Plastic pollution is usually discussed as an environmental problem....
- Microplastics are present in human organs: Researchers detected m...
> "The present data suggest a trend of increasing MNP concentration...
Nature Medicine | Volume 31 | April 2025 | 1114–1119
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nature medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Bioaccumulation of microplastics in
decedent human brains
Alexander J. Nihart
1,12
, Marcus A. Garcia
1,12
, Eliane El Hayek
1,12
, Rui Liu
1
,
Marian Olewine
1
, Josiah D. Kingston
1
, Eliseo F. Castillo
2
, Rama R. Gullapalli
3
,
Tamara Howard
4
, Barry Bleske
5
, Justin Scott
6
, Jorge Gonzalez-Estrella
6
,
Jessica M. Gross
7
, Michael Spilde
8
, Natalie L. Adolphi
9
, Daniel F. Gallego
9
,
Heather S. Jarrell
9
, Gabrielle Dvorscak
9
, Maria E. Zuluaga-Ruiz
10
,
Andrew B. West
11
& Matthew J. Campen
1
Rising global concentrations of environmental microplastics and
nanoplastics (MNPs) drive concerns for human exposure and health
outcomes. Complementary methods for the robust detection of tissue
MNPs, including pyrolysis g as c hr om at og raphy–mass spectrometry,
attenuated total reectance–Fourier transform infrared spectroscopy and
electron microscopy with energy-dispersive spectroscopy, conrm the
presence of MNPs in human kidney, liver and brain. MNPs in these organs
primarily consist of polyethylene, with lesser but signicant concentrations
of other polymers. Brain tissues harbor higher proportions of polyethylene
compared to the composition of the plastics in liver or kidney, and electron
microscopy veried the nature of the isolated brain MNPs, which present
largely as nanoscale shard-like fragments. Plastic concentrations in these
decedent tissues were not inuenced by age, sex, race/ethnicity or cause
of death; the time of death (2016 versus 2024) was a signicant factor,
with increasing MNP concentrations over time in both liver and brain
samples (P = 0.01). Finally, even greater accumulation of MNPs was observed
in a cohort of decedent brains with documented dementia diagnosis,
with notable deposition in cerebrovascular walls and immune cells.
These results highlight a critical need to better understand the routes
of exposure, uptake and clearance pathways and potential health
consequences of plastics in human tissues, particularly in the brain.
Environmental concentrations of anthropogenic microplastic and
nanoplastic (MNP), polymer-based particulates ranging from 500 µm
in diameter down to 1 nm, have increased exponentially over the past
half century
1,2
. The extent to which MNPs cause human harm or toxic-
ity is unclear, although recent studies associated MNP presence in
carotid atheromas with increased inflammation and risk of future
adverse cardiovascular events
3,4
. In controlled cell culture and animal
exposure studies, MNPs exacerbate disease or drive toxic outcomes,
but at concentrations with unclear relevance to human exposures and
body burdens
5,6
. The mantra of the field of toxicology—‘dose makes the
poison’ (Paracelsus)—renders such discoveries as easily anticipated;
what is not clearly understood is the tissue distribution and internal
dose of MNPs in humans, which confounds our ability to interpret the
controlled exposure study results.
So far, visual microscopic spectroscopy methods have identified
particulates in organs, such as the lungs, intestine
7
and placenta
8
.
These methods are often limited to larger (>5 µm) particulates; thus,
smaller nanoplastics are unintentionally excluded. As a new approach,
Received: 29 April 2024
Accepted: 9 December 2024
Published online: 3 February 2025
Check for updates
A full list of afiliations appears at the end of the paper. e-mail: mcampen@salud.unm.edu
Nature Medicine | Volume 31 | April 2025 | 1114–1119
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Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Results and discussion
We obtained de-identified, postmortem human liver (right central paren-
chyma), kidney (wedge piece containing cortex and medulla) and brain
(frontal cortex) samples, retrospectively from 2016 and 2024 autopsy
specimens (Supplementary Table 1), in cooperation with and approval
from the University of New Mexico (UNM) Office of the Medical Investi-
gator (OMI) in Albuquerque, New Mexico (NM), under the guidance of
a trained forensic pathologist (D.F.G.) who selected consistent regions
pyrolysis gas chromatography–mass spectrometry (Py-GC/MS) has
been applied to blood
9
, placentas
10
and recently major blood vessels
3,4
in a manner that appears more cumulative, quantitative and less biased
when coupled with orthogonal methods. Py-GC/MS data between labs
has been comparable, providing confidence in this method for human
tissue analysis
3,9,10
. Here we applied Py-GC/MS in concert with visualiza-
tion methods to assess the relative distribution of MNPs in major organ
systems from human decedent livers, kidneys and brains.
10,000
a b
c d
0.001
NS
0.0127
1,000
100
10
Microplastics concentration (µg g
–1
)Polyethylene concentration (µg g
–1
)
Brain microplastics (µg g
–1
)
Total mass (%)
10,000
0.0647
NS
0.0048
2000 2010
Collection year
2020
50,000
Dementia
cases
Normal brains
NC
MD
MA
NM
Liver 2016
Liver 2024
Kidney 2016
Kidney 2024
Brain 2016
Brain 2024
Liver 2016
Liver 2024
Kidney 2016
Kidney 2024
Brain 2016
Brain 2024
Liver 2016
Liver 2024
Kidney 2016
Kidney 2024
Brain 2016
Brain 2024
40,000
30,000
20,000
10,000
10,000
5,000
0
1,000
100
10
1
100
75
50
PU
PMMA
ABS
PS
PC
SBR
PET
N66
N6
PVC
PP
PE
25
0
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 log
10
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
95% confidence interval; two-sided Mann–Whitney test). d, Additional brain
samples from specimens collected from 1997 to 2013 were obtained from the
Duke Kathleen Price Bryan Brain Bank in North Carolina (n = 13, blue diamonds;
NC), the Harvard Brain Tissue Resource Center in Massachusetts (n = 9,
green diamonds; MA) and the National Institute of Child Health and Human
Development Brain and Tissue Bank at the University of Maryland (n = 5, orange
diamonds; MD) show lower concentrations of microplastics. Brain samples from
decedents with diagnosed dementia (n = 12, purple circles) from UNM exhibit
far greater MNP concentrations than brain tissues from participants without
dementia from New Mexico (red thin-outline diamonds; NM). Overall linear
regression trend was significantly nonzero (P < 0.0001) with an R
2
= 0.3982;
summary points for 2016 and 2024 normal UNM OMI brains reflect mean ± s.d.
N66, nylon 66; ABS, acrylonitrile butadiene styrene; PET, polyethylene
terephthalate; N6, nylon-6; PMMA, poly(methyl methacrylate);
PU, polyurethane; PC, polycarbonate; PS, polystyrene.
Nature Medicine | Volume 31 | April 2025 | 1114–1119
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Brief Communication https://doi.org/10.1038/s41591-024-03453-1
from all organs. 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). These were higher than
previously published data for human placentas (median = 63.4 µg g
−1
)
10
and testes (median = 299 µg g
−1
)
11
. Brain samples, all derived from the
frontal cortex, exhibited substantially higher concentrations of MNPs
than liver or kidney (two-way analysis of variance (ANOVA), P < 0.0001),
but comparable to recently published Py-GC/MS data from carotid
plaques
4
, with a median of 3345 µg g
−1
(25–75%: 1,267–5,213 µg g
−1
) in 2016
samples and 4917 µg g
−1
(25–75%: 4,026–5,608 µg g
−1
) in 2024 samples
(Fig. 1a and Supplementary Table 1).
Liver and brain samples from 2024 had significantly higher con-
centrations of MNPs than 2016 samples on both post hoc multiple
comparisons of the two-way ANOVA (Supplementary Tables 4–7 and
Supplementary Fig. 6), consistent with results from a multiple regres
-
sion analysis of brain concentrations considering the potential influ-
ence of other demographic variables (Supplementary Tables 8–10).
Five brain samples from 2016 (highlighted in orange in Fig. 1a) were
analyzed independently by colleagues at Oklahoma State University
using Py-GC/MS, and those values were consistent with our findings
(P = 0.49 for a Student’s t test comparing UNM and OSU data). The
proportion of polyethylene (PE) in the brain (75% on average) was
greater relative to other polymers and compared to PE in the liver and
kidney (P < 0.0001; Fig. 1b and Extended Data Fig. 1). PE, polypropylene
(PP), polyvinyl chloride (PVC) and styrene-butadiene rubber (SBR)
concentrations specifically increased from 2016 to 2024 in liver and
brain samples (Fig. 1c and Extended Data Fig. 2). PE predominance
was confirmed with attenuated total reflectance–Fourier transform
infrared spectroscopic analysis from five brain samples, although
other polymers were not as consistent in prevalence, possibly due to
differences in prevalence across size distributions and limited sampling
(Supplementary Tables 9–13 and Supplementary Figs. 17–25).
To expand these findings, we obtained brain tissue from earlier
time frames (1997–2013) with a mean age of death comparable to the
NM cohorts (52.8 ± 34.3 years) from locations in the eastern United
States, along with samples from a repository of dementia cases at
UNM. Py-GC/MS analysis revealed lower overall MNP concentrations in
East Coast samples (median = 1,254 µg g
−1
; Supplementary Table 1 and
Fig. 1d). While geographical differences cannot be ruled out, we applied
a simple linear regression including all normal brain biospecimen data,
which revealed significantly increasing trends for total plastics, PE, PP,
PVC and SBR (Extended Data Fig. 2). To extend findings to a specific
neurological condition, Py-GC/MS was conducted on 12 dementia cases
collected in the NM OMI. These cases included Alzheimer’s disease
(n = 6), vascular dementia (n = 3) and other dementia (n = 3) specimens
from 2019 to 2024. Py-GC/MS analysis revealed total plastics con-
centrations in dementia samples (median = 26,076 µg g
−1
; Fig. 1d and
Supplementary Table 1) that were higher than in any normal frontal
cortex cohort (P < 0.0001 by two-sided t test). Atrophy of brain tissue,
impaired blood–brain barrier integrity and poor clearance mechanisms
are hallmarks of dementia and would be anticipated to increase MNP
concentrations; thus, no causality is assumed from these findings.
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).
Within the liver, these inclusions were widely dispersed but also notably
aggregated within acellular regions consistent with the expected fre-
quency and morphology of lipid droplets, with rod-shaped particles in
the 1–5 µm size range (Extended Data Fig. 3a). In the kidney, an elevated
presence of refractile inclusions of similar sizes was noted in glomeruli
and along tubules (Extended Data Fig. 3a–d). Based on elevated con-
centrations of polymers identified by Py-GC/MS in these tissues, we
suspected that much of the MNPs may be present in the nanoscale
range, too small for visualization by light microscopy. Transmission
electron microscopy (TEM) was therefore conducted on the dispersed
KOH-insoluble pellets obtained from the liver and kidney (Extended
Data Fig. 3e,f and Supplementary Fig. 9). While this visualization
method cannot provide spectroscopic confirmation of polymer com
-
position, we observed common shapes and sizes across samples and
tissue types. Particulates isolated from the pellets and well-dispersed
appeared shard-like and were typically less than 0.4 µm in length,
consistent with recent findings of nanoplastics in farmed mussels
12
.
SEM with energy-dispersive spectroscopy confirmed that particles
observed in livers, kidneys and brains were principally composed of
carbon (Extended Data Figs. 4–7). Based on the larger morphology
of particulates observed in situ versus those isolated and dispersed
from the pellets of digested tissue, we postulate that aggregation of
nanoplastics may occur in the liver and kidney.
In brain tissues, larger (1–5 µm) refractile inclusions were not seen,
but smaller particulates (<1 µm) were noted in the brain parenchyma
(Fig. 2a–c and Supplementary Figs. 10–15). Given the resolution limita-
tions of light microscopy, we examined resuspended brain pellets by
TEM, which revealed largely 100–200 nm long shards or flakes (Fig. 2d
and Supplementary Figs. 9 and 16). In situ, we confirmed that particles
found in the brain were carbon-based by SEM with energy-dispersive
X-ray spectrometry (EDS; Extended Data Figs. 6 and 7). In dementia
samples, many refractile inclusions were prominent in regions with
inflammatory cells and along the vascular wall (Fig. 2e,f). MNP uptake
and distribution pathways are poorly understood, and the mechanism
of how nanoplastics are delivered to and taken up into the brain is
unknown. Insights from Daphnia magna suggest clathrin-dependent
endocytosis and macropinocytosis may underlie nanoplastic transloca-
tion within the intestine
13
; we posit a similar uptake may occur in human
ingestion of lipids that would also facilitate selective transfer into the
brain. While blood was not cleared from the decedent’s organs during
autopsy, it is unlikely that the nanoplastics in the brain are selectively
contained in the vascular compartment, as the kidneys and livers would
also have comparable blood volumes.
While we suspected that MNPs might accumulate in the body over
a lifespan, the lack of correlation between total plastics and decedent
age (P = 0.87 for brain data) does not support this (Supplementary
Fig. 1). However, total mass concentration of plastics in the brains
analyzed in this study increased by approximately 50% in the past
8 years. Thus, we postulate that the exponentially increasing environ-
mental concentrations of MNPs
2,14
may analogously increase internal
maximal concentrations. Although there are few studies to draw on
yet performed in mammals, in zebrafish exposed to constant concen-
trations, nanoplastic uptake increased to a stable plateau and cleared
after exposure
15
; however, the maximal internal concentrations were
increased proportionately with higher nanoplastic exposure concen-
trations. While clearance rates and elimination routes of MNPs from the
brain remain uncharacterized, it is possible that an equilibrium—albeit
variable between people—might occur between exposure, uptake and
clearance, with environmental exposure concentrations ultimately
determining the internal body burden.
Although the current data derive from multiple tissue banks and
two analytic sites replicating key results, the new analytical Py-GC/
MS methods applied here are yet to be widely adopted and refined
into standardized tests for clinical specimens. Both analytical labora-
tories (UNM and OSU) observed a ~25% within-sample coefficient of
variation, which does not alter the conclusions regarding temporal
trends or accumulation in brains relative to other tissues, given the
magnitude of those effects. Numerous quality control steps ensure that
external contaminants are not impacting the results, including Py-GC/
MS assessment of KOH and formalin storage control sample ‘blanks’
and measurements of the polymer composition of all plastic tubes
and pipette tips that are essential in the digestion and measurement
process (Supplementary Figs. 2–4). Decedent specimen collections
over the past 30 years were not focused on minimizing external plastic
Nature Medicine | Volume 31 | April 2025 | 1114–1119
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Brief Communication https://doi.org/10.1038/s41591-024-03453-1
200 nm
25 µm
25 µm
25 µm
a b
c
d
e
f
5 µm2 µm
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
innumerable shard- or flake-like solid particulates following dispersion, with
dimensions largely <200 nm in length and <40 nm in width. e,f, Polarization wave
microscopy reveals substantially more refractile inclusions in dementia cases,
especially in regions with associated immune cell accumulation (e) and along
the vascular walls (f). All images were collected on a small subset of participants
(n = 10 for normal brains; n = 3 for dementia cases) to provide visual evidence to
support analytical chemistry.
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Brief Communication https://doi.org/10.1038/s41591-024-03453-1
contamination. However, given the consistent nature of handling and
processing across all organ samples within objectively clean clinical and
forensic settings, the significant accumulation of MNPs in the brain can
-
not be dismissed as an artifact of contamination. Furthermore, the 2016
samples were stored for 84–96 months compared to only 2–4 months
for the 2024 samples, which exhibited greater concentrations of poly-
mer. Thus, contamination from plastic storage vessels should not
influence the conclusions. For the brain, especially, greater attention
to anatomical features, such as white versus gray matter, vasculariza-
tion and glia content, should be carefully evaluated in future studies to
reduce variation. Finally, by obtaining only a single sample from each
organ for each participant, distribution heterogeneity within tissues
remains uncharacterized.
Our estimates of polymer mass concentration could be impacted
by several factors that may lead to overestimation or underestima-
tion. The KOH digestion extensively eliminated biological material
from the pellets through saponification of triglycerides and dena-
turing of proteins (Supplementary Fig. 5). However, the final pellets
still contained unknown residual biomatrix, which could present
challenges for mass spectral interference. KOH reduced the liver
and kidney mass by 99.4%, while the brain samples were reduced by
91.8%, that is, the resultant average pellet mass derived from 500 mg
of starting material was approximately 3 mg and 41 mg, respectively.
This discrepancy is proportional to, and consistent with, the mass of
the polymer measured. However, unknown organic molecules likely
remain and influence the resultant Py-GC/MS spectra. Lipids have
been noted as a potential source of interference in Py-GC/MS analysis
of PE
16
. Our method of KOH digestion and physical separation of sol-
ids was designed to reduce this concern, rather than augment it with
a liquid–liquid extraction in organic solvents that would selectively
drive lipid partitioning. Furthermore, the spectra suggest a reduc-
tion of longer carbon chains in the pyrolysis chromatogram, which
is potentially due to advanced oxidative degradation of the MNPs
and excess carbonyl formation that may lead to an underestima-
tion of the concentration, as our standards are created with pristine
polymers
17,18
. Finally, given the observed small size of nanoscale
particles isolated from the human specimens (typically <200 nm in
length), it is likely that ultracentrifugation incompletely collected
nanoplastics in the analytical samples, also contributing to potential
underestimation. The shape and size of observed nanoparticles in the
isolated material from human specimens taxes the limits of modern
analytical instrumentation but may reflect an end-stage product of
plastic degradation that is uniquely suited for human uptake and
accumulation.
Conclusions
The present data suggest a trend of increasing MNP concentrations in
the brain and liver. The majority of MNPs found in tissues consist of PE
and appear to be nanoplastic shards or flakes. MNP concentrations in
normal decedent brain samples were 7–30 times greater than the con-
centrations seen in livers or kidneys, and brain samples from dementia
cases exhibited even greater MNP presence. These data are associative
and do not establish a causal role for such particles affecting health.
For this, refinements to the analytical techniques, more complex study
designs and much larger cohorts are needed. Given the exponentially
rising environmental presence of MNPs
19–21
, these data compel a much
larger effort to understand whether MNPs have a role in neurological
disorders or other human health effects.
Online content
Any methods, additional references, Nature Portfolio reporting sum-
maries, source data, extended data, supplementary information,
acknowledgements, peer review information; details of author con-
tributions and competing interests; and statements of data and code
availability are available at https://doi.org/10.1038/s41591-024-03453-1.
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Creative Commons licence, unless indicated otherwise in a credit
1
Department of Pharmaceutical Sciences, College of Pharmacy, University of New Mexico Health Sciences, Albuquerque, NM, USA.
2
Division of
Gastroenterology and Hepatology, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
3
Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
4
Department of Cell Biology and Physiology,
School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
5
Department of Pharmacy Practice and Administrative
Sciences, College of Pharmacy, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
6
School of Civil & Environmental
Engineering, Oklahoma State University, Stillwater, OK, USA.
7
Clinical and Translational Science Center, University of New Mexico Health Sciences
Center, Albuquerque, NM, USA.
8
Department of Earth and Planetary Sciences, University of New Mexico, Albuquerque, NM, USA.
9
Ofice of the Medical
Investigator, University of New Mexico, Albuquerque, NM, USA.
10
Grupo de Investigación en Rehabilitación de la Universidad del Valle (GIRUV),
Cali, Colombia.
11
Duke Center for Neurodegeneration and Neurotherapeutics, Duke University, Durham, NC, USA.
12
These authors contributed equally:
Alexander J. Nihart, Marcus A. Garcia, Eliane El Hayek.
e-mail: mcampen@salud.unm.edu
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Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Methods
Human tissue samples
The same tissue collection protocol at the UNM OMI was used for
2016 and 2024. Small pieces of representative organs (3–5 cm
3
) were
routinely collected at autopsy and stored in 10% formalin. Additionally,
decedent samples from a cohort with confirmed dementia (n = 12) were
included, also collected at the UNM OMI under identical procedures.
Limited demographic data (age, sex, race/ethnicity, cause of death
and date of death) were available due to the conditions of specimen
approval; age of death, race/ethnicity and sex were relatively consist-
ent across cohorts (Supplementary Table 1). Additional brain samples
(n = 28) were obtained from repositories on the East Coast of the United
States to provide a greater range for the year of death (going back to
1997). All studies were approved by the respective Institutional Review
Boards.
Py-GC/MS detection of polymer solids
Py-GC/MS is an informative and reliable method to determine plas-
tic concentrations in liquid and solid tissue samples, with ample
assurance of accuracy, quality and rigor
3,4,9,10
. Briefly, solid particu-
lates are isolated from chemically digested tissue samples and then
combusted to reveal signature mass spectra for select polymers (see
full details in Supplementary Methods—Pyrolysis gas chromatogra-
phy–mass spectrometry (PY-GC/MS)). Thus, the Py-GC/MS output
is derived from enriched solid polymer particles and not soluble
components from the digested tissue. Samples (~500 mg) were
digested with 10% potassium hydroxide for at least 3 days at 40 °C.
Samples were then ultracentrifuged at 100,000g for 4 h to generate
a pellet enriched in solid materials resistant to such digestion, which
included polymer-based solids
10
. A 1–2 mg portion of the resulting
pellet was then analyzed by single-shot Py-GC/MS and compared to
a microplastics-CaCO
3
standard containing the following 12 specific
polymers: PE, PVC, nylon 66, SBR, acrylonitrile butadiene styrene,
polyethylene terephthalate, nylon-6, poly(methyl methacrylate),
polyurethane, polycarbonate, PP and polystyrene. Py-GCMS oper-
ating settings and polymer pyrolyzate targets are described in Sup-
plementary Tables 2 and 3, with examples of spectra from samples,
standards and blanks shown in Supplementary Figs. 2–4. Polymer
spectra were identified via F-Search MPs v2.1 software (Frontier
Labs). The resulting data were normalized to the original sample
weight to render a mass concentration (µg g
−1
).
Data analysis
Details of statistical analyses (normalization steps, two-way ANOVA
and multiple regression) are provided in the Supplementary Meth-
ods—Statistical analysis.
Reporting summary
Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.
Data availability
More extensive methods and results are provided in the online Sup-
plementary Information. Full demographic and analytical results are
provided in Dryad (https://doi.org/10.5061/dryad.b8gtht7p8).
Acknowledgements
We thank J.D. Hesch at Hesch Consulting for her critical review of
this manuscript. This research was funded by the National Institute of
Health (P20 GM130422 (to M.J.C. and R.G.), R01 ES032037 (to E.F.C.),
R01 ES014639 (to M.J.C.), K12 GM088021 (to M.A.G.), P50 MD015706
(to E.E.H. and J.G.-E.), P30 ES032755 (to B.B.), UL1 TR001449 (to J.G.)
and R15 ES034901 (to J.S. and J.G.-E.)).
Author contributions
M.J.C., E.F.C., M.A.G., E.E.H., B.B. and J.G.-E. conceptualized the project
and secured funding. M.J.C., A.J.N., M.A.G., J.S., J.G.-E., E.E.H., R.R.G.,
D.F.G., J.M.G., B.B. and A.B.W. wrote the original draft of the paper.
D.F.G., A.J.N., M.O., H.S.J., G.D., M.E.Z.-R., N.L.A. and A.B.W. did sample
procurement, identiication and diagnosis. M.A.G., R.L., J.D.K., J.G.-E. and
J.S. performed analytical chemistry and sample analysis. H.S.J., M.J.C.,
E.F.C. and A.B.W. provided compliance assurance. E.E.H., T.H., M.S. and
R.R.G. performed imaging. J.M.G. and M.J.C. performed statistical analysis.
Competing interests
The authors declare no competing interests.
Additional information
Extended data is available for this paper at https://doi.org/10.1038/
s41591-024-03453-1.
Supplementary information The online version contains supplementary
material available at https://doi.org/10.1038/s41591-024-03453-1.
Correspondence and requests for materials should be addressed to
Matthew J. Campen.
Peer review information Nature Medicine thanks Gary Miller and the
other, anonymous, reviewer(s) for their contribution to the peer review
of this work. Primary Handling Editor: Jerome Staal, in collaboration
with the Nature Medicine team.
Reprints and permissions information is available at
www.nature.com/reprints.
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 1 | Overall compositional outcomes, in relative proportion
of the total polymer mass. Overall compositional outcomes, in relative
proportion of the total mass, are shown for (a) liver, kidney and brain samples
and (b) a cross-comparison of data for brains from all cohorts (polyethylene
(PE), polypropylene (PP), polystyrene (PS), acrylonitrile butadiene styrene resin
(ABS), sytrene-butadiene rubber (SBR), polymethyl methacrylate (PMMA),
polycarbonate (PC), polyvinyl chloride (PVC), polyurethane (PU), polyethylene
terephthalate (PET), nylon-6 (N6) and nylon-6,6 (N66)). Additionally, relative
proportions of polymers from Fourier transform infrared (FTIR) spectroscopic
analysis in brains are shown for comparison (last 5 columns in a). In general,
4 polymers, PE, PP and PVC comprise approximately 90% of the mass of samples,
with nylon being an additional major component in some samples. Each column
represents a unique subject (see Supplementary Table 1 for demographic data).
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 2 | Comparison of polypropylene and polyvinyl chloride
in all organs across time. Comparison of (a) polypropylene and (b) polyvinyl
chloride across time and organs for NM OMI samples (see subject demographics
in Supplementary Table 1). P-values shown indicate significant differences
between 2016 and 2024 samples by a two-sided Mann–Whitney test. c, Simple
linear regression (shown with 95% CI represented by dashed lines) was performed
for total plastics, polyethylene, polypropylene, polyvinyl chloride and styrene-
butadiene rubber measured in normal decedent brains from 2004 (average
of east coast samples), 2016 and 2024 (NM OMI samples). Mean ± 95% CI are
shown for each cluster of samples. Regression analysis for all plastics rendered a
p-value < 0.0001 for each polymer, with R
2
values ranging from 0.25 to 0.48.
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 3 | TEM, polarization wave microscopy, and SEM images
of putative microplastics from liver and kidney. Example SEM (a,b) and
polarization wave microscopy (c,d) images of decedent histological specimens
and TEM images (e,f) of nanoparticulates derived from liver (left) and kidney
(right). While these methods do not permit spectroscopic identification
of particulate molecular composition, the bulk of particulates that were
predominantly polymer as assessed by ATR–FTIR appear to be of these sizes and
shapes. Energy-dispersive spectroscopy confirmed that particles were carbon-
based and not mineral (Extended Data Figs. 4 and 5). Visual fields for SEM were
39.5 µm and 15.4 µm (a) and 135 µm and 9 µm (b). Example TEM images from the
dispersed pellet that was derived from KOH digestion and ultracentrifugation
resolved innumerable shard-like solid particulates, with dimensions largely
<200 nm in length and <40 nm in width. Polarization wave microscopic images
were collected on a small subset of subjects (N = 12) to provide visual evidence to
support analytical chemistry.
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 4 | SEM–EDS imaging of solid inclusions from the hepatic
lipid droplets. Locations of EDS are described in the SEM image (a). Particles
in the droplet (1,2) render carbon-rich spectra (b,c) compared to a region (3)
of hepatic tissue (d). The droplet is transected by the sectioning, and thus the
background (4) reveals a silica-rich spectra consistent with the glass histology
slide (e). Importantly, these particulates do not appear to be metallic or mineral.
Imaging was conducted on sections from two subjects with consistent findings.
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 5 | SEM–EDS imaging of solid inclusions in the kidney.
Locations of EDS are described in the SEM image (a). Renal tissue (b) displays
spectra with lower relative carbon concentration than the observed particle
(c). Importantly, these particulates do not appear to be metallic or mineral.
Silicon and gold signals are derived from the mounting media. Imaging was
conducted on sections from two subjects with consistent findings.
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 6 | SEM–EDS imaging of a particulate cluster in a brain
specimen. Locations of EDS are described in the SEM image (a). The particulate
regions (locations 1 and 3) exhibit a greater carbon signal in the spectra
(b,d) compared to the background brain tissue (location 2; c). Importantly, these
particulates do not appear to be metallic or mineral. Imaging was conducted on
sections from two subjects with consistent findings.
Nature Medicine
Brief Communication https://doi.org/10.1038/s41591-024-03453-1
Extended Data Fig. 7 | SEM–EDS imaging of particulate in a brain specimen.
Locations of EDS are described in the SEM image (a). The background brain tissue
(location 1) exhibits a lower carbon signal in the spectrum (b) compared to the
particulate region (location 2; c). Importantly, these particulates do not appear
to be metallic or mineral. Imaging was conducted on sections from two subjects
with consistent findings.
Plastic pollution is usually discussed as an environmental problem. But what happens when tiny plastic particles enter our bodies?
In this 2025 paper, researchers analyzed postmortem human brain, liver, and kidney tissue to investigate the presence of microplastics and nanoplastics. Using chemical analysis and microscopy, they reported that brain samples contained substantially higher concentrations of plastic-associated material than liver or kidney samples. They also found higher concentrations in samples collected in 2024 than in comparable samples from 2016.
The findings raise fascinating questions about how these particles enter the brain, how long they remain there, and whether they affect human health. But an important distinction remains: detecting plastic in brain tissue does not establish that it causes neurological disease.
- Microplastics are present in human organs: Researchers detected micro- and nanoplastics (MNPs) in the brain, liver, and kidneys using multiple analytical methods.
- The brain had a distinct plastic profile: Polyethylene was the predominant polymer, and brain tissue contained a higher proportion of it than liver or kidney tissue. The particles were largely tiny, shard-shaped fragments.
- Plastic concentrations increased over time: Brain and liver samples collected in 2024 had higher measured concentrations than samples from 2016.
- No clear demographic differences were found: Concentrations were not significantly associated with age, sex, race/ethnicity, or cause of death in this study.
- Higher levels were observed in dementia cases: Brain samples from people with a documented dementia diagnosis showed greater accumulation, particularly around blood vessel walls and in immune cells.
- Important unanswered questions remain: Researchers still need to establish how plastics enter and leave the body, why they accumulate in certain tissues, and whether they contribute to health problems.
Key takeaway: The study provides evidence of micro- and nanoplastics in human organs, but it does not establish that these particles cause dementia or other diseases.
> "The present data suggest a trend of increasing MNP concentrations in the brain and liver. The majority of MNPs found in tissues consist of PE and appear to be nanoplastic shards or flakes. MNP concentrations in normal decedent brain samples were 7–30 times greater than the concentrations seen in livers or kidneys, and brain samples from dementia cases exhibited even greater MNP presence. These data are associative and do not establish a causal role for such particles affecting health. For this, refinements to the analytical techniques, more complex study designs and much larger cohorts are needed. Given the exponentially rising environmental presence of MNPs, these data compel a much larger effort to understand whether MNPs have a role in neurological disorders or other human health effects."