Dataset Information

Accumulation of Ambient Black Carbon Particles Within Key Memory-Related Brain Regions.

ABSTRACT:

Importance

Ambient air pollution is a worldwide problem, not only related to respiratory and cardiovascular diseases but also to neurodegenerative disorders. Different pathways on how air pollutants could affect the brain are already known, but direct evidence of the presence of ambient particles (or nanoparticles) in the human adult brain is limited.

Objective

To examine whether ambient black carbon particles can translocate to the brain and observe their biodistribution within the different brain regions.

Design, setting, and participants

In this case series a label-free and biocompatible detection technique of nonincandescence-related white light generation was used to screen different regions of biobanked brains of 4 individuals from Belgium with neuropathologically confirmed Alzheimer disease for the presence of black carbon particles. The selected biological specimens were acquired and subsequently stored in a biorepository between April 2013 and April 2017. Black carbon measurements and data analysis were conducted between June 2020 and December 2022.

Main outcomes and measures

The black carbon load was measured in various human brain regions. A Kruskal-Wallis test was used to compare black carbon loads across these regions, followed by Dunn multiple comparison tests.

Results

Black carbon particles were directly visualized in the human brain of 4 individuals (3 women [75%]; mean [SD] age, 86 [13] years). Screening of the postmortem brain regions showed a significantly higher median (IQR) number of black carbon particles present in the thalamus (433.6 [289.5-540.2] particles per mm3), the prefrontal cortex including the olfactory bulb (420.8 [306.6-486.8] particles per mm3), and the hippocampus (364.7 [342.0-448.7] particles per mm3) compared with the cingulate cortex (192.3 [164.2-277.5] particles per mm3), amygdala (217.5 [147.3-244.5] particles per mm3), and the superior temporal gyrus (204.9 [167.9-236.8] particles per mm3).

Conclusions and relevance

This case series provides evidence that ambient air pollution particles are able to translocate to the human brain and accumulate in multiple brain regions involved in cognitive functioning. This phenomenon may contribute to the onset and development of neurodegenerative disorders.

SUBMITTER: Vanbrabant K

PROVIDER: S-EPMC11004827 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accumulation of Ambient Black Carbon Particles Within Key Memory-Related Brain Regions.

Vanbrabant Kenneth K Van Dam Debby D Bongaerts Eva E Vermeiren Yannick Y Bové Hannelore H Hellings Niels N Ameloot Marcel M Plusquin Michelle M De Deyn Peter Paul PP Nawrot Tim S TS

JAMA network open 20240401 4

<h4>Importance</h4>Ambient air pollution is a worldwide problem, not only related to respiratory and cardiovascular diseases but also to neurodegenerative disorders. Different pathways on how air pollutants could affect the brain are already known, but direct evidence of the presence of ambient particles (or nanoparticles) in the human adult brain is limited.<h4>Objective</h4>To examine whether ambient black carbon particles can translocate to the brain and observe their biodistribution within t ...[more]

PMID: 38592718

Similar Datasets

Project description:BackgroundUnderstanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophage carbon load (MaCL) is a novel cytology method that quantifies lung deposition dose of black carbon, however it has limited feasibility in large-scale epidemiological study due to the labor-intensive manual counting.ObjectiveTo assess the association between MaCL and episodic elevation of combustion particles; to develop artificial intelligence based counting algorithm for MaCL assay.MethodsSputum slides were collected during episodic elevation of ambient PM2.5 (n = 49, daily PM2.5 > 10 µg/m3 for over 2 weeks due to wildfire smoke intrusion in summer and local wood burning in winter) and low PM2.5 period (n = 39, 30-day average PM2.5 < 4 µg/m3) from the Lovelace Smokers cohort.ResultsOver 98% individual carbon particles in macrophages had diameter <1 µm. MaCL levels scored manually were highly responsive to episodic elevation of ambient PM2.5 and also correlated with lung injury biomarker, plasma CC16. The association with CC16 became more robust when the assessment focused on macrophages with higher carbon load. A Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP) was developed based on the Mask Region-based Convolutional Neural Network. MacLEAP algorithm yielded excellent correlations with manual counting for number and area of the particles. The algorithm produced associations with ambient PM2.5 and plasma CC16 that were nearly identical in magnitude to those obtained through manual counting.Impact statementUnderstanding lung black carbon deposition is crucial for comprehending health effects of combustion particles. We developed "Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP)", the first artificial intelligence algorithm for quantifying airway macrophage black carbon. Our study bolstered the algorithm with more training images and its first use in air pollution epidemiology. We revealed macrophage carbon load as a sensitive biomarker for heightened ambient combustion particles due to wildfires and residential wood burning.

Project description:BackgroundEvidence is accumulating that elevated levels of particulate air pollution, including black carbon, have been linked to gastrointestinal disorders and a lower intestinal bacterial richness and diversity. One of the hypothesized underlying mechanisms is the absorption of air pollution-related particles from the gastrointestinal tract.MethodsWe visualized and quantified black carbon particles via white light generation under femtosecond-pulsed laser illumination in ileum and colon biopsies of five human patients. The biodistribution was assessed in three different layers (i.e., mucosa, submucosa, and muscularis propria).FindingsBlack carbon particles could be identified in all three tissue layers of the ileum and colon biopsies of five participants (two men and three women; mean ± standard deviation age, 76.40 ± 7.37 years), and their carbonaceous nature was confirmed via emission fingerprinting. The median (±SD) black carbon load was borderline statistically significantly higher in the ileum compared to the colon (1.21 × 105 ± 1.68 × 104 particles/mm3 versus 9.34 × 104 ± 1.33 × 104 particles/mm3; p = 0.07) and was driven by a difference in black carbon load in the submucosa layer (p = 0.01). Regarding the three tissue layers, loads were higher in the submucosa, compared with the mucosa (ileum: +76%, p < 0.0001; colon: +70%, p = 0.0001) and muscularis propria (ileum: +88%, p < 0.0001; colon: +88%, p < 0.0001). In ileum, loads were borderline higher in the mucosa versus muscularis propria (p = 0.09).InterpretationThis explorative study provides real-life evidence that black carbon particles can reach the intestinal tissue and accumulate in different intestinal tissue layers. These findings support further research into how particulate air pollution directly affects gastrointestinal health.FundingThessa Van Pee holds a doctoral fellowship from the Research Foundation Flanders (FWO), grant number: 11C7421N. Tim Nawrot is a Methusalem grant holder.

Project description:Environmental stimulation during brain development is an important risk factor for the development of neurodegenerative disease. Clinical evidence indicates that prenatal exposure to particulate air pollutants leads to diffuse damage to the neurovascular unit in the developing brain and accelerates neurodegeneration. Maternal exposure to carbon black nanoparticles (CB-NPs), used as a model for particulate air pollution, induces long-lasting diffuse perivascular abnormalities. We aimed to comprehensively characterize the perivascular abnormalities related to maternal NPs exposure using Fourier transform infrared microspectroscopy (in situ FT-IR) and classical staining analysis. Pregnant ICR mice were intranasally treated with a CB-NPs suspension (95 μg/kg at a time) on gestational days 5 and 9. Brains were collected 6 weeks after birth and sliced to prepare 10-μm-thick serial sections. Reflective spectra of in situ FT-IR were acquired using lattice measurements (x-axis: 7, y-axis: 7, 30-μm apertures) around a centered blood vessel. We also performed mapping analysis of protein secondary structures. Serial sections were stained with using periodic acid-Schiff or immunofluorescence to examine the phenotypes of the perivascular areas. Peaks of amide I bands in spectra from perivascular areas were shifted by maternal NPs exposure. However, there were two types of peak-shift in one mouse in the exposure group. Some vessels had a large peak-shift and others had a small peak-shift. In situ FT-IR combined with traditional staining revealed that the large peak-shift was induced around blood vessel adjacent to astrocytes with glial fibrillary acidic protein and aquaporin-4 over-expression and perivascular macrophages (PVMs) with enlarged lysosome granules. Furthermore, protein secondary structural analysis indicated that maternal NPs exposure led to increases in β-sheet content and decreases in α-helix content in areas that are mostly close to the centered blood vessel displaying histopathological changes. These results suggest that β-sheet-rich waste proteins, which are denatured by maternal NPs exposure, likely accumulate in the perivascular space as they are processed by the clearance systems in the brain. This may in turn lead the denaturation of PVMs and astrocyte activation. The risk of neurodegeneration may be enhanced by exposure to particulate air pollutants during brain development following the perivascular accumulation of β-sheet-rich waste proteins.

Dataset Information

Accumulation of Ambient Black Carbon Particles Within Key Memory-Related Brain Regions.

Importance

Objective

Design, setting, and participants

Main outcomes and measures

Results

Conclusions and relevance

Publications

Accumulation of Ambient Black Carbon Particles Within Key Memory-Related Brain Regions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets