Capillary Plasma GFAP and NfL Track In Vivo Tauopathy Progression in PS19 Mice

Capillary Plasma GFAP and NfL Track In Vivo Tauopathy Progression in PS19 Mice | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Capillary Plasma GFAP and NfL Track In Vivo Tauopathy Progression in PS19 Mice Anna Harima, Natsumi Kobayashi, Sharma Sanjiv, Takahiko Tokuda, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8912963/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Alzheimer’s disease (AD) is characterized by progressive tau pathology and neurodegeneration. While blood-based biomarkers such as glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau at threonine 181 (p-Tau181) are increasingly utilized for detecting these pathological processes, conventional venous blood sampling poses limitations for frequent and decentralized monitoring. This study aimed to evaluate the utility of capillary blood and skin interstitial fluid (ISF) as minimally invasive matrices for monitoring tau-related pathology in a tauopathy mouse model. Methods Microdialysis-based ISF collection was first optimized in C57BL/6J mice to confirm protein recovery and minimize blood contamination. Venous plasma, capillary plasma, and ISF were subsequently collected from PS19 tauopathy mice (n = 29) and wild-type mice (n = 17) at defined disease stages (4–12 months of age). Concentrations of GFAP, NfL, and p-Tau181 were quantified using the Simoa platform. Tau pathology was assessed by AT8 immunohistochemistry. Statistical analyses included Spearman correlation, linear regression, and receiver operating characteristic (ROC) curve analysis. Results In PS19 mice, both venous and capillary plasma concentrations of GFAP and NfL significantly correlated with brain tau pathology scores (p < 0.0001). Capillary plasma levels closely mirrored venous concentrations, with strong cross-matrix correlations. In contrast, p-Tau181 levels did not consistently correlate with pathological burden in either matrix. ISF levels of all biomarkers showed no significant correlation with brain pathology or plasma levels, likely due to technical limitations of microdialysis and the inherently low protein concentration in ISF. Conclusions Capillary blood–derived GFAP and NfL reliably reflect tau-related neurodegeneration in PS19 mice and represent promising minimally invasive biomarkers suitable for longitudinal and translational research. In contrast, current ISF sampling approaches are insufficient for AD biomarker detection and require further methodological refinement. Alzheimer’s disease Tau pathology minimally invasive biomarkers GFAP NfL pTau181 capillary blood interstitial fluid PS19 mice single molecule array (Simoa) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Dementia affects an estimated 57 million people worldwide, and this number is projected to rise to approximately 153 million by 2050 as populations age and risk factor profiles shift [ 1 ]. The associated health-care and societal costs are substantial and continue to increase; global spending on dementia care was estimated at around US $ 260–270 billion in 2019, with sustained annual growth since 2000 [ 2 ]. Alzheimer’s disease (AD) is the most common cause of dementia and is characterised neuropathologically by extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles composed of abnormally phosphorylated tau, accompanied by synaptic and neuronal loss [ 3 ]. Over the past decade, fluid and imaging biomarkers have transformed the diagnosis and staging of AD. Core cerebrospinal fluid (CSF) biomarkers—reduced Aβ42 (or Aβ42/Aβ40 ratio) together with elevated total tau and phosphorylated tau—show high diagnostic accuracy for AD pathology, particularly when used in combination with amyloid and tau positron emission tomography (PET) [ 3 – 5 ]. More recently, ultrasensitive immunoassays have enabled the detection of these markers in blood, and plasma phosphorylated tau at threonine 181 (p-Tau181) has emerged as a robust blood-based correlate of amyloid and tau pathology and clinical stage [ 6 ]. Likewise, neurofilament light chain (NfL) reflects axonal injury across neurodegenerative disorders, and glial fibrillary acidic protein (GFAP) is increasingly recognised as a marker of astroglial activation; both have strong prognostic value in AD and in prodromal at-risk populations [ 7 , 8 ]. The emergence of disease-modifying therapies has further underscored the importance of detecting AD at the earliest symptomatic stages. In the CLARITY-AD phase 3 trial, the anti-Aβ monoclonal antibody lecanemab, administered to individuals with early AD (mild cognitive impairment due to AD or mild AD dementia with confirmed amyloid pathology), produced a moderate but statistically significant slowing of cognitive and functional decline over 18 months compared with placebo [ 9 ]. These data, together with biomarker-based staging frameworks, suggest that therapeutic benefit is likely greatest when interventions are initiated early in the disease course, thereby increasing the need for accessible and scalable biomarker assessments that can be used in longitudinal and decentralised settings [ 4 ]. Despite their clinical utility, conventional biomarker assessments still rely heavily on venous blood draws and CSF sampling. CSF collection is invasive, resource-intensive, and often unacceptable to patients, whereas venepuncture can be a practical barrier for repeated or home-based monitoring, particularly in older adults or those with needle phobia and limited venous access [ 10 , 11 ]. Consequently, there is growing interest in minimally invasive sampling strategies that use small volumes of capillary blood or alternative biological fluids [ 12 ]. Recent studies have demonstrated that NfL and GFAP measured from finger-prick or capillary samples correlate strongly with their venous counterparts and retain analytical stability under delayed processing and ambient shipping conditions, supporting the feasibility of minimally invasive blood sampling in humans [ 13 – 15 ]. However, whether capillary-derived biomarkers quantitatively reflect the burden of histopathologically defined tau pathology in the brain remains unestablished. In parallel, other biofluids—such as saliva, sweat, tears, and skin interstitial fluid (ISF)—are being explored as sources of AD-related biomarkers and as matrices for wearable or minimally invasive biosensors [ 12 ]. ISF is particularly attractive because its biochemical composition closely mirrors that of plasma, and it can be accessed with microneedles or microdialysis-based devices that allow repeated sampling with minimal discomfort [ 16 ]. Proof-of-concept studies have shown that ISF can be used to monitor metabolites such as glucose and insulin in animals and humans using wearable microneedle patches or continuous droplet microfluidic sensors [ 17 ]. However, it remains unclear whether large neurodegeneration-related proteins such as GFAP, NfL, or p-Tau181 can be reliably captured and quantified from skin ISF in vivo, and whether their ISF concentrations track central tau pathology to a similar extent as in plasma. PS19 mice, which overexpress human P301S mutant tau, develop age-dependent tau aggregation, gliosis, and neurodegeneration that recapitulate key features of human tauopathies [ 18 , 19 ]. This model provides a well-characterised platform to examine the relationships between fluid biomarkers and brain tau pathology. While venous plasma biomarkers have been studied extensively in clinical cohorts, the extent to which GFAP, NfL, and p-Tau181 measured in capillary plasma or skin ISF reflect the underlying burden of tau pathology in vivo has not been systematically evaluated in preclinical models. In mice, venous blood can be collected with sufficient accuracy; however, capillary sampling offers practical advantages by enabling minimally invasive, repeated collection from the same animal. This enables longitudinal monitoring of biomarker dynamics, reduces inter-animal variability, and enhances statistical power while minimizing the number of animals required. Therefore, we designed this study to establish foundational evidence in a well-characterized tauopathy mouse model. Specifically, we aimed to (i) optimize skin ISF sampling conditions in C57BL/6J mice and (ii) quantify GFAP, NfL, and p-Tau181 in venous plasma, capillary plasma, and skin ISF from PS19 and wild-type mice across defined disease stages, while concurrently assessing brain tau pathology via AT8 immunohistochemistry. Recognizing the growing adoption of capillary blood sampling in clinical research and its utility for minimally invasive, repeated collection, we investigated whether capillary-derived biomarkers reflect brain tau pathology to a similar extent as venous measures. In parallel, we assessed the technical feasibility and limitations of detecting large neurodegeneration-related proteins from skin ISF in vivo . Methods Study design This study evaluated whether the concentrations of glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau at threonine 181 (p-Tau181) in minimally invasive biofluids—capillary blood plasma and skin interstitial fluid (ISF)—reflect brain tau pathology in PS19 tauopathy model mice. The experimental workflow included the following steps: Optimisation of ISF microdialysis using healthy C57BL/6J mice (pilot validation of the skin ISF collection technique). Collection of biofluids (venous blood plasma, capillary blood plasma, and skin ISF) from PS19 mice and wild-type (WT) littermate controls. Quantification of biomarkers (GFAP, NfL, and p-Tau181) in the collected samples using Simoa® ultra-sensitive immunoassays. Blinded histopathological assessment of brain tau pathology using AT8 immunostaining for phosphorylated tau. In total, 29 PS19 mice and 17 WT mice of both sexes were included in the biomarker analyses, sampled at ages 4, 6, 8, 10, or 12 months. A schematic overview of the study design is provided in Fig. 1 . Animals To validate the skin ISF collection technique (pilot study), we used three 8-week-old and three 12-month-old male C57BL/6J mice (SLC Japan, Shizuoka, Japan). For the main biomarker experiments, we employed the PS19 tauopathy mouse model (B6;C3-Tg(Prnp-MAPT*P301S)PS19Vle/J, referred to as PS19) and its background strain, B6C3F1/J, as wild-type controls. The PS19 and wild-type mice used in this study were obtained by breeding two PS19 transgenic males (Jackson Laboratory stock #008169) with five B6C3F1/J females (stock #100010). Newborn pups were genotyped from tail biopsies to identify hemizygous PS19 transgenics (PS19 Hemi) and wild-type littermates. The final experimental cohort consisted of 29 PS19 Hemi mice (18 females and 11 males) and 17 wild-type mice (10 females and 7 males). All mice were group-housed (2–6 per cage) under a 12-hour light/dark cycle with food and water provided ad libitum. Mice were monitored daily for welfare, and humane endpoints were pre-specified (weight loss > 20%, inability to feed, hindlimb paralysis). Sampling was carried out at the ages defined in the Results. No animals were excluded unless they reached humane endpoints or died naturally prior to sampling. Detection of Albumin from Mouse Skin ISF Mice were anesthetized (4% isoflurane for induction, then maintained at 2% isoflurane) and the hair on the dorsal skin was shaved. A 22G needle (Terumo, Tokyo, Japan) was inserted into the dermis as a guide, and a microdialysis probe (100 kDa cutoff membrane; MAB14.15.4, Microbiotech AB, Stockholm, Sweden) was threaded through the needle tract and left in place under the skin. Skin ISF was collected by perfusing the probe with Ringer’s solution (Otsuka Pharmaceutical, Tokyo, Japan) at a flow rate of 5.5–8.0 µL/min for 20 minutes (see Supplementary Fig. 1). While still under anesthesia, a midline laparotomy was performed and venous blood was drawn from the posterior vena cava, immediately mixing it with 0.2% EDTA to prevent coagulation. Immediately thereafter, the posterior aorta was severed to euthanize the animal by exsanguination. The collected blood was centrifuged at 10,000 rpm for 5 minutes at 20°C to separate plasma. Both the skin ISF samples and plasma samples were stored at − 80°C until analysis. Albumin concentrations (µg/mL) in the plasma and ISF were measured colorimetrically as a functional validation of the ISF collection. We used a Mouse Albumin ELISA Kit (Fujifilm Wako, Osaka, Japan) according to the manufacturer’s protocol to quantify albumin in each sample. Collection of Body Fluid Samples from PS19 and Wild‑Type Mice Body fluid samples and brain tissues were collected from cohorts of PS19 and wild-type mice at 4, 6, 8, 10, and 12 months of age (n = 4–8 mice per genotype at each age; see Fig. 1 for study schema). All sample collections were performed between 9:00 AM and 2:00 PM to minimize the influence of circadian variation on biomarker levels. Mice were anesthetized with 4% isoflurane (induction) and maintained on 2% isoflurane during the procedure. To prevent hypothermia during anaesthesia, animals were placed on a thermostatically controlled heating pad throughout the procedure. First, capillary blood was collected by performing a submandibular puncture: a 5 mm disposable lancet (MediPoint Inc., Mineola, NY, USA) was used just posterior to the mandible to yield approximately 3–4 drops of blood. Next, using the same microdialysis method described above, at least 55 µL of skin ISF was collected from the dorsal lumbar skin of each mouse (Supplementary Fig. 1). Subsequently, a laparotomy was performed, venous blood was drawn from the posterior vena cava, and the posterior aorta was incised to sacrifice the mouse by exsanguination. Death was confirmed by a veterinarian (T.M.) before proceeding to tissue collection. The brain was then immediately removed from the carcass and fixed by immersion in 10% neutral-buffered formalin. All blood samples were handled promptly to obtain plasma. Capillary blood and venous blood were transferred to tubes containing 0.2% EDTA-2Na to prevent coagulation. The blood was centrifuged at 10,000 rpm for 5 minutes at 20°C, and the supernatants were collected as plasma. All plasma samples and ISF samples were stored in polypropylene tubes at − 80°C until analysis. Tau Pathology Staging Formalin-fixed brain tissues were processed for histopathological analysis of tau lesions. Each brain was sectioned at approximately 2 mm posterior to bregma (perpendicular to the coronal plane), and the tissue was embedded in paraffin. Sections of 3 µm thickness were cut from the paraffin blocks for immunohistochemistry. After deparaffinization, antigen retrieval was performed by autoclaving the slides in deionized water at 121°C for 20 minutes. Endogenous peroxidase activity was quenched with 3% hydrogen peroxide in methanol, and nonspecific binding was blocked by incubating sections in 1% bovine serum albumin in phosphate-buffered saline. The sections were then incubated with a primary antibody against phosphorylated tau (AT8; Thermo Fisher Scientific/Invitrogen, Carlsbad, CA, USA; 1:50 dilution) to label p-tau deposits. After thorough rinsing, a horseradish peroxidase–labeled polymer anti-mouse IgG secondary antibody (Dako, Carpinteria, CA, USA) was applied. Immunoreactivity was visualized using a diaminobenzidine (DAB) substrate (ImmPACT DAB Kit, Vector Laboratories, Burlingame, CA, USA), yielding a brown reaction product, and slides were counterstained with hematoxylin. Tau pathology in the brain was evaluated using a simplified six-stage scoring system based on the method of Hurtado et al. [ 20 ] (see Supplementary Methods). In brief, multiple brain regions—including cortical areas, amygdalar nuclei, the hippocampal formation (CA1–CA3 regions, dentate gyrus, and mossy fiber pathway), hypothalamus, and thalamus—were examined for AT8-positive tau inclusions. Each region was semi-quantitatively graded for AT8 immunoreactivity on a 0–3 scale, where 0 = no staining, 1 = sparse, 2 = moderate, and 3 = intense. In addition, the presence or absence of AT8-positive deposits in the mossy fibers of the hippocampus was noted separately. Three veterinary pathologists (A.H., N.K., and T.M.) independently scored the slides in a blinded manner, and the mean of their scores for each region was used for analysis. Representative histological images corresponding to tau pathology stages I–VI are shown in Supplementary Fig. 2. Simoa Biomarker Quantification Concentrations of p-Tau181, NfL, and GFAP in the skin ISF, capillary plasma, and venous plasma samples were measured using a Simoa HD-X Analyzer (Quanterix, Lexington, MA, USA), an automated ultra-sensitive digital immunoassay platform. All assays were performed according to the manufacturer’s instructions. Prior to measurement, plasma samples were diluted 40-fold and ISF samples 10-fold using the appropriate assay diluent. All samples (from PS19 and wild-type mice) were analyzed in a single batch, using a single lot of reagents and a shared set of calibration standards for consistency. Analyte concentrations were calculated based on a standard curve generated for each biomarker. Any sample reading that fell below the assay’s limit of detection was treated as zero for statistical purposes. Statistical Analysis All statistical analyses were performed using GraphPad Prism 8 (GraphPad Software, San Diego, CA, USA). The Mann–Whitney U test (two-tailed) was used for nonparametric comparisons between two groups. Correlations between biomarker levels (in ISF, venous plasma, and capillary plasma) and brain tau pathology scores were evaluated using Spearman’s rank correlation coefficient. Any potential outliers in the data were identified using linear regression residual analysis combined with the ROUT method (Q = 1%) for outlier detection. To assess the ability of each biomarker to discriminate tau pathology status, receiver operating characteristic (ROC) curve analysis was performed. For each biomarker, the area under the ROC curve (AUC) was calculated along with the 95% confidence interval, and statistical significance was determined. We defined the “AT8-positive” group as PS19 mice with moderate to severe tau pathology (stages II–VI) and the “AT8-negative” group as mice with no or minimal tau pathology (PS19 mice at stage I, plus all wild-type mice). The optimal cutoff value for each biomarker was determined by maximizing the Youden Index (sensitivity + specificity – 1) to best distinguish AT8-positive cases from AT8-negative cases. Results Albumin Levels in Plasma and Skin Interstitial Fluid To verify the efficacy of the microdialysis method for collecting skin ISF, we conducted pilot experiments in the C57BL/6J mice (8-week-old and 12-month-old males). Albumin concentrations in venous plasma were 64.45 mg/mL (2-month-old, n = 3) and 48.13 mg/mL (12-month-old, n = 3), with no significant age-related difference (p = 0.400, Mann–Whitney; Fig. 2 ). In skin interstitial fluid (ISF), albumin levels were 7.37 µg/mL and 5.24 µg/mL in 2-month-old and 12-month-old mice, respectively (n = 3 and n = 3), also without significant age differences (p = 0.400). Across all mice, ISF albumin concentrations were approximately 1/9000 of venous plasma levels. Plasma Biomarker Levels and Association with Tau Pathology Tau pathology increased progressively with age in PS19 mice (n = 29), and staging scores were strongly correlated with age (Spearman ρ = 0.716, p < 0.001; Fig. 3 ). AT8 immunoreactivity first appeared in the amygdala and piriform cortex at 4–6 months, extended into hippocampal and cortical regions at 8 months, and became widespread by 10–12 months. No AT8 positivity was observed in wild-type (WT) mice (n = 17). Venous plasma concentrations of GFAP, NfL and p-Tau181 were significantly higher in PS19 mice (GFAP: mean ± SD 192.7 ± 149.3 pg/ml, 95% CI of the mean 135.9–249.4, n = 29; NfL: mean ± SD 1360.7 ± 1084.1 pg/ml, 95% CI of the mean 948.3–1773.1, n = 29; p-Tau181: mean ± SD 4071.2 ± 4190.8 pg/ml, 95% CI of the mean 2477.1–5665.3, n = 29) than in WT controls (GFAP: mean ± SD 38.6 ± 49.9 pg/ml, 95% CI of the mean 12.9–64.3, n = 17; NfL: mean ± SD 95.6 ± 89.0 pg/ml, 95% CI of the mean 49.8–141.4, n = 17; p-Tau181: mean ± SD 21.4 ± 39.1 pg/ml, 95% CI of the mean 1.2–41.5, n = 17) (GFAP: p < 0.0001; NfL: p < 0.0001; p-Tau181: p < 0.0001, Mann–Whitney U test; Fig. 4 ). In PS19 mice (n = 29), venous GFAP strongly correlated with tau pathology (ρ = 0.739, p < 0.0001), and venous NfL also showed a significant correlation (ρ = 0.576, p = 0.002; Fig. 5 ). Venous p-Tau181 did not correlate significantly with pathology (ρ = 0.317, p = 0.114). Capillary plasma concentrations of GFAP, NfL and p-Tau181 were also significantly higher in PS19 mice (GFAP: mean ± SD 224.8 ± 245.6 pg/ml, 95% CI of the mean 121.1–328.5, n = 24; NfL: mean ± SD 1096.1 ± 1241.9 pg/ml, 95% CI of the mean 571.7–1620.6, n = 24; p-Tau181: mean ± SD 4563.1 ± 3538.4 pg/ml, 95% CI of the mean 3102.5–6023.7, n = 25) than in WT controls (GFAP: mean ± SD 39.0 ± 26.8 pg/ml, 95% CI of the mean 25.2–52.8, n = 17; NfL: mean ± SD 78.9 ± 67.6 pg/ml, 95% CI of the mean 44.1–113.6, n = 17; p-Tau181: mean ± SD 33.7 ± 32.1 pg/ml, 95% CI of the mean 17.2–50.2, n = 17) (GFAP: p = 0.0223; NfL: p = 0.0052; p-Tau181: p < 0.0001, Mann–Whitney U test; Fig. 4 ). Plasma concentrations of GFAP, NfL, and p-Tau181 in venous blood and capillary blood showed equivalent values, with no significant differences observed. Capillary plasma levels of GFAP (ρ = 0.671, p < 0.0001) and NfL (ρ = 0.669, p < 0.0001) correlated with tau pathology, whereas p-Tau181 did not (ρ = 0.215, p = 0.301; Fig. 5 ). To determine whether biomarker concentrations were influenced by chronological age, we evaluated associations between each plasma biomarker and age in PS19 mice. GFAP and NfL showed moderate monotonic increases with age in both venous and capillary plasma (Spearman ρ range: 0.45–0.62; Supplementary Fig. 5), consistent with their strong associations with tau pathology. In contrast, p-Tau181 did not show significant age-related changes in either matrix (ρ 0.10). These analyses indicate that the age dependence of GFAP and NfL largely parallels the progression of tau pathology, whereas p-Tau181 remains age-stable in this model. Skin ISF Biomarkers and Tau Pathology In PS19 mouse skin ISF, no significant differences were observed for GFAP, NfL, or p-Tau181 (GFAP: mean ± SD 4.9 ± 4.8 pg/ml, 95% CI of the mean 1.2–8.5, n = 9; NfL: mean ± SD 0.6 ± 1.3 pg/ml, 95% CI of the mean − 0.4–1.6, n = 9; p-Tau181: mean ± SD 29.1 ± 45.1 pg/ml, 95% CI of the mean − 5.6–63.7, n = 9) compared to wild-type mice (GFAP: mean ± SD 7.5 ± 6.5 pg/ml, 95% CI of the mean − 2.9–17.9, n = 4; NfL: mean ± SD 0.1 ± 0.2 pg/ml, 95% CI of the mean − 0.2–0.3, n = 4; p-Tau181: mean ± SD 8.0 ± 2.5 pg/ml, 95% CI of the mean 4.1–12.0, n = 4) (GFAP: p = 0.308, NfL: p > 0.999, p-Tau181: p = 0.711, Mann–Whitney U test; Fig. 4 ). The concentrations of GFAP, NfL, or p-Tau181 in these skin ISFs were clearly lower than those derived from venous or capillary blood. In PS19 mice with sufficient ISF yields (n = 10), GFAP, NfL and p-Tau181 measured in ISF showed no significant correlations with tau pathology (GFAP: ρ = − 0.072, p = 0.855; NfL: ρ = − 0.299, p = 0.458; p-Tau181: ρ = 0.118, p = 0.766; Fig. 5 ). Cross-Matrix Associations Between Venous Plasma, Capillary Plasma and ISF Venous and capillary plasma concentrations were strongly correlated for GFAP (ρ = 0.830, p < 0.0001; n = 23) and NfL (ρ = 0.812, p < 0.0001; Fig. 6 ). No significant venous–capillary correlation was observed for p-Tau181 (ρ = 0.216, p = 0.312). No significant correlations were detected between skin ISF and plasma biomarkers (venous or capillary) in either PS19 or WT mice (Supplementary Figs. 4–5). ROC Analysis for Classification of Tau Pathology To assess the discriminative performance of plasma biomarkers for tau pathology, PS19 mice with Stage II–VI pathology were classified as “pathology-positive,” while Stage I PS19 mice and all WT mice were designated as “pathology-negative.” Cutoff values for each biomarker were determined using ROC curve analysis. For GFAP, the optimal cutoff value was 65.7 pg/mL in venous blood plasma (AUC = 0.912, 95% CI = 0.824–0.999, p < 0.0001) and 122.9 pg/mL in capillary blood plasma (AUC = 0.764, 95% CI = 0.601–0.927, p = 0.004) (Fig. 7 , Table 1 ). In venous plasma, 4 of 11 Stage II mice fell below the cutoff (false negatives), whereas all 15 mice at Stage III or higher exceeded the threshold. Among 20 pathology-negative mice, only one WT mouse was misclassified as a false positive. In capillary plasma, 5 of 9 Stage II and 2 of 3 Stage III mice fell below the cutoff. All mice with Stage IV or higher pathology were correctly classified as positive. Three of 17 WT mice exceeded the cutoff in capillary plasma (false positives). For NfL, the cutoff in venous plasma was 538.6 pg/mL (AUC = 0.883, 95% CI = 0.783–0.983, p < 0.0001), and 364.6 pg/mL in capillary plasma (AUC = 0.810, 95% CI = 0.669–0.950, p < 0.0001) (Fig. 7 , Table 1 ). In venous plasma, 5 of 11 Stage II and 2 of 3 Stage III mice were false negatives. All Stage IV or higher mice exceeded the threshold, and no false positives were observed among pathology-negative mice. In capillary plasma, the same pattern was observed: 5 of 9 Stage II and 2 of 3 Stage III mice fell below the cutoff, while all Stage IV or higher mice were correctly classified. No false positives were observed among pathology-negative mice. For p-Tau181, the venous plasma cutoff was 1,295.0 pg/mL (AUC = 0.958, 95% CI = 0.889–1.000, p < 0.0001), and 975.7 pg/mL in capillary plasma (AUC = 0.897, 95% CI = 0.786–1.000, p < 0.0001) (Fig. 7 , Table 1 ). In venous plasma, 2 of 11 Stage II mice were false negatives, while all mice at Stage III or above exceeded the threshold. One of 3 Stage I PS19 mice exceeded the cutoff, resulting in a false positive among pathology-negative animals. In capillary plasma, 2 of 3 Stage III mice were false negatives, while all Stage IV or higher mice exceeded the cutoff. However, 2 of 3 Stage I PS19 mice showed false positives in capillary plasma. Table 1 ROC Curve Analysis of Plasma Biomarkers for Classifying Brain Tau Pathology Venous blood Capillary blood GFAP NfL p-Tau181 GFAP NfL p-Tau181 AUC 0.912 0.883 0.958 0.764 0.81 0.897 Specificity (%) 95 100 95 100 90 90 Sensitivity (%) 84.6 73.1 92.3 66.7 66.7 90.9 Cutoff value (pg/ml) 65.7 538.6 1295 .0 122.9 364.6 975.7 N AT8+: 26, AT8-: 20 AT8+: 26, AT8-: 20 AT8+: 26, AT8-: 20 AT8+: 22, AT8-: 20 AT8+: 21, AT8-: 20 AT8+: 21, AT8-: 20 p-value (X 2 ) < 0.0001 < 0.0001 < 0.0001 0.0038 0.0007 < 0.0001 95%CI 0.8242 .cf0 { font-family: Segoe UI; font-size: 10.5pt; } ~ 0.9989 0.7827 .cf0 { font-family: Segoe UI; font-size: 10.5pt; } ~ 0.9827 0.8891 .cf0 { font-family: Segoe UI; font-size: 10.5pt; } ~ 1.000 0.6012 .cf0 { font-family: Segoe UI; font-size: 10.5pt; } ~ 0.9273 0.6689 .cf0 { font-family: Segoe UI; font-size: 10.5pt; } ~ 0.9501 0.7863 .cf0 { font-family: Segoe UI; font-size: 10.5pt; } ~ 1.000 Pathology-positive cases were defined as PS19 mice with Stage II–VI tau pathology (AT8+), and pathology-negative cases as PS19 mice at Stage I or wild-type mice (AT8-). Cutoff values were determined by ROC analysis using the maximum Youden index. AUC, area under the curve; CI, confidence interval. Discussion This study investigated the relationships between Alzheimer’s disease–related fluid biomarkers and brain tau pathology in PS19 mice using venous plasma, capillary blood, and skin ISF. Our findings align with recent human studies demonstrating strong concordance between capillary and venous blood measurements of GFAP and NfL [ 14 , 15 ], reinforcing the biological robustness of capillary sampling. Importantly, the present work extends these observations by anchoring biomarker levels to histopathologically staged tau pathology, thereby providing mechanistic validation that cannot be obtained from clinical or imaging-based cohorts alone. Among the three biomarkers examined, GFAP and NfL consistently tracked the severity of tau pathology in both venous and capillary blood, whereas p-Tau181 did not show a significant correlation with histopathological burden. The strong agreement between capillary and venous concentrations of GFAP and NfL further supports the feasibility of using minimally invasive peripheral sampling to monitor central neurodegenerative processes. Notably, capillary sampling via lancet puncture enables repeated measurements with minimal technical expertise, providing a practical avenue for longitudinal biomarker studies in mouse models and translational applications in humans [ 21 , 22 ]. GFAP has emerged as a sensitive indicator of astrocytic activation and disease progression in tauopathies and Alzheimer's disease [ 23 – 25 ]. In agreement with these observations, the present study found that GFAP in both venous and capillary plasma increased in parallel with tau pathology in PS19 mice, and the two matrices exhibited a strong correlation. The ROC-derived venous plasma cutoff (65.7 pg/mL) showed high sensitivity and specificity, whereas capillary-derived GFAP demonstrated reduced sensitivity despite high specificity. Several factors may contribute to this difference. GFAP is expressed in peripheral tissues [ 8 ], and local skin stimulation from lancet puncture may transiently influence GFAP levels in capillary samples. Additionally, biomarker concentrations in capillary blood may be more susceptible to pre-analytical variability and local microvascular dynamics. Given the limited sample size in this study, larger cohorts will be required to confirm optimal thresholds and assess their stability across age and pathology stages. NfL strongly correlated with tau pathology in both venous and capillary blood, and the two plasma sources were highly concordant. These findings are consistent with human studies reporting strong correlations between capillary and venous NfL, as well as high analytical reproducibility in finger-prick sampling [ 14 ]. ROC analysis demonstrated high discriminatory performance for venous NfL and modestly lower performance for capillary NfL. Similar to GFAP, sensitivity of the capillary measurements may be influenced by sample volume constraints and technical variability during peripheral sampling. Nevertheless, both venous and capillary NfL values exceeded their respective thresholds in all animals with advanced (stage IV or higher) pathology, indicating that NfL reliably reflects the onset and progression of widespread axonal injury in this tauopathy model. Although p-Tau181 distinguished PS19 from wild-type mice with high ROC accuracy, its concentrations did not correlate with histopathological tau burden in either venous or capillary plasma. These findings align with reports that p-Tau181 may be more reflective of amyloid-related processes than of tau tangle accumulation itself [ 25 , 26 ]. Another likely factor is assay specificity. The Simoa assay used in this study primarily quantifies N-terminal tau fragments (Np-pTau181). However, tau undergoes sequential C-terminal and N-terminal cleavages during neurofibrillary tangle (NFT) maturation, including early cleavage at D421 and subsequent truncations [ 27 ]. As a result, N-terminal–based assays may not adequately capture the tau species predominant in later-stage pathology. Notably, despite the lack of linear correlation with tau burden, capillary p-Tau181 effectively discriminated between AT8-positive and AT8-negative brains. This suggests potential utility as a binary classifier of pathological presence, offering a simple and minimally invasive method to monitor major transitions in tau pathology. Such application may be particularly valuable in longitudinal or screening contexts where full pathological quantification is impractical. Recent advances, such as mid-p-tau assays [ 28 ] and MTBR-tau (e.g., p-Tau243) assays, detect a broader spectrum of tau fragments, including regions implicated in paired-helical filament (PHF) formation [ 29 ]. These emerging markers show stronger associations with tau PET and clinical progression than p-Tau181 in several human studies. Incorporating assays that target mid-region or microtubule-binding-region tau species, together with optimizing pre-analytical processes, may improve the ability of plasma tau biomarkers to more accurately reflect tau pathology. GFAP, NfL, and p-Tau181 in skin ISF did not correlate with brain pathology or plasma biomarker concentrations. Several technical issues may contribute. Microdialysis can alter ISF composition due to mechanical disruption, immune activation, and dilution effects [ 16 ]. Recovery efficiency is influenced by flow rate, probe permeability, diffusion gradients, and molecular size [ 30 ]. The ISF albumin concentration measured here was ~ 1/9000 of plasma, suggesting substantial dilution or altered protein recovery. Additionally, probe-to-probe variability may affect detection sensitivity, particularly for low-abundance proteins. Future optimization of ISF sampling—such as improved microdialysis membranes, recovery correction factors, or alternative dermal sampling platforms—will be necessary to evaluate whether ISF can reliably reflect neurodegenerative biomarkers. In contrast to blood-based studies, the lack of association between ISF biomarkers and tau pathology observed here highlights current technical limitations of dermal ISF sampling for large neurodegeneration-related proteins. A key limitation of this study is that Simoa measurements were performed once per sample due to limited sample volume, particularly for capillary blood and skin ISF. This restricted the ability to assess analytical variability and reproducibility. Outlier detection using ROUT (Q = 1%) identified several values in venous and capillary plasma (Supplementary Fig. 6); however, the biological or technical basis for these deviations could not be fully explored. Ultra-sensitive platforms capable of analysing micro-volumes with lower variability may benefit future work. In addition, the semi-quantitative tau pathology staging used here, although designed to capture regionally distributed pathology, may not fully reflect incremental differences in total tau burden, particularly at higher stages (e.g., stage V vs. VI). This may have limited the resolution of correlation analyses between brain pathology and fluid biomarker levels. Conclusions This study demonstrates that GFAP and NfL measured from capillary blood reliably mirror venous concentrations and correlate with the severity of tau pathology in PS19 mice, supporting their potential as minimally invasive biomarkers for neurodegeneration. p-Tau181 showed high group-level discriminatory accuracy but limited capacity to track pathology severity, likely reflecting assay-specific and disease-stage-specific factors. Skin ISF biomarkers did not correlate with pathology under current sampling conditions, emphasizing the need for further methodological refinements. Together, these findings highlight the feasibility of capillary blood biomarker assessment for longitudinal monitoring in mouse models and indicate promising translational relevance for early, low-burden biomarker testing. Continued improvements in assay sensitivity, tau epitope coverage, and ISF sampling technologies are expected to enhance the precision and applicability of minimally invasive biomarkers for Alzheimer’s disease and related tauopathies. Abbreviations AD Alzheimer’s disease AT8 Antibody against phosphorylated tau (Ser202/Thr205) AUC Area under the curve CB Capillary blood CI Confidence interval ELISA Enzyme-linked immunosorbent assay GFAP Glial fibrillary acidic protein IHC Immunohistochemistry ISF Interstitial fluid NfL Neurofilament light chain PBS Phosphate-buffered saline p-Tau181 Phosphorylated tau at threonine 181 ROC Receiver operating characteristic Simoa Single molecule array VB Venous blood WT Wild-type Declarations Ethics approval and consent to participate All animal procedures were conducted in accordance with institutional guidelines and were approved by the Animal Experiment Committee of Tokyo University of Agriculture and Technology (Approval Nos. R05-21 and R06-106). The use of PS19 mice was additionally approved by the university’s Biosafety Subcommittee (Approval No. R4-99). Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the MRC-AMED UK–Japan collaboration project “Multi-analyte prognostic and diagnostic screening in blood and skin for Alzheimer’s disease” (MR/X02153X/1 to SS and 22jm0210099h0001 to KT). Authors' contributions KT and TM conceptualized and supervised the study. AH, NK, KT, YY, and AN performed the experiments. KT and TM analyzed the data and wrote the manuscript. All authors reviewed and approved the final version of the manuscript. Conceptualization: SS, KT, TM. Methodology: AH, SS, TT, MH, KT, TM. Investigation: AH, NK, TM. Visualization: AH, TM. Funding acquisition: SS, KT. Resources: SS, TT, MH. Project administration: KT, TM. Supervision: SS, KT, TM. Writing – original draft: AH, TM. Writing – review & editing: All authors. Acknowledgements We thank the members of the Laboratory of Veterinary Toxicology at Tokyo University of Agriculture and Technology for their support with animal experiments. We also acknowledge Ms. Sayo Matsuura (National Institute for Quantum Science and Technology) for her expert technical assistance with Simoa analyses. References Nichols E, Steinmetz JD, Vollset SE, Fukutaki K, Chalek J, Abd-Allah F, et al. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. Lancet Public Health. 2022;7:e105–25. https://doi.org/10.1016/S2468-2667(21)00249-8 . Pedroza P, Miller-Petrie MK, Chen C, Chakrabarti S, Chapin A, Hay S, et al. 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Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy Mouse Model. Neuron. 2007;53:337–51. https://doi.org/10.1016/j.neuron.2007.01.010 . Zhong MZ, Peng T, Duarte ML, Wang M, Cai D. Updates on mouse models of Alzheimer’s disease. Mol Neurodegener. 2024;19:23. https://doi.org/10.1186/s13024-024-00712-0 . Hurtado DE, Molina-Porcel L, Iba M, Aboagye AK, Paul SM, Trojanowski JQ, et al. Aβ Accelerates the Spatiotemporal Progression of Tau Pathology and Augments Tau Amyloidosis in an Alzheimer Mouse Model. Am J Pathol. 2010;177:1977–88. https://doi.org/10.2353/ajpath.2010.100346 . Grady M, Pineau M, Pynes MK, Katz LB, Ginsberg B. A Clinical Evaluation of Routine Blood Sampling Practices in Patients With Diabetes: Impact on Fingerstick Blood Volume and Pain. J Diabetes Sci Technol SAGE Publications Inc. 2014;8:691–8. https://doi.org/10.1177/1932296814533172 . Groenendijk WN, Griffin TP, Islam MN, Blake L, Wall D, Bell M, et al. Remote capillary blood collection for HbA1c measurement during the COVID-19 pandemic: A laboratory and patient perspective. Diabet Med. 2022;39:e14897. https://doi.org/10.1111/dme.14897 . Rajan KB, Aggarwal NT, McAninch EA, Weuve J, Barnes LL, Wilson RS, et al. Remote Blood Biomarkers of Longitudinal Cognitive Outcomes in a Population Study. Ann Neurol. 2020;88:1065–76. https://doi.org/10.1002/ana.25874 . Verberk IMW, Laarhuis MB, van den Bosch KA, Ebenau JL, van Leeuwenstijn M, Prins ND, et al. Serum markers glial fibrillary acidic protein and neurofilament light for prognosis and monitoring in cognitively normal older people: a prospective memory clinic-based cohort study. Lancet Healthy Longev Elsevier. 2021;2:e87–95. https://doi.org/10.1016/S2666-7568(20)30061-1 . Salvadó G, Ossenkoppele R, Ashton NJ, Beach TG, Serrano GE, Reiman EM, et al. Specific associations between plasma biomarkers and postmortem amyloid plaque and tau tangle loads. EMBO Mol Med Springer Nat. 2023;15:e17123. https://doi.org/10.15252/emmm.202217123 . Therriault J, Vermeiren M, Servaes S, Tissot C, Ashton NJ, Benedet AL, et al. Association of Phosphorylated Tau Biomarkers With Amyloid Positron Emission Tomography vs Tau Positron Emission Tomography. JAMA Neurol. 2023;80:188–99. https://doi.org/10.1001/jamaneurol.2022.4485 . Guillozet-Bongaarts AL, Garcia-Sierra F, Reynolds MR, Horowitz PM, Fu Y, Wang T, et al. Tau truncation during neurofibrillary tangle evolution in Alzheimer’s disease. Neurobiol Aging. 2005;26:1015–22. https://doi.org/10.1016/j.neurobiolaging.2004.09.019 . Tagai K, Tatebe H, Matsuura S, Hong Z, Kokubo N, Matsuoka K, et al. A novel plasma p-tau181 assay as a specific biomarker of tau pathology in Alzheimer’s disease. Transl Neurodegener. 2024;13:44. https://doi.org/10.1186/s40035-024-00439-4 . Horie K, Salvadó G, Koppisetti RK, Janelidze S, Barthélemy NR, He Y, et al. Plasma MTBR-tau243 biomarker identifies tau tangle pathology in Alzheimer’s disease. Nat Med Nat Publishing Group. 2025;31:2044–53. https://doi.org/10.1038/s41591-025-03617-7 . Korf J, Huinink KD, Posthuma-Trumpie GA. Ultraslow microdialysis and microfiltration for in-line, on-line and off-line monitoring. Trends Biotechnol. 2010;28:150–8. https://doi.org/10.1016/j.tibtech.2009.12.005 . Additional Declarations No competing interests reported. Supplementary Files SI251217.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8912963","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593664254,"identity":"de5f8ee2-ecb9-46dc-b889-b26daa004b72","order_by":0,"name":"Anna Harima","email":"","orcid":"","institution":"Tokyo University of Agriculture and Technology","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Harima","suffix":""},{"id":593664255,"identity":"4994629b-f9af-4fa9-9486-5c269118fde0","order_by":1,"name":"Natsumi Kobayashi","email":"","orcid":"","institution":"Tokyo University of Agriculture and Technology","correspondingAuthor":false,"prefix":"","firstName":"Natsumi","middleName":"","lastName":"Kobayashi","suffix":""},{"id":593664256,"identity":"5e2b9831-8268-471c-8dbc-f04c25deaafe","order_by":2,"name":"Sharma Sanjiv","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Sharma","middleName":"","lastName":"Sanjiv","suffix":""},{"id":593664257,"identity":"e33a98c1-2924-4774-b6be-dff2f964fdc2","order_by":3,"name":"Takahiko Tokuda","email":"","orcid":"","institution":"National Institutes for Quantum Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Takahiko","middleName":"","lastName":"Tokuda","suffix":""},{"id":593664258,"identity":"61b07ab3-7d98-435f-93c9-b297f6c2d335","order_by":4,"name":"Makoto Higuchi","email":"","orcid":"","institution":"National Institutes for Quantum Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Makoto","middleName":"","lastName":"Higuchi","suffix":""},{"id":593664262,"identity":"2ba5ea28-fd1a-437e-8757-4b01b5f31819","order_by":5,"name":"Kaori Tsukakoshi","email":"","orcid":"","institution":"Tokyo University of Science","correspondingAuthor":false,"prefix":"","firstName":"Kaori","middleName":"","lastName":"Tsukakoshi","suffix":""},{"id":593664264,"identity":"53b8253b-4958-4aab-8227-0703bfcf5970","order_by":6,"name":"Tomoaki Murakami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYFACNiCuQBE5QISWA2egWg8QreVgG4oWAkB39rHUzR/n2ckzyPcYfv7AAGQwnsWv0+xc2rEbB7clGzaw8RhLHGAAMhjOJeDXcoa9DajlQAIDG48BUAszUPkZAyK0zAFrMf5xgKGeGC1sQIc1gLWYAW05TJSWtBtnjiUbtrGllVmcMThu2EbYL2xmNypq7OT5mQ9vvlFRUS3PL0EgxOCADUwCncQmcYY4HUiAv4dkLaNgFIyCUTC8AQCWSkWFJW34pwAAAABJRU5ErkJggg==","orcid":"","institution":"Tokyo University of Agriculture and Technology","correspondingAuthor":true,"prefix":"","firstName":"Tomoaki","middleName":"","lastName":"Murakami","suffix":""}],"badges":[],"createdAt":"2026-02-19 00:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8912963/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8912963/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103042309,"identity":"c6c30027-4fa4-4eff-8c80-3d4b931e9aba","added_by":"auto","created_at":"2026-02-20 04:47:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":477445,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental design. \u003c/strong\u003e(A) Feasibility assessment of protein detection in skin interstitial fluid (ISF). Skin ISF was collected from healthy C57BL/6J mice via microdialysis, and albumin levels were measured by ELISA and compared with venous plasma. (B) Longitudinal biomarker study in PS19 and wild-type (WT) mice. PS19 (n = 29) and WT (n = 17) mice were euthanized at 4, 6, 8, 10, or 12 months of age. Venous blood, capillary blood, skin ISF, and brain tissue were collected. Fluid biomarkers (GFAP, NfL, p-Tau181) were quantified using Simoa (Quanterix), and brain tau pathology was assessed by AT8 immunohistochemistry.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/3d216320196a3f28c49aa20c.png"},{"id":103042316,"identity":"6192a48b-8231-40ab-a624-596e72a71db5","added_by":"auto","created_at":"2026-02-20 04:47:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153530,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlbumin concentrations in venous plasma and skin ISF from C57BL/6J mice. \u003c/strong\u003eEach dot represents an individual mouse. Horizontal bars indicate group means and error bars denote standard deviation (SD). Albumin concentrations in skin ISF were markedly lower than those in plasma.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/e7a6a7627656a562ba51d792.png"},{"id":103042310,"identity":"28163388-cab7-40a4-94c9-e1294986ae50","added_by":"auto","created_at":"2026-02-20 04:47:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":170082,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between brain tau pathology stage and age in PS19 mice. \u003c/strong\u003eBrain tau pathology showed a strong age-dependent increase in PS19 mice (Spearman ρ = 0.716, p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/56c51e6e7f89edcdc618e499.png"},{"id":103050517,"identity":"2572dfcd-beeb-4037-a187-28b52115c47b","added_by":"auto","created_at":"2026-02-20 07:50:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":493330,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBody fluid biomarker concentrations in PS19 and wild-type mice. \u003c/strong\u003eEach dot represents an individual mouse. Horizontal bars indicate group means and error bars denote standard deviation (SD). Comparisons between PS19 and wild-type mice were performed using the Mann–Whitney U test.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/5ded7a1a1badf8c4d5ef8180.png"},{"id":103050053,"identity":"674c4609-eb53-425f-8066-30561d52d1c5","added_by":"auto","created_at":"2026-02-20 07:47:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":311432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between brain tau pathology stage and biomarker concentrations in PS19 mice. \u003c/strong\u003eRelationships between GFAP, NfL, and p-Tau181 concentrations in venous plasma (VB), capillary plasma (CB), and skin ISF and tau pathology stage were evaluated using Spearman’s rank correlation. Correlation coefficients (ρ) and p-values are shown within each plot. The x-axis indicates tau pathology stage (1–6), and the y-axis indicates biomarker concentrations (pg/mL).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/7d081d42b06f905c6bf6fd1d.png"},{"id":103050491,"identity":"b32b46c4-5765-435f-a2c8-6842b8075cbf","added_by":"auto","created_at":"2026-02-20 07:50:17","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":545345,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelations between venous and capillary plasma biomarker concentrations. \u003c/strong\u003eIn PS19 and wild-type mice, biomarker concentrations in venous blood (VB) and capillary blood (CB) were compared using Spearman’s rank correlation. Correlation coefficients (ρ) and p-values for PS19 and wild-type mice are shown in each plot. The x-axis indicates CB biomarker concentrations, and the y-axis indicates VB biomarker concentrations (pg/mL).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/030292b9bdd06b7f744db151.png"},{"id":103042313,"identity":"d5ab43b4-b67b-41cd-aed3-4841cc0b16d9","added_by":"auto","created_at":"2026-02-20 04:47:41","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":713388,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiscriminatory performance of venous and capillary blood biomarkers for brain tau pathology in PS19 and wild-type mice. \u003c/strong\u003eReceiver operating characteristic (ROC) curves (top row) and violin plots (bottom row) for GFAP, NfL, and p-Tau181 in venous blood (top panels) and capillary blood (bottom panels), comparing AT8-positive (AT8+, PS19 stage II–VI) and AT8-negative (AT8-, PS19 stage I and WT) mice. ROC curves were generated to evaluate the ability of each biomarker to discriminate between AT8+ and AT8- mice. Violin plots illustrate the distribution of biomarker concentrations (pg/mL), with dotted horizontal lines indicating the optimal cutoff values based on the Youden Index. Each data point represents an individual animal.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/07282105f474c5e544d3d268.png"},{"id":104403048,"identity":"5f3b3ab7-5093-4a22-8123-37e22410577f","added_by":"auto","created_at":"2026-03-11 12:17:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5766734,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/827a97b2-2f21-450a-bdba-4f9a640968a3.pdf"},{"id":103042315,"identity":"7be62184-c359-4e71-b558-e79f31ab1ef2","added_by":"auto","created_at":"2026-02-20 04:47:41","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3281343,"visible":true,"origin":"","legend":"","description":"","filename":"SI251217.docx","url":"https://assets-eu.researchsquare.com/files/rs-8912963/v1/0a067a3e0fd93a6daffad33b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Capillary Plasma GFAP and NfL Track In Vivo Tauopathy Progression in PS19 Mice","fulltext":[{"header":"Background","content":"\u003cp\u003eDementia affects an estimated 57\u0026nbsp;million people worldwide, and this number is projected to rise to approximately 153\u0026nbsp;million by 2050 as populations age and risk factor profiles shift [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The associated health-care and societal costs are substantial and continue to increase; global spending on dementia care was estimated at around US\u003cspan\u003e$\u003c/span\u003e260\u0026ndash;270\u0026nbsp;billion in 2019, with sustained annual growth since 2000 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Alzheimer\u0026rsquo;s disease (AD) is the most common cause of dementia and is characterised neuropathologically by extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles composed of abnormally phosphorylated tau, accompanied by synaptic and neuronal loss [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver the past decade, fluid and imaging biomarkers have transformed the diagnosis and staging of AD. Core cerebrospinal fluid (CSF) biomarkers\u0026mdash;reduced Aβ42 (or Aβ42/Aβ40 ratio) together with elevated total tau and phosphorylated tau\u0026mdash;show high diagnostic accuracy for AD pathology, particularly when used in combination with amyloid and tau positron emission tomography (PET) [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. More recently, ultrasensitive immunoassays have enabled the detection of these markers in blood, and plasma phosphorylated tau at threonine 181 (p-Tau181) has emerged as a robust blood-based correlate of amyloid and tau pathology and clinical stage [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Likewise, neurofilament light chain (NfL) reflects axonal injury across neurodegenerative disorders, and glial fibrillary acidic protein (GFAP) is increasingly recognised as a marker of astroglial activation; both have strong prognostic value in AD and in prodromal at-risk populations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe emergence of disease-modifying therapies has further underscored the importance of detecting AD at the earliest symptomatic stages. In the CLARITY-AD phase 3 trial, the anti-Aβ monoclonal antibody lecanemab, administered to individuals with early AD (mild cognitive impairment due to AD or mild AD dementia with confirmed amyloid pathology), produced a moderate but statistically significant slowing of cognitive and functional decline over 18 months compared with placebo [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These data, together with biomarker-based staging frameworks, suggest that therapeutic benefit is likely greatest when interventions are initiated early in the disease course, thereby increasing the need for accessible and scalable biomarker assessments that can be used in longitudinal and decentralised settings [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite their clinical utility, conventional biomarker assessments still rely heavily on venous blood draws and CSF sampling. CSF collection is invasive, resource-intensive, and often unacceptable to patients, whereas venepuncture can be a practical barrier for repeated or home-based monitoring, particularly in older adults or those with needle phobia and limited venous access [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consequently, there is growing interest in minimally invasive sampling strategies that use small volumes of capillary blood or alternative biological fluids [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated that NfL and GFAP measured from finger-prick or capillary samples correlate strongly with their venous counterparts and retain analytical stability under delayed processing and ambient shipping conditions, supporting the feasibility of minimally invasive blood sampling in humans [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, whether capillary-derived biomarkers quantitatively reflect the burden of histopathologically defined tau pathology in the brain remains unestablished.\u003c/p\u003e \u003cp\u003eIn parallel, other biofluids\u0026mdash;such as saliva, sweat, tears, and skin interstitial fluid (ISF)\u0026mdash;are being explored as sources of AD-related biomarkers and as matrices for wearable or minimally invasive biosensors [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. ISF is particularly attractive because its biochemical composition closely mirrors that of plasma, and it can be accessed with microneedles or microdialysis-based devices that allow repeated sampling with minimal discomfort [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Proof-of-concept studies have shown that ISF can be used to monitor metabolites such as glucose and insulin in animals and humans using wearable microneedle patches or continuous droplet microfluidic sensors [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, it remains unclear whether large neurodegeneration-related proteins such as GFAP, NfL, or p-Tau181 can be reliably captured and quantified from skin ISF in vivo, and whether their ISF concentrations track central tau pathology to a similar extent as in plasma.\u003c/p\u003e \u003cp\u003ePS19 mice, which overexpress human P301S mutant tau, develop age-dependent tau aggregation, gliosis, and neurodegeneration that recapitulate key features of human tauopathies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This model provides a well-characterised platform to examine the relationships between fluid biomarkers and brain tau pathology. While venous plasma biomarkers have been studied extensively in clinical cohorts, the extent to which GFAP, NfL, and p-Tau181 measured in capillary plasma or skin ISF reflect the underlying burden of tau pathology \u003cem\u003ein vivo\u003c/em\u003e has not been systematically evaluated in preclinical models. In mice, venous blood can be collected with sufficient accuracy; however, capillary sampling offers practical advantages by enabling minimally invasive, repeated collection from the same animal. This enables longitudinal monitoring of biomarker dynamics, reduces inter-animal variability, and enhances statistical power while minimizing the number of animals required.\u003c/p\u003e \u003cp\u003eTherefore, we designed this study to establish foundational evidence in a well-characterized tauopathy mouse model. Specifically, we aimed to (i) optimize skin ISF sampling conditions in C57BL/6J mice and (ii) quantify GFAP, NfL, and p-Tau181 in venous plasma, capillary plasma, and skin ISF from PS19 and wild-type mice across defined disease stages, while concurrently assessing brain tau pathology via AT8 immunohistochemistry. Recognizing the growing adoption of capillary blood sampling in clinical research and its utility for minimally invasive, repeated collection, we investigated whether capillary-derived biomarkers reflect brain tau pathology to a similar extent as venous measures. In parallel, we assessed the technical feasibility and limitations of detecting large neurodegeneration-related proteins from skin ISF \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis study evaluated whether the concentrations of glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau at threonine 181 (p-Tau181) in minimally invasive biofluids\u0026mdash;capillary blood plasma and skin interstitial fluid (ISF)\u0026mdash;reflect brain tau pathology in PS19 tauopathy model mice. The experimental workflow included the following steps:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eOptimisation of ISF microdialysis using healthy C57BL/6J mice (pilot validation of the skin ISF collection technique).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCollection of biofluids (venous blood plasma, capillary blood plasma, and skin ISF) from PS19 mice and wild-type (WT) littermate controls.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eQuantification of biomarkers (GFAP, NfL, and p-Tau181) in the collected samples using Simoa\u0026reg; ultra-sensitive immunoassays.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBlinded histopathological assessment of brain tau pathology using AT8 immunostaining for phosphorylated tau.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eIn total, 29 PS19 mice and 17 WT mice of both sexes were included in the biomarker analyses, sampled at ages 4, 6, 8, 10, or 12 months. A schematic overview of the study design is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnimals\u003c/h3\u003e\n\u003cp\u003eTo validate the skin ISF collection technique (pilot study), we used three 8-week-old and three 12-month-old male C57BL/6J mice (SLC Japan, Shizuoka, Japan). For the main biomarker experiments, we employed the PS19 tauopathy mouse model (B6;C3-Tg(Prnp-MAPT*P301S)PS19Vle/J, referred to as PS19) and its background strain, B6C3F1/J, as wild-type controls.\u003c/p\u003e \u003cp\u003eThe PS19 and wild-type mice used in this study were obtained by breeding two PS19 transgenic males (Jackson Laboratory stock #008169) with five B6C3F1/J females (stock #100010). Newborn pups were genotyped from tail biopsies to identify hemizygous PS19 transgenics (PS19 Hemi) and wild-type littermates. The final experimental cohort consisted of 29 PS19 Hemi mice (18 females and 11 males) and 17 wild-type mice (10 females and 7 males).\u003c/p\u003e \u003cp\u003eAll mice were group-housed (2\u0026ndash;6 per cage) under a 12-hour light/dark cycle with food and water provided ad libitum. Mice were monitored daily for welfare, and humane endpoints were pre-specified (weight loss\u0026thinsp;\u0026gt;\u0026thinsp;20%, inability to feed, hindlimb paralysis). Sampling was carried out at the ages defined in the Results. No animals were excluded unless they reached humane endpoints or died naturally prior to sampling.\u003c/p\u003e\n\u003ch3\u003eDetection of Albumin from Mouse Skin ISF\u003c/h3\u003e\n\u003cp\u003eMice were anesthetized (4% isoflurane for induction, then maintained at 2% isoflurane) and the hair on the dorsal skin was shaved. A 22G needle (Terumo, Tokyo, Japan) was inserted into the dermis as a guide, and a microdialysis probe (100 kDa cutoff membrane; MAB14.15.4, Microbiotech AB, Stockholm, Sweden) was threaded through the needle tract and left in place under the skin. Skin ISF was collected by perfusing the probe with Ringer\u0026rsquo;s solution (Otsuka Pharmaceutical, Tokyo, Japan) at a flow rate of 5.5\u0026ndash;8.0 \u0026micro;L/min for 20 minutes (see Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eWhile still under anesthesia, a midline laparotomy was performed and venous blood was drawn from the posterior vena cava, immediately mixing it with 0.2% EDTA to prevent coagulation. Immediately thereafter, the posterior aorta was severed to euthanize the animal by exsanguination. The collected blood was centrifuged at 10,000 rpm for 5 minutes at 20\u0026deg;C to separate plasma. Both the skin ISF samples and plasma samples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis.\u003c/p\u003e \u003cp\u003eAlbumin concentrations (\u0026micro;g/mL) in the plasma and ISF were measured colorimetrically as a functional validation of the ISF collection. We used a Mouse Albumin ELISA Kit (Fujifilm Wako, Osaka, Japan) according to the manufacturer\u0026rsquo;s protocol to quantify albumin in each sample.\u003c/p\u003e\n\u003ch3\u003eCollection of Body Fluid Samples from PS19 and Wild‑Type Mice\u003c/h3\u003e\n\u003cp\u003eBody fluid samples and brain tissues were collected from cohorts of PS19 and wild-type mice at 4, 6, 8, 10, and 12 months of age (n\u0026thinsp;=\u0026thinsp;4\u0026ndash;8 mice per genotype at each age; see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for study schema). All sample collections were performed between 9:00 AM and 2:00 PM to minimize the influence of circadian variation on biomarker levels. Mice were anesthetized with 4% isoflurane (induction) and maintained on 2% isoflurane during the procedure. To prevent hypothermia during anaesthesia, animals were placed on a thermostatically controlled heating pad throughout the procedure.\u003c/p\u003e \u003cp\u003eFirst, capillary blood was collected by performing a submandibular puncture: a 5 mm disposable lancet (MediPoint Inc., Mineola, NY, USA) was used just posterior to the mandible to yield approximately 3\u0026ndash;4 drops of blood. Next, using the same microdialysis method described above, at least 55 \u0026micro;L of skin ISF was collected from the dorsal lumbar skin of each mouse (Supplementary Fig.\u0026nbsp;1). Subsequently, a laparotomy was performed, venous blood was drawn from the posterior vena cava, and the posterior aorta was incised to sacrifice the mouse by exsanguination. Death was confirmed by a veterinarian (T.M.) before proceeding to tissue collection. The brain was then immediately removed from the carcass and fixed by immersion in 10% neutral-buffered formalin.\u003c/p\u003e \u003cp\u003eAll blood samples were handled promptly to obtain plasma. Capillary blood and venous blood were transferred to tubes containing 0.2% EDTA-2Na to prevent coagulation. The blood was centrifuged at 10,000 rpm for 5 minutes at 20\u0026deg;C, and the supernatants were collected as plasma. All plasma samples and ISF samples were stored in polypropylene tubes at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis.\u003c/p\u003e\n\u003ch3\u003eTau Pathology Staging\u003c/h3\u003e\n\u003cp\u003eFormalin-fixed brain tissues were processed for histopathological analysis of tau lesions. Each brain was sectioned at approximately 2 mm posterior to bregma (perpendicular to the coronal plane), and the tissue was embedded in paraffin. Sections of 3 \u0026micro;m thickness were cut from the paraffin blocks for immunohistochemistry. After deparaffinization, antigen retrieval was performed by autoclaving the slides in deionized water at 121\u0026deg;C for 20 minutes. Endogenous peroxidase activity was quenched with 3% hydrogen peroxide in methanol, and nonspecific binding was blocked by incubating sections in 1% bovine serum albumin in phosphate-buffered saline. The sections were then incubated with a primary antibody against phosphorylated tau (AT8; Thermo Fisher Scientific/Invitrogen, Carlsbad, CA, USA; 1:50 dilution) to label p-tau deposits. After thorough rinsing, a horseradish peroxidase\u0026ndash;labeled polymer anti-mouse IgG secondary antibody (Dako, Carpinteria, CA, USA) was applied. Immunoreactivity was visualized using a diaminobenzidine (DAB) substrate (ImmPACT DAB Kit, Vector Laboratories, Burlingame, CA, USA), yielding a brown reaction product, and slides were counterstained with hematoxylin.\u003c/p\u003e \u003cp\u003eTau pathology in the brain was evaluated using a simplified six-stage scoring system based on the method of Hurtado et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] (see Supplementary Methods). In brief, multiple brain regions\u0026mdash;including cortical areas, amygdalar nuclei, the hippocampal formation (CA1\u0026ndash;CA3 regions, dentate gyrus, and mossy fiber pathway), hypothalamus, and thalamus\u0026mdash;were examined for AT8-positive tau inclusions. Each region was semi-quantitatively graded for AT8 immunoreactivity on a 0\u0026ndash;3 scale, where 0\u0026thinsp;=\u0026thinsp;no staining, 1\u0026thinsp;=\u0026thinsp;sparse, 2\u0026thinsp;=\u0026thinsp;moderate, and 3\u0026thinsp;=\u0026thinsp;intense. In addition, the presence or absence of AT8-positive deposits in the mossy fibers of the hippocampus was noted separately. Three veterinary pathologists (A.H., N.K., and T.M.) independently scored the slides in a blinded manner, and the mean of their scores for each region was used for analysis. Representative histological images corresponding to tau pathology stages I\u0026ndash;VI are shown in Supplementary Fig.\u0026nbsp;2.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSimoa Biomarker Quantification\u003c/h2\u003e \u003cp\u003eConcentrations of p-Tau181, NfL, and GFAP in the skin ISF, capillary plasma, and venous plasma samples were measured using a Simoa HD-X Analyzer (Quanterix, Lexington, MA, USA), an automated ultra-sensitive digital immunoassay platform. All assays were performed according to the manufacturer\u0026rsquo;s instructions. Prior to measurement, plasma samples were diluted 40-fold and ISF samples 10-fold using the appropriate assay diluent. All samples (from PS19 and wild-type mice) were analyzed in a single batch, using a single lot of reagents and a shared set of calibration standards for consistency. Analyte concentrations were calculated based on a standard curve generated for each biomarker. Any sample reading that fell below the assay\u0026rsquo;s limit of detection was treated as zero for statistical purposes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using GraphPad Prism 8 (GraphPad Software, San Diego, CA, USA). The Mann\u0026ndash;Whitney U test (two-tailed) was used for nonparametric comparisons between two groups. Correlations between biomarker levels (in ISF, venous plasma, and capillary plasma) and brain tau pathology scores were evaluated using Spearman\u0026rsquo;s rank correlation coefficient. Any potential outliers in the data were identified using linear regression residual analysis combined with the ROUT method (Q\u0026thinsp;=\u0026thinsp;1%) for outlier detection.\u003c/p\u003e \u003cp\u003eTo assess the ability of each biomarker to discriminate tau pathology status, receiver operating characteristic (ROC) curve analysis was performed. For each biomarker, the area under the ROC curve (AUC) was calculated along with the 95% confidence interval, and statistical significance was determined. We defined the \u0026ldquo;AT8-positive\u0026rdquo; group as PS19 mice with moderate to severe tau pathology (stages II\u0026ndash;VI) and the \u0026ldquo;AT8-negative\u0026rdquo; group as mice with no or minimal tau pathology (PS19 mice at stage I, plus all wild-type mice). The optimal cutoff value for each biomarker was determined by maximizing the Youden Index (sensitivity\u0026thinsp;+\u0026thinsp;specificity \u0026ndash; 1) to best distinguish AT8-positive cases from AT8-negative cases.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eAlbumin Levels in Plasma and Skin Interstitial Fluid\u003c/h2\u003e\n \u003cp\u003eTo verify the efficacy of the microdialysis method for collecting skin ISF, we conducted pilot experiments in the C57BL/6J mice (8-week-old and 12-month-old males). Albumin concentrations in venous plasma were 64.45 mg/mL (2-month-old, n\u0026thinsp;=\u0026thinsp;3) and 48.13 mg/mL (12-month-old, n\u0026thinsp;=\u0026thinsp;3), with no significant age-related difference (p\u0026thinsp;=\u0026thinsp;0.400, Mann\u0026ndash;Whitney; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In skin interstitial fluid (ISF), albumin levels were 7.37 \u0026micro;g/mL and 5.24 \u0026micro;g/mL in 2-month-old and 12-month-old mice, respectively (n\u0026thinsp;=\u0026thinsp;3 and n\u0026thinsp;=\u0026thinsp;3), also without significant age differences (p\u0026thinsp;=\u0026thinsp;0.400). Across all mice, ISF albumin concentrations were approximately 1/9000 of venous plasma levels.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003ePlasma Biomarker Levels and Association with Tau Pathology\u003c/h2\u003e\n \u003cp\u003eTau pathology increased progressively with age in PS19 mice (n\u0026thinsp;=\u0026thinsp;29), and staging scores were strongly correlated with age (Spearman \u0026rho;\u0026thinsp;=\u0026thinsp;0.716, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). AT8 immunoreactivity first appeared in the amygdala and piriform cortex at 4\u0026ndash;6 months, extended into hippocampal and cortical regions at 8 months, and became widespread by 10\u0026ndash;12 months. No AT8 positivity was observed in wild-type (WT) mice (n\u0026thinsp;=\u0026thinsp;17).\u003c/p\u003e\n \u003cp\u003eVenous plasma concentrations of GFAP, NfL and p-Tau181 were significantly higher in PS19 mice (GFAP: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 192.7\u0026thinsp;\u0026plusmn;\u0026thinsp;149.3 pg/ml, 95% CI of the mean 135.9\u0026ndash;249.4, n\u0026thinsp;=\u0026thinsp;29; NfL: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 1360.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1084.1 pg/ml, 95% CI of the mean 948.3\u0026ndash;1773.1, n\u0026thinsp;=\u0026thinsp;29; p-Tau181: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 4071.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4190.8 pg/ml, 95% CI of the mean 2477.1\u0026ndash;5665.3, n\u0026thinsp;=\u0026thinsp;29) than in WT controls (GFAP: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 38.6\u0026thinsp;\u0026plusmn;\u0026thinsp;49.9 pg/ml, 95% CI of the mean 12.9\u0026ndash;64.3, n\u0026thinsp;=\u0026thinsp;17; NfL: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 95.6\u0026thinsp;\u0026plusmn;\u0026thinsp;89.0 pg/ml, 95% CI of the mean 49.8\u0026ndash;141.4, n\u0026thinsp;=\u0026thinsp;17; p-Tau181: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;39.1 pg/ml, 95% CI of the mean 1.2\u0026ndash;41.5, n\u0026thinsp;=\u0026thinsp;17) (GFAP: p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; NfL: p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; p-Tau181: p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Mann\u0026ndash;Whitney U test; Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn PS19 mice (n\u0026thinsp;=\u0026thinsp;29), venous GFAP strongly correlated with tau pathology (\u0026rho;\u0026thinsp;=\u0026thinsp;0.739, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and venous NfL also showed a significant correlation (\u0026rho;\u0026thinsp;=\u0026thinsp;0.576, p\u0026thinsp;=\u0026thinsp;0.002; Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Venous p-Tau181 did not correlate significantly with pathology (\u0026rho;\u0026thinsp;=\u0026thinsp;0.317, p\u0026thinsp;=\u0026thinsp;0.114).\u003c/p\u003e\n \u003cp\u003eCapillary plasma concentrations of GFAP, NfL and p-Tau181 were also significantly higher in PS19 mice (GFAP: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 224.8\u0026thinsp;\u0026plusmn;\u0026thinsp;245.6 pg/ml, 95% CI of the mean 121.1\u0026ndash;328.5, n\u0026thinsp;=\u0026thinsp;24; NfL: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 1096.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1241.9 pg/ml, 95% CI of the mean 571.7\u0026ndash;1620.6, n\u0026thinsp;=\u0026thinsp;24; p-Tau181: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 4563.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3538.4 pg/ml, 95% CI of the mean 3102.5\u0026ndash;6023.7, n\u0026thinsp;=\u0026thinsp;25) than in WT controls (GFAP: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 39.0\u0026thinsp;\u0026plusmn;\u0026thinsp;26.8 pg/ml, 95% CI of the mean 25.2\u0026ndash;52.8, n\u0026thinsp;=\u0026thinsp;17; NfL: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 78.9\u0026thinsp;\u0026plusmn;\u0026thinsp;67.6 pg/ml, 95% CI of the mean 44.1\u0026ndash;113.6, n\u0026thinsp;=\u0026thinsp;17; p-Tau181: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 33.7\u0026thinsp;\u0026plusmn;\u0026thinsp;32.1 pg/ml, 95% CI of the mean 17.2\u0026ndash;50.2, n\u0026thinsp;=\u0026thinsp;17) (GFAP: p\u0026thinsp;=\u0026thinsp;0.0223; NfL: p\u0026thinsp;=\u0026thinsp;0.0052; p-Tau181: p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Mann\u0026ndash;Whitney U test; Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Plasma concentrations of GFAP, NfL, and p-Tau181 in venous blood and capillary blood showed equivalent values, with no significant differences observed.\u003c/p\u003e\n \u003cp\u003eCapillary plasma levels of GFAP (\u0026rho;\u0026thinsp;=\u0026thinsp;0.671, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and NfL (\u0026rho;\u0026thinsp;=\u0026thinsp;0.669, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) correlated with tau pathology, whereas p-Tau181 did not (\u0026rho;\u0026thinsp;=\u0026thinsp;0.215, p\u0026thinsp;=\u0026thinsp;0.301; Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eTo determine whether biomarker concentrations were influenced by chronological age, we evaluated associations between each plasma biomarker and age in PS19 mice. GFAP and NfL showed moderate monotonic increases with age in both venous and capillary plasma (Spearman \u0026rho; range: 0.45\u0026ndash;0.62; Supplementary Fig.\u0026nbsp;5), consistent with their strong associations with tau pathology. In contrast, p-Tau181 did not show significant age-related changes in either matrix (\u0026rho;\u0026thinsp;\u0026lt;\u0026thinsp;0.25, p\u0026thinsp;\u0026gt;\u0026thinsp;0.10). These analyses indicate that the age dependence of GFAP and NfL largely parallels the progression of tau pathology, whereas p-Tau181 remains age-stable in this model.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eSkin ISF Biomarkers and Tau Pathology\u003c/h2\u003e\n \u003cp\u003eIn PS19 mouse skin ISF, no significant differences were observed for GFAP, NfL, or p-Tau181 (GFAP: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 pg/ml, 95% CI of the mean 1.2\u0026ndash;8.5, n\u0026thinsp;=\u0026thinsp;9; NfL: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 pg/ml, 95% CI of the mean\u0026thinsp;\u0026minus;\u0026thinsp;0.4\u0026ndash;1.6, n\u0026thinsp;=\u0026thinsp;9; p-Tau181: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 29.1\u0026thinsp;\u0026plusmn;\u0026thinsp;45.1 pg/ml, 95% CI of the mean\u0026thinsp;\u0026minus;\u0026thinsp;5.6\u0026ndash;63.7, n\u0026thinsp;=\u0026thinsp;9) compared to wild-type mice (GFAP: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5 pg/ml, 95% CI of the mean\u0026thinsp;\u0026minus;\u0026thinsp;2.9\u0026ndash;17.9, n\u0026thinsp;=\u0026thinsp;4; NfL: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 pg/ml, 95% CI of the mean\u0026thinsp;\u0026minus;\u0026thinsp;0.2\u0026ndash;0.3, n\u0026thinsp;=\u0026thinsp;4; p-Tau181: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD 8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 pg/ml, 95% CI of the mean 4.1\u0026ndash;12.0, n\u0026thinsp;=\u0026thinsp;4) (GFAP: p\u0026thinsp;=\u0026thinsp;0.308, NfL: p\u0026thinsp;\u0026gt;\u0026thinsp;0.999, p-Tau181: p\u0026thinsp;=\u0026thinsp;0.711, Mann\u0026ndash;Whitney U test; Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The concentrations of GFAP, NfL, or p-Tau181 in these skin ISFs were clearly lower than those derived from venous or capillary blood.\u003c/p\u003e\n \u003cp\u003eIn PS19 mice with sufficient ISF yields (n\u0026thinsp;=\u0026thinsp;10), GFAP, NfL and p-Tau181 measured in ISF showed no significant correlations with tau pathology (GFAP: \u0026rho; = \u0026minus;\u0026thinsp;0.072, p\u0026thinsp;=\u0026thinsp;0.855; NfL: \u0026rho; = \u0026minus;\u0026thinsp;0.299, p\u0026thinsp;=\u0026thinsp;0.458; p-Tau181: \u0026rho;\u0026thinsp;=\u0026thinsp;0.118, p\u0026thinsp;=\u0026thinsp;0.766; Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eCross-Matrix Associations Between Venous Plasma, Capillary Plasma and ISF\u003c/h2\u003e\n \u003cp\u003eVenous and capillary plasma concentrations were strongly correlated for GFAP (\u0026rho;\u0026thinsp;=\u0026thinsp;0.830, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; n\u0026thinsp;=\u0026thinsp;23) and NfL (\u0026rho;\u0026thinsp;=\u0026thinsp;0.812, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). No significant venous\u0026ndash;capillary correlation was observed for p-Tau181 (\u0026rho;\u0026thinsp;=\u0026thinsp;0.216, p\u0026thinsp;=\u0026thinsp;0.312). No significant correlations were detected between skin ISF and plasma biomarkers (venous or capillary) in either PS19 or WT mice (Supplementary Figs. 4\u0026ndash;5).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eROC Analysis for Classification of Tau Pathology\u003c/h2\u003e\n \u003cp\u003eTo assess the discriminative performance of plasma biomarkers for tau pathology, PS19 mice with Stage II\u0026ndash;VI pathology were classified as \u0026ldquo;pathology-positive,\u0026rdquo; while Stage I PS19 mice and all WT mice were designated as \u0026ldquo;pathology-negative.\u0026rdquo; Cutoff values for each biomarker were determined using ROC curve analysis.\u003c/p\u003e\n \u003cp\u003eFor GFAP, the optimal cutoff value was 65.7 pg/mL in venous blood plasma (AUC\u0026thinsp;=\u0026thinsp;0.912, 95% CI\u0026thinsp;=\u0026thinsp;0.824\u0026ndash;0.999, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and 122.9 pg/mL in capillary blood plasma (AUC\u0026thinsp;=\u0026thinsp;0.764, 95% CI\u0026thinsp;=\u0026thinsp;0.601\u0026ndash;0.927, p\u0026thinsp;=\u0026thinsp;0.004) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In venous plasma, 4 of 11 Stage II mice fell below the cutoff (false negatives), whereas all 15 mice at Stage III or higher exceeded the threshold. Among 20 pathology-negative mice, only one WT mouse was misclassified as a false positive. In capillary plasma, 5 of 9 Stage II and 2 of 3 Stage III mice fell below the cutoff. All mice with Stage IV or higher pathology were correctly classified as positive. Three of 17 WT mice exceeded the cutoff in capillary plasma (false positives).\u003c/p\u003e\n \u003cp\u003eFor NfL, the cutoff in venous plasma was 538.6 pg/mL (AUC\u0026thinsp;=\u0026thinsp;0.883, 95% CI\u0026thinsp;=\u0026thinsp;0.783\u0026ndash;0.983, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and 364.6 pg/mL in capillary plasma (AUC\u0026thinsp;=\u0026thinsp;0.810, 95% CI\u0026thinsp;=\u0026thinsp;0.669\u0026ndash;0.950, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In venous plasma, 5 of 11 Stage II and 2 of 3 Stage III mice were false negatives. All Stage IV or higher mice exceeded the threshold, and no false positives were observed among pathology-negative mice. In capillary plasma, the same pattern was observed: 5 of 9 Stage II and 2 of 3 Stage III mice fell below the cutoff, while all Stage IV or higher mice were correctly classified. No false positives were observed among pathology-negative mice.\u003c/p\u003e\n \u003cp\u003eFor p-Tau181, the venous plasma cutoff was 1,295.0 pg/mL (AUC\u0026thinsp;=\u0026thinsp;0.958, 95% CI\u0026thinsp;=\u0026thinsp;0.889\u0026ndash;1.000, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and 975.7 pg/mL in capillary plasma (AUC\u0026thinsp;=\u0026thinsp;0.897, 95% CI\u0026thinsp;=\u0026thinsp;0.786\u0026ndash;1.000, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). In venous plasma, 2 of 11 Stage II mice were false negatives, while all mice at Stage III or above exceeded the threshold. One of 3 Stage I PS19 mice exceeded the cutoff, resulting in a false positive among pathology-negative animals. In capillary plasma, 2 of 3 Stage III mice were false negatives, while all Stage IV or higher mice exceeded the cutoff. However, 2 of 3 Stage I PS19 mice showed false positives in capillary plasma.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eROC Curve Analysis of Plasma Biomarkers for Classifying Brain Tau Pathology\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eVenous blood\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCapillary blood\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGFAP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNfL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-Tau181\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGFAP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNfL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-Tau181\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensitivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCutoff value (pg/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e538.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1295 .0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e364.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e975.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT8+: 26, AT8-: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT8+: 26, AT8-: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT8+: 26, AT8-: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT8+: 22, AT8-: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT8+: 21, AT8-: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT8+: 21, AT8-: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-value (X\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8242 \u003cstyle\u003e\n .cf0 {\n font-family: Segoe UI;\n font-size: 10.5pt;\n }\n \u003c/style\u003e~ 0.9989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7827 \u003cstyle\u003e\n .cf0 {\n font-family: Segoe UI;\n font-size: 10.5pt;\n }\n \u003c/style\u003e~ 0.9827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8891 \u003cstyle\u003e\n .cf0 {\n font-family: Segoe UI;\n font-size: 10.5pt;\n }\n \u003c/style\u003e~ 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6012 \u003cstyle\u003e\n .cf0 {\n font-family: Segoe UI;\n font-size: 10.5pt;\n }\n \u003c/style\u003e~ 0.9273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6689 \u003cstyle\u003e\n .cf0 {\n font-family: Segoe UI;\n font-size: 10.5pt;\n }\n \u003c/style\u003e~ 0.9501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7863 \u003cstyle\u003e\n .cf0 {\n font-family: Segoe UI;\n font-size: 10.5pt;\n }\n \u003c/style\u003e~ 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003ePathology-positive cases were defined as PS19 mice with Stage II\u0026ndash;VI tau pathology (AT8+), and pathology-negative cases as PS19 mice at Stage I or wild-type mice (AT8-). Cutoff values were determined by ROC analysis using the maximum Youden index. AUC, area under the curve; CI, confidence interval.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the relationships between Alzheimer\u0026rsquo;s disease\u0026ndash;related fluid biomarkers and brain tau pathology in PS19 mice using venous plasma, capillary blood, and skin ISF. Our findings align with recent human studies demonstrating strong concordance between capillary and venous blood measurements of GFAP and NfL [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], reinforcing the biological robustness of capillary sampling. Importantly, the present work extends these observations by anchoring biomarker levels to histopathologically staged tau pathology, thereby providing mechanistic validation that cannot be obtained from clinical or imaging-based cohorts alone. Among the three biomarkers examined, GFAP and NfL consistently tracked the severity of tau pathology in both venous and capillary blood, whereas p-Tau181 did not show a significant correlation with histopathological burden. The strong agreement between capillary and venous concentrations of GFAP and NfL further supports the feasibility of using minimally invasive peripheral sampling to monitor central neurodegenerative processes. Notably, capillary sampling via lancet puncture enables repeated measurements with minimal technical expertise, providing a practical avenue for longitudinal biomarker studies in mouse models and translational applications in humans [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGFAP has emerged as a sensitive indicator of astrocytic activation and disease progression in tauopathies and Alzheimer's disease [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In agreement with these observations, the present study found that GFAP in both venous and capillary plasma increased in parallel with tau pathology in PS19 mice, and the two matrices exhibited a strong correlation. The ROC-derived venous plasma cutoff (65.7 pg/mL) showed high sensitivity and specificity, whereas capillary-derived GFAP demonstrated reduced sensitivity despite high specificity. Several factors may contribute to this difference. GFAP is expressed in peripheral tissues [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and local skin stimulation from lancet puncture may transiently influence GFAP levels in capillary samples. Additionally, biomarker concentrations in capillary blood may be more susceptible to pre-analytical variability and local microvascular dynamics. Given the limited sample size in this study, larger cohorts will be required to confirm optimal thresholds and assess their stability across age and pathology stages.\u003c/p\u003e \u003cp\u003eNfL strongly correlated with tau pathology in both venous and capillary blood, and the two plasma sources were highly concordant. These findings are consistent with human studies reporting strong correlations between capillary and venous NfL, as well as high analytical reproducibility in finger-prick sampling [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. ROC analysis demonstrated high discriminatory performance for venous NfL and modestly lower performance for capillary NfL. Similar to GFAP, sensitivity of the capillary measurements may be influenced by sample volume constraints and technical variability during peripheral sampling. Nevertheless, both venous and capillary NfL values exceeded their respective thresholds in all animals with advanced (stage IV or higher) pathology, indicating that NfL reliably reflects the onset and progression of widespread axonal injury in this tauopathy model.\u003c/p\u003e \u003cp\u003eAlthough p-Tau181 distinguished PS19 from wild-type mice with high ROC accuracy, its concentrations did not correlate with histopathological tau burden in either venous or capillary plasma. These findings align with reports that p-Tau181 may be more reflective of amyloid-related processes than of tau tangle accumulation itself [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Another likely factor is assay specificity. The Simoa assay used in this study primarily quantifies N-terminal tau fragments (Np-pTau181). However, tau undergoes sequential C-terminal and N-terminal cleavages during neurofibrillary tangle (NFT) maturation, including early cleavage at D421 and subsequent truncations [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. As a result, N-terminal\u0026ndash;based assays may not adequately capture the tau species predominant in later-stage pathology.\u003c/p\u003e \u003cp\u003eNotably, despite the lack of linear correlation with tau burden, capillary p-Tau181 effectively discriminated between AT8-positive and AT8-negative brains. This suggests potential utility as a binary classifier of pathological presence, offering a simple and minimally invasive method to monitor major transitions in tau pathology. Such application may be particularly valuable in longitudinal or screening contexts where full pathological quantification is impractical.\u003c/p\u003e \u003cp\u003eRecent advances, such as mid-p-tau assays [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and MTBR-tau (e.g., p-Tau243) assays, detect a broader spectrum of tau fragments, including regions implicated in paired-helical filament (PHF) formation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These emerging markers show stronger associations with tau PET and clinical progression than p-Tau181 in several human studies. Incorporating assays that target mid-region or microtubule-binding-region tau species, together with optimizing pre-analytical processes, may improve the ability of plasma tau biomarkers to more accurately reflect tau pathology.\u003c/p\u003e \u003cp\u003eGFAP, NfL, and p-Tau181 in skin ISF did not correlate with brain pathology or plasma biomarker concentrations. Several technical issues may contribute. Microdialysis can alter ISF composition due to mechanical disruption, immune activation, and dilution effects [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Recovery efficiency is influenced by flow rate, probe permeability, diffusion gradients, and molecular size [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The ISF albumin concentration measured here was ~\u0026thinsp;1/9000 of plasma, suggesting substantial dilution or altered protein recovery. Additionally, probe-to-probe variability may affect detection sensitivity, particularly for low-abundance proteins. Future optimization of ISF sampling\u0026mdash;such as improved microdialysis membranes, recovery correction factors, or alternative dermal sampling platforms\u0026mdash;will be necessary to evaluate whether ISF can reliably reflect neurodegenerative biomarkers. In contrast to blood-based studies, the lack of association between ISF biomarkers and tau pathology observed here highlights current technical limitations of dermal ISF sampling for large neurodegeneration-related proteins.\u003c/p\u003e \u003cp\u003eA key limitation of this study is that Simoa measurements were performed once per sample due to limited sample volume, particularly for capillary blood and skin ISF. This restricted the ability to assess analytical variability and reproducibility. Outlier detection using ROUT (Q\u0026thinsp;=\u0026thinsp;1%) identified several values in venous and capillary plasma (Supplementary Fig.\u0026nbsp;6); however, the biological or technical basis for these deviations could not be fully explored. Ultra-sensitive platforms capable of analysing micro-volumes with lower variability may benefit future work. In addition, the semi-quantitative tau pathology staging used here, although designed to capture regionally distributed pathology, may not fully reflect incremental differences in total tau burden, particularly at higher stages (e.g., stage V vs. VI). This may have limited the resolution of correlation analyses between brain pathology and fluid biomarker levels.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates that GFAP and NfL measured from capillary blood reliably mirror venous concentrations and correlate with the severity of tau pathology in PS19 mice, supporting their potential as minimally invasive biomarkers for neurodegeneration. p-Tau181 showed high group-level discriminatory accuracy but limited capacity to track pathology severity, likely reflecting assay-specific and disease-stage-specific factors. Skin ISF biomarkers did not correlate with pathology under current sampling conditions, emphasizing the need for further methodological refinements.\u003c/p\u003e \u003cp\u003eTogether, these findings highlight the feasibility of capillary blood biomarker assessment for longitudinal monitoring in mouse models and indicate promising translational relevance for early, low-burden biomarker testing. Continued improvements in assay sensitivity, tau epitope coverage, and ISF sampling technologies are expected to enhance the precision and applicability of minimally invasive biomarkers for Alzheimer\u0026rsquo;s disease and related tauopathies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlzheimer\u0026rsquo;s disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAT8\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntibody against phosphorylated tau (Ser202/Thr205)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCapillary blood\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnzyme-linked immunosorbent assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGFAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlial fibrillary acidic protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunohistochemistry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eISF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterstitial fluid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNfL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeurofilament light chain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphate-buffered saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ep-Tau181\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphorylated tau at threonine 181\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSimoa\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSingle molecule array\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVenous blood\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWild-type\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eAll animal procedures were conducted in accordance with institutional guidelines and were approved by the Animal Experiment Committee of Tokyo University of Agriculture and Technology (Approval Nos. R05-21 and R06-106). The use of PS19 mice was additionally approved by the university\u0026rsquo;s Biosafety Subcommittee (Approval No. R4-99).\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the MRC-AMED UK\u0026ndash;Japan collaboration project \u0026ldquo;Multi-analyte prognostic and diagnostic screening in blood and skin for Alzheimer\u0026rsquo;s disease\u0026rdquo; (MR/X02153X/1 to SS and 22jm0210099h0001 to KT).\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eKT and TM conceptualized and supervised the study. AH, NK, KT, YY, and AN performed the experiments. KT and TM analyzed the data and wrote the manuscript. All authors reviewed and approved the final version of the manuscript. Conceptualization: SS, KT, TM. Methodology: AH, SS, TT, MH, KT, TM. Investigation: AH, NK, TM. Visualization: AH, TM. Funding acquisition: SS, KT. Resources: SS, TT, MH. Project administration: KT, TM. Supervision: SS, KT, TM. Writing \u0026ndash; original draft: AH, TM. Writing \u0026ndash; review \u0026amp; editing: All authors.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank the members of the Laboratory of Veterinary Toxicology at Tokyo University of Agriculture and Technology for their support with animal experiments. We also acknowledge Ms. Sayo Matsuura (National Institute for Quantum Science and Technology) for her expert technical assistance with Simoa analyses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNichols E, Steinmetz JD, Vollset SE, Fukutaki K, Chalek J, Abd-Allah F, et al. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. Lancet Public Health. 2022;7:e105\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2468-2667(21)00249-8\u003c/span\u003e\u003cspan address=\"10.1016/S2468-2667(21)00249-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedroza P, Miller-Petrie MK, Chen C, Chakrabarti S, Chapin A, Hay S, et al. 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Ultraslow microdialysis and microfiltration for in-line, on-line and off-line monitoring. Trends Biotechnol. 2010;28:150\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tibtech.2009.12.005\u003c/span\u003e\u003cspan address=\"10.1016/j.tibtech.2009.12.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alzheimer’s disease, Tau pathology, minimally invasive biomarkers, GFAP, NfL, pTau181, capillary blood, interstitial fluid, PS19 mice, single molecule array (Simoa)","lastPublishedDoi":"10.21203/rs.3.rs-8912963/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8912963/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAlzheimer\u0026rsquo;s disease (AD) is characterized by progressive tau pathology and neurodegeneration. While blood-based biomarkers such as glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau at threonine 181 (p-Tau181) are increasingly utilized for detecting these pathological processes, conventional venous blood sampling poses limitations for frequent and decentralized monitoring. This study aimed to evaluate the utility of capillary blood and skin interstitial fluid (ISF) as minimally invasive matrices for monitoring tau-related pathology in a tauopathy mouse model.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eMicrodialysis-based ISF collection was first optimized in C57BL/6J mice to confirm protein recovery and minimize blood contamination. Venous plasma, capillary plasma, and ISF were subsequently collected from PS19 tauopathy mice (n\u0026thinsp;=\u0026thinsp;29) and wild-type mice (n\u0026thinsp;=\u0026thinsp;17) at defined disease stages (4\u0026ndash;12 months of age). Concentrations of GFAP, NfL, and p-Tau181 were quantified using the Simoa platform. Tau pathology was assessed by AT8 immunohistochemistry. Statistical analyses included Spearman correlation, linear regression, and receiver operating characteristic (ROC) curve analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn PS19 mice, both venous and capillary plasma concentrations of GFAP and NfL significantly correlated with brain tau pathology scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Capillary plasma levels closely mirrored venous concentrations, with strong cross-matrix correlations. In contrast, p-Tau181 levels did not consistently correlate with pathological burden in either matrix. ISF levels of all biomarkers showed no significant correlation with brain pathology or plasma levels, likely due to technical limitations of microdialysis and the inherently low protein concentration in ISF.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eCapillary blood\u0026ndash;derived GFAP and NfL reliably reflect tau-related neurodegeneration in PS19 mice and represent promising minimally invasive biomarkers suitable for longitudinal and translational research. In contrast, current ISF sampling approaches are insufficient for AD biomarker detection and require further methodological refinement.\u003c/p\u003e","manuscriptTitle":"Capillary Plasma GFAP and NfL Track In Vivo Tauopathy Progression in PS19 Mice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-20 04:47:34","doi":"10.21203/rs.3.rs-8912963/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f7d8d357-599a-4658-8fbd-fe4703e367d2","owner":[],"postedDate":"February 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T15:10:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-20 04:47:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8912963","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8912963","identity":"rs-8912963","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}