Isaacs and Kennie, 1973); observed range 0–53); and (4) executive functioning (the Trail Making Test Part B (Reitan, 1958), assessed as the number of correct displacements divided by time to perform the test; observed range 0–42). The latent cognitive score trajectory over the 17 years following baseline was estimated using latent process mixed model for multivariate repeated measures (Proust-Lima et al., 2013) (See Supplementary Methods).
### 2.2.3. Assessment of brain volumes

MRI examinations were performed at three visits (at inclusion and the 4-y and 10-y follow-up visits) on a 1.5-T Gyroscan Interra system (Philips Medical System, the Netherlands), except the last one that was acquired on a 3-T Achieva (Philips Medical System, the Netherlands). The protocol for MRI acquisition is described in Supplementary Methods. FreeSurfer 5.1 software was used for cortical surface reconstruction and for estimation of gray matter volumes for each region of the Destrieux parcellation atlas (Destrieux et al., 2010). MTL volume was defined as the sum of amygdalar, parahippocampal, and hippocampal volumes of both hemispheres.

## 2.3. Plasma POP measurements

Fasting blood samples were collected at baseline in heparinized vacutainers, centrifuged at 1000 g for 10 min and stored at -80 °C in a biobank. Stored plasma samples were transferred on dry ice to the Leres laboratory (Laboratoire d'Etude et de Recherche en Environnement et Santé, Rennes, France) in 2022, where POP concentrations were determined by gas chromatography coupled to tandem mass spectrometry (GC/MS/MS). A detailed description of the method including quality assurance and quality control (QA/QC) is provided elsewhere (Génard-Walton et al., 2023), and in the Supplementary Material. Briefly, after the addition of internal standards (ISTDs) followed by a protein denaturation step, POPs were extracted from serum samples by solid phase extraction (SPE). Organic extracts in hexane were then stored in a freezer for a minimum of 2 h, evaporated at 30 °C under a nitrogen stream and adjusted to 500 µL of hexane prior to be transferred into 2 mL amber glass vials and stored at -18 °C. GC/MS/MS analyses were performed using a 7890B GC system coupled to a 7010B GC/MS Triple Quad (Agilent Technologies, Santa Clara, California, United States) operated in electron impact ionization (EI) mode (70 eV). The mass spectrometer (triple quadrupole) was operated in multiple reaction monitoring (MRM) mode. The two most intense and specific MRM transitions of each compound (quantifier and qualifier transitions) were monitored for identification, confirmation and quantification. Mass-Hunter software (B.07.06) was used for instrument control, data acquisition and quantification. It should be noted that the laboratory participates successfully for many years now in the external quality assessment schemes of the centre de toxicologie du Québec (CTQ) (AMAP Ring Test for Persistent Organic Pollutants in Human Serum) and obtained Cofrac (French Committee for Accreditation) accreditation for this method in accordance with the ISO/CEI 17,025 standard (accreditation n°8-3557, https://www.cofrac.fr).

The plasma concentrations of 44 POPs were assessed, including 20 OCPs (aldrin, dieldrin, o,p'-DDE, o,p'-DDT, p,p'-DDE, p,p'-DDT, cis-nonachlor, trans-nonachlor, oxychlordane, α-endsulfan, β-endsulfan, mirex, heptachlor, cis-heptachlor epoxide, trans-heptachlor epoxide, toxaphene parlar 50, α-hexachlorocyclohexane [HCH], β-HCH, γ-HCH, hexachlorobenzene [HCB]), 16 PCB congeners (28, 31, 52, 74, 99, 101, 118, 153, 156, 170, 180, 183, 187, 194, and the coeluted pairs 138–163 and 196–203), and 8 BFR congeners (the polybrominated diphenyl ethers [PBDEs] 28, 47, 66, 85, 99, 100, and 154, and the polybromobiphenyl [PBB] congener 153).

After excluding 16 compounds detected in <5 % of samples (aldrin, o,p'-DDE, o,p'-DDT, α-endsulfan, β-endsulfan, heptachlor, trans-heptachlor epoxide, toxaphene parlar 50, PCB 31 and all BFRs except BDE 47 – none of which showed differing detection patterns by incident dementia status), 28 compounds were retained for statistical analyses, including 12 OCPs, 15 PCBs and 1 BFR. Limits of detection (LD) for these compounds ranged from 0.01 µg/L to 0.10 µg/L.

## 2.4. Statistical analyses

### 2.4.1. POP measurement pre-processing

POPs were modeled in continuous or in categories, depending on the

proportions of values below the limit of detection (LD), above the limit of quantification (LQ), and in between (i.e., [LD-LQ], where values correspond to uncertain measurements provided by the instrument). Out of the 28 POPs considered, 8 had values ≥LQ in fewer than half of the samples and were categorized into either 3 categories (<LD, [LD-LQ], ≥LQ) when the proportion of values ≥LQ ranged from 5 to 50 %, or into 2 categories (<LD, ≥LD) when the proportion of values ≥LQ was below 5 %. Conversely, the remaining 20 POPs, which had values ≥LQ in at least half of the samples, were treated as continuous variables. In this case, values <LD were imputed, while values between [LD-LQ] were retained, assuming that despite imprecision in their estimation, they were more reliable than imputed values. After imputation by maximum likelihood estimation for left-censored data, assuming a lognormal distribution (5 datasets were generated) (Baccarelli et al., 2005), POP measurement data were log-transformed and standardized.

The 28 POP measurement variables (8 categorical, 20 continuous) were subsequently entered into a factorial analysis for mixed data – a generalization of Principal Component Analysis that handles mixed data types – to reduce dimensionality and summarize the shared information among correlated POPs. We extracted the first component, which explained 37 % of the data variance and was associated with higher levels of all 28 POPs included in the analysis (Supplementary Fig. 2). This first component was used as a summary plasma biomarker measure of total POP exposure.

### 2.4.2. Multivariable analysis

In multivariable analyses of incident dementia, the hazard ratios (HRs) of dementia per 1-SD increase in the POP factorial score and individual POP concentrations or per each category of POPs compared to the non-detected category were estimated using Cox proportional hazard models with cohort time as a time scale. The time of dementia onset was imputed at the midpoint interval between the last visit without dementia and the visit at which dementia was diagnosed. For participants who did not develop dementia, the follow-up time was censored at their last completed visit, whether due to death, loss to follow-up, or end of study. Of note, loss to follow-up remained within the expected range, with proportions of survivors examined at years 2, 4, 7, 10, 12, 14, and 17 being: 94 %, 87 %, 89 %, 85 %, 79 %, 76 % and 73 %, respectively. The proportional hazard assumption was assessed through the interaction between logarithmic time and Schoenfeld residuals.

The associations between each POP (and the POP factorial score) and the trajectories of cognitive decline (latent score of global cognition) or brain atrophy (MTL volume) were estimated using multivariable linear mixed models. Linear mixed models included an intercept representing the cognitive score or MTL volume at baseline, a linear function of time assessing change over time, with corresponding random effects to account for inter-individual variability, POP exposure and covariates (both as a simple effect and in interaction with time). For analyses of the latent score of global cognition, we included an indicator for the first cognitive assessment, as well as test-specific errors to account for differences in measurement errors between the combined cognitive tests. For analyses of MTL volumes, we accounted for the change of MRI scanner at the last MRI examination (from a 1.5 T to a 3 T) by adding a last visit indicator and scanner-specific errors (which allow differences in measurement errors between the 3 T and 1.5 T scanners).

The assumption of a linear relationship between each of the 20 POPs modeled in continuous and brain aging outcomes were investigated using restricted cubic splines for dementia risk, and with natural splines for trajectories of cognition and brain volumes.

Models were primarily adjusted for age at baseline, sex, the level of education, ApoE-ε4 gene, BMI, and total plasma lipid concentrations (and their interactions with time in mixed models). These covariates were selected a priori as key potential confounders, as they are major risk factors for dementia (Livingston et al., 2024), and are also likely to influence plasma POP concentrations (Mansouri and Reggabi, 2021). Then, we evaluated the robustness of results to additional adjustment for
smoking, alcohol consumption, fish consumption, physical activity, cardiometabolic risk factors, number of regularly taken medications, depressive symptoms (and their interactions with time in mixed models).

We considered tests at nominal statistical significance (without correction for multiple testing) as relevant for subsequent exploration, and we secondarily evaluated the robustness of the results through consistency of associations across the three dementia-related outcomes.

Furthermore, we explored potential effect modifications by sex and ApoE-ε4 carrier status (Richardson et al., 2014; Eid et al., 2022; Lin et al., 2008), by sequentially testing interaction terms with each POP. Due to the relatively moderate sample size to study interactions, these investigations were considered exploratory and commented in the text when patterns of associations were consistent in at least two of the three outcomes.

In sensitivity analyses, we excluded individuals (i) reporting a recent weight loss in the last three months, and (ii) obese individuals, because both weight change and obesity alter POP pharmacokinetics and may lead to exposure misclassification (Wolff et al., 2007; Lee et al., 2020). These exclusions also considered the complex and potentially bidirectional relationship between body weight and dementia, as midlife obesity is an established risk factor for dementia, while unintentional weight loss in late-life may be a marker for preclinical dementia (Pedditizi et al., 2016). Furthermore, to account for potential competitive risk by death, we conducted cause-specific Cox models, in which death without prior dementia was treated as a censoring event.

Missing data on covariates (which were missing for 11.1 % for fish consumption, 8.7 % for physical activity, and ≤2.0 % for diabetes, smoking, alcohol, ApoE-ε4 status and plasma lipids) were imputed by multiple imputation using the chained equations method (5 imputed data sets). Estimates obtained on each imputed dataset were pooled according to the Rubin rule (Rubin, 1987).

Statistical analyses were performed using R software version 4.4.2 (with packages mice 3.16.0, FactoMineR 2.11, splines 4.4.2, lcm 1.9.2, nlme 3.1–160, and survival 3.4-0).

# 3. Results

## 3.1. Description of the study population

The study participants were 72.5 years old on average at baseline, 58 % were women and 29 % did not reach secondary school (Table 1). Compared to the 1589 participants from 3C-Bordeaux excluded from the analyses, the 515 included participants were generally younger, more educated, and in better health (Supplementary Table 1).

The POPs with the highest median plasma concentrations at baseline were p,p'-DDE and PCB 153, reaching 3.2 and 2.0 ng/mL, respectively (Supplementary Table 2). Strong correlations were observed between plasma concentrations of POPs, especially between PCB congeners (Supplementary Fig. 2, 3). Although the determinants of plasma POPs could slightly differ between pollutants (Supplementary Fig. 4), overall, participants with higher plasma POP concentrations, as reflected by the POP factorial score (Supplementary Fig. 2), were older, had higher educational level, consumed more alcohol and fish, had higher plasma lipids and were more likely to report a recent weight loss; they were also less likely to take many medications and to have depressive symptoms (Table 1). Conversely to these generally consistent associations between most covariates and POP levels, the relationship of circulating POPs with BMI appeared somehow contrasted across POP families. Hence, higher BMI was related to increased plasma levels of most OCP, but decreased levels of some highly chlorinated PCB (Supplementary Fig. 4).

The median follow-up for cognition and dementia assessment was 12.7 (range 0–18.4) years, over which cognitive function declined on average 1.2 standard-unit per decade, and 105 (21 %) participants developed dementia, including 76 (72 %) Alzheimer's Disease. The median follow-up for MRI measurements was 4.1 (range 0–11.0) years

<caption>**Table 1**</caption>

Participants' characteristics according to a summary measure of baseline plasma concentrations of 28 persistent organic pollutants (POPs) (with ≥5 % detection rate) included in the analysis, the 3C-Bordeaux Study (N = 515).

<table><thead><tr><th rowspan="2"></th><th rowspan="2">Total Population (N = 515)</th><th colspan="4">Quartiles of the factorial score on POPs</th></tr><tr><th>Q1<br>(n = 129)</th><th>Q2<br>(n = 129)</th><th>Q3<br>(n = 128)</th><th>Q4<br>(n = 129)</th></tr></thead><tbody><tr><td>Age, years, mean (SD)</td><td>72.5 (4.0)</td><td>71.7<br>(3.5)</td><td>72.4<br>(4.0)</td><td>72.3<br>(4.0)</td><td>73.6<br>(4.1)</td></tr><tr><td>Sex, female</td><td>58.1</td><td>54.3</td><td>57.4</td><td>62.5</td><td>58.1</td></tr><tr><td>Education, &lt;secondary school</td><td>28.7</td><td>35.7</td><td>29.5</td><td>26.6</td><td>23.3</td></tr><tr><td>ApoE-ε4 carrier</td><td>19.0</td><td>16.4</td><td>20.5</td><td>15.9</td><td>22.5</td></tr><tr><td>Recent weight loss (3 last months) ≥1 kg</td><td>11.1</td><td>8.6</td><td>7.1</td><td>11.3</td><td>17.5</td></tr><tr><td>Number of regularly taken medication, mean (SD)</td><td>4.1 (2.7)</td><td>4.6<br>(2.9)</td><td>3.9<br>(2.7)</td><td>4.0<br>(2.7)</td><td>3.8<br>(2.6)</td></tr><tr><td>History of CVD<sup>a</sup></td><td>27.2</td><td>27.1</td><td>24.8</td><td>26.6</td><td>30.2</td></tr><tr><td>Hypertension<sup>b</sup></td><td>73.4</td><td>69.0</td><td>72.9</td><td>78.1</td><td>73.6</td></tr><tr><td>Diabetes mellitus<sup>c</sup></td><td>6.5</td><td>6.3</td><td>7.1</td><td>5.6</td><td>7.0</td></tr><tr><td>Plasma cholesterol, mmol/L, mean (SD)</td><td>5.7 (0.9)</td><td>5.4<br>(0.9)</td><td>5.6<br>(0.9)</td><td>5.8<br>(0.9)</td><td>6.1<br>(0.9)</td></tr><tr><td>Plasma triglycerides, mmol/L, mean (SD)</td><td>1.2 (0.6)</td><td>1.0<br>(0.4)</td><td>1.2<br>(0.5)</td><td>1.2<br>(0.5)</td><td>1.5<br>(0.8)</td></tr><tr><td>Plasma total lipids,<sup>d</sup> mmol/L, mean (SD)</td><td>6.7 (1.1)</td><td>6.3<br>(1.0)</td><td>6.6<br>(1.0)</td><td>6.8<br>(1.0)</td><td>7.3<br>(1.2)</td></tr><tr><td>Body Mass Index</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;25 kg/m<sup>2</sup></td><td>40.4</td><td>41.9</td><td>41.1</td><td>42.2</td><td>35.7</td></tr><tr><td>25–30 kg/m<sup>2</sup></td><td>43.3</td><td>41.1</td><td>41.9</td><td>43.0</td><td>48.1</td></tr><tr><td>≥30 kg/m<sup>2</sup></td><td>16.3</td><td>17.1</td><td>17.1</td><td>14.8</td><td>16.3</td></tr><tr><td>Smoking</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0 pack-year</td><td>62.5</td><td>64.1</td><td>62.5</td><td>60.8</td><td>61.7</td></tr><tr><td>&lt;20 pack-year</td><td>17.1</td><td>14.8</td><td>15.6</td><td>16.8</td><td>21.1</td></tr><tr><td>≥20 pack-year</td><td>20.6</td><td>21.1</td><td>21.9</td><td>22.4</td><td>17.2</td></tr><tr><td>Daily alcohol intake</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>0 g/d</td><td>18.8</td><td>24.2</td><td>15.6</td><td>21.3</td><td>14.2</td></tr><tr><td>≤12 g/d</td><td>44.5</td><td>52.3</td><td>43.0</td><td>37.0</td><td>45.7</td></tr><tr><td>12–24 g/d</td><td>18.0</td><td>14.8</td><td>18.8</td><td>19.7</td><td>18.9</td></tr><tr><td>&gt;24 g/d</td><td>18.6</td><td>8.6</td><td>22.7</td><td>22.0</td><td>21.3</td></tr><tr><td>Fish consumption<sup>e</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt;1 time/week</td><td>6.3</td><td>8.0</td><td>2.6</td><td>7.1</td><td>7.6</td></tr><tr><td>1–2 times/week</td><td>19.7</td><td>20.4</td><td>27.2</td><td>16.1</td><td>15.1</td></tr><tr><td>2–3 times/week</td><td>25.5</td><td>33.6</td><td>25.4</td><td>23.2</td><td>20.2</td></tr><tr><td>3–4 times/week</td><td>21.8</td><td>22.1</td><td>21.1</td><td>25.9</td><td>18.5</td></tr><tr><td>≥4 times/week</td><td>26.6</td><td>15.9</td><td>23.7</td><td>27.7</td><td>38.7</td></tr><tr><td>Regular physical activity<sup>f</sup></td><td>33.0</td><td>31.7</td><td>35.9</td><td>28.2</td><td>36.2</td></tr><tr><td>Depressive symptoms<sup>g</sup></td><td>15.7</td><td>20.3</td><td>16.1</td><td>17.3</td><td>9.3</td></tr></tbody></table>

Abbreviations: ApoE ε4, allele ε4 for the apolipoprotein E gene; CVD cardio and cerebrovascular diseases.

Figures are percentages of non-missing values unless otherwise stated. Due to rounding, the sum of percentages may deviate slightly from 100 %. Values were missing for fish consumption (11.3 %), physical activity (8.7 %), weight loss (1.9 %), diabetes (1.7 %), depressive symptoms (1.4 %), tobacco (1.2 %), alcohol (1.0 %), ApoE4 (1.0 %) and plasma lipids (0.2 %).

<sup>a</sup> self-reported history of myocardial infarction, angina, heart rhythm disorders and heart failure, arteritis of the lower limbs disease, stroke or cardiac/vascular surgery.

<sup>b</sup> systolic to diastolic blood pressure ≥140/90 mm Hg or treated.

<sup>c</sup> fasting glucose ≥7.2 mmol/L or treated.

<sup>d</sup> computed from total cholesterol and triglycerides levels following Philips et al (1989)'s equation.

<sup>e</sup> Food Frequency Questionnaire administered at the first follow-up visit (2001–2002).

<sup>f</sup> practicing a sport or an intensive leisure activity (e.g., hiking) ≥1 h/wk or engaging in a more moderate activity (e.g., walking or household) ≥1 h/d.

<sup>g</sup> Center for Epidemiologic Studies Depression scale ≥16 or treated.
over which the MTL to total intracranial volume ratio decreased on average 0.25 standard-unit per decade.

## 3.2. Associations of plasma POP measurements with dementia-related outcomes

In multivariable-adjusted models, the POP factorial score was not associated with any of the three brain aging outcomes (Fig. 1). Similarly, when looking at each POP individually, we found no evidence of adverse relationships, except for PCB 52 that was associated with a higher risk of dementia (hazard ratio (HR) [95 % confidence interval (CI)] = 1.73 [1.11; 2.70] for participants with detected compared to non-detected concentrations) but neither with cognitive decline nor brain atrophy (Fig. 2 and Supplementary Table 3). On the contrary, there were trends toward protective associations for higher p,p'-DDT and most PCBs with lower dementia risk and lower cognitive decline (Fig. 2). For instance, a 1 SD-increase in p,p'-DDT log-concentrations was associated with a 22 % decrease in dementia risk (HR [95 % CI] = 0.78 [0.63–0.98], p = 0.032) and a 0.05-SD [−0.01; 0.11] slower rate of cognitive decline per decade, that did not reach statistical significance (Supplementary Table 3). This apparently protective trend was especially true for women (Supplementary Fig. 5), although interaction tests were not statistically significant. However, there was no association of DDT or any PCBs with MTL atrophy. Results remained similar after adjusting for smoking, alcohol consumption, fish consumption, physical activity, history of cardiovascular disease, hypertension, diabetes mellitus, number of regularly taken medications and depressive symptoms (Supplementary Fig. 6). We also obtained similar results when focusing on the risk of AD specifically, rather than all-cause dementia.

The investigation of the dose-response relationship between POPs and brain aging outcomes suggested some departure from linear associations for PCB congeners 99, 118, 138–163, 153, 183, and 187 in relation with dementia risk, but these observations did not reproduce with the two other outcomes (cognitive decline and brain atrophy) and did not change the main conclusions toward null associations overall (Supplementary Figs. 7–9).

## 3.3. Additional analyses

We observed significant interactions between plasma levels of several POPs and the ApoE gene on MTL atrophy, specifically with PCB congeners 180, 194, and 196–203, which showed consistent patterns of associations with incident dementia and cognitive decline (Supplementary Fig. 10). For example, higher plasma levels of PCB 194 were linked to an increased risk of dementia, steeper cognitive decline and accelerated MTL atrophy among ApoE-ε4 carriers (HR [95 % CI] for dementia risk per each SD increase in log-PCB 194 = 1.51 [1.03–2.21]; β coefficient (95 % CI) for cognitive decline = -0.18 [−0.37; 0.02]; for MTL atrophy = -0.28 [−0.49; −0.06]), whereas these associations were reversed in ApoE-ε4 non-carriers (interaction p-values ≤ 0.01).

In sensitivity analyses, associations weakened slightly toward the null for most POPs in relation to cognitive decline when excluding individuals reporting recent weight loss, and for highly chlorinated PCBs in relation to dementia risk when excluding obese participants (Supplementary Fig. 11). Moreover, accounting for the potential competing risk of death prior to dementia – death occurring in 46 % of participants during follow-up – yielded results similar to our primary analysis.

## 4. Discussion

In this large French cohort of community-dwelling older adults followed for up to 17 years, we found no consistent evidence of adverse associations between plasma concentrations of several POPs and incident dementia, cognitive decline or brain atrophy. Some signals emerged for specific POPs but remained inconclusive. In particular, PCB 52 was related to higher dementia risk, but this was not consistent across other outcomes. Besides, highly chlorinated PCBs showed harmful associations with all outcomes among ApoE-ε4 carriers, but opposite associations among non-carriers. Conversely, associations were in some instance contrary to expectations, i.e., whereby higher levels in p,p'-DDT and certain PCBs were associated with lower dementia risk or cognitive decline. Beyond a weak biological plausibility, these “protective” associations were of limited robustness as most of these were borderline significant trends, and generally not consistent across outcomes and/or population strata (e.g., limited to women and ApoE-ε4

<figure><img src="image_3.png" /></figure>

**Fig. 1.** Multivariable associations of a summary measure of baseline plasma concentrations of 28 persistent organic pollutants (POPs) (with ≥5 % detection rate) included in the analysis with (A) incident dementia, (B) cognitive decline, and (C) atrophy of the Medial Temporal Lobe Volume (MTL), the 3C-Bordeaux Study (N = 515) The absolute risk of dementia and trajectories of global cognition and MTL volumes over time were plotted for three representative levels of low, medium and high POP exposure (percentiles at 25, 50 % and 75 %). The absolute risk of dementia over time was estimated by cause-specific Cox models taking into account potential competitive risk by death. Trajectories of change in global cognition and MTL volume were estimated using multivariable linear mixed models across repeated measures, including an intercept representing the cognitive or volume level at baseline (with corresponding random effect) and a linear function of time to approximate the change over decades of the cognitive score or MTL volume (with corresponding random effects). Models were adjusted for baseline age, sex, level of education, status for the ε4 allele of the apolipoprotein E [ApoEε4] gene, body mass index, total plasma lipid levels (and their interactions with time for linear mixed models). NOTE: The mean predicted trajectories of global cognitive score and MTL volume were plotted for a chosen profile of covariate, i.e., for an average study participant profile (a woman aged 72 years at study baseline; ApoEε4 non-carrier; with more than primary education level; overweight (25–30 kg/m²); and with a plasma lipid concentration of 6.7 mmol/L). Note that the choice of profile is made to optimize graphical representation and has no influence on the differences in trajectories estimated by the model.
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Multivariable associations of baseline plasma concentrations of 28 persistent organic pollutants (POPs) (with ≥5 % detection rate) included in the analysis with incident dementia, cognitive decline, and atrophy of the Medial Temporal Lobe (MTL) Volume over time, the 3C Bordeaux Study (N = 515) Beta coefficients (95 % Confidence Intervals) are per 1-SD increase in standardized log-transformed concentrations for POP modeled in continuous, or relative to the reference category (i. e., <LD) for POPs modeled in categories. Coefficients were estimated using multivariable Cox Proportional Hazards models for incident dementia or linear mixed models for cognitive decline and MTL atrophy. For linear mixed models, we used a linear function of time (with corresponding random effect) to approximate the change over decades of the standardized cognitive score or MTL volume; the displayed coefficients correspond to the estimated effects of POPs on this linear change over decades. Models were adjusted for baseline age, sex, level of education, status for the ε4 allele of the apolipoprotein E [ApoEε4] gene, body mass index, total plasma lipid levels (and their interactions with time for linear mixed models). NOTE: the direction of coefficients is interpreted differently depending on the model: higher risks of dementia are indicated by coefficients >0 (higher = worst), while steeper decline and MTL atrophy are indicated by coefficients <0 (lower = worst).</figcaption></figure>

non-carriers).

The epidemiological studies that have investigated non-occupational PCB or OCP exposure in relation to cognitive aging or dementia have so far yielded conflicting results. While higher blood levels of PCBs have been associated to lower cross-sectional cognitive performance (Fitzgerald et al., 2008; Haase et al., 2009; Bouchard et al., 2014; Przybyla et al., 2017), steeper cognitive decline (Parada et al., 2024) and higher dementia risk (Raffetti et al., 2020), at least three prospective studies reported no significant associations (Lee et al., 2016; Tanner et al., 2020; Medehouenou et al., 2019). Similarly, higher blood OCP levels, especially DDT and DDE, were related to AD risk in two case-controls studies (Richardson et al., 2014; Singh et al., 2013) and to lower cognitive function in two cross-sectional analyses (Kim et al., 2015; Medehouenou et al., 2019); but no association was found in three

prospective studies in relation to dementia incidence or cognitive decline (Lee et al., 2016; Parada et al., 2024; Medehouenou et al., 2019). A number of studies also found unexpected protective trends (as in our analyses with DDT/DDE) between OCPs or PCBs and dementia prevalence (Medehouenou et al., 2014) or cognitive performance/decline (Schantz et al., 2001; Bouchard et al., 2014; Przybyla et al., 2017; Tanner et al., 2020). Of note, in one study, the association between OCPs and the risk of cognitive impairment was only evident after excluding individuals losing body weight in the last five years (Lee et al., 2016), who can have marked release from fat tissue to the circulation (which could bias association results); however in our study, associations remained similar when accounting for recent weight loss. Finally, BFRs have been far less investigated, with broadly null associations (Fitzgerald et al., 2012; Parada et al., 2024).
Differences in exposure levels, timing of exposure assessment, or population characteristics, such as specific vulnerabilities, may account for those inconsistencies across studies. Regarding the dose, the average level of exposure for most POPs (except for DDE) was generally high in our population compared to previous studies conducted in the general population. For example, the total PCB concentration in our study was a median 7.5 ng/mL which is substantially higher than levels observed during the same period among older adults in North America (1.5–1.8 ng/mL in Canada and the US) (Bouchard et al., 2014; Medehouenou et al., 2014) or Italy (5.7 ng/mL) (Raffetti et al., 2020). The relatively high exposure levels of this older French population may reflect extensive industrial PCB history in Europe, later regulation compared to North America (i.e., PCB production was phased out in 1987 in France compared to 1977 in the US), and blood collection in 3C taken closer to the ban (around 10–15 years post-ban) relative to other studies. Similarly for OCPs, compared to US elders in the 1999–2002 National Health and Nutrition Examination Surveys (NHANES), where higher p,p'-DDT, p,p'-DDE, and β-HCH levels were linked to lower cognition (Kim et al., 2015), participants in the 3C study had about six times higher β-HCH levels, while they had approximately half the DDE concentrations, and comparable DDT levels. However, POP levels measured in the general population nowadays and in 3C remain of low-grade magnitude, and lower than the doses tested in most toxicology models at which POPs demonstrate their neurotoxic effects. For example, DDT was shown to affect amyloid pathology *in vitro* and *in vivo* using exposure levels in the range of what people were nonoccupationally exposed to in the 1960s and 1970s (Eid et al., 2022).

Regarding the time-window, it is possible that the exposure window captured in our population of older persons inaccurately reflects life-course exposure to POPs, that is most likely to adversely affect brain health and aging. Experimental studies have demonstrated the developmental neurotoxicity of POPs, but less is known about how exposure through adulthood may influence brain aging trajectories (Pessah et al., 2019). Aging is associated with multiple metabolic changes, including of body weight, which strongly influence levels of lipophilic compounds stored in adipose tissue such as POPs, by affecting half-lives and distribution between adipose tissue and serum (Wolff et al., 2007; Moriceau et al., 2023). Thus, the variability of POP measurements is large in the older age range and may not be accurate enough to reflect cumulative exposure burden or the exposure levels during the relevant time window, potentially leading to inconsistent association estimates with brain endpoints.

There may also be some specific population vulnerabilities, yet not identified or incompletely characterized in existing studies, that may modify the relation of POP exposure to brain aging. We have explored most obvious potential modifiers including sex, obesity/weight loss and APOE4 carrier status. We found trends (of little consistency) that deserve further exploration in other populations. Specifically, the opposing associations between very highly-chlorinated PCBs and brain aging outcomes across APOE carrier status remain unclear. Consistent with our findings, one study reported greater susceptibility to DDE exposure of APOE4-ε4 carriers. POPs are primarily concentrated in plasma lipoproteins, with their binding to lipoproteins rising as the degree of halogenation increases (Matthews et al., 1984). Given the role of APOE in lipoprotein metabolism and lipid transport, APOE may influence POP transport and distribution to the brain. The role of APOE on POP metabolism in the context of brain aging deserves further research.

Furthermore, many POPs are endocrine-disrupting chemicals that can mimic or block hormones, including estrogens (Bonefeld-Jørgensen et al., 2001; Hamers et al., 2011), and one could hypothesize that estrogenic-modulating effects of POPs contribute to some form of neuroprotection in older age (as estrogen have documented effects in AD (Engler-Chiurazzi et al., 2016)). This may also explain why protective associations appeared stronger in women in our study (and others (Bouchard et al., 2014; Przybyla et al., 2017)); however, this remains unsupported by preclinical evidence and largely speculative at this

stage. Besides, we cannot exclude the possibility of mixture effects of POPs with other chemicals. Investigating these interactions is crucial to better capture real-world exposure and its implications for brain aging, and could be the subject of future work.

Our study has several major strengths, including its prospective design with extended follow-up, the use of a comprehensive neuropsychological battery assessing multiple cognitive domains, the clinical diagnosis of dementia adjudicated by an expert committee of neurologists, the use of MRI biomarker detecting early subclinical alterations and the assessment of POP exposure through fasting blood biomarkers. Nevertheless, we cannot exclude the possibility that our findings may be influenced by confounding, selection, or measurement biases. Despite our extensive adjustments for a broad range of potential confounders in sensitivity analyses, residual confounding from unmeasured factors may still obscure true associations. In particular, while the dynamics of adiposity over time are important determinants of POP concentrations and dementia risk in late life (Wolff et al., 2007; Lee et al., 2020; Singh-Manoux et al., 2018), we were only able to account for BMI at baseline and reported weight loss close to that baseline. Future studies might benefit from incorporating data on weight change from adulthood to old age. Additionally, healthy survivor bias cannot be ruled out, as individuals included in our study were likely to be healthier and possibly less susceptible to potential adverse effects of POPs. This concern may be especially relevant in the presence of competing risk of death, where POP exposure would increase mortality risk and thus reduce the likelihood of dementia onset. However, POP measures were not associated with mortality in our study (as in others (Fiolet et al., 2021)), and sensitivity analyses accounting for the competing risk of death prior to dementia onset suggested that this bias was unlikely to have influenced results. Furthermore, we relied on a single blood measurement to assess POP exposure, which may be prone to misclassification (Wolff et al., 2007). Blood is generally regarded as an acceptable proxy for adipose tissue – the gold-standard matrix for capturing long-term POP exposures – and a single timepoint measurement is often considered reliable due to the long half-lives of POPs. However, some studies have reported considerable variability in biomarker pharmacokinetics (Wolff et al., 2007; Moriceau et al., 2023). Repeated POP measurements or physiologically-based pharmacokinetic (PBPK) modeling of earlier POP exposure (Bachelet et al., 2019) may help address some uncertainties. Furthermore, despite our attempt to capture BFR exposure, the analytical method was not optimized for BDEs and limits of detection and quantification were too high to allow adequate analysis in relation to cognitive/brain outcomes. Finally, although the sample size is modest, our study stands as one of the largest available to date. We estimated that the number of incident dementia cases (n = 105) was sufficient to detect a minimal HR of 1.35 per 1-SD increase in POP log-concentrations. When expressed per 1-unit in ng/mL, for e.g. for total PCB log-concentrations (range approx. 0.3 to 3.3 ng/mL) this corresponds to an HR of 2.1. There is little literature available on incident dementia or longitudinal brain outcomes to assess the relevance of this effect size, but the study by Raffetti et al. suggested this is within a plausible range (Raffetti et al., 2020).

In conclusion, this analysis from a large population-based cohort study does not support an association between elevated plasma PCB and OCP concentrations and increased risk of all-cause dementia, cognitive decline, or brain atrophy in French older adults. Further insights may be gained from studies incorporating repeated POP measurements.

### CRediT authorship contribution statement

**Sophie Lefèvre-Arbogast:** Writing – original draft, Funding acquisition, Formal analysis. **Pierre Scala:** Writing – review & editing, Formal analysis. **Aurore Zorilla:** Writing – review & editing, Formal analysis. **Catherine Helmer:** Writing – review & editing, Resources, Investigation. **Jade Chaker:** Writing – review & editing, Resources. **Arthur David:** Writing – review & editing, Resources, Funding acquisition.
**Fabien Mercier:** Writing – review & editing, Resources, Formal analysis, Data curation. **Cécilia Samieri:** Writing – review & editing, Supervision, Funding acquisition, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

**Funding sources:** The Three-City Study is conducted under a partnership agreement between the Institut National de la Santé et de la Recherche Médicale (INSERM), the Institut de Santé Publique, Épidémiologie et Développement of the University of Bordeaux and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The Three-City Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l'Éducation Nationale, Institut de la Longévité, Regional Governments of Aquitaine and Bourgogne, Fondation de France, Ministry of Research-INSERM Programme "Cohortes et collections de données biologiques", French National Research Agency COGNUT ANR-06-PNRA-005 and ANR 2007LVIE 003, the Fondation Plan Alzheimer (FCS 2009–2012), the Caisse Nationale pour la Solidarité et l'Autonomie (CNSA), and Roche Pharma. The sponsors were not involved in the design of the study or in the data analyses or manuscript elaboration.

This project received research support from the "Fondation pour la Recherche Médicale" (ENV202003011520), the association of patients and families "France Alzheimer & Maladies Apparentées" (AAP PFA 2023) and the European Union (European project ExpoSignalz – GAP n°101156353). Views and opinions expressed are however those of the author(s) only, and do not necessarily reflect those of the European. Neither the European Union, nor the granting authority can be held responsible for them.

The authors would like to thank the Leres team for the POP analysis, in particular Marine Elandaloussi and Thi Phuong Thao Dao, for their contribution to optimizing the analytical method and carrying out the analysis campaign, respectively. The authors also acknowledge the research infrastructure France Exposome.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.envint.2025.109756.

## Data availability

Data will be made available on request.

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