Abstract Parkinson’s disease (PD) is increasingly viewed as both a neurological and metabolic disorder, with the gut-brain axis playing a key role. This study explored how polystyrene (PS) nanoplastics contributed to PD progression by examining their metabolic impact in an A53T α-synuclein (αS) mouse model. Mice given PS nanoplastics orally (2 mg/kg every other day for three months) displayed compromised gut barrier integrity, including a 30% drop in goblet cells and increased epithelial apoptosis in the ileum. Microbial diversity in the ileum rose sharply, with an overgrowth of Desulfovibrio spp. linked to neuroinflammation and αS aggregation. KEGG analysis confirmed apoptosis and lipopolysaccharide biosynthesis pathways influenced by nanoplastics, while metabolomics identified over 200 altered fecal metabolites, including those associated with cytochrome P450 activity and disruptions to cancer-related pathways. Additionally, histopathology revealed liver inflammation, underscoring the systemic effects of nanoplastic exposure. Overall, our findings suggest that environmental nanoplastics may aggravate PD physiopathology through gut-liver axis disruption and metabolic dysregulation. graphic file with name 41531_2025_1145_Figa_HTML.jpg Subject terms: Biological techniques, Microbiology, Neuroscience, Diseases, Pathogenesis, Risk factors Introduction Plastic pollution is a global problem with long-term environmental and human health implications^[32]1–[33]3. Despite awareness by the scientific community and policymakers that measures are urgently needed to reduce reliance on industrial and domestic plastics, accumulation of plastics has nonetheless continued to outpace efforts aimed at curbing their pervasive presence in landfills, air, water and soil^[34]4. One major obstacle to achieving the circular economy of plastics stems from their strong resistance to degradation by physical, chemical or biological forces, either naturally or through human intervention^[35]5. Research over the past two decades has revealed that plastics, especially the smallest micro- and nanoplastics, can pose a threat to biosystems in the ecosphere^[36]6. The physicochemical properties of micro- and nanoplastics, for example, are ideally suited for partitioning into the amphiphilic membranes of plant and animal cells, including those of human, leading to their bioaccumulation and integration into the food chain^[37]7–[38]9. At the molecular and cellular levels, the small size and large surface area of micro- and nanoplastics can stimulate cytokine overproduction, damage to endoplasmic reticulum and mitochondria, oxidative stress, inflammation, and cell death^[39]10–[40]12. In addition, exogenous plastic particulates possess the potential to disrupt endocrine and immune functions as well as the homeostasis of gut microbiota, impair intestinal barrier integrity, and exacerbate metabolic disorders and inflammatory diseases^[41]13–[42]16. Concerning their fingerprints on neurotoxicity, growing evidence has implicated nanoplastics as an exogenous factor to neuroinflammation and impaired neurotransmission^[43]17–[44]21, mediated either directly or through the gut-brain axis^[45]22–[46]26. The crucial need for deciphering nanoplastic-brain interaction is underscored by a recent finding, where abundant nanoplastics were detected in post-mortem human brains, particularly in those of individuals who had dementia^[47]27. Among the various neurological disorders, Parkinson’s disease (PD) is a movement impairment affecting millions worldwide, and its potential link to environmental toxins has gained much attention in the past few years^[48]26,[49]28. As highlighted by meta-analyses, chronic exposure to environmental toxins, including nanoplastics, can disrupt mitochondrial function, induce oxidative stress, alter proteostasis, and trigger neuroinflammation—key mechanisms in dopaminergic neuron degeneration and the development of PD^[50]29. Specifically, preliminary research has revealed that oral exposure to nanoplastics can disrupt energy metabolism, leading to PD-like symptoms in mice^[51]30. Nanoplastics administered intragastrically have been shown to induce neurotoxicity by altering circadian rhythm-related pathways^[52]24. Alpha-synuclein (αS), a major protein constituent of Lewy bodies in PD neurons, displayed a strong affinity for anionic nanoplastics via non-specific interactions^[53]31,[54]32. Additionally, co-injecting nanoplastics and short αS fibrils into the striatum facilitated the spread of PD pathology across interconnected brain regions in non-transgenic mice, resulting in αS inclusions in the midbrain^[55]31. We have recently shown that gastrointestinally administered nanoplastics hitch-hiked the gut-brain axis of αS to exacerbate PD pathophysiology^[56]33. Similar to other nanoplastic-neurological studies, our findings focused on cerebral damage and animal behavior entailed by nanoplastic exposure. As PD is not merely a neurological disorder but also a metabolic disease^[57]34,[58]35, here we examined through metabolomics the dysfunction of the digestive tract of a PD model, to offer more insights into the overlooked metabolic hallmarks of PD pathophysiology stressed by nanoplastic exposure. Results Physicochemical properties of polystyrene (PS) nanoplastics The amino acid sequence of protein A53T αS is illustrated in Fig. [59]1a. The size and morphology of PS nanoplastics were characterized by transmission electron microscopy (TEM) in ultra-pure water and phosphate-buffered saline (PBS). As expected, TEM imaging showed an average nanoplastic size of ~50 nm and a circular shape (Fig. [60]1b). The Fourier transform infrared spectroscopy (FTIR) spectrum (Fig. [61]1b) displayed a peak near 3000 cm^−^1, indicating the presence of C-H tensile vibrations absorption. The additional peaks near 1500 cm^−^1 can be attributed to the aromatic C=C tensile vibrations of the benzene ring in styrene, while peaks near 700 cm^−^1 correspond to C-H aromatic bending vibrations, suggesting a substituent on the benzene ring. In addition, the ^1H nuclear magnetic resonance (NMR) spectrum in Fig. [62]1b shows the characteristic signals of pure PS, confirming their composition and purity. Fig. 1. Materials characterizations. [63]Fig. 1 [64]Open in a new tab a Amino acid sequence of A53T αS. b Characterizations of PS nanoplastics used in the study. (i) TEM image of the nanoplastics, where the diameter data was obtained with Image J and the histogram was from GraphPad Prism 9.0. Scale bar: 50 nm. (ii) FTIR spectrum of the nanoplastics, showing transmittance (%) and functional groups across the wavenumber range of 500–3500 cm^−^1. (iii) ^1H NMR spectrum of the nanoplastics at 500 MHz in CDCl[3]. Effects of PS nanoplastics and A53T αS on mouse intestinal function Prior to use, endotoxins in all purchased PS nanoplastic samples were confirmed to be below 0.01 EU/mL in concentration (the minimum detection limit of the kit), ensuring minimal interference with biological responses via a Limulus Amebocyte Lysate (LAL) assay. Additionally, PS suspensions were freshly prepared in sterile PBS before each experiment. Goblet cell secretion is essential for maintaining the integrity of the epithelial barrier^[65]36,[66]37. Goblet cells produce mucin, which prevents most intestinal bacteria from penetrating the intestinal epithelial barrier^[67]38. The extent of damage to the inner wall of the upper duodenum and ileum, as observed through hematoxylin and eosin (HE) staining, was greater in the PS and PS + A53T αS groups compared to the PBS and A53T αS groups (Fig. [68]2a, b). Upon exposure to PS (P < 0.05, One-way ANOVA test) or A53T αS (P < 0.01, One-way ANOVA test), a significant decrease in the number of ileum goblet cells was found in mice compared to PBS-treated mice (Fig. [69]2b, d). In addition, exposure to PS and A53T αS led to increased apoptosis of intestinal epithelial cells, emphasizing the damaging effects of PS on the intestinal epithelium (Fig. [70]2c, f). On the other hand, changes to the number of colon goblet cells were negligible in A53T αS-treated mice compared to PBS-treated mice (P > 0.05, One-way ANOVA test) (Fig. [71]2e, g). This discrepancy may be attributed to the administration site of A53T in the small intestine. Collectively, these observations suggest that PS exposure and A53T αS may synergistically aggravate intestinal barrier dysfunction, with a trend toward more severe disruption in the small intestine compared to the large intestine. However, since our experiment primarily focused on the small intestine, further investigation is needed to evaluate the effects of A53T αS on the large intestine, where αS is also known to be distributed^[72]39,[73]40. Fig. 2. Effects of PS nanoplastics and A53T αS on mouse intestinal function. [74]Fig. 2 [75]Open in a new tab a Representative HE-staining images of the upper duodenum in mice six months post-injection with PBS, PS nanoplastics or A53T αS. Scale bar: 400 μm. b Representative HE-staining images of the ileum in mice six months post-injection with PBS, PS nanoplastics or A53T αS. Scale bar: 200 μm. c TUNEL staining images of the ileum in mice. Scale bar: 400 μm. d Statistical analysis of ileum goblet cells per villus across different groups. e Statistical analysis of colon goblet cells per crypt across different groups. f Statistical analysis of (c). g Representative HE-staining images of the colon in mice six months post-injection with PBS, PS nanoplastics or A53T αS. Scale bar: 200 μm. h TUNEL staining images of the colon in mice. Scale bar: 200 μm. One-way ANOVA test was used between multiple comparisons, and unpaired two-tailed Student’s t-test was applied for comparison between two groups. Nanoplastics altered the profile of small intestinal microbiota in an A53T αS mouse model Recent studies have reported that changes in the population of small intestinal bacteria are likely related to PD pathogenesis, highlighting the prevalence of small intestinal bacterial overgrowth (SIBO) in PD subjects^[76]41–[77]43. SIBO can cause intestinal symptoms due to microbial gas accumulation, such as bloating, burping, and abdominal pain, which affect intestinal transit time and cause diarrhea or severe constipation^[78]44. Severe SIBO can impair macronutrient absorption, leading to weight loss and vitamin deficiencies^[79]44. The decreased ability of the small intestine and chyme formation can lead to increased flora and SIBO^[80]45. Research suggests that SIBO can trigger a local inflammatory response, compromising the intestinal barrier by disrupting tight junctions and increasing permeability. This may expose the intestinal mucosa to bacterial endotoxins such as lipopolysaccharide (LPS)^[81]46,[82]47. Additionally, the intestinal barrier plays a critical role in maintaining gut microbiota balance^[83]48. Here, we examined the small intestinal microbiota of mice, focusing on community structure and functional characteristics. Using 16S rRNA sequencing, we analyzed the microbial composition of ileal samples across four experimental groups. A Venn diagram was used to visualize shared and unique operational taxonomic units (OTUs) among the experimental groups. As shown in Fig. [84]3a, 93 OTUs were shared by the four groups, with 37, 121, 128 and 182 OTUs unique for the PBS, PS, A53T αS and PS + A53T αS groups, respectively. Notably, the total number of OTUs found in these four groups was 177, 383, 392 and 450, respectively (Fig. [85]3b), indicating significantly greater OTU numbers in PS or A53T αS mice compared to PBS-treated mice. Moreover, co-administration of PS led to a further increase in OTU numbers compared to A53T αS alone. The OTU rank curves of all three experimental groups were smoother than those for the PBS group (Fig. [86]3c). Meanwhile, Partial Least-Squares Discriminant Analysis (PLS-DA) (Fig. [87]3d) effectively differentiated the four groups, highlighting significant variations in small intestinal microbial composition. Alpha-diversity analysis (Fig. [88]3e), which was conducted to evaluate the richness and diversity of the bacterial species, revealed a significantly increased Chao index in PS or A53T αS mice, compared to the PBS group. Principal Coordinates Analysis (PCoA) based on unweighted UniFrac distances was performed to assess beta-diversity in gut microbiota and visualize differences in bacterial composition among the four groups (Fig. [89]3f). The analysis confirmed distinct beta-diversity (P = 0.0001, R^2 = 0.33, PERMANOVA), with clear separation observed between PBS and other groups. At the phylum level, variations in gut microbiota structure among the groups were analyzed, and relative abundances were quantified and presented as a stacked histogram (Fig. [90]3g). The most prominent phyla were Bacillota (also called Firmicutes) and Bacteroidota (also called Bacteroidetes). Notably, Bacillota decreased markedly (P < 0.01, One-way ANOVA test) in the PBS and PS, A53T αS, and PS + A53T αS groups (Fig. [91]3h), while Bacteroidota showed a significant increase in the PS and A53T αS (P < 0.05, Kruskal–Wallis test) groups, and no statistical difference in the PS + A53T αS group (Fig. [92]3i). Consequently, the ratio of Bacillota/Bacteroidota decreased significantly in the PS and A53T αS groups (Fig. [93]3j). Moreover, Pseudomonadota increased markedly in the PS and PS + A53T αS groups compared to the PBS group. However, the levels of Bacillota and Bacteroidota in the A53T αS group were not further altered by co-exposure to PS nanoplastics (Fig. [94]3h–j). This suggests that both single and co-exposure to A53T αS and PS nanoplastics may exacerbate the intestinal microenvironment. Previous studies have reported that PS nanoplastics reduced Firmicutes and increased Bacteroidetes^[95]49–[96]52, consistent with our findings for the A53T αS PD model stressed by nanoplastic exposure. Firmicutes and Bacteroidetes are major intestinal bacteria^[97]53, and their ratio is associated with obesity, with a higher Firmicutes-to-Bacteroidetes ratio observed in obese individuals^[98]54. An increase of Firmicutes in the cecum has been linked to enhanced nutrient absorption and development of obesity^[99]53. In addition, Pseudomonadota and Actinomycetota showed an increasing tendency in the PS, A53T αS, and PS + A53T αS groups compared to the PBS group (Fig. S[100]1a). It is important to note that Desulfovibrionales at the order level and Desulfovibrionaceae at the family level increased in the PS, A53T αS, and PS + A53T αS groups compared to the PBS group (Fig. [101]3k, l). Desulfovibrionales‌ and Desulfovibrionaceae, capable of reducing sulfate and producing hydrogen sulfide (H[2]S)^[102]55, have been found to be elevated in the intestines of Alzheimer’s patients. This suggests a potential causal link between their increased abundance and the onset of Alzheimer’s disease (AD)^[103]55. Fig. 3. Impact of PS nanoplastics or A53T αS on ileal microbiota diversity. [104]Fig. 3 [105]Open in a new tab a Venn diagram illustrating discrepancies in OTUs among the four groups. b Total number of OTUs in each group. c OTU rank curves of the four groups. d Partial Least-Squares Discriminant Analysis (PLS-DA) showing distinct clustering of the treatment groups (PS nanoplastics, A53T αS, PS + A53T αS) relative to control, indicating significant alterations in bacteria profiles. e Alpha-diversity indices reflected by the Chao. f Beta-diversity measured by Principal Coordinates Analysis (PCoA). g Relative abundance of ileal microbiota at the phylum level for each group. h Relative abundance of Bacillota. i Relative abundance of Bacteroidota. j Bacillota/Bacteroidota abundance ratio. k Relative abundance of ileal microbiota at the order level. l Relative abundance of ileal microbiota at the family level for each group. m Relative abundance of ileal microbiota at the genus level for each group. n Relative abundance of representative microbiota at the genus level. One-way ANOVA (e, f, h) or Kruskal–Wallis tests followed (i, j, n) was used between multiple comparisons, while unpaired two-tailed Student’s t-tests (e, h, i, j) or Mann–Whitney test (n) was applied for comparison between two groups. Further analysis at the family and genus levels revealed a decreasing trend for Clostridiaceae and an increasing trend for Eggerthellaceae in the PS, A53T αS, and PS + A53T αS groups compared to the PBS group (Fig. [106]S1b). Moreover, PS increased the Enterobacteriaceae count in A53T αS-treated mice, indicating changes in the intestinal flora structure. At the genus level, variations in gut microbiota structure between each group were analyzed, and the relative abundance was determined and displayed as a heat map of accumulation (Fig. [107]3m). Specifically, Kruskal–Wallis test showed a marked increase in Desulfovibrio abundance of the PS, A53T αS, and PS + A53T αS groups compared to the PBS group (Fig. [108]3n). This finding aligns with existing literature indicating that the presence of Desulfovibrio is enhanced in the gut of mice following PS exposure^[109]49. Previous research has correlated the presence of Desulfovibrio with PD, linking their high abundance to disease severity^[110]56,[111]57. Meta-analysis of gut microbes in PD patients showed a significant increase in the relative abundance of Desulfovibrio^[112]58. Desulfovibrio is a major producer of H[2]S in the gastrointestinal tract, and its LPS production may promote αS oligomerization and aggregation. In addition, Desulfovibrio also plays a role in inflammatory response and metabolic disorders^[113]56. These results point to potential changes induced by PS nanoplastics in the small intestine microbiota composition of A53T αS mice, as suggested by the intergroup species interaction network (Fig. S[114]2), in line with emerging evidence linking environmental stressors to gut dysbiosis^[115]59. To better understand the functions of these significantly altered bacteria, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Fig. S[116]3a showed the KEGG function enrichment analysis for all detected ileal microbiota. The microorganisms were primarily enriched in pathways related to metabolism and genetic information processing. Detailed KEGG results of different microbial functions are shown in Fig. S[117]3b. For the PS nanoplastics-treated group, the top five significantly affected pathways were other glycan degradation, protein digestion and absorption, N-glycan biosynthesis, sphingolipid metabolism, and amino sugar and nucleotide sugar metabolism. For the A53T αS group, the five most significantly affected metabolic pathways were other glycan degradation, protein digestion and absorption, N-glycan biosynthesis, sphingolipid metabolism, and apoptosis. For the PS + A53T αS group, N-glycan biosynthesis, amino sugar and nucleotide sugar metabolism, apoptosis, biotin metabolism, and the biosynthesis of siderophore group nonribosomal peptides were identified as the five most affected metabolic pathways. Comparisons between the PS + A53T αS and A53T αS groups revealed significant impacts on pathways such as shigellosis, glycosphingolipid biosynthesis (lacto and neolacto series), hypertrophic cardiomyopathy, fluorobenzoate degradation and non-homologous end-joining. These findings further suggest that PS nanoplastics significantly altered the microorganism function in A53T αS-treated mice. Interestingly, all group comparisons highlight alterations in apoptosis, consistent with our findings from ileum terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) results (Fig. [118]2c). In addition, it is noteworthy that the pathways related to LPS biosynthesis and apoptosis were significantly enriched in the PS, A53T αS, and PS + A53T αS groups compared to the PBS mice. LPS and intestinal flora products, coupled with local SIBO-related inflammatory changes, may promote the expression and aggregation of αS in intestinal plexus neurons and other intestinal cells^[119]60. In addition, dysregulation of intestinal flora may lead to increased exposure to various microbial or non-microbial exogenous organisms with pro-inflammatory or neurotoxic effects, potentially resulting in nutritional imbalance^[120]61. These factors can cause neuronal damage or interfere with neuronal sensitivity to damage, thereby affecting the onset and progression of PD^[121]60. Overall, exposure to PS nanoplastics led to an overgrowth of small intestine microbes and an increase in harmful bacteria, particularly Desulfovibrio, which is closely associated with the onset of PD^[122]62–[123]64. Nanoplastics altered the profile of colon microbiota in an A53T αS mouse model To further explore how PS and A53T αS exposure affected gastrointestinal dysfunction, we detected microbial composition in the colon using metagenomic sequencing. A Venn diagram was used to illustrate the number of shared and unique species across the different groups. As shown in Fig. [124]4a, a total of 1402 species were shared across all four groups, while 310, 214, 197 and 233 species were unique to the PBS, PS, A53T αS and PS + A53T αS groups, respectively. The total species count was 2217, 2347, 2145 and 2343 in the PBS, PS, A53T αS and PS + A53T αS groups, respectively (Fig. [125]4b). At the phylum level, variations in gut microbiota composition between groups were analyzed. The relative abundance of each phylum was determined and displayed as an accumulation histogram (Fig. [126]4c). Bacillota and Bacteroidota were the predominant phyla, consistent with findings from the ileal microbiota analysis. However, the relative abundance of Bacillota, Bacteroidota and the ratio of Bacillota/Bacteroidota exhibited negligible differences between the PBS group and the PS, A53T αS, and PS + A53T αS groups (Fig. S[127]4a–c). Furthermore, to evaluate the richness and diversity of the bacterial species, an alpha-diversity analysis (Fig. [128]4d) was conducted. The results revealed negligible changes in Chao1, Simpson and Shannon indices in the PS or A53T αS groups with or without PS-treated mice when compared to the PBS mice. This indicates that the species composition, uniformity, and complexity of the four groups were similar. To estimate the beta-diversity in gut microbiota and visualize the dissimilarity in bacterial composition, we performed an unweighted PLS-DA analysis (Fig. [129]4e). The results showed a significant difference in beta-diversity between the PS + A53T αS-treated mice and the PBS mice, indicating a notable shift in microbial community structure in the presence of both PS exposure and A53T αS expression. At the genus level, we identified the bacterial genera that differed significantly from the PBS group in any of the three groups. The results demonstrated that, with the exception of Akkermansia, the relative abundance of other bacterial genera was minimal, with an average relative abundance of less than 0.5% (Fig. [130]4f–h). Notably, Akkermansia decreased markedly in the A53T αS group compared to the PBS group, while no significant difference was observed between the PBS and PS + A53T αS groups (Fig. [131]4g). Fig. 4. Impact of PS nanoplastics and A53T αS on colon microbiota diversity. [132]Fig. 4 [133]Open in a new tab a Venn diagram illustrating discrepancies in species between the three groups. b Total number of species in each group. c Relative abundance of colon microbiota at the phylum level for each group. d Alpha-diversity indices reflected by the Chao1, Simpson and Shannon indices. Kruskal–Wallis or One-way ANOVA tests calculated P-values at the species or genus level. e Beta-diversity measured by PLS-DA at the genus level. f–h Relative abundance of top significant genus. Unpaired two-tailed Student’s t-tests or Mann–Whitney test was used to conduct classical univariate statistical comparisons among genus measured. To better interpret the functions of these significantly altered bacteria, we performed a functional analysis of KEGG pathway enrichment for all detected microorganisms (Fig. S[134]4d). The analysis revealed that the microorganisms were primarily associated with metabolic functions. It is worth noting that LPS biosynthesis was significantly enriched in the PS and PS + A53T αS groups compared to the PBS mice (Fig. S[135]5a, b), consistent with findings from the ileal microbiota results. These results suggest that gastrointestinal exposure to PS nanoplastics may be associated with an enrichment of LPS-secreting bacterial taxa. Such shifts could plausibly influence gut inflammatory responses, consistent with proposed mechanisms that link microbial dysbiosis to disease progression^[136]65. Nanoplastics altered the profile of fecal metabolites in an A53T αS mouse model Gut metabolites have the strongest association with the gut microbiome^[137]66. An ecological imbalance in this system can deprive the host of the positive regulatory functions of the intestinal flora, thereby exacerbating metabolic disorders^[138]67,[139]68. Metabolic disorders are an important feature of PD^[140]69, but have been largely overlooked by research focused on nanoplastics-PD pathophysiology. With this in mind, we conducted non-targeted metabolomic profiling of feces from the four groups of mice. A total of 5799 metabolites were identified (Fig. S[141]6a), and KEGG pathway classification analysis revealed that these metabolites were primarily enriched in amino acid metabolism, xenobiotics biodegradation and metabolism, lipid metabolism, nucleotide metabolism, and carbohydrate metabolism (Fig. [142]5a). Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) was employed to demonstrate clear differentiation of metabolites in PS nanoplastics and A53T αS-treated mouse ileal contents compared to the PBS group (Fig. [143]5b). The absolute change ratio of metabolites was >1.2 with a P-value < 0.05, suggesting significant changes in metabolites between the groups. Enrichment analysis of metabolic pathways was conducted using a topological analysis based on the KEGG database, and the significance of each pathway was evaluated by topological impact values. Metabolites were observed to be both up- and down-regulated in all groups (Figs. [144]5c, S[145]6b). Specifically, 257 metabolites showed significant differences between the PS nanoplastics and PBS groups, 114 metabolites differed significantly between the A53T αS and PBS groups, and 210 metabolites showed significant differences between the PS + A53T αS and PBS groups. In addition, 161 metabolites differed significantly between the PS + A53T αS and A53T αS groups (Fig. [146]5c, d). The Venn diagram highlighted 14 overlapping metabolites across the treatment groups (Fig. S[147]6c). Fig. 5. PS nanoplastics and A53T αS altered the profiles of fecal metabolites. [148]Fig. 5 [149]Open in a new tab a KEGG pathway enrichment analysis of all detected metabolites. The horizontal axis represents the number of metabolites in the KEGG annotation entries, and the vertical axis displays the enriched pathways. b PLS-DA showing distinct clustering of the treatment groups (PS nanoplastics, A53T αS, PS + A53T αS) relative to control, indicating significant alterations in metabolite profiles. c Volcano plots depicting differentially expressed metabolites. Significant differentially expressed metabolites between each comparison group were selected using the following criteria: P-value < 0.05 and absolute fold change >1.2. d, e Representative differential metabolites in the gut microbiota of mice. f KEGG analysis showing distinct metabolomic profiles of mouse feces across various treatment groups. Dot sizes represent the numbers of enriched proteins. g Representative HE-staining images of the liver in mice six months post-injection with PBS, PS nanoplastics or A53T αS. Scale bar: 200 μm. Unpaired two-tailed Student’s t-tests or Mann–Whitney test was used to conduct classical univariate statistical comparisons among metabolites measured. Key metabolites including phenylacetylglycine, 7-ketodeoxycholic acid, phosphoglycolic acid, prostaglandin E2-1-glyceryl ester, blood platelet activating factor-acether, psychosine, and docosatrienoic acid, were significantly changed in the PS mice compared to the PBS mice (Fig. [150]5d). In the PS + A53T αS mice, metabolites such as cytidine diphosphate (CDP), eicosatetraynoic acid, glycodeoxycholic acid, L-glutamic acid 5-phosphate, 6-hydroxycaproic acid, sulfur dioxide, fructoseglycine and 5-hydroxyindole showed significant alterations (Fig. [151]5e). As reported, several of these metabolites, phenylacetylglycine, 7-ketodeoxycholic acid, glycodeoxycholic acid, L-glutamic acid 5-phosphate, 6-hydroxycaproic acid, fructoseglycine and 5-hydroxyindole have been associated with liver disease. The liver is one of the most important organs for maintaining systemic metabolic homeostasis, and recent studies have suggested that impaired liver function may exacerbate the progression of PD^[152]69,[153]70. In addition, metabolites such as prostaglandin E2-1-glyceryl ester, docosatrienoic acid, CDP, eicosatetraynoic acid and 5-hydroxyindole are associated with inflammation or immune response, while phosphoglycolic acid, sulfur dioxide, and blood platelet-activating factor-acether are closely related to gastrointestinal function. Notably, 5-hydroxyindole has been reported to be associated with neurological disorders, with elevated levels linked to depressive and anxious behaviors. Aminoadipic acid, on the other hand, is associated with muscle atrophy. The above metabolic perturbations identified in the PS-associated groups appear to align with known pathways linked to PD pathogenesis, although their direct mechanistic contribution to PD pathology remains to be fully elucidated through targeted functional analyses. Meanwhile, the KEGG analysis of different comparison groups is shown in Fig. [154]5f. Studies have demonstrated that the gut microbiota produces large amounts of metabolites by breaking down and metabolizing various nutrients, which in turn maintain host homeostasis and physiology by affecting the gut microbiota^[155]71. KEGG pathway enrichment analysis showed that the differential metabolites of the PS and A53T αS groups compared with the PBS group were commonly enriched in drug metabolism-cytochrome P450 pathways and hepatocellular carcinoma pathways. These results suggest that PS nanoplastics or A53T αS may affect cytochrome P450 function. The cytochrome P450 enzyme, along with its metabolic substrates and products, plays an important role in the pathogenesis and treatment of central nervous system diseases, including AD and PD^[156]72. Moreover, these pathways are closely linked to liver function^[157]73. The differential metabolites between the PS + A53T αS and the PBS group were enriched on drug metabolism-other enzymes and biosynthesis of amino acids (Fig. [158]5f). It is worth noting that the differential metabolites of the PS and the A53T αS groups compared with the A53T αS group were enriched commonly in drug metabolism-cytochrome P450 pathway and drug metabolism-other enzymes. This indicates that the administration of PS nanoplastics altered the profile of fecal metabolites in the A53T αS mouse model. The identified pathways appear linked to liver function, and preliminary evidence suggests that nanoplastic exposure may alter gut microbial composition and increase toxic metabolite production. These microbial imbalances could exacerbate intestinal and hepatic injury, as well as metabolic dysregulation, consistent with the hypothesized crosstalk between gut microbiota and liver homeostasis^[159]74. PS nanoplastic exposure aggravated hepatic damage The gut microbiota plays a crucial role in maintaining the physiological functions of the liver, including bile acid synthesis and uptake, liver immune regulation, and metabolism^[160]75–[161]78. At the same time, microbial imbalance can influence the progression of liver diseases^[162]79–[163]81. Furthermore, the gut microbiota exhibits dynamic changes as diseases develop, such as steatosis, steatohepatitis, and hepatocellular carcinoma^[164]65,[165]82–[166]85. Long-term transplantation of the microbiota from obese nonalcoholic fatty liver disease (NAFLD) mice induced similar pathological changes in the liver^[167]86. Additionally, the gut microbiota has been reported to participate in methamphetamine-induced liver inflammation by disrupting the homeostasis of bile acids^[168]87. As one of the key metabolic organs, the dysregulation of liver-related physiological processes has been linked to PD pathophysiology^[169]69,[170]88. To further confirm liver damage caused by PS exposure, HE staining was performed. Histopathological examination showed that PS nanoplastics induced inflammatory cell infiltration in liver tissue (Fig. [171]5g). However, the effect of PS nanoplastics on liver cell apoptosis appeared negligible, as indicated by the TUNEL-positive staining in the upper duodenum of mice (Fig. S[172]7). While preliminary trends were observed, no statistically significant direct correlations were found between gut microbiota alterations and hepatic inflammation. Nonetheless, these findings raise the possibility that gut microbiota changes may interact with PS nanoplastics-induced hepatic injury, though further mechanistic studies are necessary to establish a definitive link. PS nanoplastic exposure aggravated brain damage Braak et al. contended that αS pathology could spread in a stereotypical manner via the vagus nerve, propagating from the gastrointestinal tract to the midbrain^[173]89,[174]90. Previous studies^[175]91,[176]92 further supported this hypothesis, demonstrating αS spread from the gastrointestinal tract to the brain in mice and rats. In addition, our previous immunofluorescence data revealed that PS nanoplastics promoted the entry of A53T αS into the brain within 7 days after injection^[177]33. To further demonstrate central αS pathology in connection with the gut-brain axis, we conducted a mass spectrometry analysis of mouse brain tissues. As shown in Fig. S[178]8a, no interference was detected in the PBS or PS group. Notably, the levels of A53T αS species were significantly elevated in the PS + A53T αS mouse brains (Fig. S[179]8b). These results suggest that nanoplastics may facilitate the translocation of A53T αS into the brain. Moreover, elevated IL-6 and LPS levels were observed in the brain tissues (Fig. S[180]9), indicating sustained neuroinflammation. These findings were consistent with our ileal and colonic microbiome data, which showed that exposure to PS nanoplastics or A53T αS promoted the proliferation of LPS-producing bacteria. Collectively, the results support the upregulation of inflammatory mediators in neural tissue. Gut exposure to PS nanoplastics may exacerbate brain damage, potentially by facilitating αS uptake and triggering neuroinflammatory responses. Discussion Notably, the mechanistic basis by which PS nanoplastics influence gut-brain axis pathology—particularly through molecular signaling cascades such as enteric glial cell activation and accelerated αS aggregation—has been comprehensively investigated in a complementary study^[181]33. That study demonstrated the pivotal role of inflammasome activation in mediating gut-derived inflammation that contributes to dopaminergic neuron loss. Its findings offer essential mechanistic support for the pathological and functional outcomes observed in the current study across the gut, liver, and brain. These current findings (Fig. [182]6) support the growing understanding that PD is not only a neurodegenerative disorder but also closely related to gastrointestinal and metabolic dysfunction^[183]34,[184]35. Specifically, we have found that long-term exposure to PS nanoplastics significantly disrupted intestinal homeostasis, induced microbial dysbiosis, and altered metabolic profiles in an A53T αS mouse model (Figs. [185]2, [186]3, [187]6). These disruptions, collectively, highlight a critical role of the gut-liver-brain axis in PD pathogenesis and underscore nanoplastics as an aggravating environmental factor to the disease. Fig. 6. [188]Fig. 6 [189]Open in a new tab Schematic summary of PS nanoplastic-induced disruptions along the gut-liver-brain axis and their relevance to PD pathology. The decrease in ileal goblet cells and epithelial apoptosis (Fig. [190]2) indicates compromised intestinal barrier integrity, which may promote systemic inflammation and facilitate the translocation of microbial products, such as LPS. The overrepresentation of Desulfovibrio, a genus associated with H₂S production and αS aggregation, suggests that microbial shifts induced by nanoplastics could influence PD pathology (Fig. [191]3). This interpretation of the pathogenic nature of Desulfovibrio expansion is in good agreement with prior reports linking Desulfovibrio with PD severity^[192]62,[193]64. Moreover, our metagenomic analyses revealed significant enrichment of pathways related to apoptosis and LPS biosynthesis, both in the ileum and colon (Fig. [194]4). These findings further link microbial alterations to gut inflammation and epithelial dysfunction. While alpha-diversity changes were significant in the ileum, only beta-diversity differed notably in the colon, suggesting site-specific responses to PS nanoplastics. Our fecal metabolomic profiling (Fig. [195]5) provided additional insights into the metabolic stress induced by PS exposure. Disturbed metabolites involved in pyrimidine metabolism and cytochrome P450 activity converged to an association between microbiota alterations and hepatic metabolism. Notably, several metabolites altered by nanoplastic exposure, such as glycodeoxycholic acid, eicosatetraynoic acid and 5-hydroxyindole, have been implicated in liver dysfunction, inflammation, and neurological disorders^[196]93–[197]95. The metabolomic profiling revealed distinct alterations in key metabolites across experimental groups, which provided critical insights into potential mechanisms linking PS nanoplastic exposure and A53T αS overexpression to PD pathology. In the PS group, metabolites such as phenylacetylglycine (PAG, P < 0.01, Student’s t-test), 7-ketodeoxycholic acid (P < 0.05, Student’s t-test) and psychosine (P < 0.05, Student’s t-test) were significantly altered (Fig. [198]5d). The elevated PAG levels observed in PS nanoplastics-exposed mice may signify compromised hepatic detoxification. PAG is synthesized in the liver via glycine conjugation of phenylacetate, a gut microbiota-derived metabolite^[199]96. Its accumulation often reflects impaired hepatic glycine-N-acyltransferase activity due to liver injury^[200]97. Furthermore, PAG is a gut microbial-host co-metabolite derived from phenylalanine catabolism and a biomarker of cardiovascular disease^[201]98. As a secondary bile acid derivative, 7-ketodeoxycholic acid is synthesized via gut microbiota-dependent modification of primary bile acids. Bile acids act as signaling molecules modulating gut-brain communication; their dysregulation may impair intestinal barrier integrity^[202]99, facilitating the translocation of pro-inflammatory microbial products (such as LPS) that propagate neuroinflammation and αS pathology. Psychosine, a sphingolipid, is recognized for its involvement in diverse pathological mechanisms across neurological disorders^[203]100. Elevated psychosine is mechanistically linked to PD and other neurological disorders through its role in lysosomal dysfunction and αS pathogenesis^[204]101. Collectively, our metabolomic profiling highlighted PS nanoplastics-induced dysregulation of key metabolites linked to PD pathology. PS nanoplastics may perturb gut-liver-brain axis interactions, potentially exacerbating lysosomal damage and neuroinflammation processes implicated in PD pathogenesis. In the PS + A53T αS group, CDP (P < 0.05, Mann–Whitney U test), glycodeoxycholic acid (GDCA, P < 0.05, Student’s t-test) and sulfur dioxide (SO[2], P < 0.05, Student’s t-test) showed significant alterations (Fig. [205]5e). CDP, a central intermediate metabolite in phospholipid and nucleotide biosynthesis^[206]102, supports neuronal membrane integrity and mitochondrial energy homeostasis^[207]103. Its depletion could impair synaptic vesicle formation and exacerbate ATP deficiency, synergizing with αS-induced mitochondrial dysfunction. Additionally, CDP deficiency may signal hepatic metabolic stress, potentially linking gut-liver axis dysregulation to neurodegeneration via systemic antioxidant depletion^[208]104. While these mechanisms are plausible, further studies are needed to establish direct causal links between CDP levels and PD pathology. GDCA, a secondary bile acid synthesized conjugation of deoxycholic acid, serves as a key activator of FXR and TGR5 receptors that regulate inflammation^[209]105,[210]106. Its depletion in the PS-exposed mice suggests compromised hepatic bile acid secretion, a hallmark of chronic liver disease. PS nanoplastics-induced GDCA reduction highlights a novel pathway linking hepatic metabolic dysfunction to PD progression via gut-liver-brain crosstalk. SO₂, generated via microbial degradation of sulfur-containing amino acids, is a double-edged molecule: at physiological levels, it modulates redox signaling^[211]107, but excess SO₂ induces oxidative stress, DNA damage and inflammatory response^[212]108. Oxidative stress and inflammation play an important role in the degeneration of dopaminergic neurons in PD; therefore, PS nanoplastic-induced SO[2] increase may represent an indirect promotion of PD progression through inflammatory and oxidative processes. Additionally, our histopathological examination confirmed that PS nanoplastics-induced hepatic inflammation (Fig. [213]5). While TUNEL staining did not show increased apoptosis in liver tissues, infiltration of inflammatory cells suggests an early stage of hepatic stress. This inflammation may further exacerbate PD-related metabolic dysfunction via the gut-liver axis. Emerging studies highlight dose-dependent neurotoxic effects of PS nanoplastics. In mouse models, oral PS nanoplastics (50 nm, 0.25–250 mg/kg/day) induced PD-like neurodegeneration after 28 days of exposure, even at a dose of 2.5 mg/kg^[214]30. In another study, orally taken PS nanoplastics (50 nm, 0.5–50 mg/kg/day) induced neuron damage and microglial activation in the mouse brain at doses as low as 10 mg/kg after 7 days of exposure^[215]109. The thresholds may vary by particle size and surface charge: cationic PS nanoplastics elicited greater neurotoxicity than anionic counterparts^[216]110, as they entailed electrostatic attractions with cell membranes to promote their uptake^[217]111. Anionic nanoplastics, in comparison, can harness both transcellular and paracellular transport mechanisms, alongside their heightened capability to achieve systemic circulation and effectively cross biological barriers^[218]3. The nanoplastic exposure level used in this study (2 mg/kg every other day) reflects environmentally relevant doses, consistent with recent reports of nanoplastics found in human blood, lungs, placenta, and brain tissue^[219]27. The observed disruption to the gut-liver-brain axis suggests that even low-dose exposure may pose systemic risks. Vulnerable populations, including individuals with neurological or metabolic conditions and children, may therefore face heightened impacts from nanoplastic exposure. In light of the prevalence of plastics, regulatory action and alternatives are crucial to overcome the long-term consequences of these invasive environmental toxins. Potential confounding factors warrant consideration. First, systemic toxicity induced by prolonged nanoplastic exposure could independently contribute to both gut and liver pathologies, complicating the attribution of observed effects solely to PD-pertinent mechanisms. Second, general inflammatory responses triggered by exogenous nanoplastics may non-specifically influence host metabolism and tissue integrity, thereby amplifying pathological readouts irrespective of the PD context. Third, while our study highlighted gastrointestinal pathology, it remains unclear whether the observed hepatic effects stemmed directly from gut dysbiosis or represented broader systemic manifestations of nanoplastic toxicity. Fourth, although this study focused on PS nanoplastics, the physicochemical diversity of environmental nanoplastics suggests that variations in plastic composition, charge, or size/molecular weight could entail distinct toxicological profiles; the lack of comparative exposure controls using inert or compositionally distinct plastic particles limits our ability to generalize findings. While the PS nanoplastics used here are environmentally relevant, future studies employing polyethylene, polyamide, or charge-neutral particles—as well as larger microplastic controls—will be critical to differentiate PD-related pathway effects from general nanoplastic toxicity. Such comparisons will also help clarify the specificity of gut-liver-brain axis perturbations attributed to PS nanoplastics. Finally, previous studies have highlighted sex-based differences in both PD pathology and gut microbiome composition^[220]112. Although our study included subjects of both sexes, the relatively small sample size within each sex group limits the ability to draw robust conclusions about sex-specific effects. Future investigations should specifically address this gap by employing larger, sex-balanced cohorts to systematically evaluate the role of sex in nanoplastic-induced pathology and PD-related mechanisms. Additionally, the single time-point design of our experiment limits the ability to establish temporal relationships between nanoplastic exposure and pathophysiological changes, thereby preventing definitive conclusions about the sequence or progression of the observed effects. Furthermore, while our analyses identified significant correlations (e.g., between LPS and αS levels, or specific microbial taxa and PD-like pathology), the absence of functional intervention studies (such as antibiotic treatments or targeted metabolite antagonism) precludes causal inference regarding these associations. These limitations underscore the need for future longitudinal studies tracking exposure dynamics and incorporating targeted interventions (pharmacological modulation, microbiota depletion) to experimentally dissect the causal mechanisms underlying the observed correlations and the role of nanoplastics in disease pathogenesis. Methods Main reagents A53T α-synuclein (αS) protein (active sequence shown in Fig. [221]1a) was acquired from QYAOBIO (ChinaPeptides Co., Ltd., China). PS nanoplastics (50 mg/mL, 50 nm) were sourced from Mreda (Beijing Mreda Technology Co., Ltd., China). Characterizations of PS nanoplastics TEM analysis was performed using a Hitachi HT7800 electron microscope, operated at 80 kV. Specifically, a 5 μL sample solution was applied to a copper grid (Zhongjing Keyi Thin Film Technology Co., Ltd., China), allowed to absorb for 10 min and with the excess fluid removed. The samples were then air-dried and examined by TEM. FTIR of the nanoplastics, set for the spectral range of 600–3600 cm⁻¹, was performed using an IRTracer-100 spectrometer (Shimadzu, Japan)^[222]113. ^1H NMR spectra of the nanoplastics were recorded on a Bruker AV 500 M (500 MHz) spectrometer using chloroform-D (CDCl[3]) as the solvent. Animal study Detailed setup of the animal experiments can be found in our earlier work^[223]33. All experimental protocols received approval from the Institutional Animal Care and Use Committee (IACUC) of the Center for Nano-Biology Safety Evaluation and Research under the GBA National Institute for Nanotechnology Innovation in Guangzhou, China (Approval No. IA-T2250710182-03). All animal experiments complied with ARRIVE guidelines. The working concentration of PS nanoplastics was 10 mg/mL for injection and 0.5 mg/mL for oral administration, respectively. The A53T αS solution was prepared at 2.5 mg/mL for injection. All animal models were established through intestinal injection on day one. The study utilized 13-week-old C57BL/6J mice (50% male and 50% female) obtained from The RUIYE Laboratories (Guangzhou, China). After laparotomy, injections were performed using a 10 μL syringe at three locations in the pyloric stomach wall and three sites in the upper duodenal wall, specifically targeting regions near the myenteric plexus. Six injection sites received a combined volume of 20 μL. Control mice received equivalent volumes of PBS at the same sites. After completing the injections, the abdominal surgical wounds were sutured. Antibiotic ointment was applied daily to the surgical sites until complete healing was achieved. After three months, mice in the PS and PS + A53T αS groups were administered with nanoplastics (2 mg/kg body weight) via oral gavage every other day for three months. The other group received an equivalent volume of PBS. After six months’ exposure to PS nanoplastics, all mice were anesthetized and then euthanized by cervical dislocation. The organs and ileal/colonic contents were collected for various analyses. 16S rRNA sequencing analysis Ileal contents were collected immediately into sterile tubes on dry ice and stored at −80 °C. Microbial genomic DNA was isolated, and its concentration was determined by a Qubit Fluorometer (Thermo Fisher Scientific). The sample quality was assessed using agarose gel electrophoresis. The polymerase chain reaction (PCR) reaction system was configured with 30 ng of qualified genomic DNA samples and corresponding fusion primers. PCR amplification was performed using the Agencourt AMPure XP magnetic field. The PCR amplified products were purified by beads and dissolved in elution buffer, labeled, and the library was completed. The fragment range and concentration of the library were examined using an Agilent 2100 Bioanalyzer. Qualified libraries were sequenced according to the size of the inserted fragments. Gut microbiota composition Colonic contents were collected into stool specimen collection tubes, flash-frozen on dry ice and stored at −80 °C until analysis. Microbial genomic DNA was extracted, and its concentration was measured by a Qubit Fluorometer (Thermo Fisher Scientific). DNA quality was assessed via agarose gel electrophoresis. Paired-end 150 (PE150) sequencing was performed using the MGISEQ-2000 platform. Clean reads were assembled using MEGAHIT software, filtering out fragments shorter than 300 bp. Statistical analysis and subsequent gene prediction were then performed. Data analysis of ileal contents The number of OTUs and unique genera shared among the four groups were analyzed and visualized using a Venn diagram, highlighting cohort-specific microbial signatures. Differences in bacterial complexity between samples were analyzed using PLS-DA (Clusters indicate clear separations between groups). Alpha-diversity was assessed using the Chao index (P < 0.05, One-way ANOVA test for multiple groups, Student’s t-test for two groups), while beta-diversity, reflecting the similarity of the microbial communities, was evaluated using PCoA (P < 0.05, PERMANOVA) based on unweighted UniFrac distances. KEGG analysis was performed to predict the abundances of functional categories. Data analysis of colonic contents A Venn diagram was used to analyze the number of shared species and unique genera among the four groups. Alpha-diversity analysis was assessed through Chao1, Simpson and Shannon indices. Beta-diversity, reflecting the similarity of the microbial communities, was analyzed using PLS-DA. KEGG analysis was conducted to predict the abundances of functional categories. Metabolomic analysis Approximately 25 mg of fecal samples were weighted and mixed with a methanol/acetonitrile/water solution (800 μM, 2:2:1, v/v). The mixture was ground at 50 Hz for 5 min and centrifuged at 25,000 × g and 4 °C for 15 min. The supernatant was freeze-dried, re-dissolved in 120 μL of methanol/water (1:1, v/v), and centrifuged at 25,000 × g and 4 °C for 15 min. The final supernatant was used for ultra-high-performance liquid chromatography (Waters, USA) coupled with tandem Q Exactive HF spectrometry (Thermo Fisher Scientific, USA). Chromatographic conditions: Sample separation was performed on a BEH C18 column (1.7 μm, 2.1 × 100 mm, Waters, USA). The mobile phase for positive ion mode consisted of a water solution containing 0.1% formic acid (Solution A) and methanol with 0.1% formic acid (Solution B). For negative ion mode, the mobile phase consisted of a water solution containing 10 mM ammonium formate (Solution A) and 95% methanol with 10 mM ammonium formate (Solution B). The elution gradients used were: 0–1 min, 2% Solution B; 1–9 min, 2–98% Solution B; 9–12 min, 98% Solution B; 12–12.1 min, 98% Solution B to 2% Solution B; 12.1–15 min, 2% Solution B. The flow rate was 0.35 mL/min, the column temperature was 45 °C, and the injection volume was 5 μL. Mass spectrometry (MS) conditions: A Q Exactive HF mass spectrometer (Thermo Fisher Scientific, USA) was used for acquiring MS1 and MS2 data. The mass spectrometry scan range was 70–1050 m/z, with an MS1 resolution of 120,000 and a maximum injection time (IT) of 100 ms. The top 3 precursors were selected for fragmentation based on their intensity, with MS2 data collected at a resolution of 30,000 and a maximum IT of 50 ms. The fragmentation energy (stepped normalized collision energy) was set to 20, 40, and 60 eV. The ion source (electrospray ionization) parameters were configured as follows: sheath gas flow rate of 40, auxiliary gas flow rate of 10, spray voltage of 3.80 kV for positive ion mode and 3.20 kV for negative ion mode, capillary temperature of 320 °C, and auxiliary gas heater temperature of 350 °C. Intestinal tissue sampling All gut tissues were cut open and washed with sterile PBS buffer (Yeasen, China) until the solution was clean and colorless (approximately 3 to 4 washes). After washing, each intestinal tissue sample was divided into two parts, one was immediately fixed with 4% paraformaldehyde and stored at a 4 °C, while the other was placed in a sterile centrifuge tube, immediately frozen in liquid nitrogen and stored at −80 °C for further analysis. HE staining The tissue sections were initially deparaffinized and rehydrated before staining with Harris’s hematoxylin reagent for 8 min. Sections were decolorized in 0.5% acid-alcohol for 3 s and rinsed with running tap water, followed by counterstaining with 0.5% eosin for 2 min. After dehydration with alcohol and xylene, the slides were examined by a pathologist. TUNEL assay After dewaxing, hydration and antigen recovery, tissue sections were treated with 3% hydrogen peroxide for 25 min to inhibit endogenous peroxidase activity. Mouse intestinal sections were incubated with 20 μg/mL DNA-free enzyme K solution (Yeasen, China) for 20 min and washed three times with PBS. Each section was covered with 50 μL TUNEL staining solution (Yeasen, China) and incubated at 37 °C in darkness for 1 h, followed by 3 PBS washes. Then the sections were stained with DAPI (Yeasen, China) for 10 min and washed with PBS 3 times. Images were obtained by fluorescence microscopy (Ex: 488 nm, Em: 525 nm). Endotoxin detection After centrifugation (20,000 × g, 20 min), the supernatant of PS nanoplastics was collected to determine the endotoxin levels using a LAL kit (Xiamen Bioendo Technology Co., Ltd., China). All procedures followed the manufacturer’s instructions. ELISA assay Whole-brain proteins were extracted using RIPA strong lysis buffer (Yeasen, China). The homogenate was centrifuged at 3000×g for 10 min at 25 °C and the supernatant was collected. Afterward, LPS and IL-6 levels were determined using commercial IL-6 and LPS ELISA kits (LunChangShuoBiotech, XiaMen) according to the manufacturer’s protocols. Brain detection of A53T αS Total brain proteins were isolated using RIPA lysis buffer (Yeasen, Shanghai). Each 300 μL protein aliquot was mixed with 300 μL of 50 mM aqueous ammonium bicarbonate and incubated at 90 °C for 30 min. Subsequently, 100 μL of 100 mM dithiothreitol was added, and the samples were heated at 60 °C for 1 h. Samples were then individually treated with 100 μL of 100 mM iodoacetamide, followed by incubation in the dark at room temperature for 30 min. Afterward, the samples were digested overnight at 37 °C with 200 μL sequencing-grade trypsin (0.2 μg/μL; Promega, USA). Reactions were halted using 2 μL formic acid. After lyophilization, samples were dissolved in 0.1% aqueous formic acid, centrifuged at 10,000 × g for 5 min at 25 °C, and desalinated prior to LC–MS/MS analysis. Chromatographic separation was performed on a Waters ACQUITY UPLC BEH C18 column [2.1 × 50 mm, 1.7 μm] equilibrated with 0.2% formic acid and acetonitrile solution at a flow rate of 0.3 mL/min. Mass spectrometry analysis was conducted in positive-ion multiple reaction monitoring. The A53T αS peptide TVEGAGSIAAATGFVK (739.9/173.1 m/z) was detected at a retention time of 2.3 min. Statistical analysis Statistical analyses were performed using GraphPad Prism 9.0 (GraphPad Software, USA), with continuous variables expressed as mean ± standard deviation (SD). Normality of datasets was rigorously assessed via the Shapiro–Wilk or Kolmogorov–Smirnov test (α = 0.05). For normally distributed data (P ≥ 0.05), intergroup differences were assessed using unpaired two-tailed Student’s t-tests, preceded by Brown-Forsythe or Bartlett’s test to verify homogeneity of variance (α = 0.05). Datasets violating normality (P < 0.05) or homogeneity of variance (P < 0.05) were analyzed using nonparametric Mann–Whitney U tests or Welch’s corrected t-tests, respectively. Multi-group comparisons adhered to parametric one-way ANOVA or nonparametric Kruskal–Wallis tests based on normality and homogeneity of variance outcomes. Supplementary information [224]Supplementary Information^ (3.9MB, docx) [225]Supplementary Information^ (1.1MB, xlsx) Acknowledgements