Exposure to the World Trade Center Particulate Matter Alters the Gut-Brain Axis in Early Onset Alzheimer’s Disease Mice

Abstract

Background:

The September 11, 2001, catastrophe unleashed widespread destruction beyond the World Center (WTC), with fires and toxic gases leaving lasting impacts. First responders at Ground Zero faced prolonged exposure to hazardous particulate matter (PM), resulting in chronic health challenges. Among the multitude of health concerns, the potential association between the WTCPM and Alzheimer’s disease (AD) has emerged as an area of intense inquiry, probing the intricate interplay between environmental factors and neurodegenerative diseases.

Objective:

We posit that a genetic predisposition to AD in mice results in dysregulation of the gut-brain axis following chronic exposure to WTCPM. This, in turn, may heighten the risk of AD-like symptoms in these individuals.

Methods:

3xTg-AD and WT mice were intranasally administered with WTCPM collected at Ground Zero within 72 hours after the attacks. Working memory and learning and recognition memory were monitored for 4 months. Moreover, brain transcriptomic analysis and gut barrier permeability along with microbiome composition were examined.

Results:

Our findings underscore the deleterious effects of WTCPM on cognitive function, as well as notable alterations in brain genes associated with synaptic plasticity, pro-survival, and inflammatory signaling pathways. Complementary, chronic exposure to the WTCPM led to increased gut permeability in AD mice and altered bacteria composition and expression of functional pathways in the gut.

Conclusions:

Our results hint at a complex interplay between gut and brain axis, suggesting potential mechanisms through which WTCPM exposure may exacerbate cognitive decline. Identifying these pathways offers opportunities for tailored interventions to alleviate neurological effects among first responders.

Keywords

Alzheimer’s disease cognitive decline gut microbiome World Center particulate matter

INTRODUCTION

In the wake of the devastating events of September 11, 2001, the collapse of the World Center (WTC) towers not only left an indelible mark on the landscape of Lower Manhattan but also unleashed a maelstrom of toxic dust and debris into the air. This toxic fallout, laden with a complex amalgamation of hazardous substances, has since been implicated in a myriad of health complications among first responders (FR), survivors, and residents of the area.1 –3 The clinical monitoring of individuals exposed to WTCPM has yielded compelling epidemiological data including cardiovascular, respiratory, and cancer indicating the detrimental impact on health of people exposed to WTCPM, highlighting a substantial public health burden.4 –9

Two decades after the WTC attack, as the FR began to age, questions have arisen regarding the long-term consequences of exposure to WTCPM and its potential neurological ramifications. Among the multitude of health concerns, the potential association between the WTCPM and AD has emerged as an area of intense scientific inquiry, probing the intricate interplay between environmental factors and neurodegenerative pathologies. 10 Clouston et al. 11 have reported signs of early dementia at midlife in FR subjected to WTCPM exposures. It seems that the risk to develop cognitive impairment in these individuals is connected to the inhalation of WTCPM pollutants including neurotoxins, asbestos, multiple chemical elements, polycyclic aromatic hydrocarbons, and pesticides, as previously described in the literature.12 –15 Additionally, a psychological component might also affect the onset and progression of memory decline in FR, such as chronic post-traumatic stress disorder (PTSD) derived from living the 9/11 traumatic and stressful experience. 16 Supporting this study, Prioux et al. 17 have associated the exposure to a traumatic event in FR, more specifically the terrorist attack in Paris 2015, with somatic symptomatology including heart dysregulation, respiratory issues, or sleep problems among others, leading to development of PTSD even 5 years later. It has been shown that PTSD individuals are more prone to develop mild cognitive impairment (MCI) and dementia.18,19, 18,19 A growing body of scientific literature indicates that FR who were exposed to high levels of WTCPM for prolonged periods of time may have a greater incidence of MCI, as well as other neurological complications, i.e., changes in white matter connectivity, decreased hippocampal volume which may put them at a greater risk of developing AD-related dementias (ADRD). 20 In a longitudinal study of FR exposed to the WTCPM, showed that these individuals carrying at least one allele of the AD-linked APOE4 variant have a significantly elevated risk of developing MCI, compared to FR with similar exposure levels and do not carry a copy of the APOE4 variant. 16

These epidemiological data have shed light on the wide-ranging health consequences of WTCPM in FR, highlighting the urgent need for comprehensive mitigation strategies. Consequently, it is important to further examine and understand the molecular changes and mechanisms upon WTCPM exposure to identify potential biomarkers linked to WTCPM exposure-related disease and targeted interventions to address the health challenges faced by affected populations. In a previous publication, we showed that recurrent exposure to WTCPM in 5xFAD mice (4–5 months old) triggers generalized immune inflammatory cascades in the periphery as well as brain gene expression changes including changes in Claudin-5 in the hippocampus, involved in blood-brain barrier (BBB) disruption, and therefore possibly contributing to cognitive deterioration and AD-type pathology. 21 This is in line with investigation done by others, where they show that chronic exposure to WTCPM could compromise BBB integrity, associated with various neurodegenerative diseases including ADRD.22 –24

There is a large body of evidence that demonstrates that exposure to environmental pollutants can alter the gut microbiome composition leading to healthy detrimental consequences, including immune dysregulation and more importantly, acceleration of onset and progression of neurodegenerative diseases such as AD.25,26, 25,26

In this investigation, we continue to elucidate the potential impact that WTCPM exposure may have on the gut-brain axis using a mouse model of early onset of AD (EOAD), monitoring longitudinally the behavioral changes, evaluating AD neuropathology, and examining the gastrointestinal (GI) permeability as well as bacteria composition.

MATERIAL AND METHODS

Rodent models

Pathogen-free, male wild-type (WT) (C57BL/6J) (Strain #000664) and EOAD mouse model or transgenic 3xTg-AD (B6.Cg-Tg(APPSwe,tauP301 L)1Lfa Psen1 ^tm1Mpm/2J) (Strain#033930-JAX), were purchased from the Jackson Laboratory Animals (Bar Harbor, ME, USA). All animals were housed in a temperature-controlled (20±2°C) vivarium and maintained on a 12/12-h light/dark cycle. Food and water were available ad libitum. This mouse model of early onset of AD was employed since it develops amyloid-β (Aβ) plaque and tangle pathology, associated with synaptic dysfunction, similar traits to those observed in AD patients. The age of the animals was selected at 8–9 months old since these animals develop Aβ plaques as early as 3–4 months and tau aggregates between 12–15 months. The age of the animals at the beginning of the study was 8–9 months old and at the end was 13–14 months old. All procedures were approved by the Institutional Animal Care and Use Committee of the Icahn School of Medicine at Mount Sinai. All animal experiments complied with the ARRIVE guidelines and were carried out in accordance with the U.K. Animals (Scientific Procedures) Act, 1986 and associated guidelines, EU Directive 2010/63/EU for animal experiments, or the National Research Council’s Guide for the Care and Use of LaboratoryAnimals.

World Center particulate matter (WTCPM) preparation and administration

WTCPM samples from ground zero

The WTCPM samples employed in this study were kindly provided by Dr. Lung-Chi Chen, Professor at NYU Langone Health. It is the sole material remaining from Ground Zero, collected within the first crucial 72 h. The WTCPM has been previously characterized, and it has been found to contain a wide range of different particle sizes including 10–53μm, 2.5–1μm, or ≤2.5μm diameters constituting 42%, 0.5%, and 1.5% of the total mass, respectively.2 –7 However, for our studies only WTC particle samples within the 10–53μm size range were used, previously stored in airtight containers at room temperature and shielded from light exposure.

WTCPM samples preparation and intranasal instillation

The preparation of WTCPM was previously described by our group and others.21,27,28 , 21,27,28 In short, WTCPM was diluted in water and sonicated for 1 h before exposure. Animals were anesthetized using isoflurane (Butler Schein, Dublin, OH), and gently positioned in a supine orientation at an angle of approximately 45°, facilitating unimpeded intranasal administration of suspended WTCPM or water. A total volume of 50μl was administered intranasally, with 25μl delivered into each nostril. The administration was conducted over three consecutive days for three weeks, with a four-day recovery period between each administration cycle. Consequently, all animals (WT and EOAD mice) underwent a total of nine exposures to either WTCPM or vehicle conditions.

The selected WTCPM dose of 125μg (1.125 mg/9 exposures) used in these studies is based on our previous investigation. 21 This dose aims to mimic the exposure air levels of the FR at Ground Zero on the 9/11. According to prior studies using the same WTCPM, this dose was the most physiologically relevant without increasing mortality in the animals.27,28, 27,28 The same authors also detailed the calculations for human equivalent dosing (HED), which involved employing allometric body weight factors of 0.67 (BW∧0.67) and 0.75 (BW∧0.75). These calculations took into consideration weight ratios of 0.02–0.03 kg for mice and 50–70 kg for humans. Additionally, they factored in the intermediate exposure to WTCPM 10–53μm for an 8-h shift at Ground Zero, estimated to be approximately 50 mg/kg.

Cognitive assessment

Spatial working memory

The study of spatial working memory via spontaneous Y-maze was performed at three different time points: 22, 82, and 142 days from the beginning of the experiment [5, 65 days (2 months) and 125 days (4 months) post last WTCPM exposure] on the same WT and EOAD mice. The behavioral protocol followed has been previously described in Iban-Arias et al. 21 Briefly, animals were placed at the start arm on a Y-shaped arm and allowed to explore freely for 10 min. The frequency of alternation on the start, left and right arms was recorded with a NIR camera and integrated with ANY-mazemark tracking software (Version 5.1 Beta, Stoelting Co., IL, USA). A spontaneous alternation occurs when a mouse enters a different arm of the maze in each of three consecutive arm entries. The spontaneous alternation rate (%) is represented by the number of triads (consecutive entries into three different arms: start, left, and right) over the total number of arm entries, calculated using the following formula: Spontaneous alternation = [# spontaneous alternations/(# arm entries –2)] * 100 (%).

Learning acquisition short-term memory and consolidation and recall long-term memory

The study of learning and recognition memory was assessed via the novel object recognition test (NOR) and performed at three different time points: 22, 82, and 142 days from the beginning of the experiment [5, 65 days (2 months) and 125 days (4 months) post last WTCPM exposure]. The behavioral protocol followed has been previously described in Iban-Arias et al. 21 Briefly, mice were allowed to habituate to the environment by placing them into square white boxes (42.5 cm L×42.5 cm W×42.5 cm H) for 2 days prior to the cognitive assessment. On experiment day, mice were placed in the same boxes containing two objects, for 10 min. After 1- and 24-h animals were placed in the same box for short term memory/learning acquisition and long-term memory/consolidation and recall testing, respectively, where the enclosure was prepared with a familiar object from the previous trial and a novel object. The 10-min exploration was recorded with a NIR camera and measured with ANY-maze^™ tracking software (Version 5.1 Beta Stoelting, Co., IL, USA). Potential learning and memory deficits were calculated using a Preference Index defined by the following formula: [Time at novel object/(Time at novel object+Time at familiar object)]×100 (%).

FITC – Dextran gut permeability assay

Living WT and EOAD mice were orally administered with 4-kDa Fluorescein 5(6)-isothiocyanate (FITC) at 82, and 142 days from the beginning of the experiment [65 days (2 months) and 125 days (4 months) post last WTCPM exposure], after performing the behavioral tests. This molecule is a dextran fluorescently labeled tracer used to measure intestinal permeability and determine gut barrier integrity. FITC does not normally translocate from the gut lumen to circulation unless there is an increase in paracellular permeability. Orally gavaged dextran transits to different regions of the GI tract depending on the incubation time between the administration and the blood collection. 4-kDa FITC dextran can reach the colon 4 h after the oral administration; therefore, we can assume that the concentration detected in plasma after this period will reflect paracellular permeability of the intestinal epithelium in this specific intestinal region. 29 Animals were fasted for 4 h prior to FITC administration, to avoid interferences in GI peristalsis and therefore in the FITC uptake. FITC-Dextran (Cat#60842-46-8, Sigma-Aldrich, MO, USA) was diluted in drinking H₂O and used at 120 mg/mL considering the weight of the animals. The solution was always protected from light due to the light sensitivity of the compound. After the fasting period, animals were orally gavaged (100μL/20 g mouse weight) using 1 mL syringes (Cat#309659, BD Microtainer, NJ, USA) attached with gavage needles (20 G, curved, 3.81 cm×2.25 mm) (Cat#CAD7910-12EA, Sigma-Aldrich, MO, USA). After 4 h, animals were anesthetized with Isoflurane (1–3% in oxygen) (Butler Schein, OH, USA), and blood was collected retroorbitally using heparinized micro-hematocrit capillary tubes (Cat#22-362-566, Fisherbrand, MA, USA) and transferred into heparin-coated tubes containing K2EDTA (Cat#365974; BD Microtainer, NJ, USA). Blood was centrifuged at 375×g for 10 min, and plasma was collected and diluted 1 : 10 in 1X PBS. To measure the 4-kDa FITC dextran concentration, samples, and standards (from 10^–5 to 10³μg/mL) were loaded in triplicates into a black 96 well-plates (Cat#3925, Corning Inc., NY, USA), and fluorescence was measured at an excitation/emission wavelength of 490/520 nm using a Varioskan™ LUX Multimode Microplate Spectrophotometer Reader (Cat#VLB000D0, Thermo Scientific, MA, USA). Emission signals from plasma of mice receiving water alone were subtracted from those of mice treated with 4-kDa FITC dextran. Final results were expressed as fold-change, taking into account the standard curve and dilution factor, using the vehicle or naïve as a reference.

Brain collection

Animals of 13–14 months old were anesthetized (125 days post last WTCPM exposure) using Isoflurane (1–3% in oxygen), to collect blood right before euthanization by cervical dislocation. Brains were collected, rinsed in cold 1X PBS, and dissected. One hippocampus was used to examine Aβ content and the other hippocampus was employed for transcriptomic studies and RT qPCR.

Measurement of Aβ content

The levels of Aβ_1–40 and Aβ_1–42 peptides in the hippocampus of 13–14-month-old EOAD mice were determined using ELISA kits specific for mouse Aβ₄₀ (Cat#KMB3481, Invitrogen, MA, USA) and mouse Aβ₄₂ (Cat#KMB3441, Invitrogen, MA, USA) following the manufacturer’s guidelines. Frozen tissue samples were homogenized in a cold buffer (800μL per mouse hippocampus –20–30 mg – or approximately 8×volume of tissue weight), containing 5 M guanidine-HCl/50 mM Tris supplemented with 1X protease inhibitor cocktail with AEBSF (Cat#78431, Thermo Fisher, MA, USA) using the tissue homogenizer Precellys^®24 at 6500 rpm for 60 s. The homogenates were then incubated on an orbital shaker for 3 h at room temperature (RT) and centrifuged at 16,000×g for 20 min. Supernatants were collected, and protein concentration was determined using the BCA assay (Cat#23225, Thermo Fisher, MA, USA). Samples were diluted twenty-fold in BSAT-PBS reaction buffer for Aβ_1–40 (Dulbecco’s phosphate buffered saline – Cat#D8537, Sigma-Aldrich, – with 5% Bovine Serum Albumin – Cat#FB99, Alkali Scientific – and 0.03% Tween-20 – Cat#11332465001, Sigma-Aldrich) or cold-PBS for Aβ_1–42. Triplicates for both standards and samples were used and incubated in Aβ_1–40 or Aβ_1–42 polyclonal antibody-precoated 96-well plates and subsequently read at 450 nm using a Varioskan™ LUX Multimode Microplate Spectrophotometer Reader (Cat#VLB000D0; Thermo Fisher, MA, USA). The levels of Aβ_1–40 and Aβ_1–42 in the hippocampus were calculated based on the measured absorbance, standard curves, total protein concentration, and dilution factor.

Transcriptomic studies

RNA extraction

RNA was extracted from hippocampi of 13–14-month-old WT and EOAD mice (125 days post last WTCPM exposure), using RNA clean & concentrator™-5 (Cat#R2051, Zymo Research, CA, USA). Tissue was homogenized in a 1.5 mL tube including 2-3 glass beads 4 mm (Cat#1.04016.0500, Sigma-Aldrich, MO, USA) in 1 mL of RNAzol^® RT (Cat#R4533, Sigma-Aldrich, MO, USA) using the Bead Mill 24 homogenizer (Cat#15-340-163, Fisher Scientific, MA, USA). After adding 400μL of DEPC-treated water, samples were centrifuged at 12,000×g for 15 min. 700μL of the supernatant was mixed with an equal part of 96–100% ethanol and transferred to a spin column. After centrifugation at 12,000×g for 30 s, the column was prewashed with RNA wash buffer and centrifuged at 12,000×g for 30 s. DNase I was added, and three more washes were done discarding the flow. Lastly, RNA was eluted in 22μL of DNase/RNase Free H₂O, and concentration was measured using a NanoDrop™ 2000 Spectrophotometer (Cat#ND-2000, ThermoFisher Scientific, MA, USA).

Multiplex brain gene expression by Nanostring

Gene expression analysis was performed on extracted RNA samples using the Nanostring nCounter platform in collaboration with the Genomics Core at the Icahn School of Medicine at Mount Sinai. Total RNA samples were standardized to 20 ng/μL, and 100 ng of material from each sample was used as input for the nCounter XT assay using the nCounter Mouse Neuropathology Profiling Panel (XT-CSO-MNROP1-12) following the manufacturer’s instructions. Briefly, the nCounter XT assay and Mouse Neuropathology Profiling Panel were used to hybridize unique fluorescent probes specific to RNA targets from a panel of 770 genes involved in six fundamental themes of neurodegeneration: neurotransmission, neuron-glia interaction, neuroplasticity, cell structure integrity, neuroinflammation, and metabolism. The probes are bound to the original RNA from each sample, and no PCR or other amplification is performed. Unbound probes are washed out and a fluorescent reading of the successfully bound probes is used to assess the counts of each target from the panel and the expression level of each target within each sample. A Nanostring Panel Standard specific to the Mouse Neuropathology Profiling Panel (XT-CSO-MNROP1-12) was run along with the sample cohort. Specifically, a Nanostring Panel Standard is a type of calibration sample that contains a pool of synthetic oligonucleotides corresponding to each probe in the matching nCounter panel and is used to establish a baseline for each target in the final data to normalize expression levels and correct for variability between different studies. Transcriptional data was exported in.rlf file format for analysis using the nSolver Analysis Software package (Version 4.0), with additional downstream analyses performed using Ingenuity Pathway Analysis (IPA; Qiagen, Inc.). Analysis of cell populations by Nanostring cell score was calculated as the average log-scale expression of characteristic genes for specific cell populations as identified by nSolver.

Table 1

Primers used for RT qPCR. All primers target mouse genes

	Primer, 5^′-> 3^′
Gene	Forward (sense)	Reverse (antisense)
Hprt (hypoxanthine phosphoribosyltransferase 1)	CCCCAAAATGGTTAAGGTTGC	AACAAAGTCTGGCCTGTATCC
Itpr2 (inositol 1,4,5-triphosphate receptor 2)	CTCTTGCCTCTGGACGACATAG	CTCCACTTCAGTGTCAACGTAGC
Cxcl12 (C-X-C motif chemokine 12)	GGAGGATAGATGTGCTCTGGAAC	AGTGAGGATGGAGACCGTGGTG
Lama2 (laminin α2)	TGGAAGTAGCCGAACCAGGACA	CACCTGGTTCAGAACGAAGTCG
Flt1 (FMS-like tyrosine kinase 1)	TGGATGAGCAGTGTGAACGGCT	GCCAAATGGCAGAGGCTTGAACG
Mapt (microtubule-associated protein tau)	CCTGACAAAGTGACCTCCAAG	CAAGGAGCCAATCTTCGACTGG
Flt4 (FMS-like tyrosine kinase 4)	AGACTGGAAGGAGGTGACCACT	CTGACACATTGGCATCCTGGATC
Calm1 (Calmodulin 1)	GCACCATCACAACCAAGGAACTG	ACTCTGGGAAGTCAATGGTGCC
Itpr3 (inositol 1,4,5-triphosphate receptor 3)	GCAACCACATCTGGACGCTCTT	AGAAGGCACTGATGGTGTCCAG
Myrf (Myelin regulatory factor)	TGGCAACTTCACCTACCACA	GTGGAACCTCTGCAAAAAGC
BCI2I1 (BCL2-like 1)	GCCACCTATCTGAATGACCACC	AGGAACCAGCGGTTGAAGCGC
Bld (BH3 interacting domain death agonist)	CCACAACATTGCCAGACATCTCG	TCACCTCATCAAGGGCTTTGGC
Ngf (nerve growth factor)	GTTTTGCCAAGGACGCAGCTTTC	GTTCTGCCTGTACGCCATCAA
Hif1a (hypoxia inducible factor 1, alpha subunit)	CCTGCACTGAATCAAGAGGTTGC	CCATCAGAAGGACTTGCTGGCT
Ikbkb (inhibitor of kappa beta kinase beta)	GCAGACTGACATTGTGGACCTG	ATCTCCTGGCTGTCACCTTCTG
Acdy5 (adenylate cyclase 5)	TGGAGATGGGAATGGACATGAT	CACGCGATGTTCACGTT
Psd95 (postsynaptic density protein 95)	GGGCCACGAAGCTGGAGCAG	CCAGGTGGTGGAGGCAGGGT

Gene expression validation by quantitative RT qPCR

Hippocampal RNA isolates were reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Cat#4368813, Thermo Fisher, MA, USA) according to the manufacturer’s instructions. 30–40 ng of RNA was used per reaction and yielded 2–3μg/μl of DNA. Three biological replicates were used for each sample. Gene expression was measured by Real-Time Quantitative Polymerase Chain Reaction (RT qPCR) using Power SYBR Green PCR Master Mix (Cat# 4367659, Thermo Fisher, MA, USA) in an ABI PRISM 7900HT Sequence Detection System at the Genomics Core at the Icahn School of Medicine at Mount Sinai. The list of genes and primers is shown in Table 1. Hypoxanthine phosphoribosyltransferase (Hprt) expression levels were used as internal control. Fold change in cDNA levels of target genes were normalized to WT vehicle or non-exposed to WTCPM using the 2^-ΔΔCt method.

Phylogenetic 16S rDNA microbiota studies

Stool collection and DNA extraction

To study the gut immune system changes after WTCPM exposure in WT and EOAD mice, stools from 13–14-month-old mice (125 days post last WTCPM exposure) were collected into empty 1.5 mL Eppendorf using sterile forceps and stored at –80°C until further analysis. Stool DNA extraction was performed using the QIAamp Fast DNA Stool Mini Kit (Cat#51604; Qiagen, MD, USA) according to the manufacturer’s instructions. Briefly, stools were transferred onto tubes containing glass beads 4 mm (Cat#1.04016.0500; Sigma-Aldrich, MO, USA) and InhibitEX buffer and homogenized using the Bead Mill24 homogenizer (Cat#15-340-163; Fisher Scientific, USA) for 1 min. Further lysis of bacteria was done by incubating the resulting homogenate at 70°C for 5 min and centrifugation at 20800×g. Protein digestion was done by adding Proteinase K into fresh tubes and incubating them at 70°C for 10 min. The resulting suspension was transferred onto the QIAamp spin columns for a few washings with absolute ethanol and 20800×g centrifugations. DNA was eluted with UltraPure DNase/RNase-Free Distilled Water and centrifuged once again. DNA quality and yields were measured in Nanodrop (Cat#ND2000; Thermo Fisher, MA, USA) and found to be from 2–30 ng/μL among all samples. Samples were stored at –80°C until further use.

PCR amplification and 16S rDNA sequencing

Stool-extracted DNA was delivered to LC Sciences, LLC (Houston, TX) in dry ice. The 5^′ ends of the primers were tagged with specific barcodes per sample and sequencing universal primers. PCR amplification was performed in a total volume of 25μL reaction mixture containing 25 ng of template DNA, 12.5μL PCR Premix, 2.5μL of each primer, and PCR-grade water to adjust the volume. The PCR conditions to amplify the prokaryotic 16S fragments consisted of an initial denaturation a 98°C for 30 s, 32 cycles of denaturation at 98°C for 10 s, annealing at 54°C for 30 s, and extension at 72°C for 45 s, and final extension at 72°C for 10 min. The PCR products were confirmed with 2% agarose gel electrophoresis. Throughout the DNA extraction process, ultrapure water, instead of a sample solution, was used to exclude the possibility of false-positive PCR results as a negative control. The PCR products were purified by AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA) and quantified by Qubit (Invitrogen, MA, USA). The amplicon pools were prepared for sequencing and the size and quantity of the amplicon library were assessed on Agilent 2100 Bioanalyzer (Agilent, CA, USA) and with the Library Quantification Kit for Illumina (Kapa Biosciences, Woburn, MA, USA), respectively. The libraries were sequenced on the NovaSeq PE250 platform according to the manufacturer’s recommendations, provided by LC-Bio.

16S data analysis

Paired-end reads were assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequence. Paired-end reads were merged using FLASH (v1.2.8). Quality filtering on the raw reads was performed under specific filtering conditions to obtain high-quality clean tags according to fqtrim (v0.94) with sliding windows to retain sequences having average quality scores≥20 and longer than 100 bp in size. Chimeric sequences were discarded using Vsearch software (v2.3.4). After dereplication using DADA2, ASV feature sequences were obtained and quantified. Singleton ASVs were excluded from further analysis. Alpha diversity and beta diversity were calculated by normalization to the same sequences randomly. Then, according to SILVA (release132) classifier, feature abundance was normalized using the relative abundance of each sample. Alpha diversity is applied in analyzing the complexity of species diversity for a sample through 5 indices, including Chao1, Observed species, Goods coverage, Shannon, Simpson, and all these indices in our samples were calculated with QIIME2. Beta diversity analysis was performed similarly by QIIME2. Graphs were generated by ggplot2 (R package v3.5.2). Blast was used for sequence alignment, and the feature sequences were annotated with SILVA database for each representative sequence. Differential analysis was performed based on relative abundance values. The Mann-Whitney U test was used for comparisons between 2 groups. The Kruskal-Wallis’s test was used for comparisons among 3 or more groups. A species with p < 0.05 is considered significantly differential species.

Statistical analysis

All values are expressed as the mean and standard error of the mean (SEM). These values are depicted in the figure legends. Grouped analysis using two-way ANOVA (or mixed model), corrected with Tukey’s posthoc test was performed for multiple comparisons with mouse strain and treatment as dependent variables. T-test analysis was used to compare two experimental groups. Outliers (2 SD from the mean) were removed from the analysis. Statistical analysis was performed using GraphPad Prism (version 9.5.0). Significant differences were set to ^* p≤0.05, ^** p≤0.01, ^*** p≤0.001, ^**** p < 0.0001.

RESULTS

WTCPM exposure compromises memory performance in EOAD mice

Prior research has uncovered an elevated prevalence of cognitive impairment among WTC FR compared to unexposed individuals, indicating deficits in reaction time, cognitive processing, and memory function. 30 Additionally, in our lab we previously demonstrated that recurrent exposure to high levels of WTCPM could exert more pronounced effects on cognition in 4–5-month-old 5xFAD mice. 21 In this study, we investigate the impact of WTCPM exposure on cognitive performance longitudinally in 8–9-month-old AD mice that develop AD-type phenotype.

Animals were intranasally administered with WTCPM for 3 consecutive days (125μg/50μl/animal/dose) for 3 weeks, with 4 days-rest between treatments (Fig. 1A–C). The spatial working memory, short term, and long-term memory were longitudinally monitored at 3 different timepoints: 5 days, 65 days (2 months) and 125 days (4 months) post-final WTCPM exposure, where the animals were 9–10 months old, 11–12 months old, and 13–14 months old, respectively (Fig. 1A–C). WT animals exposed to the WTCPM did not exhibit statistically significant changes for any of the memory tests throughout the experiment when compared to WT non exposed animals (Fig. 1A–C). In contrast, EOAD mice exposed to the WTCPM did show less frequency of alternation compared to non-exposed EOAD mice, depicting decreased spatial working memory after 5 days (^* p = 0.03) (Fig. 1Ai), and 65 days (2 months) (^* p = 0.04) (Fig. 1Bi) post final exposure. However, no significant changes were observed 125 days (4 months) after last exposure (Fig. 1Ci).

Fig. 1

A) WTCPM exposure timeline depicting the first time point at 22 days, or 5 days post last WTCPM exposure. WT and early onset of Alzheimer’s disease (EOAD or 3xTg-AD) mice were treated intranasally with either vehicle (H₂O) or WTCPM (125μg/dose diluted in H₂O) on three consecutive days for 3 weeks (with a 4-day recovery between each round of exposures). A total of 9 exposures were conducted. 5 days after last exposure memory and learning performance were measured using Y-maze and Novel Object Recognition (NOR). Evaluation of spatial working memory measuring the frequency of alternation among the three arms using the Y-maze spontaneous alternation assay (Ai). WT mice did not show significant differences (p = ns). EOAD mice exposed to WTCPM exhibited significant impairment compared to non-exposed animals (^* p = 0.03). Learning acquisition and memory consolidation and recall using the preference Index (Aii). WT mice did not show significant differences (p = ns). EOAD mice exposed to WTCPM exhibited significant impairment compared to non-exposed (^* p = 0.03). Long-term memory consolidation examined 24 h after the second session (Aiii). WT mice did not show significant differences (p = ns). EOAD mice exposed to WTCPM exhibited significant impairment compared to non-exposed mice (^* p = 0.04). B) WTCPM exposure timeline depicting the time point 65 days post last WTCPM exposure. Y-maze spontaneous alternation assay (Bi) WT mice did not show significant differences (p = ns). EOAD mice exposed to WTCPM exhibited significant impairment compared to non-exposed animals (^* p = 0.04). Learning acquisition and memory consolidation and recall using the preference Index (Bii). WT mice did not show significant differences (p = ns). EOAD mice exposed to WTCPM exhibited significant impairment compared to non-exposed (^* p = 0.03). Long-term memory consolidation examined 24 h after the second session (Biii). WT and EOAD mice did not show significant differences between treatments (p = ns). C) WTCPM exposure timeline depicting the time point 125 days post last WTCPM exposure. Y-maze spontaneous alternation assay (Ci) WT and EOAD mice did not show significant differences (p = ns). Learning acquisition and memory consolidation and recall using the preference Index (Cii). WT and EOAD mice did not show significant differences (p = ns). Long-term memory consolidation examined 24 h after the second session (Ciii). WT and EOAD mice did not show significant differences between treatments (p = ns). WT vehicle n = 8, WT WTCPM n = 8, EOAD vehicle n = 14, EOAD WTCPM n = 14. Statistics are shown in Supplementary Table 1.

Next, we assess learning acquisition and consolidation of short-term memory. For that, animals were allowed to habituation to the apparatus 24 h prior to the tests. Afterwards, mice were put back into the test boxes and presented with two identical objects to explore for 10 min. After 1 h intersession interval, mice were allowed to explore the boxes for 10 min, having one of the two objects replaced by a novel or unfamiliar object. This test showed that EOAD mice exposed to the WTCPM did show less preference for the novel object compared to non-exposed EOAD mice, reflecting reduced short term/learning acquisition memory after 5 days (^* p = 0.03) (Fig. 1Aii), and 65 days (2 months) (^* p = 0.03) (Fig. 1Bii) post final exposure. However, no significant changes were observed 125 days (4 months) after last exposure (Fig. 1Cii).

Subsequently, 24 h after the second session mice were returned to the test boxes where the novel object had been replaced with a second new object to examine long-term memory consolidation and recall. EOAD mice exposed to the WTCPM presented lower exploratory preference for the novel object compared to non-exposed EOAD mice, only 5 days (^* p = 0.04) (Fig. 1Aiii) after last WTCPM exposure, but no changes between groups were observed for the last two time points after 65 (2 months) and 125 days (4 months) post last exposure. All raw statistics are presented in Supplementary Table 1.

These results provide support for our hypothesis that repeated WTCPM exposure may have stronger effects on cognition, more specifically learning acquisition and memory consolidation, in animals that are genetically determined to develop AD-type pathology.

Aβ_1–40 and Aβ_1–42 levels in the mouse hippocampus following WTCPM exposure in old EOAD mice

Clinical studies have correlated PTSD in FR individuals with high Aβ_1–42/Aβ_1–40 in plasma. 31

Hence, to further corroborate the involvement of Aβ neuropathology in the cognitive decline observed in EOAD mice, we measured Aβ_1–42 and Aβ_1–40 levels in hippocampus by ELISA, 4 months post last WTCPM exposure.

Interestingly, we did not see an impact of WTCPM exposure in 13–14-month-old EOAD compared to EOAD vehicle in either Aβ_1–42 (p = ns) (Fig. 2A), Aβ_1–40 levels (p = ns) (Fig. 2B) or Aβ_1–42/Aβ_1–40 ratio (p = ns) (Fig. 2C). This is in accordance with previous data where 5–6-month-old 5xFAD mice did not exhibit differences in Aβ content in either the prefrontal cortex or the hippocampus. 21

This evidence plausibly supports the hypothesis that 13–14-month-old mice may reach a plateau in Aβ content in the hippocampus, since we did not observe significant WTCMP-induced differences in EOAD at this time point of the experiment, it leads us to the conclusion that these animals have likely reached the peak cognitive loss and Aβ content in this brain region.

Fig. 2

ELISA analysis for Aβ levels in the hippocampus of 13-14-month-old EOAD mice. No significant effect of WTCPM exposure was observed in EOAD mice for Aβ_1–42 (Mean±S.E.M: vehicle: 373.1±49.16; WTCPM: 333.9±41.47) (A), Aβ_1–40 (Mean ± S.E.M: vehicle: 176.1±16.79; WTCPM: 238.8±47.37) (B), or in the ratio Aβ_1–42/Aβ_1–40 (Mean ± S.E.M: vehicle: 2.21±0.33; WTCPM: 1.5±0.18) (C). EOAD vehicle n = 6, EOAD WTCPM n = 6.

WTCPM exposure alters the brain transcriptional phenotype

In a prior study we demonstrated that the exposure to WTCPM in 2–3-month-old 5xFAD mice can lead to transcriptional changes both in the periphery and in brain, depicting changes in the innate immune response and in the BBB composition. 21

In this study, we aim to examine the long-term effects of WTCPM exposure in the brain transcriptional profile of 13–14-month-old EOAD mice and WT age-matched animals. For that, hippocampi were collected after 125 days (4 months) post-final WTCPM exposure, RNA isolated (see methods for further details) and brain transcriptional changes analyzed using the Nanostring nCounter Mouse Neuropathology Panel (XT-CSO-MNROP1-12) in collaboration with the Genomics Core Facility at the Icahn School of Medicine at Mount Sinai. From screening of a total 770 genes specific for neurodegeneration, we found 12 genes differentially expressed (10 downregulated: Pecam1, Itpr2, Ntf3, Fn1, Osmr, Cxcl12, Lama2, Col4a1, Flt1, and Esam; 2 upregulated: Ggt1 and Nme5) for the pairwise comparison WT mice vehicle versus WT mice exposed to WTCPM as depicted in the volcano plot (Fig. 3A–C; Supplementary Figure 1A). These genes are known to be involved in important signaling pathways including synaptic long-term potentiation, acetylcholine receptor signaling, CXCR4 signaling, CREB signaling in Neurons, mitochondrial dysfunction or GABAergic receptor signaling pathway, VEGF signaling, or PTEN signaling and myelination signaling pathway. Gene validation was performed by RT-qPCR studies for all the differentially expressed genes found in the transcriptomics studies; however, only the expression of Itpr2 (Fig. 3Di), Cxcl12 (Fig. 3Dii), and Flt1 (Fig. 3Diii) was confirmed, where WT animals exposed to WTCPM revealed lower expression levels compared to the non-exposed WT mice (Supplementary Table 2). These genes are known to be involved in synaptic long-term potentiation, CREB signaling in neurons, acetylcholine receptor signaling pathway, Cxcr4 signaling, mitochondrial dysfunction or GABAergic receptor signaling pathway, was validated in WT mice depicting significant transcriptional downregulation of this gene due to WTCPM exposure. Analysis of cell populations by Nanostring cell score was calculated as the average log-scale expression of characteristic genes for specific cell populations as identified by nSolver. However, no significant changes were observed.

Fig. 3

Transcriptomic analysis in hippocampus of WT mice exposed to WTCPM. Volcano plot depicting differentially expressed genes in the hippocampus of WT mice exposed to WTCPM compared to vehicle WT mice. Genes where p < 0.05 are depicted in red. Top upregulated genes as identified by the absolute value of log2fold change are labeled (A). Summary of number of genes significance represented by -Log10 (p-value) >1.3 or < –1.3 (B). Bubble plot representing the significantly differentiated genes, bubble color represents each gene, and size represents the p-value (C). RT qPCR gene validation for Itpr2, (Mean±S.E.M: vehicle: 1±0.05; WTCPM: 0.75±0.03) (^* p = 0.02) (Di), Cxcl12 (Mean±S.E.M: vehicle: 1±0.06; WTCPM: 0.79±0.03) (^* p = 0.05) (Dii), Flt1 (Mean±S.E.M: vehicle: 1±0.10; WTCPM: 0.64±0.05) (^* p = 0.03) (Diii), genes are significantly downregulated in the hippocampus of WT mice following exposure to WTCPM. Heatmap showing the significantly up- and down-regulated pathways characterized by p < 0.05, and -1.5 < Z< +1.5, performed by Ingenuity pathway analysis (E). For transcriptomics studies n = 6 was used for each group. For brain gene validation n = 3 was used.

To further comprehend our transcriptomic data, additional downstream analyses were performed using Ingenuity Pathway Analysis (IPA; Qiagen, Inc.) indicating the up or down regulation of molecules and pathways that may be involved in the phenotypic or functional outcome upon WTCPM exposure. A significance threshold of p < 0.05 was established a priori to determine canonical pathway enrichment. The top and most relevant 20 differentially activated pathways were expressed using the absolute Z-score value, choosing a threshold of –1.5 > Z < 1.5. The exposure to WTCPM in WT mice revealed a downregulation of pathways associated with synaptogenesis, myelination or CREB signaling in neurons, as well as upregulation of mechanisms involving apoptosis, SAPK/JNK signaling, mitochondrial dysfunction or inflammatory signaling pathways, compared to non-exposed or vehicle WT mice, as shown in the heatmap in Fig. 3E.

Similarly, from the total 770 genes for neurodegeneration screened, we found 17 genes differentially expressed (12 downregulated: Polr2 h, Taf10, Ctns, Nol3, Uchl1, Xbp1, Cab39, Ngf, Hif1a, Ikbkb, Gtf2h1, Eif2s1; 5 upregulated: Bid, Ide, Nostrin, Itpr3, Adcy5) for the pairwise comparison EOAD vehicle mice versus EOAD mice exposed to WTCPM as shown in the volcano plot (Fig. 4A–C; Supplementary Figure 1). These genes are known to be involved in important signaling pathways including the pro-survival ERK5 signaling, myelination signaling pathway, p75NTR-mediated signaling, synaptogenesis signaling pathway, synaptic long-term potentiation, mitochondrial dysfunction, CREB signaling in neurons, glutaminergic receptor signaling pathway, or IL23 signaling pathway. Gene validation studies by RT-qPCR showed that only the expression of Itpr3 was confirmed, where EOAD mice exposed to WTCPM depicted higher expression levels compared to non-exposed mice (Fig. 4Di; Supplementary Table 2). Moreover, an additional gene tested, namely Psd95, known to be a major regulator of synaptogenesis, was observed to be decreased in EOAD mice exposed to WTCPM compared to non-exposed mice (Fig. 3Dii; (Supplementary Table 2). In a similar manner, no significant changes were observed in cell scores for this comparison. Furthermore, IPA analysis rendered the downregulation of pathways associated with pro-survival signaling pathways such as ERK5, IL4 anti-inflammatory cytokine signaling, myelination or CREB signaling in neurons, as well as upregulation of mechanisms involving autophagy, mTOR signaling, mitochondrial dysfunction, IL23 signaling pathways, or the pro cell death p75NTR receptor-mediated signaling (Fig. 4E).

Fig. 4

Transcriptomic analysis in hippocampus of EOAD mice exposed to WTCPM. Volcano plot depicting differentially expressed genes in the hippocampus of WT mice exposed to WTCPM compared to vehicle WT mice. Genes where p < 0.05 are depicted in red. Top upregulated genes as identified by the absolute value of log2fold change are labeled (A). Summary of number of genes significance represented by –Log10(p-value)>1.3 or< –1.3 (B). Bubble plot representing the significantly differentiated genes, bubble color represents each gene, and size represents the p-value (C). RT qPCR gene validation for Itpr3, (Mean±S.E.M: vehicle: 1±0.08; WTCPM: 1.26±0.06) (^* p = 0.02) (Di), Psd95 (Mean±S.E.M: vehicle: 1±0.05; WTCPM: 0.86±0.02) (^* p = 0.04), genes are significantly upregulated and downregulated, respectively, in the hippocampus of EOAD mice following exposure to WTCPM. Heatmap showing the significantly up- and down-regulated pathways characterized by p < 0.05, and –1.5 < Z< +1.5, performed by Ingenuity pathway analysis (E). For transcriptomics studies n = 6 was used for each group. For brain gene validation n = 9 was used.

The omics data of this study presents the potential impact that WTCPM exposure can have on brain gene expression 125 days (4 months) post last exposure, depicting the potential long-term effect.

Gut permeability is disrupted after WTCPM exposure in EOAD mice

It is known that GI barrier breakdown is associated with gut dysbiosis contributing to the development of central nervous system (CNS) diseases. 32 Here, we aim to examine how the exposure to WTCPM may influence the intestinal epithelial permeability in WT and in an early mouse model of AD, EOAD, 65 days (2 months), and 125 days (4 months) post last exposure.

To measure intestinal permeability and determine gut barrier integrity, WT and EOAD mice were orally administered with a dextran fluorescently labeled tracer known as 4-kDa Fluorescein 5(6)-isothiocyanate (FITC) at 82, and 142 days from the beginning of the experiment (65, and 125 days post last WTCPM exposure). This molecule does not normally translocate from the gut lumen to circulation unless there is an increase in paracellular permeability. Animals were fasted for 4 h prior to FITC gavage administration, to avoid interferences in the GI peristalsis and therefore in the FITC uptake. After 4 h post oral administration, plasma was collected, and fluorescence measured (see methods for more detailed information) (Fig. 5A). No significant changes were observed in WT mice exposed to the WTCPM compared to the non-exposed at either time point (Fig. 5Bi, ii) (p = ns). However, the EOAD group exposed to the WTCPM exhibited a statistically significant increase in fluorescence compared to the non-exposed or vehicle mice after 65 and 125 of last WTCPM exposure (^* p = 0.01; ^* p = 0.02, respectively) (Fig. 5 Ci, ii). Since, FITC typically does undergo translocation from the GI lumen to the circulatory system unless there is an increase in paracellular permeability, the presented data indicates that WTCPM exposure selectively impacts the GI tract in EOAD mice, illustrating a pronounced manifestation of intestinal hyper permeability also known as “leaky guts”.

Fig. 5

Timeline for the intestinal permeability study in 13–14-months-old WT and EOAD mice. Fasted animals were orally administered with 4-kDa Fluorescein 5(6)-isothiocyanate (FITC) at 82, and 142 days from the beginning of the experiment [65 days (2 months) and 125 days (4 months) post last WTCPM exposure], after performing the behavioral tests. After 4 h, mice were anesthetized, and blood collected retro-orbitally to isolate plasma for fluorescence measurement (A). No significant changes were observed in WT mice for 2 months post last WTCPM exposure (Mean±S.E.M: vehicle: 1±0.28; WTCPM: 0.66±0.16) (Bi), or 4 months post last WTCPM exposure (Mean±S.E.M: vehicle: 1±0.19; WTCPM: 1.27±0.25) (Ci). Increased gut permeability was observed in EOAD exposed to WTCPM compared to EOAD vehicle after 2 months post last exposure (Mean±S.E.M: vehicle: 1±0.13; WTCPM: 1.79±0.26) (^* p = 0.01) (Bii), and 4 months post last exposure (Mean±S.E.M: vehicle: 1±0.2; WTCPM: 2.98±0.34) (^* p = 0.02) (Cii).

Gut microbiome composition is altered after WTCPM exposure

There is a large body of evidence that demonstrates that exposure to environmental pollutants can alter the gut microbiome composition leading to detrimental health consequences, including immune dysregulation and more importantly, acceleration of onset and progression of neurodegenerative diseases such as AD.25,26, 25,26 To further explore the impact of WTCPM exposure on the gut microbiome richness and composition in WT and EOAD mice, stool was collected at the last time point of the experiment, 125 days post last WTCPM exposure, prior to sacrifice. DNA was isolated and 16S gene sequencing (see methods for more detailed information) was performed for identification, classification, and quantitation of different bacteriapopulations.

The gut microbial richness was measured using three different alpha-diversity indexes (α-diversity) (Fig. 6A). Using the Chao1 index, we saw that the exposure to WTCPM induced an increased on microbial α-diversity in WT and EOAD mice, the latter also seen with the Shannon index, compared to non-exposed or vehicle mice (Chao1: ^* p = 0.01; ^*** p = 0.0002, respectively; Shannon: ^** p = 0.0009) (Fig. 6Ai, ii). No significant changes were observed between the WT and EOAD vehicle groups using the Chao1 index; however, we did see significant increase in the EOAD vehicle mice compared to WT vehicle using the Shannon and the Simpson diversity indexes (^* p = 0.03; ^*** p = 0.0005, respectively) (Fig. 6Aii, iii). Significant increases were also shown between the two groups exposed to the WTCPM for the Shannon and Simpson α-diversity indexes, where EOAD mice exhibited higher microbial α-diversity than WT (^* p = 0.02; ^* p = 0.01, respectively) (Fig. 6Aii, iii). WTCPM exposure in EOAD led to statistically significant increase compared to WT vehicle mice for all indexes (^**** p < 0.0001) (Fig. 6Ai, ii, iii).

Fig. 6

Phylogenetic 16 S rDNA microbiota analysis in 13–14-months-old WT and EOAD mice. Assessment of alpha diversity using the Chao1 diversity Index (Ai), Shannon diversity index (Aii), and Simpson diversity index (Aiii). PCoA analysis of beta diversity measurements which represents the differences in the compositional gut microbial ecosystem between different groups, exhibiting major microbiome differences between donor clusters (WT vehicle blue, WT WTCPM purple, EOAD vehicle pink, and EOAD WTCPM green) (B). Heatmap representing the relative abundance of phyla for each group (C). A significant increase in Firmicutes phylum was found in EOAD vehicle compared to WT vehicle (Mean±S.E.M: WT vehicle: 38.5±3.06; EOAD vehicle: 51.98±2.54) (^* p = 0.02) (D). A significant increase in Bacteroidota phylum was found in EOAD WTCPM compared to both EOAD WTCPM (^** p = 0.005) and WT vehicle (^*** p = 0.0002) (Mean±S.E.M: WT vehicle: 27.7±2.56; EOAD vehicle: 33.4±1.25; EOAD WTCPM: 44.4±2.8) (E). Ratio Firmicutes/Bacteroidetes showed no significant changes (F). A significant decrease in Actinobacteriota phylum was found in WT WTCPM compared to WT vehicle (Mean±S.E.M: WT vehicle: 31.6±3.34; WT WTCPM: 16.6±2.19) (^*** p = 0.0001), as well as significantly lower abundance in EOAD WTCPM compared to EOAD non-exposed (Mean±S.E.M: EOAD vehicle: 11.4±1.58; EOAD WTCPM: 5.33±1.06) (^**** p < 0.0001). A decrease was also observed between vehicle mice, where EOAD presented a significant decrease (^**** p < 0.0001). WTCPM induced lower levels in EOAD mice compared to WT vehicle (^**** p < 0.0001) (G). For Phylogenetic 16 S studies: WT vehicle n = 8, WT WTCPM n = 8, EOAD vehicle n = 14, EOAD WTCPM n = 14.

We then assessed the similarities in the compositional gut microbial ecosystem among groups also known as beta diversity (β-diversity) (Fig. 6B). Principal Coordinate Analysis (PCoA) plotting of Unweighted UniFrac β-diversity, showing PCoA1 (X-axis) and PCoA2 (Y-axis), accounted for 14.35% and 6.58% of the total population variance revealed a distinct clustering for each group, where a slight overlap can be noted between WT vehicle group (blue) and EOAD vehicle (orange), WT vehicle group (blue) and WT exposed to WTCPM (purple), WT exposed to WTCPM (purple) and EOAD exposed to WTCPM (green).

Analysis for taxonomic classification of operational taxonomic units (OTUs), we identified 29 phyla as observed in the heatmap in Fig. 6C, from which 4 presented statistically significant differences among groups. The relative abundance of Firmicutes exhibited a significant increase in the EOAD vehicle group compared to the WT vehicle group (^* p = 0.02) (Fig. 6D). Another phylum that stood out in our studies was the Bacteroidota, depicting a statistically significant increase in EOAD mice exposed to WTCPM compared to EOAD vehicle and WT vehicle (^*** p = 0.0002; ^** p = 0.005, respectively) (Fig. 6E). The ratio Firmicutes/Bacteroidota (F/B) is an important indicator of microbiome health, however no significant changes were observed among groups (Fig. 6F). Additionally, another bacteria phylum that showed statistically significant changes among groups was Actinobacteriota. Exposure to WTCPM exhibited significantly lower abundance for this bacteria group in WT, and a trend decrease in EOAD mice compared to the vehicle mice (^*** p = 0.0001; ns, p = 0.06, respectively) (Fig. 6G). Also, the genetically predisposed mice to develop AD and non-exposed to WTCPM, presented lower levels for Actinobacteroidota compared to vehicle WT (^**** p < 0.0001), and this abundance seems to be even lower in EOAD mice after the exposure to the WTCPM compared to WT exposed mice (^** p = 0.001) (Fig. 6G). Additionally, within the identified taxons 801 species were analyzed, and 117 were significant in WT mice and 148 in EOAD mice (Supplementary Figure 2). We found that the five most significantly abundant species for both groups were Muribaculaceae, Dubosiella, Bifidobacterium, Lactobacillus and Lachnospiraceae. WTCPM exposure induced higher abundance in Muribaculaceae and Lachnospiraceae in WT and EOAD, and Dubosiella in EOAD mice only. Opposite effect was observed for Bifidobacterium and Lactobacillus, exhibiting lower abundance in WT and EOAD, and Dubosiella in WT mice only (Supplementary Figure 2).

Exposure to WTCPM is associated with altered gut metabolic profile

To further decipher the impact of WTCPM exposure on specific metabolic and/or functional differences in the gut microbiota of WT and EOAD mice, we performed advanced analysis for function prediction with a PICRUSt2 analysis.

KEGG pathway enrichment analysis revealed significant differences in the expression of several key functional pathways between the two pairwise comparisons used in our study (WT vehicle versus WT WTCPM; EOAD vehicle versus EOAD WTCPM). Specifically, pathways related to energy metabolism exhibited notable differential expression levels, suggesting the potential effect of WTCPM exposure in these pathways (Fig. 7A, B). We observed that exposure to WTCPM in WT mice induced significant upregulation of pyruvate metabolism (^**** p < 0.0001) (Fig. 7E), fatty acids biosynthesis (^**** p < 0.0001) (Fig. 7G), biosynthesis of unsaturated fatty acids (^** p = 0.008) (Fig. 7I), lipid biosynthesis (^** p = 0.005) (Fig. 7J) and metabolism (^* p = 0.01) (Fig. 7K), glycerolipid biosynthesis (^*** p = 0.0003) (Fig. 7 L), beta-alanine metabolism (^*** p = 0.0003) (Fig. 7N) and steroid biosynthesis (^* p = 0.03) (Fig. 7O), as well as they presented downregulation of carbohydrate metabolism (^*** p = 0.0001) (Fig. 7F) compared to the WT vehicle group. In the same manner, WTCPM exposure in EOAD mice led to upregulation of energy metabolism (^* p = 0.02) (Fig. 7D), beta-alanine metabolism (^*** p = 0.0002) (Fig. 7N) and steroid biosynthesis (^*** p = 0.0001) (Fig. 7O), and a trend in lipid biosynthesis (ns, p = 0.12) (Fig. 7J), as well as downregulation of amino acid metabolism (^**** p < 0.0001) (Fig. 7M). It is worth noting that EOAD vehicle mice presented highly expressed pathways compared to WT vehicle mice including pyruvate metabolism (^*** p = 0.0002) (Fig. 7E), fatty acids biosynthesis (^** p = 0.001) (Fig. 7G), biosynthesis of unsaturated fatty acids (^* p = 0.01) (Fig. 7I), lipid metabolism (^* p = 0.01) (Fig. 7K), glycerolipid biosynthesis (^** p = 0.008) (Fig. 7L), amino acid metabolism ^**** p < 0.0001) (Fig. 7M) and beta-alanine metabolism (^* p = 0.03) (Fig. 7N). Similarly, EOAD vehicle animals exhibited downregulated pathways such as carbohydrate metabolism (^*** p = 0.0008) (Fig. 7F) and fatty acid metabolism (^** p = 0.007) (Fig. 7H), compared to the WT vehiclegroup.

Collectively, these data suggest that exposure to WTCPM may result in gut dysbiosis, leading to dysregulation of functional pathways associated with energy metabolism, possibly affecting the disease phenotype outcome.

Fig. 7

Functional pathways PICRUSTt2 analysis. KEGG pathway enrichment analysis depicting the mean proportions of the top 20 pathways significantly regulated in WT vehicle versus WT WTCPM (A) and EOAD vehicle versus EOAD WTCPM (B). Pathways associated with energy metabolism exhibited notable differential expression levels, suggesting the potential effect of WTCPM exposure in these pathways. Significantly regulated pathways: upregulation of energy metabolism in EOAD mice exposed to WTCMPM compared to the other three experimental groups (D); exposure to WTCPM in WT mice induced significant upregulation of pyruvate metabolism ^(E); Significant downregulation of carbohydrate metabolism in all groups compared to WT vehicle (F); WTCPM exposure led to upregulation in fatty acids (FA) biosynthesis for both WT and EOAD mice compared to WT vehicle (G); However, FA metabolism was decreased in EOAD mice compared to WT vehicle (H); increased biosynthesis of unsaturated fatty acids for all groups compared to WT vehicle was observed (I); Lipid biosynthesis was upregulated in WT exposed to WTCPM compared to vehicle (J); However, lipid metabolism was increased in all groups compared to WT vehicle (K); glycerolipid biosynthesis was also increased in all groups compared to WT vehicle (L); Amino acid metabolism was highly upregulated in EOAD vehicle mice compared to the other 3 groups (M); WTCPM exposure induced upregulation in beta-alanine metabolism for both strain of mice compared to their own vehicle (N); WTCPM exposure induced also upregulation in steroid biosynthesis (O).

DISCUSSION

Two decades after the World Trade Center (WTC) attack on the 9/11 in 2001, as the FR gradually age, there is a growing concern about the long-term consequences of exposure to WTCPM and its possible impact on neurological health. Among the myriad health considerations, the potential link between WTCPM exposure and AD-like pathology has become a focal point of extensive scientific investigation, highlighting the complex dynamics between environmental elements and neurodegenerative disease. It is well documented that exposure to environmental pollutants can alter the gut microbiome leading to healthy detrimental consequences, including immune dysregulation and more importantly, acceleration of onset and progression of neurodegenerative diseases such as AD.25,26, 25,26

In this study, we aim to further elucidate the potential implications of WTCPM exposure on the gut-brain axis using a mouse model of early onset AD (EOAD), by conducting a comprehensive longitudinal assessment.

Memory performance was monitored over time, and we found only significant differences in the EOAD transgenic mice after 5 and 65 days (2 months) post-final WTCPM exposure (125μg/dose×9 doses), where the animals were 9–10 months old and 11–12 months old. However, no changes were seen 125 days (4 months), where the animals were and 13–14 months old. This may be due to vehicle mice might reach a cognitive decline plateau as a consequence of the aging process exhibiting comparable memory impairment to EOAD mice exposed to WTCPM. In a previous study, we did see significant differences in WT exposed to WTCPM (125μg/dose×9 doses) only for spatial working memory but not for short and long-term recognition memory in 6–7-month-old 5xFAD mice. 21 Here, the fact that we did see significant memory decline in EOAD but not in WT might be attributed to the heightened vulnerability of genetically predisposed EOAD mice to the adverse effects of WTCPM.

This data indicates that the exposure to WTCPM may have a more pronounced impact on genetically predisposed individuals, exacerbating the development of AD-like pathology and accelerating cognitive impairment. Consequently, these individuals may be at a higher risk of experiencing accelerated disease progression. Our findings raise important questions about individual susceptibility to environmental toxins and their interaction with genetic factors in neurodegenerative diseases. Understanding these interactions could provide valuable insights into disease mechanisms and inform personalized risk assessment and interventions in FR.

To deepen our understanding of how exposure to WTCPM impacts brain function at a pathophysiological level, we delved into transcriptome profiling within the hippocampus. Remarkably, both WT and EOAD mice displayed similar responses to WTCPM exposure. This manifested as a notable downregulation of key pro-survival signaling pathways crucial for synaptic integrity, such as CREB and ERK5, alongside an elevation in pro-apoptotic pathways like SAPK/JNK and p75NTR receptor-mediated signaling. Additionally, intriguingly, there was an upregulation observed in pathways associated with mitochondrial function and mTOR signaling. These alterations in brain gene expression likely contribute to the cognitive impairments observed in 13–14-month-old EOAD mice exposed to WTCPM, despite no significant increase in Aβ content within the hippocampus. This evidence plausibly supports the hypothesis that 13–14-month-old mice may reach a plateau in Aβ content in the hippocampus, since we did not observe significant WTCMP-induced differences in EOAD at this time point of the experiment, it leads us to the conclusion that these animals have likely reached the peak cognitive loss and Aβ content in this brain region. While the accumulation of Aβ in the AD brain is indeed a pivotal event in the onset and progression of memory impairment and dementia, 33 it is crucial to recognize that this phenomenon is not exclusive. Other significant neuropathological changes also take place within the AD brain. These multifaceted factors, such as the degeneration of cortical cholinergic and dopaminergic neurons, cerebrovascular abnormalities, and alterations in brain energy metabolism, among others, can collectively contribute to the complex nature of cognitive decline. 34 Consequently, these findings underscore the potential significance of such changes in driving the progression of AD-type symptomatology.

A substantial body of evidence indicates that exposure to environmental pollutants can disrupt both the gut barrier and the microbiome composition, resulting in adverse health outcomes, including the acceleration of neurodegenerative diseases, including AD.25,26, 25,26 However, studies specifically investigating the gut microbiome in individuals exposed to the WTCPM remain limited. To address this gap, our study aims to explore the intricate relationship between environmental pollutants, particularly chronic inhalation of WTCPM, and the gut microbiome.

Investigations have shown that exposure to PM can result in the loss of gut barrier integrity or heightened intestinal permeability, through increased release of pro-inflammatory cytokines and disrupted SCFA, leading to gut dysbiosis. 35 Accordingly, our studies depicted higher paracellular permeability of the intestinal epithelium in colon only in EOAD mice exposed to WTCPM compared to EOAD vehicle after 2 and 4 months post last exposure, but no changes were observed in WT mice. This is in line with findings from other investigations, which observed increased intestinal permeability accompanied by Aβ intestinal deposition, low-level expression of tight junction proteins and elevated levels of pro-inflammatory cytokines in a double transgenic AD mice aged 6 and 12 months compared to their age-match WT control. 36 According to the literature, the most dominant phyla we can find in the GI are Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria and Fusobacteria. 37 Generally, the F/B ratio is considered highly relevant to measure the state of the gut microbiota, where higher abundance in Bacteroidetes correlates with healthier gut composition. 38 In this study, we found that WTCPM exposure induced higher abundance in Bacteroidetes in EOAD mice compared to EOAD and WT vehicle mice; however, we did not see any changes for the F/B ratio. Actinobacteria is another important beneficial phylum crucial for gut homeostasis, 39 which seemed to be reduced upon WTCPM in both WT and EOAD mice. Classes pertaining to this phylum include Bifidobacterium, known to produce short-chain fatty acid (SCFA), crucial metabolites that play a key role in preserving the integrity of the intestinal barrier and promoting immune tolerance by reducing inflammation in the gut.40,41, 40,41 Consistent with the previous study, we found that WTCPM exposure induced a decreased in some bacteria species such as Bifidobacterium as well as Faecalibacterium, both associated to beneficial taxa, therefore highlighting the detrimental effect of WTCPM exposure on the disturbance of eubiosis and potentially contributing to AD-like pathology.

It has been confirmed that exposure to PM (ultrafine: diameter size < 0.15μm, fine: diameter size < 2.5μm, and coarse: diameter size 2.5–10μm) induces dysregulation energy metabolism, mitochondrial activity, and oxidative stress in the brain of 2-month-old Fisher rats. 42 In our studies we found higher energy demand in EOAD exposed to WTCPM (diameter size 10–53μm), as well as increased biosynthesis and metabolism of FA and lipids. This is in accordance with the study from Sun et al., 43 who showed that exposure to air pollution can enhance oxidative stress and lipotoxicity. More importantly, the high energy demand may render to changes in glucose supply and mitochondrial dysfunction, which are known hallmarks of neurodegenerative disorders including AD. 44

Our findings strongly suggest that WTCPM significantly impacts both the gut microbiome and energy metabolism in exposed individuals. Considering the crucial role of energy metabolism in aging and the development of Alzheimer’s disease (AD), this evidence supports the hypothesis that gut dysbiosis could lead to disruptions in energy regulation, potentially influencing the AD phenotype among those exposed to WTCPM (Fig. 8).

Fig. 8

WTCPM significantly affects the brain gene expression, altering mechanisms such as synaptogenesis signaling, inflammatory mechanisms, CREB signaling, SAPK/JNK signaling or mitochondrial function. Additionally, gut microbiome is also disrupted, leading to gut dysbiosis in exposed individuals who showed evidence of changes in energy metabolism. Considering the crucial role of energy metabolism in aging and the development of Alzheimer’s disease (AD), this evidence supports the hypothesis that gut dysbiosis could lead to disruptions in energy regulation, potentially influencing the AD phenotype among those exposed to WTCPM.

Nevertheless, this study aptly recognizes several limitations, particularly the exclusive use of male animals, which underscores a bias in the study regarding sex representation. There is a clear necessity to include both sexes in research to extrapolate findings more accurately from animal models to human populations. By doing so, we can effectively unravel the enduring impacts of WTCPM exposure on neurological health in FR. Additionally, the intricate bidirectional relationship between WTCPM exposure and the gut microbiome warrants extensive exploration, using advanced techniques such as metatranscriptomics, metaproteomics, and metabolomics. These approaches are crucial for gaining deeper insights into the effects of WTCPM exposure on the functional profile of individual bacterial species, as well as the production of important metabolites including SCFA and their role on the maintenance of intestinal barrierintegrity.

Conducting a longitudinal study focused on energy metabolism within the gut is imperative to ascertain whether alterations in energy balance are transient or sustained over time. Additionally, delving into brain glucose metabolism and assessing the mitochondrial state within the brain would offer deeper insights into the overall energy status of individuals exposed to WTCPM and correlate it with AD-like symptomatology.

In conclusion, this study provides a nuanced exploration of the intricate interplay between WTCPM exposure and the gut-brain axis within the realm of AD-like neurodegenerative diseases. Understanding these interconnected dynamics is crucial to fully understand the intricate health consequences of WTCPM exposure. Such insights are critical for developing preventive measures and therapeutic interventions to mitigate the burden of AD-type pathology in populations exposed to WTCPM.

AUTHOR CONTRIBUTIONS

Ruth Iban-Arias (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Validation; Visualization; Writing – original draft; Writing – review & editing); Shu-Han Wang (Formal analysis; Software; Writing – review & editing); Ariana Soares Dias Portela (Investigation; Methodology; Writing – review & editing); Eun-Jeong Yang (Conceptualization; Investigation; Methodology; Writing – review & editing); Elizabeth Griggs (Conceptualization; Investigation; Methodology; Writing – review & editing); Sibilla Masieri (Methodology; Writing – review & editing); Wen Hu (Investigation; Methodology; Writing – review & editing); Lung-Chi Chen (Conceptualization; Investigation; Methodology; Writing – review & editing); Giulio Maria Pasinetti (Conceptualization; Funding acquisition; Resources; Supervision; Writing – review & editing).

Footnotes

ACKNOWLEDGMENTS

The authors would also like to acknowledge the following persons for their courageous task of collecting WTC dust on Sep 12 and 13 near Ground Zero. The field team was led by Dr. Mitchell Cohen and consisted of M Blaustein, SI Hsu, J Duffey, J Clemente, K Schermerhorn, G Chee, C Prophete, and J Gorczynski. The authors would also like to thank Vassili Tchaikovsky for his restless technical assistance, and Susan Gursahai for her work with administrative duties.

FUNDING

The research reported in this publication was supported by the National Center For Complementary and Integrative Health (NCCIH) of the National Institutes of Health (NIH) under Award number U19AT010835. This research was also made possible by Grant number BX0005054 from the U.S. Department of Veterans Affairs (VA) awarded to G.M.P. The contents are solely the responsibility of the authors and do not necessarily represent the official views of the NCCIH, NIA, ODS, and NIH.

CONFLICT OF INTEREST

Giulio Pasinetti is an Editorial Board Member of this journal but was not involved in the peer-review process of this article nor had access to any information regarding its peer-review.

All other authors have no conflict of interest to report.

DATA AVAILABILITY

The data supporting the findings of this study are available within the article and its supplementary material. Any remaining data that support the results of the study are available on request from the corresponding author.

The supplementary material is available in the electronic version of this article: .

References

McGee

, Chen

, Cohen

, et al. Chemical analysis of World Trade Center fine particulate matter for use in toxicologic assessment. Environ Health Perspect 2003; 111; 972–980.

Vaughan

, Garrett

, Prophete

, et al. novel system to generate WTC dust particles for inhalation exposures. J Exp Sci Environ Epidemiol 2014; 24; 105–112.

Cohen

, Vaughan

, Garrett

, et al. Impact of acute exposure to WTC dust on ciliated and goblet cells in lungs of rats. Inhal Toxicol 2015; 27; 354–361.

Sloan

, Shapiro

, Sabra

, et al. Cardiovascular disease in the World Trade Center Health Program General Responder Cohort. Am J Ind Med 2021; 64; 97–107.

Cohen

, Zeig-Owens

, Joe

, et al. Long-term cardiovascular disease risk among firefighters after the World Trade Center disaster. JAMA Netw Open 2019; 2; e199775.

Antao

, Pallos

, Graham

, et al. 9/11 residential exposures: the impact of World Trade Center dust on respiratory outcomes of lower Manhattan residents. Int J Environ Res Public Health 2019; 16; 798.

Liu

, Putman

, Singh

, et al. Abnormalities on chest computed tomography and lung function following an intense dust exposure: a 17-year longitudinal study. Int J Environ Res Public Health 2019; 16; 1655.

De la Hoz

, Shapiro

, Nolan

, et al. Association of low FVC spirometric pattern with WTC occupational exposures. Respir Med 2020; 170; 106058.

Durmus

, Pehlivan

, Zhang

, et al. Lung cancer characteristics in the World Trade Center environmental health center. Int J Environ Res Public Health 2021; 18; 2689.

10.

Nabi

and Tabassum

. Role of environmental toxicants on neurodegenerative disorders. Front Toxicol 2022; 4; 837579.

11.

Clouston

SAP

, Hall

, Kritikos

, et al. Cognitive impairment and World Trade Centre-related exposures. Nat Rev Neurol 2022; 18; 103–116.

12.

Lioy

, Weisel

, Millette

, et al. Characterization of the dust/smoke aerosol that settled east of the World Trade Center (WTC) in lower Manhattan after the collapse of the WTC 11 September 2001. Environ Health Perspect 2002; 110; 703–714.

13.

Lioy

, Freeman

and Millette

. Dust: a metric for use in residential and building exposure assessment and source characterization. Environ Health Perspect 2002; 110; 969–983.

14.

Gavett

, Haykal-Coates

, Highfill

, et al. World Trade Center fine particulate matter causes respiratory tract hyper-responsiveness in mice. Environ Health Perspect 2003; 111; 981–991.

15.

Offenberg

, Eisenreich

, Chen

, et al. Persistent organic pollutants in the dusts that settled across Lower Manhattan after 11 September 2001. Environ Sci Technol 2003; 37; 502–508.

16.

Clouston

SAP

, Diminich

, Kotov

, et al. Incidence of mild cognitive impairment in World Trade Center responders: Long-term consequences of re-experiencing the events on 9/11/2001. Alzheimers Dement (Amst) 2019; 11; 628–636.

17.

Prioux

, Marillier

, Vuillermoz

, et al. PTSD and partial PTSD among first responders one and five years after the Paris terror attacks in November 2015. Int J Environ Res Public Health 2023; 20; 4160.

18.

Pellecchia

, Kritikos

, Guralnik

, et al. Physical functional impairment and the risk of incident mild cognitive impairment in an observational study of World Trade Center responders. Neurol Clin Pract 2022; 12; e162–e171.

19.

Yaffe

, Vittinghoff

, Lindquist

, et al. Posttraumatic stress disorder and risk of dementia among US veterans. Arch Gen Psychiatry 2010; 67; 608–613.

20.

Kritikos

, Clouston

SAP

, Huang

, et al. Cortical complexity in world trade center responders with chronic posttraumatic stress disorder. Transl Psychiatry 2021; 11; 597.

21.

Iban-Arias

, Trageser

, Yang

, et al. Exposure to World Trade Center dust exacerbates cognitive impairment and evokes a central and peripheral pro-inflammatory transcriptional profile in an animal model of Alzheimer’s disease. J Alzheimers Dis 2023; 91; 779–794.

22.

Sweeney

, Sagare

and Zlokovic

. Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol 2018; 14; 133–150.

23.

Gong

and Jia

. Contribution of blood-brain barrier-related blood-borne factors for Alzheimer’s disease vs. vascular dementia diagnosis: A pilot study. Front Neurosci 2022; 16; 949129.

24.

Lee

, Weerasinghe-Mudiyanselage

PDE

, Kim

, et al. Particulate matter exposure and neurodegenerative diseases: A comprehensive update on toxicity and mechanisms. Ecotoxicol Environ Saf 2023; 266; 115565.

25.

, Chi

, Bodnar

, et al. Gut microbiome toxicity: connecting the environment and gut microbiome-associated diseases. Toxics 2020; 8; 19.

26.

Rivas-Arancibia

, Miranda-Martínez

, Rodríguez-Martínez

, et al. Ozone environmental pollution: relationship between the intestine and neurodegenerative diseases. Antioxidants (Basel) 2023; 12; 1323.

27.

Hernández

, Harrington

, Ma

, et al. World Trade Center dust induces airway inflammation while promoting aortic endothelial dysfunction. Toxicol Appl Pharmacol 2020; 400; 115041.

28.

Hernández

, Vaughan

, Gordon

, et al. World Trade Center dust induces nasal and neurological tissue injury while propagating reduced olfaction capabilities and increased anxiety behaviors. Inhal Toxicol1 2022; 34; 75–188.

29.

Woting

and Blaut

. Small intestinal permeability and gut-transit time determined with low and high molecular weight fluorescein isothiocyanate-dextrans in C3H mice. Nutrients 2018; 10; 685.

30.

Clouston

SAP

, Pietrzak

, Kotov

, et al. Traumatic exposures, posttraumatic stress disorder, and cognitive functioning in World Trade Center responders. Alzheimers Dement (NY) 2017; 3; 593–602.

31.

Clouston

SAP

, Deri

, Diminich

, et al. Posttraumatic stress disorder and total amyloid burden and amyloid-β 42/40 ratios in plasma: Results from a pilot study of World Trade Center responders. Alzheimers Dement (Amst) 2019; 11; 216–220.

32.

Pellegrini

, Fornai

, D’Antongiovanni

, et al. The intestinal barrier in disorders of the central nervous system. Lancet Gastroenterol Hepatol 2023; 8; 66–80.

33.

O’Brien

and Wong

. Amyloid precursor protein processing and Alzheimer’s disease. Annu Rev Neurosci 2011; 34; 185–204.

34.

Corey-Bloom

. The ABC of Alzheimer’s disease: cognitive changes and their management in Alzheimer’s disease and related dementias. Int Psychogeriatr 2002; 14(Suppl 1), 51–75.

35.

Kish

, Hotte

, Kaplan

, et al. Environmental particulate matter induces murine intestinal inflammatory responses and alters the gut microbiome. PLoS One 2013; 8; e62220.

36.

, Liu

, Li

, et al. Intestinal changes in permeability, tight junction and mucin synthesis in a mouse model of Alzheimer’s disease. Int J Mol Med 2023; 52; 113.

37.

Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 2012; 486; 207–214.

38.

Mariat

, Firmesse

, Levenez

, et al. The Firmicutes/Bacteroidetes ratio of the human microbiota changes with age. BMC Microbiol 2009; 9; 123.

39.

Binda

, Lopetuso

, Rizzatti

, et al. Actinobacteria: A relevant minority for the maintenance of gut homeostasis. Dig Liver Dis 2018; 50; 421–428.

40.

Geirnaert

, Calatayud

, Grootaert

, et al. Butyrate-producing bacteria supplemented in vitro to Crohn’s disease patient microbiota increased butyrate production and enhanced intestinal epithelial barrier integrity. Sci Rep 2017; 7; 11450.

41.

Ewaschuk

, Diaz

, Meddings

, et al. Secreted bioactive factors from Bifidobacterium infantis enhance epithelial cell barrier function. Am J Physiol Gastrointest Liver Physiol 2014; 295; G1025–G1034.

42.

Araújo

, Jorge

, Santos

, et al. Proteomic changes driven by urban pollution suggest particulate matter as a deregulator of energy metabolism, mitochondrial activity, and oxidative pathways in the rat brain. Sci Total Environ 2019; 687; 839–848.

43.

Sun

, Zhang

, Chen

, et al. Central IKK2 inhibition ameliorates air pollution-mediated hepatic glucose and lipid metabolism dysfunction in mice with type II diabetes. Toxicol Sci 2018; 164; 240–249.

44.

Yin

, Sancheti

, Patil

, et al. Energy metabolism and inflammation in brain aging and Alzheimer’s disease. Free Radic Biol Med 2016; 100; 108–122.

Exposure to the World Trade Center Particulate Matter Alters the Gut-Brain Axis in Early Onset Alzheimer’s Disease Mice

Abstract

Background:

Objective:

Methods:

Results:

Conclusions:

Keywords

INTRODUCTION

MATERIAL AND METHODS

Rodent models

World Center particulate matter (WTCPM) preparation and administration

WTCPM samples from ground zero

WTCPM samples preparation and intranasal instillation

Cognitive assessment

Spatial working memory

Learning acquisition short-term memory and consolidation and recall long-term memory

FITC – Dextran gut permeability assay

Brain collection

Measurement of Aβ content

Transcriptomic studies

RNA extraction

Multiplex brain gene expression by Nanostring

Gene expression validation by quantitative RT qPCR

Phylogenetic 16S rDNA microbiota studies

Stool collection and DNA extraction

PCR amplification and 16S rDNA sequencing

16S data analysis

Statistical analysis

RESULTS

WTCPM exposure compromises memory performance in EOAD mice

Aβ1–40 and Aβ1–42 levels in the mouse hippocampus following WTCPM exposure in old EOAD mice

WTCPM exposure alters the brain transcriptional phenotype

Gut permeability is disrupted after WTCPM exposure in EOAD mice

Gut microbiome composition is altered after WTCPM exposure

Exposure to WTCPM is associated with altered gut metabolic profile

DISCUSSION

AUTHOR CONTRIBUTIONS

Footnotes

ACKNOWLEDGMENTS

FUNDING

CONFLICT OF INTEREST

DATA AVAILABILITY

References

Aβ_1–40 and Aβ_1–42 levels in the mouse hippocampus following WTCPM exposure in old EOAD mice