Association of pulse pressure with presynaptic dysfunction in older adults with Alzheimer’s disease: a cohort study

Abstract

Vascular aging and synaptic dysfunction are closely related to Alzheimer’s disease (AD) pathology, but the link between the two remains unclear. We aimed to investigate the relationship among pulse pressure (PP), presynaptic dysfunction, and in vivo AD pathologies, including amyloid beta (Aβ) deposition and cerebrospinal fluid (CSF) phosphorylated tau (p-tau). A total of 649 older adults, both cognitively normal and with mild cognitive impairment, were recruited from the Alzheimer’s Disease Neuroimaging Initiative database. We investigated the associations of PP with CSF GAP-43, a marker of presynaptic dysfunction, and CSF p-tau. The mediation effect of presynaptic dysfunction on the association between PP and CSF p-tau was also examined. Elevated PP was significantly associated with greater presynaptic dysfunction (unstandardized B = 26.774, 95% confidence interval (CI) [12.102, 41.447], t = 3.583, p < 0.001) and elevated levels of CSF p-tau (B = 0.102, 95% CI [0.037, 0.168], t = 3.093, p = 0.002) and total tau (B = 0.927, 95% CI [0.331, 1.524], t = 3.052, p = 0.002). A positive interaction between PP and cortical Aβ deposition (F = 12.752, p < 0.001) indicated that PP resulted in severe presynaptic dysfunction as Aβ deposition increased. Further analyses revealed that presynaptic dysfunction mediated the association between PP and CSF p-tau. PP had no significant direct effect but had a significant indirect effect (81.6% of the total) on CSF p-tau. Elevated PP exacerbated presynaptic dysfunction in nondemented older adults, particularly those with AD pathology, and can lead to tau pathology. Further research on the mechanism underlying the relationship between PP and presynaptic dysfunction is warranted.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-12821-x.

Introduction

Alzheimer’s disease (AD) is a progressive neurodegenerative condition that affects approximately one third of individuals aged ≥ 65 years and is the primary cause of dementia¹. It is characterized by sequential pathophysiologic brain changes, including deposition of amyloid beta (Aβ) plaques, formation of neurofibrillary tangles (NFT), and neurodegeneration².

Vascular risk factors (VRFs), such as hypertension and diabetes mellitus, and synaptic dysfunction are closely intertwined with AD pathology^3–6. Several studies have revealed associations between AD biomarkers and vascular aging indicators, such as brachial artery pulse pressure (PP), suggesting a direct link between vascular aging and AD progression, particularly in the early stages. In a previous study involving nondemented participants, elevated PP was found to be significantly associated with high levels of cerebrospinal fluid (CSF) phosphorylated tau (p-tau) and an interaction with reduced CSF Aβ42 levels⁷.

Synaptic dysfunction is a significant aspect of AD pathology, in which Aβ and p-tau aggregation disrupts synapse integrity. Growth-associated protein 43 (GAP-43) is a presynaptic protein involved in axonal outgrowth, synaptic plasticity, and memory formation⁸. As a biomarker of presynaptic dysfunction, increased CSF GAP-43 levels were reported in patients with AD and positively correlated with the severity of NFT and Aβ plaques⁹. Moreover, a recent study revealed that GAP-43-related synaptic alterations were associated with accelerated propagation of Aβ-related tau pathology^10,11 and predict longitudinal cognitive decline in AD^12,13. Notably, CSF GAP-43 has also been shown to reflect early synpatic degeneration in AD¹⁴. Other synpatic biomarkers—such as synaptosomal-associated protein 25 (SNAP-25), neurogranin, and 14-3-3 proteins—have also been associated with AD and other neurodegenerative disease; however, their association with early synaptic changes in AD is less well established^15,16. Given its dynamic response to both tau and Aβ pathology and its potential to detect early synaptic alterations, GAP-43 was selected in this study as a representative marker of presynaptic dysfunction.

Based on the aforementioned studies, vascular aging and synaptic dysfunction are closely related to AD pathology; however, the link between the two remains unknown. Elevated PP can lead to endothelial cell dysfunction and damage the blood-brain barrier (BBB)^17,18. Disruption of the neurovascular unit (NVU) and breakdown of the BBB can propagate neurotoxic effects and eventually lead to synaptic dysfunction and degeneration^19,20. However, the mechanism linking PP to AD pathology is not fully understood and no previous studies have investigated the associations between PP and GAP-43 and in vivo AD pathology.

In this study, we hypothesized that elevated PP contributes to AD pathology through its link with presynaptic dysfunction. Our aim was to investigate the associations of PP with presynaptic dysfunction, as measured by CSF GAP-43, and AD biomarkers in nondemented participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database.

Results

Demographic and clinical characteristics of the participants

The characteristics of the 649 participants included in the study are presented in Table 1. There were 407 individuals with mild cognitive impairment (MCI) and 242 cognitively normal (CN) participants. The low and high PP groups were comparable in terms of sex, years of education, clinical diagnosis, and apolipoprotein E ε4 (APOE4) positivity. Notably, compared with the low PP group, the high PP group was older and exhibited higher mean arterial pressure (MAP) and vascular risk score (VRS).

Table 1.

Characteristic of the participants.

	All participants	Low pulse pressure (≤ 63 mmHg)	High pulse pressure (> 63 mmHg)	t or χ2	p value
N	649	421	228
Age	71.92 ± 7.00	70.773 ± 6.86	74.036 ± 6.76	5.838	< 0.001
Female	316 (48.7)	194 (46.1)	122 (52.5)	2.976	0.085
Education (yrs)	16.373 ± 2.58	16.499 ± 2.57	16.14 ± 2.58	−1.69	0.092
Pulse pressure (mmHg)	59.348 ± 14.75	50.741 ± 8.35	75.241 ± 10.03	31.451	< 0.001
MAP (mmHg)	93.431 ± 10.27	91.458 ± 9.75	97.076 ± 10.21	6.796	< 0.001
VRS	1.185 ± 1.03	1.109 ± 0.97	1.325 ± 1.11	2.465	0.014
Current smoker	255 (39.3)	166 (39.4)	89 (39.0)	0.0002	0.989
APOE4 positivity	268 (41.3)	179 (42.5)	89 (39.0)	0.603	0.437
Clinical diagnosis				1.348	0.246
CN	242 (37.3)	148 (35.2)	94 (41.2)
MCI	407 (62.7)	273 (64.8)	134 (58.8)
Cortical Aβ deposition	1.185 ± 0.22	1.173 ± 0.22	1.206 ± 0.23	1.788	0.074
CSF GAP-43 (pg/mL)	5063.928 ± 2766.16	4732.482 ± 2389.1	5675.94 ± 3271.4	3.836	< 0.001
CSF p-tau (pg/mL)	24.666 ± 12.98	23.467 ± 12.15	26.875 ± 14.14	3.075	0.002
CSF total tau (pg/mL)	261.044 ± 118.22	248.716 ± 110.57	283.806 ± 128.34	3.487	0.001
Aβ positivity	310 (47.8)	192 (45.6)	118 (51.8)	2.001	0.157

Data are shown mean ± standard deviation or n (%).

Chi-square test or independent t-test was used to compare groups.

Aβ beta amyloid, APOE4 apolipoprotein E ε4, CN cognitively normal, GAP-43 growth-associated protein 43, MAP mean arterial pressure, MCI mild cognitive impairment, p-tau phosphorylated tau, VRS vascular risk score.

Associations of pulse pressure with presynaptic dysfunction and AD pathologies

Elevated PP was significantly associated with higher levels of CSF GAP-43 (unstandardized B = 26.774, 95% confidence interval (CI) [12.102, 41.447], t = 3.583, adjusted p = 0.001; Table 2; Fig. 1A), CSF p-tau (B = 0.102, 95% CI [0.037, 0.168], t = 3.093, adjusted p = 0.003; Table 2), and CSF total tau (t-tau) (B = 0.927, 95% CI [0.331, 1.524], t = 3.052, adjusted p = 0.003; Table 2). However, no significant association was observed between PP and cortical Aβ deposition (B = 0.0004, 95% CI [− 0.0007, 0.0014], t = 0.673, p = 0.501; Table 2).

Table 2.

Associations of pulse pressure with CSF GAP-43 and alzheimer’s disease pathologies.

	B	SE	T	p value	FDR-adjusted p	95% CI
CSF GAP-43	26.774	7.472	3.583	< 0.001	0.001*	12.102, 41.447
CSF p-tau	0.102	0.033	3.093	0.002	0.003*	0.037, 0.168
CSF total tau	0.927	0.304	3.052	0.002	0.003*	0.331, 1.524
Cortical Aβ deposition	0.0004	0.0005	0.673	0.501	0.501	−0.0007,0.0014

All analyses were adjusted for age, sex, years of education, APOE4 positivity, VRS, clinical diagnosis, and smoking status.

Aβ beta amyloid, APOE4 apolipoprotein E ε4, SE standard error, CI confidence interval, FDR false discovery rate, GAP-43 growth-associated protein 43, p-tau phosphorylated tau, VRS vascular risk score.

* Statistically significant after FDR correction (q < 0.05).

Fig. 1.

Association between PP and CSF GAP-43 in relation to cortical Aβ deposition and age group. Linear regression plots illustrating the association between PP and CSF GAP-43 (A). The interaction effects of cortical Aβ deposition (B) and age group (very old versus young old) (C) on the relationship between PP and CSF GAP-43 levels are also shown. Shaded areas represent the 95% confidence intervals. PP pulse pressure, CSF cerebrospinal fuid, GAP-43 growth-associated protein 43, Aβ amyloid-beta.

A significant positive interaction effect was observed between PP and cortical Aβ deposition in relation to CSF GAP-43 (F = 12.752, p < 0.001; Table 3; Fig. 1B). Similarly, a significant interaction was identified between Aβ positivity and PP (F = 7.897, p = 0.005; Table 3). Subgroup analyses further showed that PP was positively associated with CSF GAP-43 only in the Aβ-positive participants (B = 44.68, t = 4.538, p < 0.001; Table 3), but not in the Aβ-negative participants (B = 5.18, t = 0.497, p = 0.619; Table 3), as illustrated in the boxplots stratified by PP and Aβ status (Figure S1).

Table 3.

Interaction effects of Aβ positivity and Aβ deposition with pulse pressure on CSF GAP-43.

	B	SE	T	p value
Aβ deposition × pulse pressure	109.60	30.69	3.571	< 0.001
Aβ positivity × pulse pressure	39.501	14.057	2.810	0.005
Aβ negative	5.18	10.41	0.497	0.619
Aβ positive	44.68	9.84	4.538	< 0.001

All analyses were adjusted for age, sex, years of education, APOE4 positivity, VRS, clinical diagnosis, and smoking status. If an interaction effect was significant, subsequent subgroup analyses was performed.

Aβ beta amyloid, APOE4 apolipoprotein E ε4, GAP-43 growth-associated protein 43, PP pulse pressure, p-tau phosphorylated tau, VRS vascular risk score.

Mediation analysis further showed that CSF GAP-43 significantly mediated the association between PP and CSF p-tau. While the direct effect of PP on CSF p-tau was not significant, the indirect effect via CSF GAP-43 was significant and accounted for 81.6% of the total effect (Fig. 2).

Fig. 2.

Mediation effects of CSF GAP-43 on the association between pulse pressure and CSF phosphorylated tau. The bold lines indicate p-values of < 0.05. CSF cerebrospinal fuid, GAP-43 growth-associated protein 43, Aβ amyloid-beta, CI confidence interval, SE standard error

Interaction effects of age, sex, diagnosis, and APOE4 positivity on presynaptic dysfunction

The effects of PP on CSF GAP-43 had no interaction with APOE4 status, sex, and diagnosis (CN vs. MCI) but had a significant interaction with age group (F = 4.477, p = 0.035; Table S1). Specifically, the association between PP and CSF GAP-43 exhibited a steeper slope in the very old group than in the young old group (Fig. 1C, Table S1). Although the interaction with diagnosis was not significant, subgroup analyses showed that PP was positively associated with CSF GAP-43 in both CN (B = 26.79, p = 0.02) and MCI (B = 26.76, p = 0.005) groups, with comparable regression slopes (Figure S2).

Sensitivity analyses

To determine whether the findings were specific to PP, we repeated the analyses using systolic blood pressure (SBP), diastolic blood pressure (DBP), and MAP instead of PP. In the analyses, elevated GAP-43 levels were not significantly associated with DBP (B = − 20.20, standard error (SE) = 11.39, t = − 1.774, p = 0.076) and MAP (B = 0.18, SE = 10.53, t = 0.017, p = 0.986) but were positively associated with higher SBP (B = 13.45, SE = 6.51, t = 2.065, p = 0.039) (Table S3). However, when PP and SBP were entered into the same model, the association became nonsignificant for SBP (B = − 17.16, SE = 11.32, t = − 1.515, p = 0.130) but remained significant for PP (B = 43.05, SE = 13.08, t = 3.291, p = 0.001).

To verify the robustness of the associations between PP and CSF AD biomarkers, bootstrapped regression analyses were also performed. The bootstrapped estimates were consistent with the parametric results, confirming statistical robustness (Table 2, Table S2).

Discussion

Our findings revealed significant relationships between PP and the presynaptic dysfunction marker CSF GAP-43, and CSF p-tau levels. Mediation analysis further suggested that CSF GAP-43 may serve as potential pathway through which vascular aging contributes to tau pathology. These associations were particularly pronounced in individuals with higher cortical Aβ deposition and in the very old group. To the best of our knowledge, this is the first study to demonstrate a relationship between vascular aging and presynaptic dysfunction in older adults, even after adjusting for age, sex, APOE4 status, and VRFs. A schematic illustration of the proposed mechanism is presented in Supplementary Fig. 3.

In our study, PP was positively associated with presynaptic dysfunction in nondemented older adults, especially those who were Aβ-positive. This finding aligns with previous studies reporting synaptic dysfunction as a hallmark of AD²¹. Notably, CSF GAP-43—a key component of the presynaptic terminal involved in synaptic plasticity, axonal outgrowth, and learning processes—has been shown to be associated specifically with AD, but not with other types of dementia²².

The observed association between PP and GAP-43 may reflect underlying vascular mechanisms contributing to synaptic degeneration. In the brain, vascular cells are closely situated near parenchymal cells, including neurons, glial cells, and astrocytes, collectively forming the NVU²³. High PP is known to affect cerebral microvasculature through endothelial cell injury and ultimately disrupt the associated NVU and BBB²⁴. BBB disruption can allow entry of neurotoxic products into the brain, which can damage astrocytes and other NVU components, leading to NVU damage and synaptic dysfunction²⁵. Consistent with this mechanism, growing evidence has implied a relationship between disrupted NVU and AD-related pathology^20,26,27.

Furthermore, our findings indicate that PP may interact with Aβ pathology to exacerbate synaptic dysfunction, as measured by CSF GAP-43. Aβ deposition, often triggered by stress, neuroinflammation, and vascular/endothelial dysfunction, can increase neuronal vulnerability to PP-related damage^28,29.

Importantly, our mediation analysis further suggests that presynaptic dysfunction may be a pathway linking vascular aging to tau pathology. Specifically, CSF GAP-43 partially mediated the relationship between PP and CSF p-tau level. While a previous study using the ADNI database revealed a positive association between PP and CSF p-tau, the underlying mechanism was not precisely known⁷. It has been suggested that Aβ-indcued hyperexcitatory activity in the early stages of AD may facilitate the propagation of tau pathology in the brain³⁰. In line with this, a recent study reported that the elevated CSF GAP-43 may accelerate tau spread in patients with AD pathology¹⁰. Taken together with our findings, these results suggest that vascular aging, via increased PP, may contribute to tau pathology through presynaptic dysfunction. However, due to the cross-sectional design, causal inferences cannot be drawn, highlighting the need for longitudinal investigation to confirm the mediating role of presynaptic dysfunction.

The relationship between PP and presynaptic dysfunction was more profound in the very old group (80–91 years), when compared with that in the young old group. Considering that age is a well-known major risk factor for vascular damage and neurodegeneration, individuals in the very old group likely have increased BBB permeability and worse cerebral microvascular disease, which increase the susceptibility to vascular impact³¹.

Finally, in our sensitivity analysis, PP was specifically associated with elevated CSF GAP-43 levels but not with the other BP indicators, such as DBP and MAP. Arterial stiffening is known to be independent of other traditional VRFs and often precedes hypertension³². PP exposes the downstream circulation to increased tensile strain and triggers adaptive vessel remodeling, resulting in microcirculation damage, particularly in high-flow organs, such as the kidneys and brain³³. Therefore, rather than hypertension itself, high PP may be more closely associated with early neuronal changes, as evidenced by elevated GAP-43 levels.

A strength of this study was the relatively large sample size and the use of the ADNI database, which is well-documented with standardized biomarkers. To the best of our knowledge, our study was the first to examine the relationship between PP and presynaptic dysfunction and the first to document the mediation effect of presynaptic dysfunction on vascular aging and tau pathology. We were able to elucidate that PP was associated with early biomarkers of AD, specifically CSF GAP-43 level. The limitation of our study was its cross-sectional design, which prevented us from concluding the causality of the associations observed. Nevertheless, our findings supported the possible contribution of vascular aging to the pathogenesis and/or progression of AD through presynaptic dysfunction. This result was further supported by the observation that a high PP was associated with a greater increase in the GAP-43 level in the very old group. Another limitation was that we did not include other synaptic dysfunction markers, such as SNAP-25 and neurogranin. Further research is needed to investigate the relationship between PP and these additional markers.

In conclusion, elevated PP was found to exacerbate presynaptic dysfunction in AD by mediating tau propagation, even after adjusting for other VRFs; this relationship was not observed in non-AD individuals. Further research on the mechanisms underlying the relationship between PP and AD is warranted.

Methods

Participants

This study used the database from the ADNI (https://adni.loni.usc.edu), which was initiated in 2003 as a public-private partnership by its principal investigator, Michael W. Weiner, MD. The main goal of the ADNI is to develop and validate AD biomarkers for clinical trials using longitudinally acquired imaging and biospecimens from carefully phenotyped subjects. The ADNI study was approved by the institutional review boards of all participating centers, and all participants provided written informed consent. In this present study, 649 nondemented participants who had baseline CSF GAP-43, CSF p-tau, CSF t-tau, and ¹⁸F-florbetapir imaging were included. The study population comprised 242 CN participants and 407 with MCI.

Blood pressure assessment

Seated brachial artery systolic and diastolic blood pressures were measured. PP was calculated by subtracting DBP from SBP. Participants were categorized into high and low PP groups using a cutoff value of 63 mmHg^7,34. The MAP was calculated by adding one third of the PP to the DBP.

Vascular risk factors

Medical histories of the participants were determined during clinical interviews and physical examinations at the study site. The presence or absence of vascular risk factors (VRFs), including hypertension, diabetes mellitus, dyslipidemia, coronary heart disease, transient ischemic attack, and stroke was assessed from participant’s medical history and current medication. The VRS was calculated as the cumulative number of VRFs³⁵. Smoking status was recorded as current smoker or not.

Cerebrospinal fluid biomarkers

Lumbar punctures were performed as described in the ADNI procedures manual (https://adni.loni.usc.edu/). CSF p-tau and t-tau were measured using Elecsys phosphotau (181P) CSF and Elecsys total-tau CSF immunoassays on a Cobas e 601 analyzer (software version 05.02) at the Biomarker Research Laboratory, University of Pennsylvania USA³⁶. CSF GAP-43 levels were assessed using an in-house enzyme-linked immunosorbent assay at the Clinical Neurochemistry Laboratory of Sahlgrenska University Hospital, Mölndal, Sweden, as described previously⁹.

Positron emission tomography image analysis

Cerebral Aβ deposition was assessed using the positron emission tomography (PET) tracer ¹⁸F-florbetapir. PET images were acquired and processed as previously described³⁶. Composite region of interests was derived by calculating the weighted average of the frontal, temporal, parietal, and cingulate regions³⁷. Cortical Aβ deposition was defined as a composite standardized uptake value ratio using the entire cerebellum as a reference. Aβ positivity was determined by a cutoff value of 1.11 for cortical Aβ deposition³⁷.

Statistical analysis

All statistical analyses were conducted using R version 4.3.0 (The R Foundation for Statistical Computing, Vienna, Austria). Baseline characteristics between the high and low PP groups were compared using chi-square tests for categorical variables and independent t-tests for continuous variables. We used multiple linear regression models to test the relationships of PP with continuous variables, such as AD pathologies, which were measured as CSF p-tau, CSF t-tau, and cortical Aβ deposition. In these models, each biomarker of interest was set as a dependent variable while controlling for age, sex, years of education, APOE4 positivity, VRS, smoking status, and clinical diagnosis. In our main analysis, we applied a similar linear regression model with CSF GAP-43, a marker of presynaptic dysfunction, as the dependent variable. Assumptions of residual normality, homoscedasticity, and multicollinearity were assessed. To address mild deviations from normality and homoscedasticity identified via visual inspection, we performed bootstrap resampling (5,000 iterations) to estimate the coefficient of PP and 95% CI as a sensitivity analysis.

The interaction effect of cortical Aβ deposition with PP on CSF GAP-43 was examined by adding an interaction term (cortical Aβ deposition × PP) to the model. Furthermore, considering the potential sequential effects of GAP-43 on p-tau levels, we tested whether CSF GAP-43 mediated the association between PP and CSF p-tau. In this analysis, we adjusted for the aforementioned covariates and performed bootstrapping with 5,000 resamples.

For exploratory purposes, we also analyzed the interaction effects of PP by age group [young old (55–79 years) vs. very old (80–91 years)], sex, diagnosis, and APOE4 positivity by adding each interaction term to the linear regression model. Sensitivity analyses were conducted to examine the association between GAP-43 and alternative blood pressure indices (SBP, DBP, and MAP) in place of PP.

To account for multiple comparisons among biomarkers, we applied false discovery rate (FDR) correction using the Benjamini–Hochberg procedure. A two-sided P-value of < 0.05 was judged as statistically significant if not otherwise specified. All B values reported are unstandardized.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

N.Y.K., G.H.W., and J.H.J. conceived concept and design of the study, and participated in acquisition, analysis and interpretation of data, statistical analysis, drafting of the manuscript. ADNI provided data analyzed in the study.

Data availability

All data used in this article are available to the public at the ADNI website (https://adni.loni.usc.edu).

Declarations

Competing interests

The authors declare no competing interests.