We obtained de-identified, postmortem human liver (right central parenchyma), 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 Investigator (OMI) in Albuquerque, New Mexico (NM), under the guidance of a trained forensic pathologist (D.F.G.) who selected consistent regions 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 plaques4, 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).

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 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 R2 = 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.

Liver and brain samples from 2024 had significantly higher concentrations 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 regression analysis of brain concentrations considering the potential influence 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 concentrations 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 histologically (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 frequency 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 concentrations 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 composition, 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 mussels12. 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.

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.

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 limitations 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 translocation within the intestine13; 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 environmental concentrations of MNPs2,14 may analogously increase internal maximal concentrations. Although there are few studies to draw on yet performed in mammals, in zebrafish exposed to constant concentrations, nanoplastic uptake increased to a stable plateau and cleared after exposure15; however, the maximal internal concentrations were increased proportionately with higher nanoplastic exposure concentrations. 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 laboratories (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 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 cannot 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 polymer. 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, vascularization 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 underestimation. The KOH digestion extensively eliminated biological material from the pellets through saponification of triglycerides and denaturing 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 PE16. Our method of KOH digestion and physical separation of solids 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 reduction 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 underestimation of the concentration, as our standards are created with pristine polymers17,18. 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.