Patients with PSP (n = 56) aged > 50 years were recruited from the Department of Neurology at the First Affiliated Hospital of Zhengzhou University. Diagnoses of probable or possible PSP were made according to the MDS criteria by experienced specialists in neurodegenerative diseases who were unaware of laboratory results (Höglinger et al., 2017). Age- and sex-matched healthy controls (HCs) (n = 56) with no history of neurodegenerative disease were recruited from the Physical Examination Center of the First Affiliated Hospital of Zhengzhou University. The exclusion criteria for both groups were as follows: (1) use of antibiotics or immunosuppressants within 3 months prior to sample collection; and (2) complications such as recent or persistent inflammatory diseases, autoimmune diseases, or malignant tumors. The participants underwent a detailed clinical interview and a complete neurological examination. Demographic and clinical information, including age, sex, stroke risk factors, disease duration, and years of education were collected at the time of sampling. Participants underwent a physical examination and a battery of laboratory tests, including routine blood tests for coagulation, C-reactive protein (CRP), blood glucose and lipids, liver and kidney function, and homocysteine, as well as carotid ultrasound and MRA. Disease severity was assessed using the modified Hoehn and Yahr (H&Y) staging scale (Goetz et al., 2004), a Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale, Part III (UPDRS-III) (Goetz et al., 2008), and the Progressive Supranuclear Palsy Rating Scale (PSPRS) (Golbe and Ohman-Strickland, 2007). The Mini-Mental State Examination (MMSE) (Folstein et al., 1975) was used to assess cognitive performance. This study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University (2024-KY-0046-002), and informed consent was obtained from each participant.

Peripheral blood samples were collected in endotoxin-free K2 EDTA 10-mL tubes after overnight fasting. The samples were immediately placed on ice and centrifuged at 2,000 rpm for 10 min at 4°C to obtain plasma samples. These samples were then stored at −80°C until biochemical analysis if immediate detection was not possible.

To assess carotid atherosclerosis, we examined the bilateral carotid arteries of all participants using color Doppler ultrasound with a 7.5 MHz linear probe (GE Healthcare, Horten, Norway). Max-CIMT is the mean of the maximum left and right carotid intima-media thicknesses, which is defined as the distance from the luminal intimal interface to the medial-adventitial interface in a plaque-free area located 1–1.5 cm below the level of the distal branches of the common carotid artery. Carotid plaque was defined as a focal area of wall thickening or protrusion within the arterial lumen of any carotid artery segment (common carotid artery, bifurcation, and internal and external carotid arteries) greater than 50% of the surrounding wall thickness. Maximum carotid plaque thickness (max-CPT) (Walker et al., 2009) was measured at the most prominent point of the plaque in the multi-angle image of the carotid artery or at the maximum wall thickness in the absence of carotid plaques. The total carotid plaque number (TPN) was calculated as the sum of all plaque numbers in the common carotid artery as well as the internal and external carotid arteries. The carotid plaque score (CPS) was calculated using ultrasound according to the methodology used in the prospective ACE 1950 (Akershus Cardiac Examination 1950 study) (Ihle-Hansen et al., 2018). Each side of the carotid artery was divided into the following four segments: common carotid artery, carotid bifurcation, internal carotid artery, and external carotid artery. Plaque measurements were taken in cross-sections for each segment, and the thickness of the largest plaque in each segment was recorded and scored according to maximum diameter (plaque diameters of ≥1.5, ≥2.5, and ≥3.5 mm were scored 1, 2, and 3, respectively), with occluded segments scored as 3. Finally, the scores for all the segments on both sides were summed to obtain an overall CPS ranging from 0 to 24. The percentage of maximal stenosis (stenosis%) was calculated by measuring the residual luminal internal diameter at the site of maximal stenosis and the original internal diameter, then dividing the difference by the original internal diameter (Liu et al., 2022). The operator was blinded to the medical histories of the participants.

All MRA scans were performed using a 3 Tesla magnetic resonance imaging (MRI) scanner (Siemens Healthcare, Erlangen, Germany). MRI of intracranial arteries using three-dimensional time-of-flight gradient echo to determine the vascular territory and extent of intracranial stenosis (ICS). We recorded the number of participants with stenosis and the degree of stenosis at the narrowest point in each of the 11 predefined vascular territories, including the left and right internal carotid arteries (ICA), left and right middle cerebral arteries (MCA), left and right anterior cerebral arteries (ACA), left and right posterior cerebral arteries (PCA), left and right vertebral arteries (VA), and basilar arteries (BA). Using the criteria established in the Warfarin-Aspirin Symptomatic Intracranial Disease Trial, the degree of stenosis of the intracranial arteries was graded into five levels: 0 (normal; no detectable stenosis), 1 (mild; <50% stenosis), 2 (moderate; 51%–70% stenosis), 3 (severe; 71%–99% stenosis), and 4 (occlusion) (Samuels et al., 2000). The total score for the intracranial arteries was calculated as the global stenosis score (GSS), and the degree of stenosis was determined by the consensus of at least two neurologists.

C57BL/6J male mice were obtained from the Experimental Animal Center of Zhengzhou University. The mice were housed on a 12-h light/dark cycle with ad libitum access to food and water. Each mouse received 3–7 g/day of food and 4–7 mL/day of purified water. All procedures were performed in accordance with the Guide for the Care and Use of Laboratory Animals. The Ethics Committee of the First Affiliated Hospital of Zhengzhou University approved the study protocol and procedures (2024-KY-0046-002).

Recombinant mouse tau monomers with four structural domains (CSB-YP013481MO, CUSABIO, Wuhan, China) were co-incubated with heparin at a concentration of 1 mg/mL in a buffer (10 mM HEPES, pH 7.4, 100 mM NaCl, 5 mM dithiothreitol) (Frost et al., 2009). The mixture was shaken at 1,000 rpm for 10 days at 37°C to obtain tau-PFFs. After fragmentation using an ultrasonic crusher, the PFFs were stored at −80°C for backup.

At 6–8 weeks of age, mice (12 per group) received tail vein injections every 2 weeks with either 5 μg of tau-PFFs (25 μL, 0.2 mg/mL) or an equal volume (25 μL) of sterile phosphate-buffered saline (PBS) as a control. Tissues were harvested 3 months after the first injection. Following anesthesia via intraperitoneal injection of pentobarbital (10 mg/mL, 50 mg/kg), mice were euthanized for sample collection. Blood (0.5 mL) was obtained from the right ventricle of mice. Fresh blood (0.5 mL per mouse) from 6 mice per group immediately subjected to flow cytometry analysis, and the blood samples (0.5 mL per mouse) from the remaining 6 mice centrifuged at 3,500 rpm for 15 min to collect plasma for storage at −80°C and subsequent ELISA. All mice then underwent PBS perfusion. Aortic arches were carefully dissected, with 6 fresh specimens per group flash-frozen in dry ice for Western blot analysis and the others fixed in 4% paraformaldehyde for frozen sectioning.

Aortic tissues were fixed in 4% paraformaldehyde (PFA) for 24 h at 4°C, then cryoprotected by immersion in 30% sucrose solution (w/v in PBS) for an additional 24 h at 4°C until the tissues sank to the bottom of the vial. Samples were embedded in optimal cutting temperature (OCT) compound (Tissue-Tek, Sakura Finetek, USA), rapidly frozen on dry ice, and stored at −80°C until sectioning. For histopathological analysis, 20 μm-thick frozen sections were cut using a cryostat (Leica CM1950, Germany) at −20°C, mounted onto poly-L-lysine-coated glass slides, and air-dried for 1 h at room temperature. Sections were subsequently stained with hematoxylin and eosin (H&E) or Oil Red O (Solarbio, Beijing, China) according to the manufacturer’s protocols. For immunohistochemistry, frozen tissue sections were peroxidase blocked, followed by blocking with normal goat serum for 1 h. Subsequently, they were incubated with CD68 primary antibody (ab955, Abcam, 1:500, mouse) overnight at 4°C. After rinsing with PBS, the sections were incubated with horseradish peroxidase-conjugated secondary antibodies (ab6789, Abcam, 1:500) for 2 h at room temperature. The sections were then washed thrice for 5 min each and stained with 3,3′-diaminobenzidine. The images were captured using a DP74 camera (Olympus, Tokyo, Japan).

Fresh aortic tissue was isolated, snap-frozen with solid carbon dioxide, and homogenized in RIPA lysis buffer containing a protease inhibitor mixture (Beyotime, Shanghai, China). Homogenized fractions were centrifuged at 120,000 g for 30 min at 4°C, and the supernatant was collected. Fractions of 10 μL were separated by electrophoresis on 8% or 12% polyacrylamide gels and blotted onto polyvinylidene fluoride membranes (Millipore, Darmstadt, Germany). The membranes were blocked with 5% non-fat dry milk in TBST (Tris-buffered saline, containing 0.1% Tween-20) for 1 h at room temperature and then incubated overnight at 4°C in TBST diluted with primary antibodies. After several rinses with TBST, the membranes were incubated with horseradish peroxidase-conjugated secondary antibodies for 1 h at room temperature. Finally, the membranes were detected using enhanced chemiluminescence (Thermo Fisher Scientific). Protein expression levels were normalized to GAPDH expression levels and analyzed using the ImageJ software (v1.53, National Institutes of Health, USA).

The primary and secondary antibodies used were as follow: CD68 (ab955, Abcam, 1:500, mouse), Tau (MN1000, Invitrogen,1:500, mouse), interleukin-1beta (IL-1β, ab200478, Abcam, 1:500, rabbit), tumor necrosis factor-alpha (TNF-α, 17590-1-AP, Proteintech, 1:500, rabbit), interleukin-6(IL-6, DF6087, Affinity, 1:500, rabbit), glyceraldehyde-3-phosphate dehydrogenase (GAPDH, 10494-1-AP, Proteintech, 1:2000, rabbit), Anti-Mouse IgG H&L (ab6789, Abcam, 1:2000), Anti-Rabbit IgG H&L (ab6721, Abcam, 1:2000).

Following specimen collection, plasma biomarker levels were quantified using ELISA according to the manufacturer’s protocols. The following ELISA kits were used: Human interleukin-6 (IL-6) ELISA kit (E-HSEL-H0003, Elabscience Biotechnology, Wuhan, China), Human interleukin-1β (IL-1β) ELISA kit (E-HSEL-H0001, Elabscience Biotechnology, Wuhan, China), Human interleukin-10 (IL-10) ELISA kit (E-EL-H0005, Elabscience Biotechnology, Wuhan, China), Human interferon γ (IFN-γ) ELISA kit (E-HSEL-H0007, Elabscience Biotechnology, Wuhan, China), Human tumor necrosis factor-α (TNF-α) ELISA kit (E-HSEL-H0109c, Elabscience Biotechnology, Wuhan, China), Human total tau ELISA kit (ml057755, mlbio, Shanghai, China),and Human P-tau181 ELISA kit (ml057691, mlbio, Shanghai, China), Human P-tau396 ELISA kit (E-EL-H5314c, Elabscience Biotechnology, Wuhan, China), Mouse interleukin-6 (IL-6) ELISA kit (ml098430, mlbio, Shanghai, China), Mouse interleukin-1β (IL-1β) ELISA kit (ml098416, mlbio, Shanghai, China) and Mouse tumor necrosis factor-α (TNF-α) ELISA kit (mIC50536-1, mlbio, Shanghai, China). All procedures were performed according to the manufacturer’s instructions.

For humans, 3 mL of anticoagulated whole blood was collected from each participant. Red blood cells (RBCs) were osmotically lysed with erythrocyte lysis buffer (Solarbio, Beijing, China), washed with PBS after lysis, and 1–10 × 10⁶ cells were resuspended in a diluted 100 μL Zombie Aqua™ solution (1:100, BioLegend, USA). After 10 min incubation, the cells were resuspended, washed with PBS, and incubated with anti-human CD45 (1:100, BioLegend, USA, 2D1, APC/Cyanine7), anti-human CD14 (1:100, BioLegend, USA, HCD14, FITC), anti-human CD86 (1:100, BioLegend, USA, IT2.2, PE), and anti-human CD206 (1:100, BioLegend, USA, 15-2, Pacific BLue™) for 30 min at 4°C in the dark. After washing, fixation breakers (eBioscience, USA) were added, and the cells were incubated for 30 min at 4°C in the dark. After washing, the cells were incubated with anti-human CD68 (1:100, BioLegend, USA, Y1/82A, Alexa FLuor^® 647) for 30 min at 4°C in the dark. After washing, flow cytometry was performed using BD FACS Celesta.

For mice, blood was collected from the right ventricle and placed in a 1.5-mL anticoagulant tube. It was then incubated with anti-mouse CD45 (1:100, BD Pharmingen, USA, 30-F11, PE), anti-mouse CD11b (1:100, BD Pharmingen, USA, M1/70, APC), and anti-mouse F4/80 (1:100, Invitrogen, USA, BM8, Alexa FLuor™ 488) for 30 min in the dark at 4°C. RBCs were lysed by adding erythrocyte lysis buffer (Solarbio, Beijing, China) for 10 min at room temperature and then centrifuged at 350 g for 5 min. After washing, flow cytometry was performed using BD FACS Celesta.

Flow cytometry data were analyzed using FlowJo software (v10.4, FlowJo LLC, USA).

Statistical analyses were performed using the IBM SPSS Statistics (version 27.0, IBM Corp., Armonk, NY, USA) and GraphPad Prism 9.0 software (GraphPad Software Inc., San Diego, CA, USA). The chi-square test was used to compare proportions. Continuous variables were described as means ± standard deviation or median and interquartile range, depending on the result of a D’Agostino-Pearson normality test, and compared using the unpaired Student’s t-test or Mann–Whitney U test, respectively. Analysis of covariance (ANCOVA) was applied to compare group differences while adjusting for potential confounders (e.g., age, gender, smoking status and stroking history). Multivariable linear regression analysis was performed to examine the associations between independent variables (X-axis) and dependent variables (Y-axis), adjusting for potential confounders including age, sex, smoking status, hypertension, diabetes, dyslipidemia and stroking history. A p-value of < 0.05 was considered statistically significant.

The demographic and clinical information of the patients in the two groups are summarized in Table 1. A total of 56 HCs and 56 patients with PSP were enrolled in this study. There were no significant differences observed in atherosclerosis risk factors, including age, gender, hypertension, diabetes, dyslipidemia, and smoking, between HCs and patients with PSP. However, the prevalence of stroke was significantly higher in patients with PSP than in HCs (39.29% vs. 16.07%, p = 0.011), which is similar to a previous report (Greten et al., 2023).

In this study, we evaluated systemic atherosclerotic burden comprehensively by assessing extracranial and intracranial vascular lesions using a multimodal approach. For extracranial assessment, carotid ultrasound provided several key indices: maximum carotid intima-media thickness (max-CIMT), which measures arterial wall thickening as an early marker of generalized atherosclerosis; maximum carotid plaque thickness (max-CPT), reflecting the most severe focal plaque deposition; total plaque number (TPN) indicating the extent of multifocal plaque involvement; and carotid plaque score (CPS), a composite metric integrating plaque size and number to represent overall plaque burden. We additionally quantified the percentage of carotid stenosis to determine the degree of stenosis. For intracranial assessment, we calculated the proportion of intracranial stenosis (ICS) vascular territory to determine the spatial extent of flow-limiting lesions within specific brain-supplying arteries. Finally, the magnetic resonance angiography (MRA)-based global stenosis score (GSS) was employed as a comprehensive metric that simultaneously evaluates the severity and distribution of stenotic lesions across intracranial arterial trees. This multidimensional approach enabled precise characterization of atherosclerosis at different vascular levels and pathophysiological stages, from early wall thickening to advanced flow-limiting stenoses. Patients with PSP exhibited significantly elevated values across multiple vascular parameters compared to HCs, suggesting a greater burden of both systemic and cerebral atherosclerosis. Specifically, after adjusting for age, gender, smoking status and stroke history, the PSP group exhibited significantly higher max-CPT (2.01 mm vs. 1.59 mm, p < 0.001), TPN (median 2 vs. 1, p = 0.005), CPS (median 2 vs. 1, p < 0.001), and carotid stenosis percentage (22.5% vs. 16.0%, p = 0.004) compared to HCs; however, max-CIMT (0.93 mm vs. 0.89 mm, p = 0.065) did not differ significantly between the groups (Figures 1A–E and Table 2). Another aspect, although intracranial stenosis involvement in individual vascular territories was more frequent in the PSP group, though not statistically significant (Figure 1F and Table 2); in contrast, MRA GSS reflecting overall stenosis severity, was significantly elevated in PSP patients (median 1 vs. 0, p = 0.041) after covariate adjustment (Figure 1G and Table 2). This finding is reasonable, given that the GSS reflects the severity of overall stenosis rather than the number of lesions.

To investigate the association between the severity of atherosclerosis and disease progression in patients with PSP, we performed regression analyses with atherosclerotic measures as dependent variables and disease duration/clinical severity scales as independent variables. Potential confounding factors, including age, gender, smoking status, hypertension, diabetes, dyslipidemia, and stroke history, were adjusted for in the analyses (for MMSE, one more correction for period of education). In adjusted multivariate models, longer disease duration was independently associated with higher TPN (β = 0.348, p = 0.004). H&Y stage exhibited positive associations with max-CIMT (β = 0.328, p = 0.015), max-CPT (β = 0.331, p = 0.012), TPN (β = 0.272, p = 0.043), CPS (β = 0.300, p = 0.016), and carotid stenosis% (β = 0.256, p = 0.036), whereas UPDRS-III correlated with max-CIMT (β = 0.371, p = 0.007), max-CPT (β = 0.288, p = 0.033), and CPS (β = 0.278, p = 0.030), and PSPRS solely with CPS (β = 0.270, p = 0.036) (Figure 1H and Supplementary Table 1).

Overall, these findings indicate that individuals with PSP may exhibit a more pronounced atherosclerotic vascular profile, with a positive correlation observed between certain atherosclerotic indicators and disease severity. These vascular changes may provide a pathophysiological link between systemic atherosclerosis and neurodegeneration in PSP, supporting the potential role of vascular biomarkers in disease assessment.

To explore the reasons for the increased susceptibility of patients with PSP to atherosclerosis, we examined traditional atherosclerosis risk factors such as total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), hemoglobin A1c (HbA1c), and homocysteine (Hcy) levels in the plasma. However, we found no significant differences in the levels of TC, TG, LDL, HDL, HbA1c, or Hcy between the two groups (Figures 1I–N and Table 3).

Progressive supranuclear palsy is a primary 4-repeat tauopathy characterized by abnormal accumulation of hyperphosphorylated tau in neurons and glia, particularly within the brainstem and basal ganglia. This pathology is strongly associated with MAPT mutations and the H1 haplotype, both of which promote tau misfolding and aggregation into neurofibrillary tangles and glial cytoplasmic inclusions (Forrest et al., 2023; Badihian et al., 2024; DeRosier et al., 2024). These pathological tau species are capable of propagating in a prion-like manner and are known to elicit neuroinflammatory responses, notably through microglial activation (Williams, 2006). Although current tau-related biomarkers—such as plasma and cerebrospinal fluid tau—lack disease specificity, they may hold diagnostic and mechanistic value in PSP (Giannakis et al., 2025). Based on this rationale, we assessed plasma levels of total tau, p-tau181, and p-tau396 in patients with PSP and HCs. After adjusting for age, gender, smoking status and stroke history, total tau (179.4 pg/mL vs. 169.4 pg/mL, p < 0.001) and p-tau181 (52.81 pg/mL vs. 43.72 pg/mL, p = 0.017) levels were elevated in patients with PSP compared to HCs, consistent with previous studies (Lin et al., 2018), whereas p-tau396 levels were not significantly different (Figures 1O–Q and Table 3). After adjustment for multiple covariates in multivariate regression models, higher plasma total tau levels showed positive association with carotid stenosis percentage (β = 0.240, p = 0.046). Similarly, elevated p-tau181 levels were independently associated with increased max-CPT (β = 0.434, p < 0.001), TPN (β = 0.392, p = 0.003), CPS (β = 0.460, p < 0.001), carotid stenosis% (β = 0.460, p < 0.001), and MRA-GSS (β = 0.293, p = 0.014) (Figure 1R and Supplementary Table 2). Collectively, these results indicate that increased plasma levels of both total tau and p-tau181 in patients with PSP are potentially associated with greater severity of atherosclerotic changes.

Emerging evidence indicates a potential link between tau pathology and vascular ischemia. In primary tauopathies, regions exhibiting tau accumulation often demonstrate abnormal microvascular architecture (Merlini et al., 2016). Tau proteins have been identified as key inducers of microglial activation and the subsequent release of pro-inflammatory mediators within the central nervous system (Gao et al., 2023). At the same time, macrophage infiltration and inflammation are well-established contributors to the pathogenesis of atherosclerosis (Blagov et al., 2023; Ajoolabady et al., 2024). Given these intersecting pathways, we investigated the percentage of peripheral blood macrophages and the plasma concentrations of inflammatory cytokines associated with atherosclerosis in both groups. Flow cytometric analysis of peripheral blood (n = 10 vs. n = 10) showed that the percentage of macrophages (CD14 + CD68+) in peripheral blood was significantly higher in patients with PSP compared to HCs (6.55% vs. 4.77%, p = 0.002), and the percentage of CD86 + CD206-M1 classically activated macrophages was increased as well (95.85% vs. 92.80%, p = 0.036) (Figures 2A, B). Analysis of the clinical data revealed that participants in the PSP group had higher plasma CRP levels (1.59 mg/L vs. 0.84 mg/L, p < 0.001) (n = 56 vs. n = 56) (Figure 2C and Table 3), which suggests a systemic inflammatory response in patients with PSP. In the assay of plasma inflammatory cytokines, IL-6 (4.53 pg/mL vs. 3.38 pg/mL, p = 0.001), IL-1β (6.33 pg/mL vs. 4.34 pg/mL, p < 0.001), TNF-α(13.26 pg/mL vs. 11.28 pg/mL, p = 0.033) and IFN-γ (18.42 pg/mL vs. 15.19 pg/mL, p < 0.001) were elevated in patients with PSP compared to HCs (n = 56 vs. n = 56), whereas there was no significant difference in the levels of anti-atherosclerotic cytokine IL-10 (2.12 pg/mL vs. 2.25 pg/mL, p = 0.367) after adjusting for age, gender, smoking status and stroke history (Figures 2D–H and Table 3).

Subsequent multivariate linear regression models revealed that elevated IL-6 levels were independently associated with increased max-CIMT (β = 0.331, p = 0.013), max-CPT (β = 0.265, p = 0.044), TPN (β = 0.322, p = 0.014), and carotid stenosis% (β = 0.243, p = 0.044). Similarly, higher IFN-γ levels correlated with greater max-CPT (β = 0.341, p = 0.007), TPN (β = 0.265, p = 0.040), CPS (β = 0.307, p = 0.010), and carotid stenosis percentage (β = 0.251, p = 0.032) (Figure 2I and Supplementary Table 3). Further multivariate linear regression revealed positive correlations of total tau with IL-6 (β = 0.346, p = 0.014) and IL-1β (β = 0.312, p = 0.028), and of p-tau181 with IL-1β (β = 0.379, p = 0.008) in patients with PSP (Figure 2J and Supplementary Table 4). These results demonstrate that elevated plasma IL-6 levels in PSP patients show significant positive correlations with both multiple atherosclerosis indices and total tau levels, suggesting a potential mechanistic link between tau-associated systemic inflammation and accelerated atherosclerosis in this population.

To investigate the role of tau in the activation of peripheral blood macrophages to release inflammatory factors and atherosclerotic processes, we injected tau-PFFs into the tail vein to increase the peripheral blood tau protein concentration in C57BL/6J mice, while the control group was injected with sterile PBS. Aortic tissue and blood were collected 3 months after the start of the injection (Figure 3A). Oil Red O and H&E staining of the aortic arch in the tau-PFF group revealed heterogeneous thickening of the arterial wall with structural disorganization and increased cell numbers without atherosclerotic plaque formation (Figures 3B, C). Since CD68 is a marker of macrophages, the increased CD68 expression, as assessed by immunohistochemical staining and western blotting (p = 0.002), suggested macrophage infiltration into the arterial wall in the tau-PFF groups (Figures 3D, E). In addition, western blot analysis revealed significantly upregulated expression of tau (p = 0.015), IL-6 (p = 0.002), and IL-1β (p = 0.004) in the tau-PFFs groups compared to controls (Figure 3E), confirming enhanced tau deposition and inflammatory responses within the arterial wall. Similarly, flow cytometric analysis revealed enhanced macrophage subpopulations (CD11b + F4/80+) (7.75% vs. 4.41%, p = 0.026) in the peripheral blood of the tau-PFFs group compared to the control group (n = 6 vs. n = 6) (Figure 3F). ELISA of murine plasma inflammatory cytokines revealed elevated levels of IL-6 (p = 0.009), IL-1β (p = 0.026), and TNF-α (p = 0.015) in the tau-PFFs group compared to the control group, indicating an enhanced tau-induced inflammatory response in the peripheral blood (Figure 3G–I).