Peripheral immunity affects Alzheimer’s disease by influencing blood-brain barrier function | 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 Peripheral immunity affects Alzheimer’s disease by influencing blood-brain barrier function Jia-Hui Hou, De-Ming Jiang, Min Chu, Li-Yong Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4437508/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 The association between peripheral immunity and Alzheimer's disease (AD) has been increasingly recognized, but the underlying mechanisms are still unclear. This study aims to investigate whether peripheral immunity affects AD by influencing blood-brain barrier (BBB) function. Methods Multiple linear regression models were employed to explore the association between peripheral immune biomarkers [neutrophils percent (NEU%), lymphocytes percent (LYM%), and neutrophils / lymphocytes (NLR)] and AD biomarkers (including AD pathology, cerebral atrophy degree, and cognitive function). Subsequently, multiple linear regression models were performed to investigate the association between BBB-related biomarkers [chemotactic factor-3 (CCL26), CD40 and matrix metalloproteinase-10 (MMP10)] and AD biomarkers. Finally, causal mediation analysis with 10,000 bootstrapped iterations was conducted to investigate the functions of BBB-related biomarkers in mediating the associations peripheral immune biomarkers with AD pathology, cerebral atrophy degree, as well as cognitive function. Results A total of 543 participants (38.7% female, mean age of 74.8 years) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were involved. NEU%, LYM%, NLR, and CCL26 were significantly associated with cerebrospinal fluid (CSF) β-amyloid-42 (Aβ-42), phosphorylated-tau (P-tau), total tau (T-tau)/Aβ-42 and P-tau/Aβ-42, the associations of NEU% with AD pathology were mediated by CCL26 (proportion: 18% ~ 24%; p < 0.05). NEU%, LYM%, NLR, CCL26, CD40 and MMP10 were significantly associated with whole brain, hippocampal volume, middle temporal lobe (MTL) volume, and entorhinal cortex (EC) thickness, the associations of peripheral immune biomarkers with cerebral atrophy degree were mediated by BBB-related biomarkers (proportion: 7% ~ 17%; p < 0.05). NEU%, LYM%, NLR, CCL26, CD40 and MMP10 were significantly associated with global cognition, executive function, memory function, immediate recall, and delayed recall, the associations of peripheral immune biomarkers with cognitive function were mediated by BBB-related biomarkers (proportion: 9% ~ 24%; p < 0.05). Conclusions This study suggests that both peripheral immune and BBB-related biomarkers are associated with AD pathology deposition, cerebral atrophy degree and cognitive function, and peripheral immunity may influence AD through influencing BBB function, providing a more robust and comprehensive evidence chain for the potential role of inflammation in AD. Peripheral immunity blood brain barrier Alzheimer’s disease Mediation Figures Figure 1 Figure 2 Figure 3 Background Alzheimer's disease (AD) is a prevalent neurodegenerative disease characterized by a gradual decline in memory and other cognitive abilities, which not only greatly reduces the quality of life of patients, but also imposes a heavy burden on families and society[ 1 ]. With the aging population and population growth, the number of AD patients will continue to increase[ 2 ]. Currently available treatments can only slow down the progression of AD, effective drugs have not yet been found, mainly due to an incomplete understanding of the disease mechanism and the complexity of the disease. AD is characterized by two core pathological features, namely β-amyloid (Aβ) in senile plaques and neurofibrillary tangles (NFT) composed of hyperphosphorylated Tau (P-tau) protein[ 3 ]. Persistent brain inflammation has emerged as the third core pathological feature of AD[ 4 , 5 ]. It was previously believed that the brain inflammatory responses were confined to the central nervous system (CNS) without being influenced by peripheral immune events. However, accumulating research indicates that AD is a systemic disease, peripheral immune system also plays a crucial role in the onset of AD[ 6 ], both peripheral innate and adaptive immunity are involved in AD pathogenesis[ 7 ], and many mediators secreted by peripheral immune cells can lead to neuronal degeneration[ 8 ]. However, the mechanisms by which peripheral immune cells affect the cerebrospinal fluid (CSF) pathology, cerebral atrophy and cognitive function are not yet fully understood. As the necessary passage for peripheral immune cells to enter the CNS, in the normal state, the blood-brain barrier (BBB) serves as a vital physiological barrier that separates the CNS from harmful substances and immune cells in the peripheral circulation, it is essential for maintaining internal balance and normal neuronal function. However, in the pathological state of AD, BBB function is impaired, and BBB damage may occur before the infiltration of peripheral immune cells locally[ 9 , 10 ]. Previous studies have reported that under inflammatory conditions, the breakdown of the BBB leads to the infiltration of peripheral immune cells into the CNS[ 11 ], and the inflammatory mediators released by peripheral immune cells will further increase the permeability of the BBB, exacerbating the deposition of Aβ and tau in AD patients, further triggering the inflammatory responses[ 12 , 13 ], this established a vicious positive feedback cycle. However, there has been no exploration in human studies on whether peripheral immunity affect AD by influencing BBB function. Herein, we explored the associations of peripheral immune biomarkers [neutrophils percent (NEU%), lymphocytes percent (LYM%), and neutrophils/lymphocytes (NLR)] and BBB-related biomarkers [chemotactic factor-3 (CCL26), CD40 and matrix metalloproteinase-10 (MMP10)] with cognition, neuroimaging, and AD pathology, and to explore whether the associations between peripheral immunity with AD were mediated by BBB-related biomarkers. Materials and Methods Participants Data applied in this study were acquired from the ADNI database ( http://adniloni.usc.edu ), which is designed to test biochemical, clinical biomarkers, genetics and imaging of AD. Participants received systematic neuropsychological evaluations, as well as neurological and physical examinations at baseline and follow-up, and were offered biological samples such as CSF, blood, and urine throughout the study. This multisite longitudinal biomarker research program authorized by the institutional review committee at all participating locations has acquired written informed consent from participants. This study population is composed of all cognitively normal (CN), mild cognitive impairment (MCI), and AD participants with available routine blood test and BBB -related biomarkers. Peripheral immune and BBB-related biomarkers Peripheral immune biomarkers and BBB-related biomarkers were examined in a subset of participants from ADNI-1 study. Plasma samples were drawn by trained professionals from the venous blood in the morning after an overnight fast and were sent for analysis on the same day. Routine blood test was analyzed using an automated system, more method details could be found at http://adni.loni.usc.edu . Target blood indicators were analyzed using Luminex immunofluorescence multiplex assays following a standardized protocol. All peripheral immune biomarkers included in this analysis included the count and percentage of neutrophils, lymphocytes. BBB-related plasma biomarkers included in this analysis included CCL26, CD40 and MMP10. CSF measurements CSF was sampled by lumbar puncture, with CSF Aβ-42, total tau (T-tau), and P-tau measured at the ADNI Biomarker Core Laboratory (University of Pennsylvania) using an xMap Luminex platform with INNO-BIA AlzBio3 (Ghent, Belgium; for research use only reagents) immune assay kit-based reagents and analyzed on an automatic Elecsys cobas e 601 instrument (F. Hoffmann-La Roche) by an advanced technology known as electrochemiluminescence immunoassays (Elecsys; Roche Diagnostics, F. Hoffmann-La Roche, Basel, Switzerland). Neuroimaging Brain structural images were obtained using a 1.5 T MRI imaging system, acquiring T1-weighted, T2-weighted, and T2 fluid-attenuated inversion recovery (FLAIR) sequences MRI scans through fast gradient-echo sequences prepared with sagittal volumetric magnetization. Cortical thickness and subcortical volume were quantified using software ( https://surfer.nmr.mgh.harvard.edu/ ). Brain structures related to cognitive function including degree of atrophy of hippocampal volume, middle temporal lobe (MTL) volume, whole brain volume, and the entorhinal cortex (EC) thickness were included in the analysis. Neurocognitive Measures Cognitive function was assessed using several neuropsychological scales. Specifically, global cognitive function was evaluated through the Alzheimer’s Disease Assessment Scale (ADAS) and the Clinical Dementia Rating Sum of Boxes (CDRSB). Cognitive domains include memory, executive function, and verbal function. The ADNI memory composite score (MEM) is assessed based on the word recall item from the MMSE, word list learning and recognition tasks from ADAS-Cog, Rey Auditory Verbal Learning task, and Logical Memory I from the Wechsler Memory Test-Revised. The ADNI executive function score (EF) is evaluated based on Clock Drawing items, Wechsler Adult Intelligence Scale-Revised Digit-Symbol Substitution, Category Fluency, Trail-Making Test Parts A and B, and Digit Span Backwards[ 14 , 15 ]. Tests used to assess verbal memory include the total immediate recall score across five learning trials (RAVLT-Immediate) and logical memory delayed recall score from the Rey Auditory Verbal Learning Test (RAVLT-Delayed). Statistical analysis The study subjects were divided into CN group, MCI group, and AD group. Categorical variables were represented using numbers (percentages), and continuous variables were represented as means ± standard deviations (SD). Firstly, chi-square analysis and non-parametric tests were employed to examine intergroup differences. Subsequently, extreme values exceeding 3 SDs from the mean were removed, and individual analytes were normalized through Box-Cox transformation. We utilized multiple linear regression models to assess the correlations between various peripheral immune biomarkers/ BBB-related biomarker (independent variables) and dependent variables including AD pathology (CSF biomarkers), neuroimaging (brain structure), and cognition (global cognition, immediate memory, delayed memory, as well as MEM and EF). Then, mediation analysis was conducted using the “mediate”, “car”, and “lm” packages in R software (version 4.0.3) to explore whether the association between peripheral immune biomarkers and AD pathology deposition, cerebral atrophy degree and cognitive function is mediated by BBB-related biomarkers. The premise of establishing the model is that both the independent and mediating variables are significantly correlated with the dependent variable in linear regression analysis. Linear regression models were fitted based on the method proposed by Baron and Kenny[ 16 ]. The first equation demonstrates the influence of the independent variable on the mediating variable. The second equation shows the effect of the mediating variable on the dependent variable after controlling for the influence of the independent variable. The third equation presents the total effect of the independent variable on the dependent variable, the direct effect of the independent variable on the dependent variable after controlling for the influence of the mediating variable, and the indirect effect of the independent variable on the dependent variable without controlling for the influence of the mediating variable. All covariates in the correlation analyses included gender, age, APOE ε4 status, and education level, with total intracranial volume added as a covariate when the dependent variable was related to brain structure. Two-tailed p < 0.05 was considered significant. Graphs and statistical analyses were conducted using R software (version 4.0.3), GraphPad Prism 7.00 (San Diego, California), and IBM SPSS Statistics 26. Results Characteristics of Participants The present analysis included 543 participants, consisting of 57 CN, 381 MCI, and 105 AD participants. The whole population had a female proportion of 38.67%, an age ranges from 54 to 90 years old (74.79 ± 7.39 years old), and an APOE ε4 positive percentage of 51.57% (Table 1 ). Except for basic demographics, APOE ε4 carriers, peripheral immune biomarkers, BBB-related biomarkers, CSF biomarker levels, brain structure and levels of cognitive scores all illustrated statistically significant inter-group differences (p < 0.05). Table 1 Basic characteristics of population included Characteristics CN MCI AD P Number 57 381 105 Age (years) 75.15 ± 5.81 74.76 ± 7.40 74.70 ± 8.15 0.950 Female gender (%) 28 (49.12) 137 (35.96) 45 (42.86) 0.100 Education (years) 15.67 ± 2.81 15.62 ± 3.07 15.10 ± 3.27 0.320 APOE ε4 carriers (%) 5 (8.77) 202 (53.02) 73 (69.52) < 0.001 Peripheral immune biomarkers NEU% 60.00 ± 8.52 62.81 ± 7.85 64.60 ± 7.27 0.002 LYM % 30.00 ± 7.96 27.32 ± 7.16 26.15 ± 6.30 0.009 NLR 2.22 ± 0.99 2.57 ± 1.14 2.68 ± 1.04 0.013 BBB-related biomarkers CCL26 (pg/mL) 2.40 ± 0.41 2.60 ± 0.25 2.61 ± 0.22 < 0.001 CD40 (ng/mL) -0.11 ± 0.12 -0.13 ± 0.13 -0.09 ± 0.12 0.016 MMP10 (ng/ml) -1.29 ± 0.18 -1.36 ± 0.21 -1.27 ± 0.22 < 0.001 CSF Biomarkers Aβ (pg/ml) 1338.66 ± 244.87 748.81 ± 343.12 605.76 ± 242.94 < 0.001 P-tau (pg/ml) 19.76 ± 6.45 30.43 ± 14.44 35.57 ± 14.63 < 0.001 T-tau (pg/ml) 223.82 ± 72.32 307.28 ± 123.21 353.14 ± 126.69 < 0.001 T-tau/Aβ-42 0.15 ± 0.04 0.50 ± 0.29 0.65 ± 0.28 < 0.001 P-tau/Aβ-42 0.01 ± 0.003 0.05 ± 0.03 0.07 ± 0.03 < 0.001 Brain structure Whole brain((mm³) 1001211.14 ± 97000.10 996490.91 ± 110299.43 971594.82 ± 119575.59 0.093 Hippocampal volume(mm³) 7311.54 ± 835.55 6405.05 ± 1078.12 5774.57 ± 1158.67 < 0.001 MTL volume (mm³) 19760.56 ± 2715.02 18594.48 ± 3000.66 17088.78 ± 3379.54 < 0.001 EC thickness (mm) 3863.04 ± 674.52 3301.98 ± 752.71 2773.79 ± 671.70 < 0.001 Cognitive scores ADAS 9.51 ± 4.12 18.52 ± 6.14 28.50 ± 7.86 < 0.001 CDRSB 0.03 ± 0.11 1.59 ± 0.86 4.34 ± 1.60 < 0.001 MEM 0.98 ± 0.42 -0.06 ± 0.60 -0.78 ± 0.53 < 0.001 EF 0.59 ± 0.69 0.00 ± 0.88 -0.95 ± 0.88 < 0.001 RAVLT-immediate Recall 41.53 ± 7.21 30.75 ± 9.17 23.29 ± 7.36 < 0.001 RAVLT-Delayed Recall 12.53 ± 3.50 3.85 ± 2.67 1.35 ± 1.85 < 0.001 Abbreviations: CN, cognitively normal; MCI, mild cognitive impairment; AD, Alzheimer’s disease; NEU, Neutrophils; LYM, Lymphocytes; NLR, Neutrophil–lymphocyte ratio; CCL26, eosinophil chemotactic factor-3; MMP10, matrix metalloproteinase-10; CSF, cerebrospinal fluid; Aβ, β-Amyloid; P-tau, phosphorylated-tau; T-tau, total tau; MTL: middle temporal lobe; EC, entorhinal cortex; CDRSB, Clinical Dementia Rating Sum of Boxes; ADAS, Alzheimer's Disease Assessment Scale; MEM, memory function; EF, executive function; RAVLT-immediate, Rey Auditory Verbal Learning Test-immediate-total immediate recall score; RAVLT-Delayed Recall, Rey Auditory Verbal Learning Test- logical memory delayed recall score; Values are mean ± standard deviation (SD), or n (% of the group). Associations of peripheral immune biomarker with BBB-related biomarkers. As is shown in Additional file 1, Individuals with higher NEU% and NLR level were associated with elevated levels of CCL26 (β = 0.119, p = 0.006 for NEU% and β = 0.124, p = 0.005 for NLR), CD40 (β = 0.101, p = 0.015 for NEU% and β = 0.111, p = 0.009 for NLR), and MMP10 (β = 0.144, p < 0.001 for NEU% and β = 0.187, p < 0.001 for NLR). On the contrary, individuals with elevated LYM% were associated with the decrease in CCL26 (β = -0.101, p = 0.015), CD40 (β = -0.132, p = 0.002), and MMP10 (β = -0.141, p = 0.001). Associations of peripheral immune biomarkers with AD pathology. As is shown in Fig. 1 A and Additional file 2, peripheral immune biomarkers have significant correlations with AD pathology. Individuals with higher NEU% and NLR level were associated with lower CSF Aβ-42 (β = -0.111, p = 0.003 for NEU% and β = -0.148, p = 0.027 for NLR), higher CSF P-tau (β = 0.116, p = 0.044 for NEU% and β = 0.126, p = 0.042 for NLR), higher T-tau/Aβ-42 (β = 0.109, p = 0.038 for NEU% and β = 0.150, p = 0.023 for NLR), and higher P-tau/Aβ-42 (β = 0.104, p = 0.046 for NEU% and β = 0.161, p = 0.014 for NLR). On the contrary, individuals with elevated LYM% were associated with higher CSF Aβ-42 (β = 0.125, p = 0.049), lower T-tau/Aβ-42 (β = -0.145, p = 0.020), and lower P-tau/Aβ-42 (β = -0.104, p = 0.016). Associations of BBB-related biomarkers with AD pathology. As is shown in Fig. 1 A and Additional file 2, BBB-related biomarkers also have significant correlations with AD CSF pathology. Individuals with elevated CCL26 were associated with lower CSF Aβ-42 (β = -0.183, p < 0.001), higher T-tau/Aβ-42 (β = 0.141, p = 0.007), and higher P-tau/Aβ-42 (β = 0.141, p = 0.008). Causal mediation analyses in AD pathology. BBB-related biomarkers mediated the correlation between peripheral immune biomarkers with AD pathology. The indirect and total effects of NEU% on AD pathology, including Aβ-42 (Fig. 1 B), T-tau/Aβ-42 (Fig. 1 C), and P-tau/Aβ-42 (Fig. 1 D) reached statistical significance (p 0.05), indicating that all the associations of NEU% with Aβ-42, T-tau/Aβ-42 and P-tau/Aβ-42 were completely mediated by CCL26, with the ratio of mediation ranging from 18–24%. Associations of peripheral immune biomarkers with AD cerebral atrophy. As is shown in Fig. 2 A and Additional file 3, peripheral immune biomarkers have significant correlations with AD cerebral atrophy. Individuals with elevated NEU% and NLR were associated with smaller whole brain volume (β = -0.073, p = 0.001 for NEU% and β = -0.077, p = 0.001 for NLR), smaller hippocampal volume (β = -0.167, p < 0.001 for NEU% and β = -0.162, p < 0.001 for NLR), smaller MTL volume (β = -0.080, p = 0.041 for NEU% and β = -0.106, p = 0.012 for NLR), as well as lesser EC thickness (β = -0.140, p = 0.002 for NEU% and β = -0.134, p = 0.004 for NLR). On the contrary, individuals with elevated LYM% was associated with greater whole brain volume (β = 0.083, p < 0.001), greater hippocampal volume (β = 0.183, p < 0.001), greater MTL volume (β = 0.107, p = 0.008), as well as thicker EC thickness (β = 0.156, p < 0.001). Associations of BBB-related biomarkers with AD cerebral atrophy. As is shown in Fig. 2 A and Additional file 3, individuals with elevated CCL26 were associated with smaller whole brain volume (β = -0.065, p = 0.004), smaller MTL volume (β = -0.123, p = 0.003), as well as lesser EC thickness (β = -0.014, p = 0.003). Individuals with elevated CD40 were associated with smaller whole brain volume (β = -0.074, p = 0.002), smaller hippocampal volume (β = -0.135, p = 0.001), as well as smaller MTL volume (β = -0.098, p = 0.017). Individuals with elevated MMP10 were associated with smaller whole brain volume (β = -0.076, p < 0.001) and smaller MTL volume (β = -0.101, p = 0.010). Causal mediation analyses in AD cerebral atrophy As shown in Fig. 2 B, BBB-related biomarkers mediated the correlation between peripheral immune biomarkers and regions of interest (ROI) atrophy, CCL26 mediated the associations of NEU%, LYM% and NLR with whole brain, MTL volume and EC thickness, with the ratio of mediation ranging from 7–13%. CD40 mediated associations of NEU%, LYM%, and NLR with whole brain, hippocampal volume, and MTL volume, with the ratio of mediation ranging from 9–13%. MMP10 mediated the associations of NEU%, LYM%, and NLR with whole brain, and MTL volume, with the ratio of mediation ranging from 10–17%. Specific intermediate data can be seen in Additional file 4. Associations of peripheral immune biomarkers with cognitive function. As is shown in Fig. 3 A and Additional file 5, peripheral immune biomarkers have significant correlations with AD cognitive function. Individuals with elevated NEU% and NLR were associated with higher ADAS score (β = 0.124, p = 0.002 for NEU% and β = 0.097, p = 0.021 for NLR), higher CDRSB score (β = 0.128, p = 0.002 for NEU% and β = 0.103, p = 0.016 for NLR), lower MEM score (β = -0.175, p = 0.004 for NEU% and β = -0.214, p = 0.013 for NLR), lower EF score (β = -0.127, p = 0.015 for NEU% and β = -0.124, p = 0.026 for NLR), lower RAVLT-immediate score (β = -0.103, p = 0.012 for NEU% and β = -0.110, p = 0.008), as well as lower RAVLT-Delayed Recall score (β = -0.090, p = 0.018 for NEU% and β = -0.144, p = 0.046 for NLR). On the contrary, individuals with elevated LYM% was associated with lower ADAS score (β = -0.105, p = 0.014), lower CDRSB score (β = -0.104, p = 0.015), higher MEM score (β = 0.171, p < 0.001), higher EF score (β = 0.138, p = 0.010), higher RAVLT-immediate score (β = 0.111, p = 0.008), as well as higher RAVLT-Delayed Recall score (β = 0.144, p = 0.039). Associations of BBB-related biomarkers with cognitive function. As is shown in Fig. 3 A and Additional file 5, individuals with elevated CCL26 were associated with higher ADAS score (β = 0.146, p < 0.001), lower MEM score (β = -0.096, p = 0.050), lower RAVLT-immediate score (β = -0.094, p = 0.023 for CCL26), as well as lower RAVLT-Delayed Recall score (β = -0.188, p < 0.001 for CCL26). Individuals with elevated CD40 was associated with higher CDRSB score (β = 0.134, p = 0.002), lower MEM score (β = -0.114, p = 0.031). lower EF score (β = -0.198, p < 0.001). Individuals with elevated MMP10 was associated with higher CDRSB score (β = 0.136, p < 0.001). Causal mediation analyses in AD cognitive function. BBB-related biomarkers mediated the correlation between peripheral immune biomarkers and cognitive function, CCL26 mediated the associations of NEU% with global cognition (Fig. 3 B), immediate memory (Fig. 3 C), and delayed memory (Fig. 3 D), with the ratio of mediation ranging from 9–24%. CD40 (Fig. 3 E) and MMP10 (Fig. 3 F) only mediated the associations of NEU% with global cognition, with the ratio of mediation ranging from 9–13%. CCL26 (Fig. 3 G), CD40 (Fig. 3 H) and MMP10 (Fig. 3 I) only mediated the associations of LYM% with global cognition, with the ratio of mediation ranging from 12–16%. CCL26 (Fig. 3 J), CD40 (Fig. 3 K) and MMP10 (Fig. 3 L) only mediated the associations of NLR with global cognition, with the ratio of mediation ranging from 12–23%. Discussion Using data from 543 individuals from the ADNI, we systematically investigated the potential mechanisms between peripheral immunity and the risk of AD onset. Specifically, our study suggests a significant correlation between peripheral immune and BBB-related biomarker. Both peripheral immune and BBB-related biomarkers are significantly correlated with the AD pathology (CSF Aβ-42, P-tau, P-tau/Aβ-42, and T-tau/Aβ-42), the extent of AD-related cerebral atrophy (whole brain, hippocampal volume, MTL volume, and EC thickness), as well as cognitive function (including global cognition, executive function, memory function, immediate recall, and delayed recall). Most importantly, we found that peripheral immune biomarkers influence AD pathology, cerebral atrophy, and cognitive function through BBB-related biomarkers, providing a more robust and comprehensive evidence chain for the hypothesis of "inflammation leading to AD". AD is a systemic disease involving systemic immune reactions. A large body of research emphasizes the importance of the immune system in AD, Genome-wide association studies (GWAS) have identified immune-related genes such as CLU, CRI, CD33, CD2AP , and CD20 as risk genes[ 17 – 19 ], suggesting that manipulating this system within a strategic time window could potentially treat the disease. Under normal circumstances, a healthy brain is protected by resident immune cells (such as microglia) and peripheral immune cells circulating in the periphery[ 20 ]. AD involves the balance of the central and peripheral immune systems, as well as the balance of innate and adaptive immune systems[ 21 , 22 ]. When this balance is disrupted, peripheral immune cells are activated, leading to increased expression of pro-inflammatory cytokines. If this imbalance persists, it can trigger excessive inflammatory responses, overproduction of inflammatory mediators, causing neurons to be continuously exposed to pro-inflammatory mediators, ultimately resulting in neuronal dysfunction and cell death. NEU% are typically regarded as markers of innate immunity, while LYM% are considered markers of adaptive immunity, using ratios rather than absolute count of neutrophils or lymphocytes can control for the effects of inter-subject variability. Changes in NLR reflect an imbalance between innate and adaptive immunity[ 23 ]. In AD transgenic models, depletion or inhibition of neutrophil trafficking can reduce AD pathology deposits and improve memory function[ 24 ]. Previous research has found that AD mice with adaptive immune deficiency due to a lack of lymphocytes exhibit greater increases in Aβ pathology[ 25 ], and immunotherapy that enhances adaptive immune function can enhance Aβ clearance[ 26 ]. Altered balance of innate versus adaptive immunity also influence AD, previous study has found that NLR plays a role in the pathogenesis of AD[ 27 ]. Previous studies have indicated that even mild peripheral inflammation can disrupt the BBB, leading to the infiltration of peripheral immune cells into the brain[ 28 , 29 ], affecting the clearance of Aβ by microglia and the transport function of neurons[ 30 ], further exacerbating CNS inflammation, ultimately promoting the pathological deposition of AD and changes in cognitive function[ 11 , 31 , 32 ]. Postmortem examinations of AD have found infiltration of neutrophils and lymphocyte in the brain, suggesting peripheral immune cells have indeed crossed the BBB and entered the brain tissue[ 33 – 35 ], but the specific mechanisms and processes involved are still unclear. BBB is a special system of brain microvascular endothelial cells that prevents neurotoxic plasma components, blood cells, and pathogens from entering the brain, providing nutrients to brain tissue, and filtering harmful compounds back into the bloodstream, ensuring dynamic balance of central nervous system components. Disruption of BBB function is associated with human cognitive impairment[ 36 ], and is considered an early biomarker of AD[ 37 , 38 ]. Previous studies have found that dysfunction of the BBB in the hippocampus is associated with an increased risk of AD[ 37 , 39 ], and early breakdown of BBB have been observed before the occurrence of cerebral atrophy and cerebrospinal fluid pathological deposition in AD[ 9 , 10 ]. Changes in the level of proteins degrading the tight junctions of the BBB provide evidence for the role of the BBB in the pathogenesis of dementia, and BBB disruption is associated with subsequent central nervous system inflammation and autoimmune reactions[ 40 ]. Peripheral immune cells have the capacity to produce cytokines, chemokines, and MMPs. These molecules play crucial roles in regulating BBB function in AD[ 41 ], making them valuable as BBB-related biomarkers. MMP10 could be released by endothelial cells derived from the BBB, regulating the activation of brain-derived growth factors, enzyme degradation, and extracellular matrix remodeling, all of which are essential for the integrity of the BBB, neural network repair, and tissue formation[ 42 , 43 ]. It has been reported that in AD, Aβ disrupts the integrity of the BBB by activating MMP10, and the overexpression of MMPs degrades tight junction proteins, damages endothelial cells, leading to excessive opening of the BBB, thereby exacerbating neuroinflammation and neurotoxicity[ 44 ]. This leads to an increase in the number of aged astrocytes, causing synaptic dysfunction, neuronal damage, and ultimately neuronal death[ 45 , 46 ]. CCL26 is a member of the chemokine family, which can attract peripheral immune cells into the CNS, leading to the entry of harmful blood components into the central nervous system, resulting in cell permeability, abnormal molecular transport, and clearance[ 47 ], which is an indicator of BBB dysfunction. In AD patients, microglia and astrocytes are activated, and peripheral immune cells also overexpress[ 48 , 49 ], secreting excessive chemokines including CCL26, which increase the permeability of BBB and recruit peripheral immune cells to cross the disrupted BBB, accumulating in inflammatory brain tissue lesions and Aβ plaques[ 50 ], promoting the inflammatory response[ 51 – 54 ], and accelerating the progression of AD[ 49 , 55 ]. CD40 is a cell surface molecule primarily produced by peripheral immune cells, which, together with nitric oxide, induces increased BBB permeability and leukocyte extravasation[ 56 ]. The interaction between CD40 and its homologous ligand CD40 ligand (CD40L) is a major regulatory factor in peripheral immune responses, regulating the activation and differentiation of immune cells. CD40-CD40L-mediated aberrant neuroinflammation increases BBB permeability and damage[ 57 ], and can promote the production of neurotoxic factors by microglial cells, directly leading to BBB vascular damage[ 58 ], and synergistically enhancing the aggregation of tau protein and Aβ[ 59 , 60 ], thereby promoting the progression of AD patient[ 61 – 63 ]. In summary, given the BBB is highly sensitive to inflammatory stimuli, peripheral immunity affects AD by affect the following BBB function: 1) altering the density of the BBB; 2) increasing the permeability of BBB 3) activating astrocytes and microglia; 4) damaging endothelial cells. Our study has several strengths. Firstly, it is the first systematic exploration of the mediating role of BBB-related markers between peripheral immune cells and AD, these findings consolidated the close relationships of peripheral immunity with AD pathology, cerebral atrophy and cognitive function, supporting the hypothesis that inflammation leading to AD. Additionally, our mediation analysis exhibits strict triangular stability: we only included indicators that show all significant correlations between the independent variable and the mediator, the independent variable and the dependent variable, and the mediator and the dependent variable. There are limitations in this study. First, our exposure analysis was limited to blood cell count, percent, and derived ratios due to the lack of flow cytometry or ELISA data. Second, although BBB-related biomarkers are BBB function indicators, they cannot directly assess its integrity as effectively as contrast agents. Third, although we excluded patients with significant inflammation, we could not avoid the effect of the occasional use of anti-inflammatory drugs on the numbers of immune cells. Last, the cohort was predominantly composed of people of European ancestry, so some findings may not apply to the entire general population. Conclusions In summary, we found that peripheral immunity and BBB-related biomarkers are associated with AD pathology, cerebral atrophy and cognitive function, and peripheral cells impact AD by affecting the function of the BBB. Therefore, reducing the disruption of the BBB could serve as a potentially useful therapeutic approach to limit the harmful infiltration of peripheral immune cells into the central nervous system. Abbreviations AD Alzheimer’s disease ADNI Alzheimer’s Disease Neuroimaging Initiative Aβ β-Amyloid ADAS Alzheimer's Disease Assessment Scale BBB blood brain barrier CDRSB Clinical Dementia Rating Sum of Boxes CN cognitively normal CSF cerebrospinal fluid CNS central nervous system CCL26 eosinophil chemotactic factor-3 CD40L CD40 ligand EF executive function EC entorhinal cortex FLAIR fluid-attenuated inversion recovery HV hippocampal volume LYM% lymphocytes percent MRI magnetic resonance imaging MEM memory function MMP10 matrix metalloproteinase-10 MCI mild cognitive impairment NEU% neutrophils percent NLR neutrophil-lymphocyte ratio NFT neurofibrillary tangles P-tau phosphorylated-tau RAVLT-immediate Rey Auditory Verbal Learning Test-immediate-total immediate recall score RAVLT-Delayed Recall Rey Auditory Verbal Learning Test- logical memory delayed recall score ROS reactive oxygen species ROI regions of interest SD standard deviation TNF tumor necrosis factor T-tau total tau Declarations Ethics approval and consent to participant The study was approved by institutional review boards of all participating institutions, and written informed consent was obtained from all participants or their guardians according to the Declaration of Helsinki (consent for research). Consent for publication Not applicable. Availability of data and materials The dataset generated and analyzed in the current study is available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of China (82271464). Authors’ contributions JHH and LYW conceptualized the study, and revised the manuscript. JHH, and DMJ analyzed and interpreted the data, drafted and revised the manuscript, did the statistical analysis, and prepared all the figures. MC participated in the interpretation of the data and revision of the manuscript. All authors contributed to the writing and revisions of the paper and approved the final version. Data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. Acknowledgements Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.;Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.Data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. References Scheltens P, et al. Alzheimer's disease Lancet. 2021;397(10284):1577–90. 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(2): pp. e105-e125. DeTure MA, Dickson DW. The neuropathological diagnosis of Alzheimer's disease. Mol Neurodegener. 2019;14(1):32. 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Nation DA, et al. Blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction. Nat Med. 2019;25(2):270–6. Padrela B, et al. Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol. BMJ Open. 2024;14(3):e081635. Montagne A, et al. APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline. Nature. 2020;581(7806):71–6. Persidsky Y, et al. Blood-brain barrier: structural components and function under physiologic and pathologic conditions. J Neuroimmune Pharmacol. 2006;1(3):223–36. Yang C, et al. Neuroinflammatory mechanisms of blood-brain barrier damage in ischemic stroke. Am J Physiol Cell Physiol. 2019;316(2):C135–53. Gong QY, et al. Urolithin A alleviates blood-brain barrier disruption and attenuates neuronal apoptosis following traumatic brain injury in mice. Neural Regen Res. 2022;17(9):2007–13. Liebner S, et al. Functional morphology of the blood-brain barrier in health and disease. Acta Neuropathol. 2018;135(3):311–36. Guo P, et al. Alzheimer's disease with sleep insufficiency: a cross-sectional study on correlations among clinical characteristics, orexin, its receptors, and the blood-brain barrier. Neural Regen Res. 2023;18(8):1757–62. Nuttall RK, et al. Metalloproteinases are enriched in microglia compared with leukocytes and they regulate cytokine levels in activated microglia. Glia. 2007;55(5):516–26. De Strooper B, Karran E. The Cellular Phase of Alzheimer's Disease. Cell. 2016;164(4):603–15. Zhao Z, et al. Establishment and Dysfunction of the Blood-Brain Barrier. Cell. 2015;163(5):1064–78. Shou J, et al. CCL26 and CCR3 are associated with the acute inflammatory response in the CNS in experimental autoimmune encephalomyelitis. J Neuroimmunol. 2019;333:576967. Huber AK, et al. An emerging role for eotaxins in neurodegenerative disease. Clin Immunol. 2018;189:29–33. Liu YJ, et al. Peripheral T cells derived from Alzheimer's disease patients overexpress CXCR2 contributing to its transendothelial migration, which is microglial TNF-alpha-dependent. Neurobiol Aging. 2010;31(2):175–88. Nakayama T, et al. Eotaxin-3/CC chemokine ligand 26 is a functional ligand for CX3CR1. J Immunol. 2010;185(11):6472–9. Forssmann U, et al. Eotaxin-2, a novel CC chemokine that is selective for the chemokine receptor CCR3, and acts like eotaxin on human eosinophil and basophil leukocytes. J Exp Med. 1997;185(12):2171–6. Menzies-Gow A, et al. Eotaxin (CCL11) and eotaxin-2 (CCL24) induce recruitment of eosinophils, basophils, neutrophils, and macrophages as well as features of early- and late-phase allergic reactions following cutaneous injection in human atopic and nonatopic volunteers. J Immunol. 2002;169(5):2712–8. Sallusto F, Mackay CR, Lanzavecchia A. Selective expression of the eotaxin receptor CCR3 by human T helper 2 cells. Science. 1997;277(5334):2005–7. Choi C, et al. Multiplex analysis of cytokines in the serum and cerebrospinal fluid of patients with Alzheimer's disease by color-coded bead technology. J Clin Neurol. 2008;4(2):84–8. Bowman GL, et al. Blood-brain barrier breakdown, neuroinflammation, and cognitive decline in older adults. Alzheimers Dement. 2018;14(12):1640–50. Ots HD et al. CD40-CD40L in Neurological Disease. Int J Mol Sci, 2022. 23(8). Calingasan NY, Erdely HA, Altar CA. Identification of CD40 ligand in Alzheimer's disease and in animal models of Alzheimer's disease and brain injury. Neurobiol Aging. 2002;23(1):31–9. Laporte V, et al. CD40 deficiency mitigates Alzheimer's disease pathology in transgenic mouse models. J Neuroinflammation. 2006;3:3. Kim SH, et al. Boosting of tau protein aggregation by CD40 and CD48 gene expression in Alzheimer's disease. Faseb j. 2023;37(1):e22702. Town T, Tan J, Mullan M. CD40 signaling and Alzheimer's disease pathogenesis. Neurochem Int. 2001;39(5–6):371–80. Buchhave P, et al. Elevated plasma levels of soluble CD40 in incipient Alzheimer's disease. Neurosci Lett. 2009;450(1):56–9. Lee DW, et al. T cells expressing CD19 chimeric antigen receptors for acute lymphoblastic leukaemia in children and young adults: a phase 1 dose-escalation trial. Lancet. 2015;385(9967):517–28. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.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-4437508","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308004964,"identity":"641a8222-f4c6-45f7-bc1c-243e3750076d","order_by":0,"name":"Jia-Hui Hou","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jia-Hui","middleName":"","lastName":"Hou","suffix":""},{"id":308004965,"identity":"f6f6ae44-38f4-4968-8b2c-11ab53e9962a","order_by":1,"name":"De-Ming Jiang","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"De-Ming","middleName":"","lastName":"Jiang","suffix":""},{"id":308004966,"identity":"782b9846-712d-47f3-a570-3c0c34268fcc","order_by":2,"name":"Min Chu","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Chu","suffix":""},{"id":308004967,"identity":"796b48e7-707a-4382-bcb5-90eebe3e55a4","order_by":3,"name":"Li-Yong Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYLCCBww2CWBGQgGxWhIY0hIY2EAMA+K1HIZoYSBGi8G1M2YSiW3n8/jluxM/PDBgkOcXO0BAy+0ckJbbxZJtvJslgA4znDk7Ab8WM6CWG0AtiRuO8W4AaUkwuE2clnMgLZt/kKLlAEjLNuJssb+dVv4j4Vxy4sy23G0WCQYShP0iOTt5s8GHMrvEfuazm2/+qLCR55cmoIWBgcOAgZENzpMgpBwE2B8wMPwhRuEoGAWjYBSMWAAAeNBH6GdcV+wAAAAASUVORK5CYII=","orcid":"","institution":"Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Li-Yong","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2024-05-17 15:01:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4437508/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4437508/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57728607,"identity":"389c51f0-8d36-4620-9bd2-8c450c44f830","added_by":"auto","created_at":"2024-06-04 21:47:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":381375,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation and mediation analyses between peripheral immunity and BBB-related biomarkers with AD pathology.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ea is the effect of independent variable on mediators; b is the effect of mediators on dependent variables after controlling the influence of independent variables; c is the total effect of independent variables on dependent variables; c’ is the direct effect of independent variables on dependent variables after controlling the influence of mediators; IE is the indirect effect of independent variables on dependent variables, in this intermediary model, c = c’+ ab.\u003c/p\u003e\n\u003cp\u003eAbbreviations: Aβ, β-Amyloid; P-tau, phosphorylated-tau; T-tau, total tau; NEU%, neutrophils percent LYM%, lymphocytes percent; NLR,neutrophil-lymphocyte ratio; CCL26, eosinophil chemotactic factor-3; MMP10, matrix metalloproteinase-10;\u003c/p\u003e\n\u003cp\u003ep: 0.01 \u0026lt; * \u0026lt; 0.05, 0.001 \u0026lt; ** \u0026lt; 0.01, 0.0001 \u0026lt; *** \u0026lt; 0.001, **** \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4437508/v1/92fca8671e8dbdfac86a7821.jpg"},{"id":57728606,"identity":"2621922e-4fc5-4f85-b3b0-dd3b1f8f04f5","added_by":"auto","created_at":"2024-06-04 21:47:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":199130,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation and mediation analyses between peripheral immunity and BBB-related biomarkers with cerebral atrophy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: MTL, middle temporal lobe; EC, entorhinal cortex; NEU%, neutrophils percent; LYM%, lymphocytes percent; NLR, neutrophil-lymphocyte ratio; CCL26, eosinophil chemotactic factor-3; MMP10, matrix metalloproteinase-10;\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4437508/v1/cf453840771b3e3d39c0a67f.jpg"},{"id":57728605,"identity":"5528fb50-ccfd-4e1b-9733-6cca39962f7e","added_by":"auto","created_at":"2024-06-04 21:47:07","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":582459,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation and mediation analyses between peripheral immunity and BBB-related biomarkers with cognitive function.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: CDRSB, Clinical Dementia Rating Sum of Boxes; ADAS, Alzheimer's Disease Assessment Scale; MEM, memory function; EF, executive function; RAVLT-immediate, Rey Auditory Verbal Learning Test-immediate-total immediate recall score; RAVLT-Delayed Recall, Rey Auditory Verbal Learning Test- logical memory delayed recall score; NEU%, neutrophils percent; LYM%, lymphocytes percent; NLR, neutrophil-lymphocyte ratio; CCL26, eosinophil chemotactic factor-3; MMP10, matrix metalloproteinase-10;\u003c/p\u003e\n\u003cp\u003ep: 0.01 \u0026lt; * \u0026lt; 0.05, 0.001 \u0026lt; ** \u0026lt; 0.01, 0.0001 \u0026lt; *** \u0026lt; 0.001, **** \u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4437508/v1/4a7bd9a45e5a9894d7ece9c8.jpg"},{"id":57729708,"identity":"4f1f80b9-6ff6-4676-afe6-f5b5800b18c7","added_by":"auto","created_at":"2024-06-04 21:55:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1980556,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4437508/v1/12b574da-4809-44dc-94e6-45d6b818e5f4.pdf"},{"id":57728602,"identity":"8866c06d-da34-4726-91b1-8fa5f9acfe81","added_by":"auto","created_at":"2024-06-04 21:47:04","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1663717,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4437508/v1/f63d42a0a4e06df7f91c88b1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Peripheral immunity affects Alzheimer’s disease by influencing blood-brain barrier function","fulltext":[{"header":"Background","content":"\u003cp\u003eAlzheimer's disease (AD) is a prevalent neurodegenerative disease characterized by a gradual decline in memory and other cognitive abilities, which not only greatly reduces the quality of life of patients, but also imposes a heavy burden on families and society[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. With the aging population and population growth, the number of AD patients will continue to increase[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Currently available treatments can only slow down the progression of AD, effective drugs have not yet been found, mainly due to an incomplete understanding of the disease mechanism and the complexity of the disease.\u003c/p\u003e \u003cp\u003eAD is characterized by two core pathological features, namely β-amyloid (Aβ) in senile plaques and neurofibrillary tangles (NFT) composed of hyperphosphorylated Tau (P-tau) protein[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Persistent brain inflammation has emerged as the third core pathological feature of AD[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. It was previously believed that the brain inflammatory responses were confined to the central nervous system (CNS) without being influenced by peripheral immune events. However, accumulating research indicates that AD is a systemic disease, peripheral immune system also plays a crucial role in the onset of AD[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], both peripheral innate and adaptive immunity are involved in AD pathogenesis[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and many mediators secreted by peripheral immune cells can lead to neuronal degeneration[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, the mechanisms by which peripheral immune cells affect the cerebrospinal fluid (CSF) pathology, cerebral atrophy and cognitive function are not yet fully understood.\u003c/p\u003e \u003cp\u003eAs the necessary passage for peripheral immune cells to enter the CNS, in the normal state, the blood-brain barrier (BBB) serves as a vital physiological barrier that separates the CNS from harmful substances and immune cells in the peripheral circulation, it is essential for maintaining internal balance and normal neuronal function. However, in the pathological state of AD, BBB function is impaired, and BBB damage may occur before the infiltration of peripheral immune cells locally[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Previous studies have reported that under inflammatory conditions, the breakdown of the BBB leads to the infiltration of peripheral immune cells into the CNS[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and the inflammatory mediators released by peripheral immune cells will further increase the permeability of the BBB, exacerbating the deposition of Aβ and tau in AD patients, further triggering the inflammatory responses[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], this established a vicious positive feedback cycle. However, there has been no exploration in human studies on whether peripheral immunity affect AD by influencing BBB function. Herein, we explored the associations of peripheral immune biomarkers [neutrophils percent (NEU%), lymphocytes percent (LYM%), and neutrophils/lymphocytes (NLR)] and BBB-related biomarkers [chemotactic factor-3 (CCL26), CD40 and matrix metalloproteinase-10 (MMP10)] with cognition, neuroimaging, and AD pathology, and to explore whether the associations between peripheral immunity with AD were mediated by BBB-related biomarkers.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eData applied in this study were acquired from the ADNI database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://adniloni.usc.edu\u003c/span\u003e\u003cspan address=\"http://adniloni.usc.edu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which is designed to test biochemical, clinical biomarkers, genetics and imaging of AD. Participants received systematic neuropsychological evaluations, as well as neurological and physical examinations at baseline and follow-up, and were offered biological samples such as CSF, blood, and urine throughout the study. This multisite longitudinal biomarker research program authorized by the institutional review committee at all participating locations has acquired written informed consent from participants. This study population is composed of all cognitively normal (CN), mild cognitive impairment (MCI), and AD participants with available routine blood test and BBB -related biomarkers.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePeripheral immune and BBB-related biomarkers\u003c/h3\u003e\n\u003cp\u003ePeripheral immune biomarkers and BBB-related biomarkers were examined in a subset of participants from ADNI-1 study. Plasma samples were drawn by trained professionals from the venous blood in the morning after an overnight fast and were sent for analysis on the same day. Routine blood test was analyzed using an automated system, more method details could be found at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://adni.loni.usc.edu\u003c/span\u003e\u003cspan address=\"http://adni.loni.usc.edu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Target blood indicators were analyzed using Luminex immunofluorescence multiplex assays following a standardized protocol. All peripheral immune biomarkers included in this analysis included the count and percentage of neutrophils, lymphocytes. BBB-related plasma biomarkers included in this analysis included CCL26, CD40 and MMP10.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCSF measurements\u003c/h2\u003e \u003cp\u003eCSF was sampled by lumbar puncture, with CSF Aβ-42, total tau (T-tau), and P-tau measured at the ADNI Biomarker Core Laboratory (University of Pennsylvania) using an xMap Luminex platform with INNO-BIA AlzBio3 (Ghent, Belgium; for research use only reagents) immune assay kit-based reagents and analyzed on an automatic Elecsys cobas e 601 instrument (F. Hoffmann-La Roche) by an advanced technology known as electrochemiluminescence immunoassays (Elecsys; Roche Diagnostics, F. Hoffmann-La Roche, Basel, Switzerland).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eNeuroimaging\u003c/h2\u003e \u003cp\u003eBrain structural images were obtained using a 1.5 T MRI imaging system, acquiring T1-weighted, T2-weighted, and T2 fluid-attenuated inversion recovery (FLAIR) sequences MRI scans through fast gradient-echo sequences prepared with sagittal volumetric magnetization. Cortical thickness and subcortical volume were quantified using software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://surfer.nmr.mgh.harvard.edu/\u003c/span\u003e\u003cspan address=\"https://surfer.nmr.mgh.harvard.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Brain structures related to cognitive function including degree of atrophy of hippocampal volume, middle temporal lobe (MTL) volume, whole brain volume, and the entorhinal cortex (EC) thickness were included in the analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eNeurocognitive Measures\u003c/h2\u003e \u003cp\u003eCognitive function was assessed using several neuropsychological scales. Specifically, global cognitive function was evaluated through the Alzheimer\u0026rsquo;s Disease Assessment Scale (ADAS) and the Clinical Dementia Rating Sum of Boxes (CDRSB). Cognitive domains include memory, executive function, and verbal function. The ADNI memory composite score (MEM) is assessed based on the word recall item from the MMSE, word list learning and recognition tasks from ADAS-Cog, Rey Auditory Verbal Learning task, and Logical Memory I from the Wechsler Memory Test-Revised. The ADNI executive function score (EF) is evaluated based on Clock Drawing items, Wechsler Adult Intelligence Scale-Revised Digit-Symbol Substitution, Category Fluency, Trail-Making Test Parts A and B, and Digit Span Backwards[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Tests used to assess verbal memory include the total immediate recall score across five learning trials (RAVLT-Immediate) and logical memory delayed recall score from the Rey Auditory Verbal Learning Test (RAVLT-Delayed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe study subjects were divided into CN group, MCI group, and AD group. Categorical variables were represented using numbers (percentages), and continuous variables were represented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD). Firstly, chi-square analysis and non-parametric tests were employed to examine intergroup differences. Subsequently, extreme values exceeding 3 SDs from the mean were removed, and individual analytes were normalized through Box-Cox transformation. We utilized multiple linear regression models to assess the correlations between various peripheral immune biomarkers/ BBB-related biomarker (independent variables) and dependent variables including AD pathology (CSF biomarkers), neuroimaging (brain structure), and cognition (global cognition, immediate memory, delayed memory, as well as MEM and EF).\u003c/p\u003e \u003cp\u003eThen, mediation analysis was conducted using the \u0026ldquo;mediate\u0026rdquo;, \u0026ldquo;car\u0026rdquo;, and \u0026ldquo;lm\u0026rdquo; packages in R software (version 4.0.3) to explore whether the association between peripheral immune biomarkers and AD pathology deposition, cerebral atrophy degree and cognitive function is mediated by BBB-related biomarkers. The premise of establishing the model is that both the independent and mediating variables are significantly correlated with the dependent variable in linear regression analysis. Linear regression models were fitted based on the method proposed by Baron and Kenny[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The first equation demonstrates the influence of the independent variable on the mediating variable. The second equation shows the effect of the mediating variable on the dependent variable after controlling for the influence of the independent variable. The third equation presents the total effect of the independent variable on the dependent variable, the direct effect of the independent variable on the dependent variable after controlling for the influence of the mediating variable, and the indirect effect of the independent variable on the dependent variable without controlling for the influence of the mediating variable.\u003c/p\u003e \u003cp\u003eAll covariates in the correlation analyses included gender, age, \u003cem\u003eAPOE ε4\u003c/em\u003e status, and education level, with total intracranial volume added as a covariate when the dependent variable was related to brain structure. Two-tailed p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. Graphs and statistical analyses were conducted using R software (version 4.0.3), GraphPad Prism 7.00 (San Diego, California), and IBM SPSS Statistics 26.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of Participants\u003c/h2\u003e \u003cp\u003eThe present analysis included 543 participants, consisting of 57 CN, 381 MCI, and 105 AD participants. The whole population had a female proportion of 38.67%, an age ranges from 54 to 90 years old (74.79\u0026thinsp;\u0026plusmn;\u0026thinsp;7.39 years old), and an \u003cem\u003eAPOE\u003c/em\u003e ε4 positive percentage of 51.57% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Except for basic demographics, \u003cem\u003eAPOE ε4\u003c/em\u003e carriers, peripheral immune biomarkers, BBB-related biomarkers, CSF biomarker levels, brain structure and levels of cognitive scores all illustrated statistically significant inter-group differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic characteristics of population included\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNumber\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.15\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.76\u0026thinsp;\u0026plusmn;\u0026thinsp;7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.70\u0026thinsp;\u0026plusmn;\u0026thinsp;8.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale gender (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (49.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137 (35.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (42.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026nbsp;(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.62\u0026thinsp;\u0026plusmn;\u0026thinsp;3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAPOE ε4\u003c/em\u003e carriers\u0026nbsp;(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (8.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202 (53.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (69.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePeripheral immune biomarkers\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEU%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.81\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.60\u0026thinsp;\u0026plusmn;\u0026thinsp;7.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLYM %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.32\u0026thinsp;\u0026plusmn;\u0026thinsp;7.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.15\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBBB-related biomarkers\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCL26 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD40 (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP10 (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCSF Biomarkers\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAβ\u0026nbsp;(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1338.66\u0026thinsp;\u0026plusmn;\u0026thinsp;244.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e748.81\u0026thinsp;\u0026plusmn;\u0026thinsp;343.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e605.76\u0026thinsp;\u0026plusmn;\u0026thinsp;242.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-tau (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.76\u0026thinsp;\u0026plusmn;\u0026thinsp;6.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.43\u0026thinsp;\u0026plusmn;\u0026thinsp;14.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.57\u0026thinsp;\u0026plusmn;\u0026thinsp;14.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-tau (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e223.82\u0026thinsp;\u0026plusmn;\u0026thinsp;72.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e307.28\u0026thinsp;\u0026plusmn;\u0026thinsp;123.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e353.14\u0026thinsp;\u0026plusmn;\u0026thinsp;126.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-tau/Aβ-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-tau/Aβ-42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBrain structure\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhole brain((mm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1001211.14\u0026thinsp;\u0026plusmn;\u0026thinsp;97000.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e996490.91\u0026thinsp;\u0026plusmn;\u0026thinsp;110299.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e971594.82\u0026thinsp;\u0026plusmn;\u0026thinsp;119575.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHippocampal volume(mm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7311.54\u0026thinsp;\u0026plusmn;\u0026thinsp;835.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6405.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1078.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5774.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1158.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMTL volume (mm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19760.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2715.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18594.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3000.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17088.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3379.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEC thickness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3863.04\u0026thinsp;\u0026plusmn;\u0026thinsp;674.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3301.98\u0026thinsp;\u0026plusmn;\u0026thinsp;752.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2773.79\u0026thinsp;\u0026plusmn;\u0026thinsp;671.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCognitive scores\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.51\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.52\u0026thinsp;\u0026plusmn;\u0026thinsp;6.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDRSB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAVLT-immediate Recall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.53\u0026thinsp;\u0026plusmn;\u0026thinsp;7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.75\u0026thinsp;\u0026plusmn;\u0026thinsp;9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.29\u0026thinsp;\u0026plusmn;\u0026thinsp;7.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAVLT-Delayed Recall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: CN, cognitively normal; MCI, mild cognitive impairment; AD, Alzheimer\u0026rsquo;s disease; NEU, Neutrophils; LYM, Lymphocytes; NLR, Neutrophil\u0026ndash;lymphocyte ratio; CCL26, eosinophil chemotactic factor-3; MMP10, matrix metalloproteinase-10; CSF, cerebrospinal fluid; Aβ, β-Amyloid; P-tau, phosphorylated-tau; T-tau, total tau; MTL: middle temporal lobe; EC, entorhinal cortex; CDRSB, Clinical Dementia Rating Sum of Boxes; ADAS, Alzheimer's Disease Assessment Scale; MEM, memory function; EF, executive function; RAVLT-immediate, Rey Auditory Verbal Learning Test-immediate-total immediate recall score; RAVLT-Delayed Recall, Rey Auditory Verbal Learning Test- logical memory delayed recall score; Values are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), or n (% of the group).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of peripheral immune biomarker with BBB-related biomarkers.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Additional file 1, Individuals with higher NEU% and NLR level were associated with elevated levels of CCL26 (β\u0026thinsp;=\u0026thinsp;0.119, p\u0026thinsp;=\u0026thinsp;0.006 for NEU% and β\u0026thinsp;=\u0026thinsp;0.124, p\u0026thinsp;=\u0026thinsp;0.005 for NLR), CD40 (β\u0026thinsp;=\u0026thinsp;0.101, p\u0026thinsp;=\u0026thinsp;0.015 for NEU% and β\u0026thinsp;=\u0026thinsp;0.111, p\u0026thinsp;=\u0026thinsp;0.009 for NLR), and MMP10 (β\u0026thinsp;=\u0026thinsp;0.144, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for NEU% and β\u0026thinsp;=\u0026thinsp;0.187, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for NLR). On the contrary, individuals with elevated LYM% were associated with the decrease in CCL26 (β = -0.101, p\u0026thinsp;=\u0026thinsp;0.015), CD40 (β = -0.132, p\u0026thinsp;=\u0026thinsp;0.002), and MMP10 (β = -0.141, p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of peripheral immune biomarkers with AD pathology.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Additional file 2, peripheral immune biomarkers have significant correlations with AD pathology. Individuals with higher NEU% and NLR level were associated with lower CSF Aβ-42 (β = -0.111, p\u0026thinsp;=\u0026thinsp;0.003 for NEU% and β = -0.148, p\u0026thinsp;=\u0026thinsp;0.027 for NLR), higher CSF P-tau (β\u0026thinsp;=\u0026thinsp;0.116, p\u0026thinsp;=\u0026thinsp;0.044 for NEU% and β\u0026thinsp;=\u0026thinsp;0.126, p\u0026thinsp;=\u0026thinsp;0.042 for NLR), higher T-tau/Aβ-42 (β\u0026thinsp;=\u0026thinsp;0.109, p\u0026thinsp;=\u0026thinsp;0.038 for NEU% and β\u0026thinsp;=\u0026thinsp;0.150, p\u0026thinsp;=\u0026thinsp;0.023 for NLR), and higher P-tau/Aβ-42 (β\u0026thinsp;=\u0026thinsp;0.104, p\u0026thinsp;=\u0026thinsp;0.046 for NEU% and β\u0026thinsp;=\u0026thinsp;0.161, p\u0026thinsp;=\u0026thinsp;0.014 for NLR). On the contrary, individuals with elevated LYM% were associated with higher CSF Aβ-42 (β\u0026thinsp;=\u0026thinsp;0.125, p\u0026thinsp;=\u0026thinsp;0.049), lower T-tau/Aβ-42 (β = -0.145, p\u0026thinsp;=\u0026thinsp;0.020), and lower P-tau/Aβ-42 (β = -0.104, p\u0026thinsp;=\u0026thinsp;0.016).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of BBB-related biomarkers with AD pathology.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Additional file 2, BBB-related biomarkers also have significant correlations with AD CSF pathology. Individuals with elevated CCL26 were associated with lower CSF Aβ-42 (β = -0.183, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher T-tau/Aβ-42 (β\u0026thinsp;=\u0026thinsp;0.141, p\u0026thinsp;=\u0026thinsp;0.007), and higher P-tau/Aβ-42 (β\u0026thinsp;=\u0026thinsp;0.141, p\u0026thinsp;=\u0026thinsp;0.008).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCausal mediation analyses in AD pathology.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBBB-related biomarkers mediated the correlation between peripheral immune biomarkers with AD pathology. The indirect and total effects of NEU% on AD pathology, including Aβ-42 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), T-tau/Aβ-42 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), and P-tau/Aβ-42 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) reached statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but the direct effects did not (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that all the associations of NEU% with Aβ-42, T-tau/Aβ-42 and P-tau/Aβ-42 were completely mediated by CCL26, with the ratio of mediation ranging from 18\u0026ndash;24%.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of peripheral immune biomarkers with AD cerebral atrophy.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Additional file 3, peripheral immune biomarkers have significant correlations with AD cerebral atrophy. Individuals with elevated NEU% and NLR were associated with smaller whole brain volume (β = -0.073, p\u0026thinsp;=\u0026thinsp;0.001 for NEU% and β = -0.077, p\u0026thinsp;=\u0026thinsp;0.001 for NLR), smaller hippocampal volume (β = -0.167, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for NEU% and β = -0.162, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for NLR), smaller MTL volume (β = -0.080, p\u0026thinsp;=\u0026thinsp;0.041 for NEU% and β = -0.106, p\u0026thinsp;=\u0026thinsp;0.012 for NLR), as well as lesser EC thickness (β = -0.140, p\u0026thinsp;=\u0026thinsp;0.002 for NEU% and β = -0.134, p\u0026thinsp;=\u0026thinsp;0.004 for NLR). On the contrary, individuals with elevated LYM% was associated with greater whole brain volume (β\u0026thinsp;=\u0026thinsp;0.083, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), greater hippocampal volume (β\u0026thinsp;=\u0026thinsp;0.183, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), greater MTL volume (β\u0026thinsp;=\u0026thinsp;0.107, p\u0026thinsp;=\u0026thinsp;0.008), as well as thicker EC thickness (β\u0026thinsp;=\u0026thinsp;0.156, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of BBB-related biomarkers with AD cerebral atrophy.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Additional file 3, individuals with elevated CCL26 were associated with smaller whole brain volume (β = -0.065, p\u0026thinsp;=\u0026thinsp;0.004), smaller MTL volume (β = -0.123, p\u0026thinsp;=\u0026thinsp;0.003), as well as lesser EC thickness (β = -0.014, p\u0026thinsp;=\u0026thinsp;0.003). Individuals with elevated CD40 were associated with smaller whole brain volume (β = -0.074, p\u0026thinsp;=\u0026thinsp;0.002), smaller hippocampal volume (β = -0.135, p\u0026thinsp;=\u0026thinsp;0.001), as well as smaller MTL volume (β = -0.098, p\u0026thinsp;=\u0026thinsp;0.017). Individuals with elevated MMP10 were associated with smaller whole brain volume (β = -0.076, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and smaller MTL volume (β = -0.101, p\u0026thinsp;=\u0026thinsp;0.010).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCausal mediation analyses in AD cerebral atrophy\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, BBB-related biomarkers mediated the correlation between peripheral immune biomarkers and regions of interest (ROI) atrophy, CCL26 mediated the associations of NEU%, LYM% and NLR with whole brain, MTL volume and EC thickness, with the ratio of mediation ranging from 7\u0026ndash;13%. CD40 mediated associations of NEU%, LYM%, and NLR with whole brain, hippocampal volume, and MTL volume, with the ratio of mediation ranging from 9\u0026ndash;13%. MMP10 mediated the associations of NEU%, LYM%, and NLR with whole brain, and MTL volume, with the ratio of mediation ranging from 10\u0026ndash;17%. Specific intermediate data can be seen in Additional file 4.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of peripheral immune biomarkers with cognitive function.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and Additional file 5, peripheral immune biomarkers have significant correlations with AD cognitive function. Individuals with elevated NEU% and NLR were associated with higher ADAS score (β\u0026thinsp;=\u0026thinsp;0.124, p\u0026thinsp;=\u0026thinsp;0.002 for NEU% and β\u0026thinsp;=\u0026thinsp;0.097, p\u0026thinsp;=\u0026thinsp;0.021 for NLR), higher CDRSB score (β\u0026thinsp;=\u0026thinsp;0.128, p\u0026thinsp;=\u0026thinsp;0.002 for NEU% and β\u0026thinsp;=\u0026thinsp;0.103, p\u0026thinsp;=\u0026thinsp;0.016 for NLR), lower MEM score (β = -0.175, p\u0026thinsp;=\u0026thinsp;0.004 for NEU% and β = -0.214, p\u0026thinsp;=\u0026thinsp;0.013 for NLR), lower EF score (β = -0.127, p\u0026thinsp;=\u0026thinsp;0.015 for NEU% and β = -0.124, p\u0026thinsp;=\u0026thinsp;0.026 for NLR), lower RAVLT-immediate score (β = -0.103, p\u0026thinsp;=\u0026thinsp;0.012 for NEU% and β = -0.110, p\u0026thinsp;=\u0026thinsp;0.008), as well as lower RAVLT-Delayed Recall score (β = -0.090, p\u0026thinsp;=\u0026thinsp;0.018 for NEU% and β = -0.144, p\u0026thinsp;=\u0026thinsp;0.046 for NLR). On the contrary, individuals with elevated LYM% was associated with lower ADAS score (β = -0.105, p\u0026thinsp;=\u0026thinsp;0.014), lower CDRSB score (β = -0.104, p\u0026thinsp;=\u0026thinsp;0.015), higher MEM score (β\u0026thinsp;=\u0026thinsp;0.171, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher EF score (β\u0026thinsp;=\u0026thinsp;0.138, p\u0026thinsp;=\u0026thinsp;0.010), higher RAVLT-immediate score (β\u0026thinsp;=\u0026thinsp;0.111, p\u0026thinsp;=\u0026thinsp;0.008), as well as higher RAVLT-Delayed Recall score (β\u0026thinsp;=\u0026thinsp;0.144, p\u0026thinsp;=\u0026thinsp;0.039).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociations of BBB-related biomarkers with cognitive function.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and Additional file 5, individuals with elevated CCL26 were associated with higher ADAS score (β\u0026thinsp;=\u0026thinsp;0.146, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower MEM score (β = -0.096, p\u0026thinsp;=\u0026thinsp;0.050), lower RAVLT-immediate score (β = -0.094, p\u0026thinsp;=\u0026thinsp;0.023 for CCL26), as well as lower RAVLT-Delayed Recall score (β = -0.188, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for CCL26). Individuals with elevated CD40 was associated with higher CDRSB score (β\u0026thinsp;=\u0026thinsp;0.134, p\u0026thinsp;=\u0026thinsp;0.002), lower MEM score (β = -0.114, p\u0026thinsp;=\u0026thinsp;0.031). lower EF score (β = -0.198, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Individuals with elevated MMP10 was associated with higher CDRSB score (β\u0026thinsp;=\u0026thinsp;0.136, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCausal mediation analyses in AD cognitive function.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBBB-related biomarkers mediated the correlation between peripheral immune biomarkers and cognitive function, CCL26 mediated the associations of NEU% with global cognition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), immediate memory (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), and delayed memory (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD), with the ratio of mediation ranging from 9\u0026ndash;24%. CD40 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE) and MMP10 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF) only mediated the associations of NEU% with global cognition, with the ratio of mediation ranging from 9\u0026ndash;13%. CCL26 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG), CD40 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH) and MMP10 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI) only mediated the associations of LYM% with global cognition, with the ratio of mediation ranging from 12\u0026ndash;16%. CCL26 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eJ), CD40 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eK) and MMP10 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL) only mediated the associations of NLR with global cognition, with the ratio of mediation ranging from 12\u0026ndash;23%.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing data from 543 individuals from the ADNI, we systematically investigated the potential mechanisms between peripheral immunity and the risk of AD onset. Specifically, our study suggests a significant correlation between peripheral immune and BBB-related biomarker. Both peripheral immune and BBB-related biomarkers are significantly correlated with the AD pathology (CSF Aβ-42, P-tau, P-tau/Aβ-42, and T-tau/Aβ-42), the extent of AD-related cerebral atrophy (whole brain, hippocampal volume, MTL volume, and EC thickness), as well as cognitive function (including global cognition, executive function, memory function, immediate recall, and delayed recall). Most importantly, we found that peripheral immune biomarkers influence AD pathology, cerebral atrophy, and cognitive function through BBB-related biomarkers, providing a more robust and comprehensive evidence chain for the hypothesis of \"inflammation leading to AD\".\u003c/p\u003e \u003cp\u003eAD is a systemic disease involving systemic immune reactions. A large body of research emphasizes the importance of the immune system in AD, Genome-wide association studies (GWAS) have identified immune-related genes such as \u003cem\u003eCLU, CRI, CD33, CD2AP\u003c/em\u003e, and \u003cem\u003eCD20\u003c/em\u003e as risk genes[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], suggesting that manipulating this system within a strategic time window could potentially treat the disease. Under normal circumstances, a healthy brain is protected by resident immune cells (such as microglia) and peripheral immune cells circulating in the periphery[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. AD involves the balance of the central and peripheral immune systems, as well as the balance of innate and adaptive immune systems[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. When this balance is disrupted, peripheral immune cells are activated, leading to increased expression of pro-inflammatory cytokines. If this imbalance persists, it can trigger excessive inflammatory responses, overproduction of inflammatory mediators, causing neurons to be continuously exposed to pro-inflammatory mediators, ultimately resulting in neuronal dysfunction and cell death.\u003c/p\u003e \u003cp\u003eNEU% are typically regarded as markers of innate immunity, while LYM% are considered markers of adaptive immunity, using ratios rather than absolute count of neutrophils or lymphocytes can control for the effects of inter-subject variability. Changes in NLR reflect an imbalance between innate and adaptive immunity[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In AD transgenic models, depletion or inhibition of neutrophil trafficking can reduce AD pathology deposits and improve memory function[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Previous research has found that AD mice with adaptive immune deficiency due to a lack of lymphocytes exhibit greater increases in Aβ pathology[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and immunotherapy that enhances adaptive immune function can enhance Aβ clearance[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Altered balance of innate versus adaptive immunity also influence AD, previous study has found that NLR plays a role in the pathogenesis of AD[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Previous studies have indicated that even mild peripheral inflammation can disrupt the BBB, leading to the infiltration of peripheral immune cells into the brain[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], affecting the clearance of Aβ by microglia and the transport function of neurons[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], further exacerbating CNS inflammation, ultimately promoting the pathological deposition of AD and changes in cognitive function[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Postmortem examinations of AD have found infiltration of neutrophils and lymphocyte in the brain, suggesting peripheral immune cells have indeed crossed the BBB and entered the brain tissue[\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], but the specific mechanisms and processes involved are still unclear.\u003c/p\u003e \u003cp\u003eBBB is a special system of brain microvascular endothelial cells that prevents neurotoxic plasma components, blood cells, and pathogens from entering the brain, providing nutrients to brain tissue, and filtering harmful compounds back into the bloodstream, ensuring dynamic balance of central nervous system components. Disruption of BBB function is associated with human cognitive impairment[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and is considered an early biomarker of AD[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Previous studies have found that dysfunction of the BBB in the hippocampus is associated with an increased risk of AD[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and early breakdown of BBB have been observed before the occurrence of cerebral atrophy and cerebrospinal fluid pathological deposition in AD[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Changes in the level of proteins degrading the tight junctions of the BBB provide evidence for the role of the BBB in the pathogenesis of dementia, and BBB disruption is associated with subsequent central nervous system inflammation and autoimmune reactions[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePeripheral immune cells have the capacity to produce cytokines, chemokines, and MMPs. These molecules play crucial roles in regulating BBB function in AD[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], making them valuable as BBB-related biomarkers. MMP10 could be released by endothelial cells derived from the BBB, regulating the activation of brain-derived growth factors, enzyme degradation, and extracellular matrix remodeling, all of which are essential for the integrity of the BBB, neural network repair, and tissue formation[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. It has been reported that in AD, Aβ disrupts the integrity of the BBB by activating MMP10, and the overexpression of MMPs degrades tight junction proteins, damages endothelial cells, leading to excessive opening of the BBB, thereby exacerbating neuroinflammation and neurotoxicity[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This leads to an increase in the number of aged astrocytes, causing synaptic dysfunction, neuronal damage, and ultimately neuronal death[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. CCL26 is a member of the chemokine family, which can attract peripheral immune cells into the CNS, leading to the entry of harmful blood components into the central nervous system, resulting in cell permeability, abnormal molecular transport, and clearance[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], which is an indicator of BBB dysfunction. In AD patients, microglia and astrocytes are activated, and peripheral immune cells also overexpress[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], secreting excessive chemokines including CCL26, which increase the permeability of BBB and recruit peripheral immune cells to cross the disrupted BBB, accumulating in inflammatory brain tissue lesions and Aβ plaques[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], promoting the inflammatory response[\u003cspan additionalcitationids=\"CR52 CR53\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], and accelerating the progression of AD[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. CD40 is a cell surface molecule primarily produced by peripheral immune cells, which, together with nitric oxide, induces increased BBB permeability and leukocyte extravasation[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The interaction between CD40 and its homologous ligand CD40 ligand (CD40L) is a major regulatory factor in peripheral immune responses, regulating the activation and differentiation of immune cells. CD40-CD40L-mediated aberrant neuroinflammation increases BBB permeability and damage[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], and can promote the production of neurotoxic factors by microglial cells, directly leading to BBB vascular damage[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], and synergistically enhancing the aggregation of tau protein and Aβ[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], thereby promoting the progression of AD patient[\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In summary, given the BBB is highly sensitive to inflammatory stimuli, peripheral immunity affects AD by affect the following BBB function: 1) altering the density of the BBB; 2) increasing the permeability of BBB 3) activating astrocytes and microglia; 4) damaging endothelial cells.\u003c/p\u003e \u003cp\u003eOur study has several strengths. Firstly, it is the first systematic exploration of the mediating role of BBB-related markers between peripheral immune cells and AD, these findings consolidated the close relationships of peripheral immunity with AD pathology, cerebral atrophy and cognitive function, supporting the hypothesis that inflammation leading to AD. Additionally, our mediation analysis exhibits strict triangular stability: we only included indicators that show all significant correlations between the independent variable and the mediator, the independent variable and the dependent variable, and the mediator and the dependent variable.\u003c/p\u003e \u003cp\u003eThere are limitations in this study. First, our exposure analysis was limited to blood cell count, percent, and derived ratios due to the lack of flow cytometry or ELISA data. Second, although BBB-related biomarkers are BBB function indicators, they cannot directly assess its integrity as effectively as contrast agents. Third, although we excluded patients with significant inflammation, we could not avoid the effect of the occasional use of anti-inflammatory drugs on the numbers of immune cells. Last, the cohort was predominantly composed of people of European ancestry, so some findings may not apply to the entire general population.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, we found that peripheral immunity and BBB-related biomarkers are associated with AD pathology, cerebral atrophy and cognitive function, and peripheral cells impact AD by affecting the function of the BBB. Therefore, reducing the disruption of the BBB could serve as a potentially useful therapeutic approach to limit the harmful infiltration of peripheral immune cells into the central nervous system.\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\"\u003eADNI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlzheimer\u0026rsquo;s Disease Neuroimaging Initiative\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAβ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eβ-Amyloid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlzheimer's Disease Assessment Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBBB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eblood brain barrier\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDRSB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinical Dementia Rating Sum of Boxes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecognitively normal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecerebrospinal fluid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCNS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecentral nervous system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCL26\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eeosinophil chemotactic factor-3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCD40L\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCD40 ligand\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eexecutive function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eentorhinal cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFLAIR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efluid-attenuated inversion recovery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehippocampal volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLYM%\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elymphocytes percent\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ememory function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMP10\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ematrix metalloproteinase-10\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emild cognitive impairment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNEU%\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneutrophils percent\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneutrophil-lymphocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNFT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneurofibrillary tangles\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eP-tau\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ephosphorylated-tau\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRAVLT-immediate\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRey Auditory Verbal Learning Test-immediate-total immediate recall score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRAVLT-Delayed Recall\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRey Auditory Verbal Learning Test- logical memory delayed recall score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereactive oxygen species\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eregions of interest\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etumor necrosis factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT-tau\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etotal tau\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by institutional review boards of all participating institutions, and written informed consent was obtained from all participants or their guardians according to the Declaration of Helsinki (consent for research).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset generated and analyzed in the current study is available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;This work was supported by the National Natural Science Foundation of China (82271464).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJHH and LYW conceptualized the study, and revised the manuscript. JHH, and DMJ analyzed and interpreted the data, drafted and revised the manuscript, did the statistical analysis, and prepared all the figures. MC participated in the interpretation of the data and revision of the manuscript. All authors contributed to the writing and revisions of the paper and approved the final version. Data used in the preparation of this article were obtained from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection and sharing for this project was funded by the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer\u0026rsquo;s Association; Alzheimer\u0026rsquo;s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.;Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research \u0026amp; Development, LLC.; Johnson \u0026amp; Johnson Pharmaceutical Research \u0026amp; Development LLC.; Lumosity; Lundbeck; Merck \u0026amp; Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and education, and the study is coordinated by the Alzheimer\u0026rsquo;s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.Data used in the preparation of this article were obtained from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eScheltens P, et al. 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Lancet. 2015;385(9967):517\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Peripheral immunity, blood brain barrier, Alzheimer’s disease, Mediation","lastPublishedDoi":"10.21203/rs.3.rs-4437508/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4437508/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe association between peripheral immunity and Alzheimer's disease (AD) has been increasingly recognized, but the underlying mechanisms are still unclear. This study aims to investigate whether peripheral immunity affects AD by influencing blood-brain barrier (BBB) function.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eMultiple linear regression models were employed to explore the association between peripheral immune biomarkers [neutrophils percent (NEU%), lymphocytes percent (LYM%), and neutrophils / lymphocytes (NLR)] and AD biomarkers (including AD pathology, cerebral atrophy degree, and cognitive function). Subsequently, multiple linear regression models were performed to investigate the association between BBB-related biomarkers [chemotactic factor-3 (CCL26), CD40 and matrix metalloproteinase-10 (MMP10)] and AD biomarkers. Finally, causal mediation analysis with 10,000 bootstrapped iterations was conducted to investigate the functions of BBB-related biomarkers in mediating the associations peripheral immune biomarkers with AD pathology, cerebral atrophy degree, as well as cognitive function.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 543 participants (38.7% female, mean age of 74.8 years) from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) were involved. NEU%, LYM%, NLR, and CCL26 were significantly associated with cerebrospinal fluid (CSF) β-amyloid-42 (Aβ-42), phosphorylated-tau (P-tau), total tau (T-tau)/Aβ-42 and P-tau/Aβ-42, the associations of NEU% with AD pathology were mediated by CCL26 (proportion: 18% ~ 24%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). NEU%, LYM%, NLR, CCL26, CD40 and MMP10 were significantly associated with whole brain, hippocampal volume, middle temporal lobe (MTL) volume, and entorhinal cortex (EC) thickness, the associations of peripheral immune biomarkers with cerebral atrophy degree were mediated by BBB-related biomarkers (proportion: 7% ~ 17%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). NEU%, LYM%, NLR, CCL26, CD40 and MMP10 were significantly associated with global cognition, executive function, memory function, immediate recall, and delayed recall, the associations of peripheral immune biomarkers with cognitive function were mediated by BBB-related biomarkers (proportion: 9% ~ 24%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study suggests that both peripheral immune and BBB-related biomarkers are associated with AD pathology deposition, cerebral atrophy degree and cognitive function, and peripheral immunity may influence AD through influencing BBB function, providing a more robust and comprehensive evidence chain for the potential role of inflammation in AD.\u003c/p\u003e","manuscriptTitle":"Peripheral immunity affects Alzheimer’s disease by influencing blood-brain barrier function","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 21:46:59","doi":"10.21203/rs.3.rs-4437508/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"
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