Examining the independent and moderating effects of arterial stiffness and cerebral blood flow on total hippocampal and hippocampal subfield volumes

Introduction: There is a critical link between vascular disease and the progression to dementia. The hippocampus has been implicated in memory and cognitive decline. In this study, we investigate the independent and moderating effects of increased arterial stiffness (AS) and reduced cerebral blood flow (CBF) on hippocampal volume (HV) in a large MRI sample of community-dwelling older adults from the Irish Longitudinal Study on Ageing (TILDA).

Methods: Longitudinal data from study participants for Wave 1 (2009–2011) and Wave 3 (2014-2015) were included. This included health and social information as well as a nurse-administered health assessment. Patients who had complete AS, CBF and MR-hippocampal measurements were included. Pseudo-continuous arterial spine labelling was performed to quantify whole CBF. Volumetric analysis was performed using FreeSurfer 6.0 recon-all processing pipeline.

Results: 395 patients met inclusion criteria. This four-year follow up longitudinal study demonstrated that (i) prolonged elevated AS (at wave 1 and wave 3), (ii) the interaction between higher AS at wave 1 and lower CBF at wave 3 and (iii) the interaction between prolonged elevated AS (at wave 1 and wave 3) and reduced CBF at wave 3 were associated with smaller HV.

Conclusion: Increased arterial stiffness and reduced CBF were not independently associated with smaller HV. However, in combination, persistently elevated AS and reduced CBF is associated with smaller HV. These effects were equally exerted across all hippocampal subfields tested. Our findings suggest a lag effect in the arterial stiffness and hippocampal volume relationship. We propose that the subsequent reduction in cerebral blood flow observed with elevated arterial stiffness may be the missing link in the pathway associating arterial stiffness with hippocampal atrophy.

Introduction

Dementia is a major health issue with considerable health, social and economic costs for individuals, their families, and societies. It presents significant challenges to healthcare systems, affecting approximately 57 million people worldwide, a number which is predicted to rise to 153 million by 2050. As no cure exists, the identification of risk factors and the implementation of prevention strategies are a crucial step towards decreasing dementia incidence (Nichols et al., 2022). Cardiovascular health is believed to play an important role in this pathogenesis, and arterial stiffening has been identified as a key risk factor that increases dementia risk (Scuteri, 2007).

The deleterious effects of elevated arterial stiffness (AS) on cerebral health are well-established. Increased arterial stiffening has been associated with lower total brain volumes and a higher incidence of cerebral artefacts and white matter lesions in healthy older adults and in patient cohorts in both cross-sectional and longitudinal studies (Henskens et al., 2008; Matsumoto et al., 2007; Ohmine et al., 2008). The literature also supports a link between elevated arterial stiffness and cognitive impairment with progression to dementia (Henskens et al., 2008; Pase et al., 2016; Rouch et al., 2018; Benetos et al., 2012; Scuteri et al., 2007; Hanon et al., 2005). Negative associations between AS and total hippocampal volumes (a hallmark of AD) have been observed in many cross-sectional and longitudinal studies (Baradaran et al., 2021; Bown et al., 2021).

It has been proposed that increased arterial stiffness leads to cerebral hypoperfusion (Ajamu et al., 2021; Suri et al., 2020; Sadekova et al., 2018; Jefferson et al., 2018; Muhire et al., 2019; Tarumi et al., 2011). This may, in turn, lead to neuronal death with subsequent cerebral atrophy, as is seen selectively in the hippocampus in memory decline (Jack et al., 2000; Jack et al., 1998; Jobst et al., 1994). Several studies have reported an association between lower cerebral blood flow with smaller hippocampal volumes and progression to cognitive impairment (Knoops et al., 2009; Mak et al., 2014; Chao et al., 2010). The link between increasing arterial stiffness and reduced cerebral blood flow is also well established (Ajamu et al., 2021; Suri et al., 2020; Sadekova et al., 2018; Jefferson et al., 2018; Muhire et al., 2019; Tarumi et al., 2011). However, the causal relationships and interactions between these pathways, as well as associated compensatory mechanisms are less well understood. For example, to date, no studies have together described the independent and moderating effects of increased arterial stiffness and reduced CBF on the hippocampal volume in a healthy older population, but it could be assumed that raised arterial stiffness either alone or in combination with a reduction in cerebral blood flow may lead to selective atrophy of the hippocampus through this proposed mechanism of hypoperfusion and neuronal death. Additionally, no studies have addressed the issue of specific hippocampal subfields, and some subfields appear to be more vulnerable to hypoxia and ischemia than others, like the Cornu Ammonis (CA) 1, CA4, and subiculum subfields (Schmidt-Kastner and Freund, 1991; Bonnekoh et al., 1990; Kim et al., 2015). For example, a recent study by Pin et al. (2021), examined the rate of volume loss in the hippocampal subfields CA1-CA3, CA4 and the subiculum over four-years in 249 non-demented older adults and examined their interaction with white matter hyperintensities, believed to be a surrogate marker for vascular damage. They identified the subiculum to be particularly vulnerable to ischemia with a significant association between WMH’s and subiculum volume loss, independent of vascular risk factors (p = 0.03) (Pin et al., 2021).

In this study, we investigate the independent and moderating effects of AS and CBF on total hippocampal volume in a large MRI sample of community-dwelling older adults from a nationally representative population-based study, the Irish Longitudinal Study on Ageing (TILDA). In supplementary analyses, we also examine if these effects are specific to certain hippocampal subfields which are known to be vulnerable to AS and CBF alterations: the CA1, CA3, CA4, subiculum, and dentate gyrus (DG). Specifically, we test the hypotheses that (i) higher AS is associated with lower total hippocampal volumes and that (ii) reduced CBF may moderate this relationship. We also test the hypotheses that (iii) persistently higher AS over a four-year follow-up period and (iv) the co-occurrence of higher AS and low CBF may have more significant effects on hippocampal volumes. Finally we hypothesize that these effects may be exerted maximally in the CA-1, CA-4 and subiculum subfields.

Methods

Study design and participants

We used data from a nationally representative population-based study of community-dwelling older adults aged 50 years and older resident in the Republic of Ireland, The Irish Longitudinal Study on Ageing (TILDA). TILDA’s random sampling procedure and study design have been previously described (Whelan and Savva, 2013). Participants have been followed biennially from Wave 1 (2009–2011), and this study includes data from Wave 1 (2009–2011) and Wave 3 (2014–2015). At each wave, a computer-assisted personal interview (CAPI) collected information on the participants’ social and health information. At Wave 1 and Wave 3, participants were also invited to take part in an extensive nurse-administered health assessment in a dedicated health centre or a modified version in the participant’s home. Among the 6,687 who completed a CAPI at Wave 3, 4,309 attended the health centre, of whom 560 underwent multimodal Magnetic Resonance Imaging (MRI). The study sample consists of 395 participants who had arterial stiffness measurements at Wave 1 and Wave 3, and cerebral blood flow and MR-hippocampal volume measurements at Wave 3 (Supplementary Figure 1).

MRI protocol

MRI scanning was completed at Wave 3, at the National Centre for Advanced Medical Imaging (CAMI) at St. James’s Hospital, Dublin, using a 3 Tesla Philip’s Achieva system and a 32 channel head coil. The protocol included a T1-weighted 3D Magnetisation Prepared Rapid Gradient Echo (MP-RAGE) sequence, with the following parameters: FOV (mm): 240 × 218 × 162; 0.9 mm isotropic resolution; SENSE factor: 2; TR: 6.7 ms; TE: 3.1 ms; flip angle: 9; and pseudo-continuous arterial spin labelling (pCASL) sequences. Upstreaming arterial blood flow in the neck was labelled using a series of tightly packed inversion pulses. Following this, a short interval was allowed to facilitate this labelled blood to perfuse the brain parenchyma. The perfused brain was then imaged using a 2D multislice single echo-planar imaging (EPI) with suppression of the background tissue performed on two occasions during the pCASL sequence. The pCASL sequences parameters were: field of view 240 × 240 mm², the matrix was 80 × 80, the repetition time was 4,000 ms, the echo time was 9 ms, flip angle of 90^o, SENSE of 3.5 and the scan duration was 4 min and 16 s. A total of 13 slices were obtained yielding 30 dynamic scans and a total of 780 images. An 1800 millisecond labelling duration in addition to a post-label delay (PLD) of 1800 ms were applied, as advised in the ASL consensus paper (Alsop et al., 2015).

Outcome

Hippocampal volume measurement

All T1w images were reviewed by a trained operator blind to participant identity for image artifact and for the presence of lesions. Volumetric analysis was performed using FreeSurfer version 6.0 recon-all processing pipeline, an automated segmentation tool for volume measurement (Dale et al., 1999; Fischl et al., 1999). The details of the segmentation methods have been previously described (Iglesias et al., 2015). The hippocampal subfield option, described previously (Iglesias et al., 2015), was used to segment the hippocampus and its subfields and we extracted the CA-1, CA-3, CA-4, subiculum and dentate gyrus (DG). All hippocampal segmentations were reviewed by a trained operator who was blinded to participant identity and no datasets had significant error reported by this trained operator in both total and subfield volume measurements.

Exposures

Arterial stiffness (AS)

Carotid-femoral pulse wave velocity (cf-PWV) was measured at Wave 1 and Wave 3 (at four-year follow up) by tonometry (Vicorder®). This non-invasive measurement is the gold standard for quantifying arterial stiffness and is performed by measuring the pulse wave velocity at the carotid artery and the femoral artery. In TILDA, mean cf-PWV was calculated at each wave as the average of two cf-PWV measurements. A cf-PWV value greater than 12 m/s is indicative of arterial stiffness, as outlined by the European Society of Hypertension and European Society of Cardiology (2013).

Total cerebral blood flow (CBF)

Mean whole brain grey matter cerebral blood flow (CBF) at Wave 3 was quantified as the rate of delivery of arterial blood to brain tissue measured using pCASL-MRI. MRI analysis was performed using Oxford ASL (v.4.0) (FMRIB Software Library, FSL; The University of Oxford, UK) in the FMRIB Software Library (Smith et al., 2004). Analyses steps have been described elsewhere (Knight et al., 2021).

Covariates

Covariates included age, sex, education (none/primary, secondary, or tertiary/higher), pre-existing self-reported physician-diagnosed cardiovascular diseases and events (CVDEs), systolic and diastolic blood pressure, antihypertensive medications, lifestyle factors and estimated intracranial volume (eTIV). These were identified as potential confounders of the relationships between AS, CBF and hippocampal volumes. CVDEs included history of angina, heart attack, congestive heart failure, stroke, transient ischemic attack, and atrial fibrillation. Data were pooled to create a dichotomous CVDEs variable, for absence (disease-free) or presence (≥1) of CVDEs. Average seated blood pressure was measured using an Omron blood pressure monitor (two readings taken 1 min apart). Antihypertensive medications corresponded to the anatomical therapeutic chemical codes C02, C03, C07, C08, or C09. Smoker status was defined as never, past, or current. The CAGE questionnaire (Mayfield et al., 1974) was used as the measure of problematic alcohol consumption and was represented as a binary variable. Physical activity was recorded through the International Physical Activity Questionnaire (IPAQ) (Hagströmer et al., 2006); short-form and classified as low, moderate or high. BMI: weight and height were measured using a SECA electronic floor scales and a SECA 240 wall mounted measuring rod, respectively.

Statistical analysis

Data descriptors

All statistical analyses were performed using R software version 4.2.2 (R Core Team, 2020). Descriptive statistics are given for the study sample and per AS group (cf-PWV ≤ 12 m/s vs. cf-PWV > 12 m/s) and CBF tertile. Continuous variables are described as unadjusted means with standard deviations (SD); categorical variables are given as percentages (%). Independent t-tests and chi-squared tests were used to assess differences between AS groups; ordered logistic regressions were used to assess differences between tertiles of CBF. To estimate selection bias, the observed sample was also compared to the excluded cohort using independent t-tests and chi-squared tests.

Examining the relationship between AS, CBF, and total hippocampal volume

Ordinary Least Squares (OLS) regressions were used to assess the independent and moderating effects of AS and CBF on total hippocampal volume. Cross-sectional analyses included Cf-PWV at Wave 3 and CBF at Wave 3 (continuous variables) as predictors in separate models; they were then adjusted for each other in subsequent models; final models included an interaction term between the two. Further analyses included Cf-PWV at Wave 1 as predictor. Therefore, final models also included an interaction term between Cf-PWV at Wave 1 and Cf-PWV at Wave 3 and between Cf-PWV at Wave 1, Cf-PWV at Wave 3 and CBF at Wave 3.

Supplementary analyses

Linear mixed effect models were used to examine the independent and moderating effects of AS and CBF on hippocampal subfield volumes. Subfield volumes were z-score transformed to allow direct comparison of the effects of AS and CBF by subfield, as the volume distribution of each subfield varies. In cross-sectional analyses, fixed effects included, in separate models first, Cf-PWV and CBF at Wave 3 and hippocampal subfields (the CA1 subfield set as the reference level) with an interaction term. Cf-PWV x subfields and CBF x subfields were then adjusted for each other in subsequent models. Finally, three way interactions between Cf-PWV, CBF and subfield volumes were tested. In follow-up analyses, fixed effects were Cf-PWV at Wave 1 and hippocampal subfields with an interaction term. In subsequent models, Cf-PWV at Wave 1 x subfield volumes was adjusted for Cf-PWV at Wave 3 x subfield volumes and for CBF at Wave 3 x subfield volumes. Final models included three way interactions between Cf-PWV at Wave 1, Cf-PWV at Wave 3 and subfield volumes, and between Cf-PWV at Wave 1, CBF at Wave 3 and subfield volumes. We also tested a four way interaction between Cf-PWV at Wave 1, Cf-PWV at Wave 3, CBF and subfield volumes. The significance of interaction terms was assessed through likelihood ratio tests comparing additive models with models with an interaction term. In all models, participants constituted the random intercept. In all analyses, baseline models included age, sex and eTIV as covariates. Fully adjusted models further controlled for education, CVDEs, blood pressure, antihypertensive medications, and lifestyle factors.

Results

Sample characteristics

A total of 395 participants were included in our analysis (Supplemental Figure 1). Mean age was 68.3 years (SD 7.2), 54.2% were women (Table 1). Compared to the excluded cohort (n = 6,292), the included participants were older (p < 0.01), more likely to have a higher level of education (p < 0.01), to be non-smoker (p < 0.01), have a lower BMI (p = 0.04) and more likely to exercise (p = 0.02).

Table 1

Table 1. Characteristics of the study sample (N = 395).

At Wave 1, n = 50 (13%) of the cohort had a cf-PWV value of greater than 12 m/s. Similar prevalence was observed at Wave 3 with 58 participants (15%) having raised arterial stiffness. Mean CBF was 36.5 (SD = 7.9) and no difference in mean CBF was found between cf-PWV groups (cf-PWV ≤ 12 m/s vs. cf-PWV > 12 m/s) at Wave 1 (p = 0.80) or Wave 3 (p = 0.34). Descriptive characteristics per AS group at Wave 1 and Wave 3 and CBF tertile at Wave 3 are given in Supplementary Tables 1–3.

The independent and moderating effects of AS and CBF on total hippocampal volume

Cross-sectional analyses

In baseline models, no statistically significant association was seen between Cf-PWV (B = 0.04; 95% CI = −0.01, 0.07; p = 0.06) or CBF (B = 0.01; 95% CI = −2.45 × 10⁻³, 0.02; p = 0.19) at Wave 3 and total hippocampal volume when examined independently or when mutually adjusted including an interaction term between Cf-PWV and CBF which also did not reach statistical significance (B = 3.70 × 10⁻³; 95% CI = −1.07 × 10⁻³, 8.47 × 10⁻³; p = 0.09). Findings were the same in fully adjusted models (Supplementary Table 4).

Follow-up analyses

In baseline models, no significant association between Cf-PWV at Wave 1 and total hippocampal volume (B = -0.02; 95% CI = −0.06, 0.02; p = 0.37) was seen when examined alone or when adjusted for CBF in an additive model (B = -0.02; 95% CI = −0.06, 0.02; p = 0.38). However, a model including an interaction between Cf-PWV at Wave 1 and CBF shows a statistically significant interaction (B = 0.01; 95% CI = 2.50 × 10⁻³, 0.01; p < 0.01; Table 2, Panel B, Figure 1); the interaction between higher Cf-PWV at Wave 1 and lower CBF at Wave 3 was associated with lower hippocampal volume, suggesting that high CBF may serve as buffer against volume atrophy in the presence of high AS.

Table 2

Table 2. Estimates and 95% confidence intervals of the combined effects of Carotid-femoral pulse wave velocity (Cf-PWV) i.e. arterial stiffness at Wave 1 and cf-PWV at Wave 3 (Panel A), the combined effects of Cf-PWV at Wave 1 and cerebral blood flow (CBF) at Wave 3 (Panel B) on total hippocampal volume and the three-way interaction model of cf-PWV at wave 1, cf-PWV at wave 3 and CBF at wave 3 on total hippocampal volumes (Panel C).

Figure 1

Figure 1. The combined effects of Cf-PWV at Wave 1 and CBF at Wave 3 on total hippocampal volume. Cf-PWV = Carotid-femoral pulse wave velocity (m/s); W1/3 = Wave 1/3; CBF_{GM =} Mean whole brain grey matter cerebral blood flow (ml/100 g/min). The interaction between Cf-PWV at Wave 1 and CBF at Wave 3 was also significant (p = 0.003); the combination of high Cf-PWV at Wave 1 and low CBF at Wave 3 was associated with lower total hippocampal volume, suggesting that high CBF may serve as buffer against volume atrophy in the presence of high cf-PWV (i.e raised arterial stiffness).

When adjusted for Cf-PWV at Wave 3 in an additive model, higher Cf-PWV at Wave 1 was borderline associated with lower hippocampal volume (B = -0.02; 95% CI = −0.03, 1.64 × 10⁻⁴; p = 0.05). A model including the interaction between Cf-PWV at Wave 1 and Cf-PWV at Wave 3 demonstrated a significant effect (B = −0.02; 95% = −0.02, −0.002; p = 0.03; Table 2, Panel A, Figure 2) such that higher Cf-PWV at Wave 1 WITH Cf-PWV at Wave 3 was associated with lower total hippocampal volume.

Figure 2

Figure 2. The combined effects of Cf-PWV at Wave 1 and cf-PWV at Wave 3 on total hippocampal volume. Cf-PWV = Carotid-femoral pulse wave velocity (m/s); W1/3 = Wave 1/3. The interaction between Cf-PWV at Wave 1 and Cf-PWV at Wave 3 was significant (p = 0.03). The combination of high Cf-PWV at Wave 1 and high Cf-PWV at Wave 3 was associated with total lower hippocampal volume.

The three-way interaction between Cf-PWV at Wave 1, Cf-PWV at Wave 3 and CBF at Wave 3 shows an effect of a 4-year persistently high AS and low CBF on total hippocampal volume (B = 4.88 × 10–3, 95% CI = 2.63 × 10–3, 7.14 × 10–3; p < 0.01), with the interaction between higher Cf-PWV at Wave 1, higher Cf-PWV at Wave 3 and lower CBF being associated with lower hippocampal volume (Table 2, Panel C, Figure 3). Similar findings were observed in fully adjusted models (Supplementary Table 5).

Figure 3

Figure 3. The combined effects of arterial stiffness (Cf-PWV) at Wave 1, arterial stiffness (Cf-PWV) at Wave 3 and CBF at Wave 3 on total hippocampal volume. Cf-PWV = Carotid-femoral pulse wave velocity (m/s); W1/3 = Wave 1/3; CBF_{GM =} Mean whole brain grey matter cerebral blood flow (ml/100 g/min). The three-way interaction between Cf-PWV at Wave 1, Cf-PWV at Wave 3 and CBF_GM at Wave 3 was significant (p < 0.001). The combination of a 4-year persistent high AS and low CBF_GM (high Cf-PWV at Wave 1, high Cf-PWV at Wave 3 and lower CBF_GM) is associated with lower hippocampal volume.

Supplementary analyses

Cross-sectional

In baseline models, the interaction between cf-PWV and hippocampal subfield volumes at Wave 3 was significant (χ²₍₁₅₎ = 10.5; p = 0.03). There was a positive relationship between cf-PWV and the volumes of the subfields CA1, CA3 and CA4 (Supplementary Table 6, Panel A/Supplementary Figure 2, Panel A). The interaction between CBF and subfields at Wave 3 was also significant (χ²₍₁₅₎ = 9.72; p = 0.04). There was a positive relationship between CBF and the volumes of the subiculum and DG (Supplementary Table 6, Panel B/Supplementary Figure 2, Panel B). The associations were robust to mutual adjustment (Supplementary Table 6, Panel C). The interaction between cf-PWV, CBF and subfields at Wave 3 was significant (p = 0.01; Supplementary Table 6, Panel D; Supplementary Figure 2, Panel C). Increased AS (high cf-PWV) with preserved CBF at Wave 3 was associated with larger subfield volumes. However, the interaction between high AS and low CBF was not significant, except for the CA3 volume. Similar findings were observed in fully adjusted models (Supplementary Table 7).

Follow-up

In baseline models, the interaction between cf-PWV at Wave 1 and hippocampal subfield volumes at Wave 3 was significant (χ²₍₁₅₎ = 14.9; p < 0.01). There was a negative relationship between cf-PWV at Wave 1 and the volumes of the subiculum, DG and CA4 subfields (Supplementary Table 8, Supplementary Figure 3, Panel A), which were robust to CBF adjustment (Supplementary Table 8, Supplementary Figure 3, Panel B). Only associations with the DG and CA4 remained significant after adjustment for cf-PWV at Wave 3 (Supplementary Table 8, Supplementary Figure 3, Panel C). The interaction between cf-PWV at Wave 1, cf-PWV at Wave 3 and subfields was not significant (p = 0.55) nor the interaction between cf-PWV at Wave 1, CBF at Wave 3 and subfields (p = 0.33). The interaction between higher cf-PWV at Wave 1 and higher cf-PWV at Wave 3 was associated with lower volumes across subfields (Supplementary Figure 3, Panel B) as was the interaction of higher cf-PWV at Wave 1 and lower CBF at Wave 3 (Supplementary Figure 3, Panel C). Finally, the interaction between cf-PWV at Wave 1, cf-PWV at Wave 3, CBF at Wave 3 and subfields was not significant (p = 0.46). The interaction of higher cf-PWV at Wave 1, higher cf-PWV at Wave 3 and lower CBF at Wave 3 was associated with lower volumes across subfields too. Similar findings were observed in fully adjusted models (Supplementary Table 9).

Discussion

We examined the independent and moderating effects of elevated arterial stiffness and reduced cerebral blood flow on hippocampal volumes and subfield volumes, in a relatively large MRI sample of community-dwelling older adults from ‘The Irish Longitudinal Study on Ageing’.

Our cross-sectional analyses showed that there were no independent associations between raised AS or reduced CBF with total hippocampal volumes. Longitudinal analyses of arterial stiffness suggested that higher AS in the preceding 4 years was independently associated with lower total hippocampal volumes when adjusted for AS at wave 3 in an additive model, however this effect was small. Significant associations between carotid compliance (a surrogate marker for arterial stiffness) and hippocampal volume have been observed in a study of 614 subjects at 20-year follow-up MRI as part of the Atherosclerosis Risk in the Community (ARIC) Study (Baradaran et al., 2021). Carotid compliance was calculated by continuous measurement of the variation in carotid artery diameter during the cardiac cycle, using ultrasound. It is defined as the ‘absolute volume increase within the carotid artery segment during the cardiac cycle, divided by the arterial pulse pressure’. Therefore, the lower the carotid compliance value, the greater the degree of arterial stiffness. Whilst cf-PWV has been consistently cited as the ‘gold standard’ measure of arterial stiffness, conversion tools have been utilised to convert carotid compliance values to local-PWV values, which show significant correlation to the patients cf-PWV measurements (Alhalimi et al., 2021).

Similarly, Bown’s longitudinal study of 278 adults over the age of 60 who had serial MRI brain studies at baseline, 18 months, 3, 5 and 7 years as part of the Vanderbilt Memory and Ageing Project, showed that an elevated baseline pulse wave velocity was associated with a greater decrease in hippocampal volume over time (Bown et al., 2021). As per the SMART-MR Study, the association between cerebral blood flow measurements and hippocampal volumes were lost after adjustment for age and sex (Knoops et al., 2009).

Our analyses examining the combined effects of raised AS and reduced CBF on total hippocampal volume (HV) and the prolonged effect of raised AS over a four-year period showed that (i) prolonged elevated AS (at wave 1 and 3), (ii) the interaction between higher AS at Wave 1 (baseline) and lower CBF at Wave 3 and (iii) the interaction between prolonged elevated AS (at wave 1 and wave 3) and reduced CBF at wave 3 were associated with smaller hippocampal volumes. Our findings suggest a lag effect in the arterial stiffness and hippocampal volume relationship. We propose that the subsequent reduction in cerebral blood flow observed with elevated arterial stiffness may be the missing link in the pathway linking arterial stiffness to hippocampal atrophy. This association between raised arterial stiffness and reduced cerebral blood flow is already reported in the literature in both animal and human subjects (Ajamu et al., 2021; Suri et al., 2020; Sadekova et al., 2018; Jefferson et al., 2018; Muhire et al., 2019). However, contrary to our expectations, reduced CBF at wave 3 in isolation was not associated with hippocampal atrophy, nor was elevated arterial stiffness at Wave 1. Only the combination of both in a model including an interaction term was associated with reduced HV, suggesting CBF plays a buffering effect in the presence of elevated AS. Total hippocampal volume was smaller only in the presence of both higher AS and lower CBF whereas the association between AS and HV was positive in the presence of preserved CBF. The literature does not fully explain why this may be the case. Perhaps when arterial stiffness starts to increase, there is an initial compensatory mechanism that transiently increases flow, but with prolonged exposure, this relationship reverses. A number of authors have proposed that this is due to the fact that in healthy individuals, a compensatory reduction in vascular bed resistance occurs in response to cerebral hypoperfusion, and this maintains adequate cerebral perfusion (Marstrand et al., 2002; Mitchell et al., 2011). Perhaps in the setting of progressive cerebral small vessel disease (i.e increased arterial stiffness), this autoregulation is impaired and thus increased AS leads to an increase in the transmission of harmful pulsatility into the thin-walled cerebral microcirculation, which is unequipped to deal with this increased pressure. This could, over time, ultimately result in vascular remodelling, and resultant reduction in cerebral blood flow and perfusion (Marstrand et al., 2002; Mitchell et al., 2011; Mitchell, 2021). The structure of the hippocampus makes it especially vulnerable to ischemia. The blood supply to the hippocampus is derived primarily from branches of the posterior cerebral artery (PCA) and contributory vessels from the anterior choroidal artery. Animal studies have examined the microvasculature of the hippocampus and unanimously report that the hippocampus has one of the lowest microvascular densities, relative to the surrounding cerebral cortices (Shaw et al., 2021; Nair et al., 1960; Zhang et al., 2019; Kirst et al., 2020).

The hippocampus also has a relatively long distance between its micro vessels and parent supplying artery. On top of this, the hippocampus is highly sensitive to hypoxia and ischemic insult with its high metabolic demand, and this therefore creates a perfect storm scenario whereby the hippocampus is highly vulnerable to vascular insult whilst simultaneously being ill-equipped to deal with states of hypoperfusion (Muhire et al., 2019; Wang and Michaelis, 2010). Therefore, maintaining adequate hippocampal perfusion is essential to preserve cognitive and memory function.

We hypothesised that the CA-1 subfield of the hippocampus would demonstrate preferential vulnerability to ischemia, compared to the other subfields examined; CA2, CA3, CA4, and DG. We hypothesized from our literature search that the CA4 and subiculum may also show regional vulnerability to raised arterial stiffness. However, this hypothesis was only partially confirmed by our results. The supplementary analyses demonstrated that the subiculum and the DG may in fact be most sensitive to higher AS and lower CBF, but these results were not consistent across our analyses. Also, a positive cross-sectional association was observed between AS and the CA-1, CA-3 and CA-4 subfields. The analyses examining these interaction effects suggest a similar effect of raised AS and reduced CBF across all subfields, with smaller subfield volumes observed across the board, as per total HV.

Whilst no prior study, to the best of our knowledge, has specifically examined the effects of increased arterial stiffness and reduced cerebral blood flow on hippocampal subfield volumes, several authors have examined the link between vascular risk factors on specific hippocampal subfield volumes as well as animal models which have investigated the effects of global brain ischemia on the hippocampus and its subfields (Wilde et al., 1997; Sugawara et al., 2000; Wu et al., 2008; Shing et al., 2011).

CA-1 is widely reported in the literature (Sugawara et al., 2000; Wu et al., 2008; Shing et al., 2011) to be the subfield that harbours the most sensitivity to ischemia and hypoxia and thus we tested the independent and moderating effects of AS and CBF on the subfields CA3, CA4, DG and subiculum, with the CA-1 as a reference level. However, this effect of hippocampal atrophy with raised AS and reduced CBF, contrary to our hypothesis, was exerted equally across all subfields tested. We had hypothesised that the CA-1 subfield would be most vulnerable owing to the vascularisation of the hippocampus and the fragility of its vascular network (Spallazzi et al., 2019; Duvernoy et al., 2013; Marinkovic et al., 1999), but this was not borne out in our study. However, along with several authors we observed small independent associations between elevated AS and reduced CBF with smaller volumes of the subiculum (Kim et al., 2015; Pin et al., 2021; Wu et al., 2008; Li et al., 2016).

Pin et al. investigated the effects of neurovascular damage on hippocampal subfields in their study of 249 non-demented adults who underwent two 1.5 Tesla MRI scans, 4 years apart. They examined the association between the atrophy of the CA1-3, CA4 and subiculum with the presence of white matter hyperintensities (WMH’s), which are thought to result from chronic hypoxia (Pin et al., 2021; Tubi et al., 2020). Interestingly, they reported that the subiculum was the only tested subfield in which volume loss correlated with white matter hyperintensities, independent of other vascular risk factors. Whilst these authors did not examine the impact of raised arterial stiffness or reduced cerebral blood flow on hippocampal subfield volumes, they used white matter hyperintensities as a marker of cerebral small vessel disease and linked the increasing quantities of WMH’s to the increasing rates of subiculum atrophy in their longitudinal analyses of their study cohort (Pin et al., 2021). The findings from our study of healthy ageing adults supports the findings of Pin (Pin et al., 2021) and other authors (Kim et al., 2015; Li et al., 2016) and highlight the subiculum as a hippocampal subfield of interest that may demonstrate preferential sensitivity to hypoxia, ischemia, and cerebrovascular insult. There is an obvious paucity of recent research in the literature examining this selective vulnerability of specific subfields to ischemia and in particular the effects of a combination of raised arterial stiffness and reduced cerebral blood flow on the subfield volumes. The hippocampus is the principal site of neurogenesis (specifically within the dentate gryus) and the rate of hippocampal neurogenesis has been shown to decline in patients with Alzheimer’s dementia compared to healthy subjects (Moreno-Jimenez et al., 2019; Lempriere, 2019). This is important in the identification of possible modifiable risk factors that can be used to treat patients with hippocampal vascular insults and thus impaired neurogenesis. Medications such as angiotensin-converting enzymes inhibitors, angiotensin II receptor blockers and calcium channel blockers have been demonstrated to reduce arterial stiffness, promote vascular remodelling and improve endothelial function (Dudenbostel and Glasser, 2012). Further research is required to establish whether these benefits may be extended to the improvement of hippocampal perfusion and neurogenesis.

It is important to better understand this long-accepted link between vascular disease and cognitive decline in order to develop potential therapeutic targets. Better understanding of the pattern of hippocampal atrophy within distinct subfields will help clinicians identify patients that are at risk of cognitive decline. Thus, by mitigating a patient’s vascular risk profile we may reduce their risk of embarking on this pathway of elevated arterial stiffness, reduced cerebral blood flow, subsequent hippocampal atrophy and utimately cognitive decline.

Limitations

Firstly, loss to follow-up patients and missing data in others meant that the study sample was overall healthier than those excluded; therefore, the generalizability of our findings is less certain, but we believe this does not negatively impact upon the observed associations.

Second, although PWV was examined in a follow-up manner (measurement repeated at 4-year follow up), there were no repeated measures for cerebral blood flow and hippocampal volumes and thus a causal link between arterial stiffness, cerebral blood flow and hippocampal volumes cannot be established. Our follow-up analyses suggest that prolonged exposure to elevated arterial stiffness may over time have an effect on hippocampal volume. Further research examining changes in AS, CBF and HV over time is warranted to fully understand these relationships.

Third, we used a measurement of total cerebral blood flow. However, hippocampal blood flow measurements may help to better understand the effect of CBF on HV. It is possible that the null independent relationship observed between CBF and HV was linked to a lack of specificity (total CBF versus hippocampal blood flow specifically).

Fourth, there are some limitations to automatic segmentation of the hippocampal subfields such that the segmentation may be based off low-resolution T1-weighted images. Difficulty in distinguishing some specific subfields such as the molecular layer have been reported in the literature (Iglesias et al., 2015; Wisse et al., 2021) and a combination of T1 and T2 weighted images for the purpose of segmentation has been proposed. A combined T1 and T2 weighted approach for the purpose of subfield segmentation was not possible in our study due to the varying in-plane resolutions between the two (T1w images were 0.9 mm isotropic; T2 weighted images were 0.58 × 0.72 × 4 mm). The alternative approach, validation of automated FreeSurfer segmentation with manual segmentation would be a time-costly process, with an estimated 50 h of manual segmentation required per case (Iglesias et al., 2015). This impracticality would limit the sample size possible for such analyses. Our relatively large sample size and the consistency of our methodology with respect to other large cohort studies (i.e UK Biobank) afford the opportunity for our results to be replicated in future studies.

Finally, this study focused on a specific subset of hippocampal subfield volumes that had been previously identified from the literature search. This was performed in order to achieve sufficient power for the statistical analysis.

Strengths

To our knowledge, this is the first study to examine the independent and moderating effects of elevated arterial stiffness and reduced cerebral blood flow on hippocampal volumes and subfield volumes in a relatively large MRI sample of community-dwelling older adults from a population-based study. Our analyses were also adjusted for a large range of confounding factors including age, sex, education status, cardiovascular comorbidities, medications, and lifestyle factors. It is also the first study to explore the effect of prolonged exposure of elevated AS over a four-year follow up period on hippocampal subfield volumes, the closest study coming from Pin et al. who looked at hippocampal subfield volume loss and WMH’s over a 4 year follow-up period. Other studies looking at specific subfields have been smaller and cross-sectional in nature (Kim et al., 2015; Li et al., 2016), and have not specifically examined the independent and combined effects of raised AS and reduced CBF on the hippocampus. While this is the first attempt to disentangle these effects on the hippocampus, this study should however be considered preliminary and exploratory but supports the need for future work examining changes in AS, CBF and HV over a longer period of time.

Conclusion

Our study shows that increased arterial stiffness and reduced CBF are not independently associated with whole hippocampal or hippocampal subfield volumes. However, when combined, increased arterial stiffness for a longer duration (spanning the 4 year follow-up period) in combination with a reduction in cerebral blood flow is associated with lower hippocampal volumes. These effects were equally exerted across all hippocampal subfields tested in this study.

Improving our knowledge surrounding the mechanisms that lead to the hippocampal atrophy has clinical implications. Understanding the hippocampal vasculature and its response to hypoperfusion is critical in the development of potential therapeutic targets in patients with an elevated vascular risk profile. Targeting these vascular risk factors, such as arterial stiffness, may help lower the rate of hippocampal atrophy and thus slow the onset of cognitive impairment in our ageing population.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Trinity College Faculty of Health Sciences Research Ethics Committee, Dublin, Ireland. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

MH: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing. DC: Data curation, Formal analysis, Methodology, Writing – review & editing. SK: Data curation, Formal analysis, Writing – review & editing. AF: Formal analysis, Writing – review & editing. JM: Conceptualization, Methodology, Project administration, Software, Supervision, Validation, Writing – original draft, Writing – review & editing. RK: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Writing – review & editing. CL: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the funding for The Irish Longitudinal Study on Ageing (TILDA) is provided by the Irish Government, the Health Research Board (HRB), The Atlantic Philanthropies, and the Irish Life PLC. CDL is supported with funding from the Health Research Board (HRB) of Ireland under an Emerging Investigator Award (EIA-2017-012).

Acknowledgments

The authors would like to acknowledge the continued commitment and cooperation of the TILDA participants and research team. MRI data collection was supported by the National Centre for Advanced Medical Imaging (CAMI). A specific acknowledgment to Jason McMorrow in CAMI.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Correction note

This article has been corrected with minor changes. These changes do not impact the scientific content of the article.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnagi.2025.1466294/full#supplementary-material

References

Ajamu, S. O., Fenner, R. C., Grigorova, Y. N., Cezayirli, D., Morrell, C. H., Lakatta, E. G., et al. (2021). Association of central arterial stiffness with hippocampal blood flow and N-acetyl aspartate concentration in hypertensive adult dahl salt sensitive rats. J. Hypertens. 39, 2113–2121. doi: 10.1097/HJH.0000000000002899

PubMed Abstract | Crossref Full Text | Google Scholar

Alhalimi, T., Lim, J., Gourley, D., and Tanaka, H. (2021). Converting and standardizing various measures of arterial stiffness to pulse wave velocity. Pulse 9, 72–82. doi: 10.1159/000517872

PubMed Abstract | Crossref Full Text | Google Scholar

Alsop, D. C., Detre, J. A., Golay, X., Günther, M., Hendrikse, J., Hernandez-Garcia, L., et al. (2015). Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn. Reson. Med. 73, 102–116. doi: 10.1002/mrm.25197

PubMed Abstract | Crossref Full Text | Google Scholar

Baradaran, H., Delic, A., McNally, J. S., Alexander, M., Majersik, J. J., Parker, D. L., et al. (2021). Carotid compliance and parahippocampal and hippocampal volume over a 20-year period. Dement. Geriatr. Cogn. Disord. Extra 11, 227–234. doi: 10.1159/000518234

PubMed Abstract | Crossref Full Text | Google Scholar

Benetos, A., Watfa, G., Hanon, O., Salvi, P., Fantin, F., Toulza, O., et al. (2012). Pulse wave velocity is associated with 1-year cognitive decline in the elderly older than 80 years: the PARTAGE study. J. Am. Med. Dir. Assoc. 13, 239–243. doi: 10.1016/j.jamda.2010.08.014

PubMed Abstract | Crossref Full Text | Google Scholar

Bonnekoh, P., Barbier, A., Oschlies, U., and Hossmann, K. A. (1990). Selective vulnerability in the gerbil hippocampus: morphological changes after 5-min ischemia and long survival times. Acta Neuropathol. 80, 18–25. doi: 10.1007/BF00294217

PubMed Abstract | Crossref Full Text | Google Scholar

Bown, C. W., Khan, O. A., Moore, E. E., Liu, D., Pechman, K. R., Cambronero, F. E., et al. (2021). Elevated aortic pulse wave velocity relates to longitudinal gray and white matter changes. Arterioscler. Thromb. Vasc. Biol. 41, 3015–3024. doi: 10.1161/ATVBAHA.121.316477

PubMed Abstract | Crossref Full Text | Google Scholar

Chao, L. L., Buckley, S. T., Kornak, J., Schuff, N., Madison, C., Yaffe, K., et al. (2010). ASL perfusion MRI predicts cognitive decline and conversion from MCI to dementia. Alzheimer Dis. Assoc. Disord. 24, 19–27. doi: 10.1097/WAD.0b013e3181b4f736

PubMed Abstract | Crossref Full Text | Google Scholar

Dale, A. M., Fischl, B., and Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage 9, 179–194. doi: 10.1006/nimg.1998.0395

PubMed Abstract | Crossref Full Text | Google Scholar

Dudenbostel, T., and Glasser, S. P. (2012). Effects of antihypertensive drugs on arterial stiffness. Cardiol. Rev. 20, 259–263. doi: 10.1097/CRD.0b013e31825d0a44

PubMed Abstract | Crossref Full Text | Google Scholar

Duvernoy, H. M., Cattin, F., and Risold, P.-Y. (2013). The human hippocampus: Functional anatomy, vascularization and serial sections with MRI. 4th Edn. Berlin, Heidelberg: Springer Berlin Heidelberg.

Google Scholar

European Society of Cardiology (2013). 2013 Practice guidelines for the management of arterial hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology (ESC): ESH/ESC Task Force for the Management of Arterial Hypertension. J. Hypertens. 31, 1925–1938. doi: 10.1097/HJH.0b013e328364ca4c

Crossref Full Text | Google Scholar

Fischl, B., Sereno, M. I., and Dale, A. M. (1999). Cortical surface-based analysis. Part II: inflation, flattening, and a surface-based coordinate system. NeuroImage 9, 195–207. doi: 10.1006/nimg.1998.0396

PubMed Abstract | Crossref Full Text | Google Scholar

Hagströmer, M., Oja, P., and Sjöström, M. (2006). The international physical activity questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr. 9, 755–762. doi: 10.1079/phn2005898

PubMed Abstract | Crossref Full Text | Google Scholar

Hanon, O., Haulon, S., Lenoir, H., Seux, M. L., Rigaud, A. S., Safar, M., et al. (2005). Relationship between arterial stiffness and cognitive function in elderly subjects with complaints of memory loss. Stroke 36, 2193–2197. doi: 10.1161/01.STR.0000181771.82518.1c

PubMed Abstract | Crossref Full Text | Google Scholar

Henskens, L. H., Kroon, A. A., van Oostenbrugge, R. J., Gronenschild, E. H., Fuss-Lejeune, M. M., Hofman, P. A., et al. (2008). Increased aortic pulse wave velocity is associated with silent cerebral small-vessel disease in hypertensive patients. Hypertension 52, 1120–1126. doi: 10.1161/HYPERTENSIONAHA.108.119024

PubMed Abstract | Crossref Full Text | Google Scholar

Iglesias, J. E., Augustinack, J. C., Nguyen, K., Player, C. M., Player, A., Wright, M., et al. (2015). A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: application to adaptive segmentation of in vivo MRI. NeuroImage 115, 117–137. doi: 10.1016/j.neuroimage.2015.04.042

PubMed Abstract | Crossref Full Text | Google Scholar

Jack, C. R., Petersen, R. C., Xu, Y., O’Brien, P. C., Smith, G. E., Ivnik, R. J., et al. (2000). Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology 55, 484–490. doi: 10.1212/wnl.55.4.484

PubMed Abstract | Crossref Full Text | Google Scholar

Jack, C. R., Petersen, R. C., Xu, Y., O’Brien, P. C., Smith, G. E., Ivnik, R. J., et al. (1998). Rate of medial temporal lobe atrophy in typical aging and Alzheimer’s disease. Neurology 51, 993–999. doi: 10.1212/wnl.51.4.993

PubMed Abstract | Crossref Full Text | Google Scholar

Jefferson, A. L., Cambronero, F. E., Liu, D., Moore, E. E., Neal, J. E., Terry, J. G., et al. (2018). Higher aortic stiffness is related to lower cerebral blood flow and preserved cerebrovascular reactivity in older adults. Circulation 138, 1951–1962. doi: 10.1161/CIRCULATIONAHA.118.032410

PubMed Abstract | Crossref Full Text | Google Scholar

Jobst, K. A., Smith, A. D., Szatmari, M., Esiri, M. M., Jaskowski, A., Hindley, N., et al. (1994). Rapidly progressing atrophy of medial temporal lobe in Alzheimer’s disease. Lancet 343, 829–830. doi: 10.1016/s0140-6736(94)92028-1

PubMed Abstract | Crossref Full Text | Google Scholar

Kim, G. H., Lee, J. H., Seo, S. W., Kim, J. H., Seong, J. K., Ye, B. S., et al. (2015). Hippocampal volume and shape in pure subcortical vascular dementia. Neurobiol. Aging 36, 485–491. doi: 10.1016/j.neurobiolaging.2014.08.009

PubMed Abstract | Crossref Full Text | Google Scholar

Kirst, C., Skriabine, S., Vieites-Prado, A., Topilko, T., Bertin, P., Gerschenfeld, G., et al. (2020). Mapping the fine-scale organization and plasticity of the brain vasculature. Cell 180, 780–795.e25. doi: 10.1016/j.cell.2020.01.028

PubMed Abstract | Crossref Full Text | Google Scholar

Knight, S. P., Laird, E., Williamson, W., O’Connor, J., Newman, L., Carey, D., et al. (2021). Obesity is associated with reduced cerebral blood flow - modified by physical activity. Neurobiol. Aging 105, 35–47. doi: 10.1016/j.neurobiolaging.2021.04.008

PubMed Abstract | Crossref Full Text | Google Scholar

Knoops, A. J., van der Graaf, Y., Appelman, A. P., Mali, W. P., and Geerlings, M. I. (2009). Total cerebral blood flow and hippocampal volume in patients with arterial disease. The SMART-MR study. J. Cereb. Blood Flow Metab. 29, 1727–1733. doi: 10.1038/jcbfm.2009.91

PubMed Abstract | Crossref Full Text | Google Scholar

Lempriere, S. (2019). Birth of hippocampal neurons declines in Alzheimer disease. Nat. Rev. Neurol. 15:245. doi: 10.1038/s41582-019-0182-4

PubMed Abstract | Crossref Full Text | Google Scholar

Li, X., Li, D., Li, Q., Li, Y., Li, K., Li, S., et al. (2016). Hippocampal subfield volumetry in patients with subcortical vascular mild cognitive impairment. Sci. Rep. 6:20873. doi: 10.1038/srep20873

PubMed Abstract | Crossref Full Text | Google Scholar

Mak, H. K., Qian, W., Ng, K. S., Mak, H. K.-F., Chan, Q., Song, Y.-Q., et al. (2014). Combination of MRI hippocampal volumetry and arterial spin labeling MR perfusion at 3-tesla improves the efficacy in discriminating Alzheimer’s disease from cognitively normal elderly adults. J. Alzheimers Dis. 41, 749–758. doi: 10.3233/JAD-131868

PubMed Abstract | Crossref Full Text | Google Scholar

Marinkovic, S., Gibo, H., Brigante, L., Nikodijević, I., and Petrović, P. (1999). The surgical anatomy of the perforating branches of the anterior choroidal artery. Surg. Neurol. 52, 30–36. doi: 10.1016/s0090-3019(99)00043-9

PubMed Abstract | Crossref Full Text | Google Scholar

Marstrand, J. R., Garde, E., Rostrup, E., Ring, P., Rosenbaum, S., Mortensen, E. L., et al. (2002). Cerebral perfusion and cerebrovascular reactivity are reduced in white matter hyperintensities. Stroke 33, 972–976. doi: 10.1161/01.str.0000012808.81667.4b

PubMed Abstract | Crossref Full Text | Google Scholar

Matsumoto, M., Inoue, K., and Moriki, A. (2007). Associations of brachial-ankle pulse wave velocity and carotid atherosclerotic lesions with silent cerebral lesions. Hypertens. Res. 30, 767–773. doi: 10.1291/hypres.30.767

PubMed Abstract | Crossref Full Text | Google Scholar

Mayfield, D., McLeod, G., and Hall, P. (1974). The CAGE questionnaire: validation of a new alcoholism screening instrument. Am. J. Psychiatry 131, 1121–1123. doi: 10.1176/ajp.131.10.1121

PubMed Abstract | Crossref Full Text | Google Scholar

Mitchell, G. F. (2021). Arterial stiffness in aging: does it have a place in clinical practice?: recent advances in hypertension. Hypertension 77, 768–780. doi: 10.1161/HYPERTENSIONAHA.120.14515

PubMed Abstract | Crossref Full Text | Google Scholar

Mitchell, G. F., van Buchem, M. A., Sigurdsson, S., Gotal, J. D., Jonsdottir, M. K., Kjartansson, Ó., et al. (2011). Arterial stiffness, pressure and flow pulsatility and brain structure and function: the age, gene/environment susceptibility--Reykjavik study. Brain 134, 3398–3407. doi: 10.1093/brain/awr253

PubMed Abstract | Crossref Full Text | Google Scholar

Moreno-Jimenez, E. P., Flor-Garcia, M., Terreros-Roncal, J., Rábano, A., Cafini, F., Pallas-Bazarra, N., et al. (2019). Adult hippocampal neurogenesis is abundant in neurologically healthy subjects and drops sharply in patients with Alzheimer’s disease. Nat. Med. 25, 554–560. doi: 10.1038/s41591-019-0375-9

PubMed Abstract | Crossref Full Text | Google Scholar

Muhire, G., Iulita, M. F., Vallerand, D., Youwakim, J., Gratuze, M., Petry, F. R., et al. (2019). Arterial stiffness due to carotid calcification disrupts cerebral blood flow regulation and leads to cognitive deficits. J. Am. Heart Assoc. 8:e011630. doi: 10.1161/JAHA.118.011630

PubMed Abstract | Crossref Full Text | Google Scholar

Nair, V., Palm, D., and Roth, L. J. (1960). Relative vascularity of certain anatomical areas of the brain and other organs of the rat. Nature 188, 497–498. doi: 10.1038/188497a0

PubMed Abstract | Crossref Full Text | Google Scholar

Nichols, E., Steinmetz, J. D., Vollset, S. E., Fukutaki, K., Chalek, J., Abd-Allah, F., et al. (2022). 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 7, e105–e125. doi: 10.1016/S2468-2667(21)00249-8

PubMed Abstract | Crossref Full Text | Google Scholar

Ohmine, T., Miwa, Y., Yao, H., Yuzuriha, T., Takashima, Y., Uchino, A., et al. (2008). Association between arterial stiffness and cerebral white matter lesions in community-dwelling elderly subjects. Hypertens. Res. 31, 75–81. doi: 10.1291/hypres.31.75

PubMed Abstract | Crossref Full Text | Google Scholar

Pase, M. P., Beiser, A., Himali, J. J., Tsao, C., Satizabal, C. L., Vasan, R. S., et al. (2016). Aortic stiffness and the risk of incident mild cognitive impairment and dementia. Stroke 47, 2256–2261. doi: 10.1161/STROKEAHA.116.013508

PubMed Abstract | Crossref Full Text | Google Scholar

Pin, G., Coupe, P., Nadal, L., Helmer, C., Mazoyer, B., Catheline, G., et al. (2021). Distinct hippocampal subfields atrophy in older people with vascular brain injuries. Stroke 52, 1741–1750. doi: 10.1161/STROKEAHA.120.031743

PubMed Abstract | Crossref Full Text | Google Scholar

R Core Team (2020). R: a language and environment for statistical computing. Vienna, Austria: R foundation for statistical computing.

Google Scholar

Rouch, L., Cestac, P., Sallerin, B., Andrieu, S., Bailly, H., Beunardeau, M., et al. (2018). Pulse wave velocity is associated with greater risk of dementia in mild cognitive impairment patients. Hypertension 72, 1109–1116. doi: 10.1161/HYPERTENSIONAHA.118.11443

PubMed Abstract | Crossref Full Text | Google Scholar

Sadekova, N., Iulita, M. F., Vallerand, D., Muhire, G., Bourmoum, M., Claing, A., et al. (2018). Arterial stiffness induced by carotid calcification leads to cerebral gliosis mediated by oxidative stress. J. Hypertens. 36, 286–298. doi: 10.1097/HJH.0000000000001557

PubMed Abstract | Crossref Full Text | Google Scholar

Schmidt-Kastner, R., and Freund, T. F. (1991). Selective vulnerability of the hippocampus in brain ischemia. Neuroscience 40, 599–636. doi: 10.1016/0306-4522(91)90001-5

PubMed Abstract | Crossref Full Text | Google Scholar

Scuteri, A. (2007). Slowing arterial aging: how far have we progressed? J. Hypertens. 25, 509–510. doi: 10.1097/HJH.0b013e328017f71c

PubMed Abstract | Crossref Full Text | Google Scholar

Scuteri, A., Tesauro, M., Appolloni, S., Preziosi, F., Brancati, A. M., and Volpe, M. (2007). Arterial stiffness as an independent predictor of longitudinal changes in cognitive function in the older individual. J. Hypertens. 25, 1035–1040. doi: 10.1097/HJH.0b013e3280895b55

PubMed Abstract | Crossref Full Text | Google Scholar

Shaw, K., Bell, L., Boyd, K., Grijseels, D. M., Clarke, D., Bonnar, O., et al. (2021). Neurovascular coupling and oxygenation are decreased in hippocampus compared to neocortex because of microvascular differences. Nat. Commun. 12:3190. doi: 10.1038/s41467-021-23508-y

PubMed Abstract | Crossref Full Text | Google Scholar

Shing, Y. L., Rodrigue, K. M., Kennedy, K. M., Fandakova, Y., Bodammer, N., Werkle-Bergner, M., et al. (2011). Hippocampal subfield volumes: age, vascular risk, and correlation with associative memory. Front. Aging Neurosci. 3:2. doi: 10.3389/fnagi.2011.00002

PubMed Abstract | Crossref Full Text | Google Scholar

Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23, S208–S219. doi: 10.1016/j.neuroimage.2004.07.051

PubMed Abstract | Crossref Full Text | Google Scholar

Spallazzi, M., Dobisch, L., Becke, A., Berron, D., Stucht, D., Oeltze-Jafra, S., et al. (2019). Hippocampal vascularization patterns: a high-resolution 7 tesla time-of-flight magnetic resonance angiography study. Neuroimage Clin. 21:101609. doi: 10.1016/j.nicl.2018.11.019

PubMed Abstract | Crossref Full Text | Google Scholar

Sugawara, T., Kawase, M., Lewen, A., Noshita, N., Gasche, Y., Fujimura, M., et al. (2000). Effect of hypotension severity on hippocampal CA1 neurons in a rat global ischemia model. Brain Res. 877, 281–287. doi: 10.1016/s0006-8993(00)02684-6

PubMed Abstract | Crossref Full Text | Google Scholar

Suri, S., Chiesa, S. T., Zsoldos, E., Mackay, C. E., Filippini, N., Griffanti, L., et al. (2020). Associations between arterial stiffening and brain structure, perfusion, and cognition in the Whitehall II imaging sub-study: a retrospective cohort study. PLoS Med. 17:e1003467. doi: 10.1371/journal.pmed.1003467

PubMed Abstract | Crossref Full Text | Google Scholar

Tarumi, T., Shah, F., Tanaka, H., and Haley, A. P. (2011). Association between central elastic artery stiffness and cerebral perfusion in deep subcortical gray and white matter. Am. J. Hypertens. 24, 1108–1113. doi: 10.1038/ajh.2011.101

PubMed Abstract | Crossref Full Text | Google Scholar

Tubi, M. A., Feingold, F. W., Kothapalli, D., Hare, E. T., King, K. S., Thompson, P. M., et al. (2020). White matter hyperintensities and their relationship to cognition: effects of segmentation algorithm. NeuroImage 206:116327. doi: 10.1016/j.neuroimage.2019.116327

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, X., and Michaelis, E. K. (2010). Selective neuronal vulnerability to oxidative stress in the brain. Front. Aging Neurosci. 2:12. doi: 10.3389/fnagi.2010.00012

PubMed Abstract | Crossref Full Text | Google Scholar

Whelan, B. J., and Savva, G. M. (2013). Design and methodology of the Irish longitudinal study on ageing. J. Am. Geriatr. Soc. 61, S265–S268. doi: 10.1111/jgs.12199

Crossref Full Text | Google Scholar

Wilde, G. J., Pringle, A. K., Wright, P., Wilde, G. J. C., and Iannotti, F. (1997). Differential vulnerability of the CA1 and CA3 subfields of the hippocampus to superoxide and hydroxyl radicals in vitro. J. Neurochem. 69, 883–886. doi: 10.1046/j.1471-4159.1997.69020883.x

PubMed Abstract | Crossref Full Text | Google Scholar

Wisse, L. E. M., Chetelat, G., Daugherty, A. M., Flores, R., la Joie, R., Mueller, S. G., et al. (2021). Hippocampal subfield volumetry from structural isotropic 1 mm (3) MRI scans: a note of caution. Hum. Brain Mapp. 42, 539–550. doi: 10.1002/hbm.25234

PubMed Abstract | Crossref Full Text | Google Scholar

Wu, W., Brickman, A. M., Luchsinger, J., Ferrazzano, P., Pichiule, P., Yoshita, M., et al. (2008). The brain in the age of old: the hippocampal formation is targeted differentially by diseases of late life. Ann. Neurol. 64, 698–706. doi: 10.1002/ana.21557

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, X., Yin, X., Zhang, J., Li, A., Gong, H., Luo, Q., et al. (2019). High-resolution mapping of brain vasculature and its impairment in the hippocampus of Alzheimer’s disease mice. Natl. Sci. Rev. 6, 1223–1238. doi: 10.1093/nsr/nwz124

PubMed Abstract | Crossref Full Text | Google Scholar