Bioaccumulation of microplastics in decedent human brains

Alexander J. Nihart, Marcus A. Garcia, Eliane El Hayek, Rui Liu, Marian Olewine, Josiah D. Kingston, Eliseo F. Castillo, Rama R. Gullapalli, Tamara Howard, Barry Bleske, Justin Scott, Jorge Gonzalez-Estrella, Jessica M. Gross, Michael Spildes, Natalie L. Adolphi, Daniel F. Gallego, Heather S. Jarrell, Gabrielle Dvorscak, Maria E. Zuluaga-Ruiz, Andrew B. West, Matthew J. Campen
nature medicine
University of New Mexico Health Sciences

Table of Contents

Overall Summary

Study Background and Main Findings

This study investigated the presence and concentration of micro- and nanoplastics (MNPs) in human liver, kidney, and brain tissues obtained from decedents. The researchers found significantly higher MNP concentrations in brain tissue compared to liver and kidney (P < 0.0001, two-way ANOVA). They also observed a significant increase in MNP concentrations in both liver and brain tissues between samples collected in 2016 and 2024 (P-values from Mann-Whitney tests). Furthermore, brain samples from individuals diagnosed with dementia exhibited significantly higher MNP concentrations compared to those without dementia. The predominant polymer type identified in brain tissue was polyethylene (PE).

Research Impact and Future Directions

The study provides compelling evidence for the presence of micro- and nanoplastics (MNPs) in human tissues, including the brain, with significantly higher concentrations found in brain tissue compared to liver and kidney. A notable temporal increase in MNP concentrations was observed between 2016 and 2024, and a strong association was found between MNP accumulation and dementia diagnosis. However, it is crucial to emphasize that the study establishes correlation, not causation, between MNP presence and dementia. The observed association does not prove that MNPs cause or contribute to dementia; other factors related to dementia could influence MNP accumulation, or a common underlying factor could influence both.

The study's practical utility lies in its novel demonstration of MNP presence in human brain tissue and the quantification of MNP concentrations in different organs. This provides a crucial foundation for future research investigating the potential health consequences of MNP exposure, particularly concerning neurological effects. The findings highlight the growing concern of environmental MNP pollution and its potential impact on human health, placing this work in the context of a rapidly evolving field of research.

While the study presents significant findings, uncertainties remain. The mechanisms of MNP uptake, distribution, and clearance in humans are still poorly understood. The study acknowledges the limitations of using decedent tissues and the need for standardized analytical methods. The authors appropriately recommend further research to investigate these mechanisms, explore the potential link between MNP exposure and neurodegenerative diseases, and develop more refined analytical techniques. The guidance provided is cautious and emphasizes the need for more research before drawing definitive conclusions about the health risks of MNPs.

Critical unanswered questions include the specific pathways by which MNPs cross the blood-brain barrier, the long-term effects of chronic MNP exposure on brain health, and whether MNPs play a causal role in the development of dementia or other neurological disorders. While the methodological limitations, such as the use of decedent tissues and the lack of detailed contamination control protocols in the Methods section, do raise some concerns, the use of multiple analytical techniques and the replication of key results across different tissue banks and analytical sites provide some reassurance. However, the lack of detailed contamination control protocols could potentially affect the absolute quantification of MNPs, although the relative comparisons between groups are likely still valid. Further research with more rigorous contamination control is needed to confirm the absolute MNP concentrations.

Critical Analysis and Recommendations

Higher MNP Concentrations in Brain (written-content)
The study found significantly higher MNP concentrations in brain tissue compared to liver and kidney (P < 0.0001). This highlights the potential vulnerability of the brain to MNP accumulation, raising concerns about neurological impacts.
Section: Results
Temporal Increase in MNP Concentrations (written-content)
MNP concentrations in liver and brain tissues increased significantly between 2016 and 2024. This suggests increasing human exposure to MNPs, paralleling rising environmental concentrations, and necessitating further investigation into long-term health consequences.
Section: Results
Elevated MNP Levels in Dementia Cases (written-content)
Brain samples from individuals with dementia had significantly higher MNP concentrations. While this association is intriguing, it does *not* prove causation and requires further investigation.
Section: Results
Robust Analytical Method (written-content)
The study utilized Py-GC/MS, a robust method validated in other studies, for MNP quantification. This enhances the credibility of the findings, especially for smaller nanoplastics often missed by traditional methods.
Section: Methods
Effective Data Visualization (graphical-figure)
Figure 1 clearly visualizes the key findings of MNP concentrations across tissues and time points. This makes the results more accessible and understandable, supporting the study's conclusions.
Section: Results
Lack of Detailed Contamination Control (written-content)
The Methods section lacks crucial details about contamination control procedures during tissue collection and processing. This omission raises concerns about potential external MNP contamination influencing the results, affecting the accuracy of absolute MNP quantification.
Section: Methods
Missing Absolute MNP Concentrations (written-content)
The Results section does not report the absolute MNP concentrations found in each tissue type. This omission makes it difficult to grasp the overall magnitude of MNP presence and compare findings to other studies.
Section: Results
Limited Literature Comparison (written-content)
The Discussion fails to adequately compare the current findings with existing literature on MNP exposure and health effects. A more thorough comparison would strengthen the study's conclusions and highlight its contribution to the field.
Section: Discussion

Section Analysis

Abstract

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Introduction

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Results

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Non-Text Elements

Fig. 1 | Overview of total MNP concentrations from all decedent samples from...
Full Caption

Fig. 1 | Overview of total MNP concentrations from all decedent samples from liver, kidney and brain. a, Microplastic concentrations in liver, kidney and brain decedent human samples (n = 20–28 separate participants for each timepoint; Supplementary Table 1) from the UNM OMI. Data are shown on a log10 scale, with the bar representing the group median value and 95% confidence interval. Orange-colored symbols in the 2016 brain samples were analyzed independently at Oklahoma State University. P values from Mann-Whitney tests (two-sided) indicate significant differences in samples from the same organ between 2016 and 2024 (with more comprehensive statistical treatments in Supplementary Methods-Statistical analysis). Brain MNP concentrations were significantly higher than liver and kidney, analyzed by two-way ANOVA (P < 0.0001). b, Overall distribution of 12 different polymers suggests a greater accumulation of PE in the brain relative to liver or kidney (average shown per group; see Extended Data Fig. 1 for individual data). c, PE (which was in the highest abundance and consistently had the highest confidence spectra) concentrations in all organs followed similar trends compared to total plastics (also represented as group median value and

Figure/Table Image (Page 2)
Fig. 1 | Overview of total MNP concentrations from all decedent samples from liver, kidney and brain. a, Microplastic concentrations in liver, kidney and brain decedent human samples (n = 20–28 separate participants for each timepoint; Supplementary Table 1) from the UNM OMI. Data are shown on a log10 scale, with the bar representing the group median value and 95% confidence interval. Orange-colored symbols in the 2016 brain samples were analyzed independently at Oklahoma State University. P values from Mann-Whitney tests (two-sided) indicate significant differences in samples from the same organ between 2016 and 2024 (with more comprehensive statistical treatments in Supplementary Methods-Statistical analysis). Brain MNP concentrations were significantly higher than liver and kidney, analyzed by two-way ANOVA (P < 0.0001). b, Overall distribution of 12 different polymers suggests a greater accumulation of PE in the brain relative to liver or kidney (average shown per group; see Extended Data Fig. 1 for individual data). c, PE (which was in the highest abundance and consistently had the highest confidence spectra) concentrations in all organs followed similar trends compared to total plastics (also represented as group median value and
First Reference in Text
Py-GC/MS measurements of MNP concentrations in decedent liver and kidney specimens were similar, with the median value of total plastics at 433 and 404 µg g⁻¹, respectively, from 2024 samples (Fig. 1a and Supplementary Table 1).
Description
  • Microplastic concentrations and statistical analysis: Figure 1 presents an overview of microplastic and nanoplastic (MNP) concentrations in human tissues. Panel a shows the concentrations of microplastics in liver, kidney, and brain samples obtained from deceased individuals. These samples were collected at two different time points: 2016 and 2024. The number of participants for each time point ranges from 20 to 28. These samples were part of a study conducted at the University of New Mexico's Office of the Medical Investigator (UNM OMI). The data is displayed on a log10 scale, which means that each increment on the y-axis represents a tenfold increase in concentration. The bar in each group represents the median value, which is the midpoint of the data when arranged in order, and the error bars indicate a 95% confidence interval, providing a range within which the true population median is likely to fall. The data for the 2016 brain samples, shown in orange, were analyzed separately at Oklahoma State University. The statistical significance of differences between samples from the same organ collected in 2016 versus 2024 was assessed using a Mann-Whitney test, a statistical test used to compare two independent groups when the data is not normally distributed. The p-value indicates the probability of observing the results if there is no actual difference between the groups; a smaller p-value suggests a stronger evidence against the null hypothesis (no difference). A two-way ANOVA (analysis of variance) was used to analyze whether brain MNP concentrations were significantly different from liver and kidney concentrations. ANOVA is a statistical test that can detect differences between the means of two or more groups. The caption reports that the p-value for this comparison was less than 0.0001, indicating a very statistically significant difference.
  • Polymer distribution: Panel b shows the overall distribution of 12 different polymers (types of plastics) found in the samples. This distribution is presented as the average percentage of each polymer's mass within each organ (liver, kidney, and brain). The figure suggests that polyethylene (PE) accumulates more in the brain compared to the liver or kidney. The individual data for this panel can be found in Extended Data Figure 1.
  • Polyethylene concentrations: Panel c displays the concentrations of polyethylene (PE) in all organs, following similar trends to the total plastic concentrations. Polyethylene (PE) had the highest abundance and the most reliable spectral data. The concentrations are shown as group median values, similar to panel a. The p-values are calculated using the Mann-Whitney test.
Scientific Validity
  • Justification of statistical tests: The use of Mann-Whitney tests for comparing MNP concentrations between 2016 and 2024 is appropriate given that MNP concentration data may not be normally distributed. However, the caption should explicitly state whether data were tested for normality and justify the choice of non-parametric tests if normality assumptions were violated.
  • Consideration of confounding factors: The ANOVA results indicating significantly higher MNP concentrations in the brain compared to the liver and kidney are compelling. However, it's important to consider potential confounding factors, such as differences in tissue processing or analytical sensitivity across different organs. These potential confounders should be addressed in the discussion.
  • Definition of 'confidence spectra': The statement that PE had the highest abundance and consistently had the highest confidence spectra is important for justifying the focus on PE in panel c. However, the criteria for determining 'confidence spectra' should be clearly defined in the methods or supplementary information.
Communication
  • Caption length and density: The caption is comprehensive, providing a good overview of what each panel of Figure 1 represents. However, it's quite dense, and breaking it into shorter sentences might improve readability.
  • Justification of statistical tests: While the caption mentions the use of statistical tests, it might be beneficial to briefly state the rationale for choosing those specific tests (Mann-Whitney and two-way ANOVA) in the context of the data's characteristics.
  • Clarity of references to other figures: Referencing Extended Data Fig. 1 in panel (b) is appropriate, but consider whether a very brief description of what this figure shows could be incorporated into the caption for added clarity.
Fig. 2 | Visualization of putative plastics in the brain. a, b, Polarization...
Full Caption

Fig. 2 | Visualization of putative plastics in the brain. a, b, Polarization wave microscopy (a, black arrows indicate refractory inclusions; inset is a digital magnification for clarity) and SEM (b, visual fields are 15.4 and 20.1 µm wide) were used to scan sections of brain from decedent human samples. c, Large (>1 µm) inclusions were not observed; additional polarization wave examples are highlighted (white arrows highlight submicron refractory inclusions). Resolution limitations of these technologies drove the use of TEM to examine the extracts from the pellets used for Py-GC/MS. d, Example TEM images resolved

Figure/Table Image (Page 4)
Fig. 2 | Visualization of putative plastics in the brain. a, b, Polarization wave microscopy (a, black arrows indicate refractory inclusions; inset is a digital magnification for clarity) and SEM (b, visual fields are 15.4 and 20.1 µm wide) were used to scan sections of brain from decedent human samples. c, Large (>1 µm) inclusions were not observed; additional polarization wave examples are highlighted (white arrows highlight submicron refractory inclusions). Resolution limitations of these technologies drove the use of TEM to examine the extracts from the pellets used for Py-GC/MS. d, Example TEM images resolved
First Reference in Text
Using scanning electron microscopy (SEM) and polarization wave microscopy, refractory inclusions were identified in all organs histo-logically (Fig. 2, Extended Data Fig. 3 and Supplementary Figs. 7-16).
Description
  • Polarization wave microscopy and SEM: Figure 2 presents visual evidence of potential plastic particles within brain tissues. Panels a and b show images obtained using two different types of microscopy: polarization wave microscopy and scanning electron microscopy (SEM). Polarization wave microscopy uses polarized light to identify materials that are birefringent, meaning they split light into two rays with different refractive indices, often used to visualize crystalline materials. In the image (panel a), black arrows point to 'refractory inclusions,' which are materials that resist changes, indicating they might be foreign particles. The inset in panel a provides a magnified view for better clarity. Panel b shows a scanning electron microscopy (SEM) image, where electrons scan the surface of the sample to create a detailed image. The visual fields for the SEM images are 15.4 and 20.1 micrometers wide, which gives a sense of the scale being observed.
  • Resolution limitations and submicron inclusions: Panel c notes that large inclusions, specifically those larger than 1 micrometer (a unit of length equal to one-millionth of a meter), were not observed in the samples. The panel highlights additional examples of polarization wave microscopy images, with white arrows indicating submicron refractory inclusions, which are inclusions smaller than 1 micrometer. The text mentions that the resolution limitations of polarization wave microscopy and SEM led the researchers to use transmission electron microscopy (TEM).
  • Transmission electron microscopy (TEM): Panel d shows example images obtained using transmission electron microscopy (TEM). TEM involves passing a beam of electrons through a very thin sample to create an image, allowing for much higher resolution than light microscopy or SEM. This technique was used to examine extracts from the pellets that were also used for pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS), a method used to identify the chemical composition of the sample. The TEM images are meant to resolve the nature of the particles identified by the other methods.
Scientific Validity
  • Need for spectroscopic confirmation: The use of multiple microscopy techniques (polarization wave microscopy, SEM, and TEM) provides complementary evidence for the presence of putative plastics. However, it's crucial to acknowledge that morphological identification alone is insufficient for definitive identification of plastic particles. Spectroscopic confirmation (e.g., Raman spectroscopy, FTIR) is needed to confirm the chemical composition of the observed inclusions.
  • Quantification and detection limits: The caption mentions that 'large (>1 μm) inclusions were not observed,' which is an important negative finding. However, it would be helpful to quantify the number of samples examined by each technique and to provide an estimate of the detection limits for each method.
  • Representativeness of TEM results: The statement that 'resolution limitations of these technologies drove the use of TEM' is valid. However, it's important to acknowledge that TEM analysis is typically performed on a small subset of samples due to its time-consuming nature. Therefore, the TEM results may not be fully representative of the entire sample set.
Communication
  • Rationale for imaging techniques: The caption effectively describes the progression of imaging techniques used, from polarization wave microscopy and SEM to TEM. However, it would be helpful to explicitly state the rationale for using each technique and how they complement each other in addressing the research question.
  • Explanation of TEM's advantages: While the caption mentions the limitations of polarization wave microscopy and SEM in resolving submicron inclusions, it could be strengthened by briefly explaining why TEM is better suited for this purpose (e.g., higher resolution).
  • Description of refractory inclusions: The use of arrows to indicate refractory inclusions in the polarization wave microscopy images is clear. However, it might be helpful to provide a brief description of what these inclusions are and why they are considered 'putative plastics.'

Discussion

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Methods

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