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. Author manuscript; available in PMC: 2025 Mar 31.
Published in final edited form as: J Alzheimers Dis. 2024;97(4):1851–1860. doi: 10.3233/JAD-230930

Blood pressure variability and plasma Alzheimer’s disease biomarkers in the SPRINT trial

Isabel J Sible a, Daniel A Nation b,c,*
PMCID: PMC11957751  NIHMSID: NIHMS2063422  PMID: 38306042

Abstract

Background:

Recent observational studies suggest higher blood pressure (BP) variability (BPV) is associated with Alzheimer’s disease (AD) biomarkers amyloid-beta (Aß) and tau. Less is known about relationships in interventional cohorts with strictly controlled mean BP levels.

Objective:

Investigate the longitudinal relationship between BPV and change in plasma AD biomarkers under standard vs intensive BP treatment.

Methods:

In this post hoc analysis of the SPRINT trial, 457 participants (n = 206 in standard group, n = 251 in intensive group) underwent repeated BP measurement between baseline and 12-months follow-up, and venipuncture at baseline and median (IQR) 3.5 (3.0 – 4.0) years later to determine plasma AD biomarkers total tau and Aß1–42:Aß1–40 ratio. BPV was calculated as tertiles of variability independent of mean. Linear mixed models investigated the effect of BPV × time on AD biomarker levels.

Results:

Higher BPV was associated with increased levels of total tau in the standard group (ß [95% CI] 1st vs 3rd tertiles of BPV: .21 [.02, .41], p = .035), but not in the intensive group (ß [95% CI] 1st vs 3rd tertiles of BPV: −.02 [−.19, .16], p = .843). BPV was not associated with Aß1–42:Aß1–40 ratio in either group. Mean BP was not associated with biomarkers.

Conclusions:

Higher BPV was associated with increased plasma total tau under standard BP treatment. Findings add new evidence to prior observational work linking BPV to AD pathophysiology and suggest that, despite strict control of mean BP, BPV remains a risk for pathophysiological change underlying risk for AD.

Clinical trial information:

ClinicalTrials.gov; NCT01206062

Keywords: blood pressure variability, plasma, biomarkers, Alzheimer’s disease, tau

INTRODUCTION

Vascular mechanisms may be a key target for reducing dementia risk [1]. The results of the Systolic Blood Pressure Intervention Trial (SPRINT) clinical trial [2] support this aim and suggest that intensive blood pressure (BP) lowering, when compared to standard BP lowering, may reduce risk for cardiovascular [3] and cerebrovascular disease [4] as well as mild cognitive impairment [5], often a precursor to dementia. The trial findings added exciting evidence to the hypothesis that what benefits heart health may also benefit brain health. Similar to most BP clinical trials and observational studies, the SPRINT trial focused on mean BP, but emerging evidence from cardiovascular, cerebrovascular, and, most recently, aging research suggest the variability in BP may be an understudied aspect of control relevant to health outcomes [6]. BP levels fluctuate over second-to-second to even year-to-year cycles due to complex internal and external stimuli [7]. These fluctuations are now recognized to carry important health information that is distinct from and oftentimes a better predictor of outcomes than mean BP levels [8,9]. A large and growing number of studies report higher BP variability (BPV) is associated with cognitive impairment and decline [8,10], cerebrovascular disease severity and progression [11,12], and risk for and progression of dementia, including Alzheimer’s disease (AD) [13–15], independent of mean BP levels. Other recent work has found links between higher BPV and AD pathophysiology, such as cerebrospinal fluid [16] and plasma [17] amyloid-beta (Aß) and tau. These biomarker findings highlight the increasingly appreciated overlap between modifiable vascular factors and AD [18,19]. However, these findings were in observational cohorts with varying degrees of BP control, and it remains unclear how BPV may be related to AD biomarkers in interventional cohorts with rigorously modified BP. Findings could help inform how newer aspects of BP control, such as managing BPV, may be harnessed to reduce AD pathophysiological changes that can precede cognitive symptoms by decades [20]. To investigate this possibility, we conducted a post hoc analysis of the SPRINT trial to examine the longitudinal relationship between BPV and plasma AD biomarker change under standard vs intensive BP lowering.

METHODS

Participants

Data were obtained from the SPRINT trial, a publicly available deidentified dataset from the National Heart, Lung, and Blood Institute that has been described in detailed elsewhere [2,21]. The present investigation was a post hoc analysis of this data. SPRINT was a multicenter randomized, controlled study cohort trial in the United States and Puerto Rico conducted between November 2010 and March 2013 investigating whether intensive BP lowering could reduce cardiovascular risk when compared to standard BP treatment. Participants were recruited from the local community and a variety of clinical settings, such as primary care, nephrology, and geriatrics. At screening, participants were ≥ 50 years old, hypertensive (systolic BP 130 mmHg – 180 mmHg), and at risk for cardiovascular disease (≥1 of the following risk factors: history of cardiovascular disease, chronic kidney disease [estimated glomerular filtration rate < 60 mL/min per 1.73 m2], 10-year Framingham cardiovascular disease risk [22] ≥ 15%, ≥ 75 years of age). Participants were excluded for history of stroke, diabetes, or heart failure, residing in a nursing home, diagnosis of dementia based on medical record review, or receiving medication primarily used to treat dementia. Participants were randomized 1:1 to either standard treatment (<140 mmHg systolic BP target) or intensive treatment (<120 mmHg systolic BP target).

Standard protocol approvals, registrations, and patient consents

The SPRINT study was approved by an Institutional Review Board at each site. All participants provided their informed consent before treatment randomization.

Measures

BP assessment

The SPRINT BP protocol has been described in detail previously [2,3,5,23,24]. BP was measured using an automated BP device (Professional Digital Blood Pressure Monitor [Omron Healthcare; model 907XL]) at study baseline, 1-, 2-, and 3-months follow-up, and then every 3 months for up to 6 years follow-up. BP values from each visit were recorded as the average of 3 serial seated BP measurements after a 5-minute period of rest. Participants were prohibited from completing questionnaires, talking, or texting during the rest period and BP collection. BP levels reached a relatively stable plateau in both treatment groups at 3-months follow-up [25]. We calculated BPV from BP measurements collected at 3-, 6-, 9-, and 12-months follow-up. This approach aimed to minimize the effect of initial BP fluctuation in the intensive treatment group and is consistent with other recent BPV studies using the SPRINT dataset [25–28]. Intraindividual BPV was calculated from the 4 BP measurements (e.g., from 3-, 6-, 9-, and 12-months follow-up visits) as variability independent of mean (VIM), an index of BPV that is uncorrelated with mean BP across visits [29,30]. VIM was calculated as: VIM = standard deviation (SD)/meanx, where the power x was derived from non-linear curve fitting of BP SD against mean BP using the nls package in R Project, as previously described [12,29,31–33]. To confirm that BPV VIM was not significantly correlated with mean BP, we conducted a bivariate correlation (r = .04, p = .210). We divided BPV values into tertiles for all main analyses. Identical analyses using the SD and coefficient of variation [CV; 100 × SD/mean] of BPV tertiles are reported in the Supplementary Materials. Analyses using continuous BPV values are reported in the Supplementary Materials. Mean BP was calculated from BP values collected over the same 9-month period as BPV (e.g., 3-, 6-, 9-, 12-months follow-up) and divided into tertiles.

Plasma AD biomarker assessment

As part of a pilot study within SPRINT, participants underwent venipuncture to determine plasma levels for Aß1–40, Aß1–42, and total tau. The present investigation examined plasma total tau and Aß1–42:Aß1–40 ratio. Samples were collected at study baseline and a single follow-up visit. The median (IQR) follow-up in the present study was 3.5 (3.0 – 4.0) years from study baseline. Sample assays were assessed using the Simoa® Human Neurology 3-Plex A assay. As described in the SPRINT ancillary study protocol, frozen plasma samples from the SPRINT central laboratory were shipped on dry ice without thawing to the University of Kentucky where they were stored at −80.0° Celsius. Samples were then thawed on ice and centrifuged at maximum speed for 10 minutes at 4° Celsius. All samples were assayed in duplicate and were run with kits from the same lot for each analyte. Samples were randomly distributed across assay batches, with paired baseline and follow-up samples always performed within the same assay batch.

Other measurements

The following variables were determined at study baseline: race (Black; Hispanic; White; other), body mass index (BMI [kg/m2]), number of antihypertensive medications used (all classes), Framingham 10-year CVD risk score, history of smoking (never vs former vs current).

Data availability

All data are available through the SPRINT group.

STATISTICAL ANALYSIS

First, we used linear mixed models to investigate the effect of BPV × time (independent variable) on plasma AD biomarker levels (dependent variable). Random intercepts for participant and randomization site were included in the models. Time was calculated as days since treatment randomization. The SPRINT trial aimed to lower systolic BP [2]. Therefore, we focused our analyses on systolic BPV, consistent with other recent studies on BPV using the SPRINT dataset [25,27,34]. Next, we used linear mixed models to examine the effect of mean BP × time on plasma AD biomarker levels to compare potential associations with BPV. We also conducted identical BPV × time analyses using the SD and CV indices of BPV (Supplementary Materials). Supplementary analyses used continuous BPV values (Supplementary Materials). All models were stratified by intensive vs standard treatment group and covaried for age, sex, race, and mean BP. Finally, we conducted sensitivity analyses additionally controlling for 1) number of antihypertensive medications used, 2) Framingham risk score, 3) BMI, and 4) history of smoking (see Supplementary Materials). All analyses were 2-tailed with significance set at p < .05. All analyses were carried out in R [35].

RESULTS

457 participants (n = 206 in the standard treatment group, n = 251 in the intensive treatment group) were included in the present study (Table 1). In the standard treatment group, baseline plasma Aß1–42:Aß1–40 ratio was mean (SD) .2 (.1) pg/mL and baseline plasma total tau was mean (SD) 8.4 (3.2) pg/mL. In the intensive treatment group, baseline plasma Aß1–42:Aß1–40 ratio was mean (SD) .1 (.2) pg/mL and baseline plasma total tau was mean (SD) 8.4 (3.5) pg/mL. This suggests the study sample’s baseline plasma AD biomarker burden was below profiles seen in Mild Cognitive Impairment or AD.

Table 1.

Baseline clinical and demographic information.

Intensive (n = 251) Standard (n = 206) F or x2 p-value
Age (years) 69.9 (6.8) 70.0 (7.4) .002 .964
Sex (n, % female) 110 (43.8%) 83 (40.3%) .44 .506
Race/ethnicity (n, %) 4.19 .242
 Black 67 (26.7%) 58 (28.2%)
 Hispanic 6 (2.4%) 11 (5.3%)
 White 174 (69.3%) 136 (66.0%)
 Other 4 (1.6%) 1 (0.5%)
Education (n, %) .62 .733
 Less than college/other 137 (54.6%) 120 (58.3%)
 College 38 (15.1%) 29 (14.1%)
 Graduate school 76 (30.3%) 57 (27.7%)
BMI (kg/m2) 29.4 (5.2) 29.7 (5.3) .39 .535
FRS 10-year risk score 19.3 (10.6) 19.8 (10.3) .31 .576
Medical history (n, %)
 Cardiovascular disease* 33 (13.2%) 27 (13.1%) .001 .99
 Hypertension† 235 (93.6%) 188 (91.3%) .61 .436
Medication use (n, %)
 Antihypertensive agents 229 (91.2%) 180 (87.4%) 1.40 .236
No. antihypertensive agents used (median, IQR) 2 (2) 2 (2) 1.83 .767
Systolic BP (mmHg)
 Mean 120.6 (8.5) 135.6 (7.6) 391.4 <.001
 SD 9.7 (5.3) 10.1 (5.1) .71 .401
 CV 8.0 (4.1) 7.5 (3.7) 2.02 .156
 VIM 12.9 (8.1) 11.8 (7.1) 2.13 .146
Diastolic BP (mmHg)
 Mean 67.0 (7.5) 74.9 (8.9) 104.9 <.001
 SD 5.6 (2.9) 6.1 (3.1) 3.86 .05
 CV 8.3 (4.3) 8.2 (4.0) .07 .786
 VIM 8.4 (2.8) 8.3 (2.7) .02 .881
Plasma Aß1–42:Aß1–40 .1 (.2) .2 (.1) 1.30 .255
Plasma total tau 8.4 (3.5) 8.4 (3.2) .06 .803
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Means and SDs shown unless otherwise indicated.

*

SPRINT history of cardiovascular disease is defined as presence of clinical cardiovascular disease (other than stroke; a) previous myocardial infarction, percutaneous coronary intervention, coronary artery bypass grafting, carotid endarterectomy, carotid stenting; b) peripheral disease with revascularization; c) acute coronary syndrome with or without resting ECG change, ECG changes on a graded exercise test, or positive cardiac imaging study; d) at least 50% diameter stenosis or a coronary, carotid, or lower extremity artery; e) abdominal aortic aneurysm ≥5cm with or without repair) or subclinical cardiovascular disease (a) coronary artery calcium score ≥400 Agatston units within the past 2 years; b) ankle brachial index ≤.90 within the past 2 years; c) left ventricular hypertrophy by ECG [based on computer reading], echocardiogram report, or other cardiac imaging procedure report within the past 2 years) at study baseline.

†

SPRINT history of hypertension is defined as yes vs no to “Have you ever been told by a physician that you have hypertension or high blood pressure?”

Abbreviations: BP = blood pressure; BMI = body mass index; FRS = Framingham risk score; SD = standard deviation; CV = coefficient of variation; VIM = variability independent of mean

BPV

As shown in Table 2 and Figure 1, higher BPV in the standard treatment group was associated with increased levels of plasma total tau (standardized ß [95% CI] comparing 1st vs 3rd tertiles of BPV: .21 [.02, .41], p = .035). BPV in the standard treatment group was not significantly related to plasma Aß1–42:Aß1–40 ratio (ß [95% CI] comparing 1st vs 3rd tertiles of BPV: −.02 [−.13, .10], p = .766).

Table 2.

Linear mixed model estimates (standardized ß [95% CI]) of the 2-way interaction of BPV × time on plasma AD biomarker levels by treatment group.

Tertile 1 Tertile 2 Tertile 3 p-value for trend
Standard treatment
 Total tau Ref .001 [−.18, .19] .21 [.02, .41] .035
 Aß1–42:Aß1–40 ratio Ref −.10 [−.21, .01] −.02 [−.13, .10] .766
Intensive treatment
 Total tau Ref .11 [−.07, .29] −.02 [−.19, .16] .843
 Aß1–42:Aß1–40 ratio Ref .02 [−.05, .09] .04 [−.03, .10] .303
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Models adjusted for age, sex, race, and mean BP.

Figure 1. Elevated BPV is associated with increased plasma total tau in the standard treatment group.

Figure 1.

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Conditional effects of BPV by time on change in plasma total tau (pg/mL) in the standard treatment group. Lines represent rate of change for each tertile of BPV. Models adjusted for age, sex, race, and mean BP.

Abbreviations: BPV = blood pressure variability

BPV in the intensive treatment group was not significantly associated with levels of plasma total tau (ß [95% CI] comparing 1st vs 3rd tertiles of BPV: −.02 [−.19, .16], p = .843) or Aß1–42:Aß1–40 ratio (ß [95% CI] comparing 1st vs 3rd tertiles of BPV: .04 [−.03, .10], p = .303).

Analyses using the SD and CV indices of BPV tertiles, as well as continuous BPV values, showed a consistent pattern, with stronger associations observed with VIM and CV when compared to SD (Supplementary Tables 1 and 2).

Mean BP

There were no significant associations between mean BP and plasma AD biomarker levels in either treatment group (p’s = .128 – 989) (Table 3).

Table 3.

Linear mixed model estimates (standardized ß [95% CI]) of the 2-way interaction of mean BP × time on plasma AD biomarker levels by treatment group.

Tertile 1 Tertile 2 Tertile 3 p-value for trend
Standard treatment
 Total tau Ref −.33 [−.78, .12] −.34 [−.79, .10] .128
 Aß1–42:Aß1–40 ratio Ref −.06 [−.32, .20] .002 [−.25, .25] .989
Intensive treatment
 Total tau Ref .02 [−.15, .18] .10 [−.16, .36] .472
 Aß1–42:Aß1–40 ratio Ref .01 [−.05, .07] −.05 [−.15, .06] .382
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Models adjusted for age, sex, and race.

Sensitivity analyses

Findings with BPV and plasma total tau in the standard treatment group remained significant in sensitivity analyses additionally controlling for 1) number of antihypertensive medications used, 2) Framingham risk score, 3) BMI, and 4) history of smoking (p’s = .034 - .036) (Supplementary Table 3).

DISCUSSION

The present study provides novel evidence that elevated BPV is associated with increased plasma total tau, despite rigorously controlled mean BP levels in the standard treatment group of the SPRINT trial. In contrast, BPV was not associated with plasma Aß1–42:Aß1–40 ratio in the standard treatment group, and BPV was not associated with plasma Aß1–42:Aß1–40 ratio or total tau in those undergoing intensive BP lowering. These findings add to previous observational work linking BPV to amyloid (A) [16,17], tau (T) [16,17,36], and neurodegeneration (N) [16,17] biomarkers of AD, and suggest that even with rigorously controlled mean BP, higher BPV remains a risk for neurodegeneration that may be tau-mediated. Importantly, BP remains a relatively accessible therapeutic target, and one that is also modifiable via pharmacological and non-pharmacological interventions. Study findings offer new evidence that controlling BPV, in addition to controlling mean BP levels, may have the potential to reduce pathophysiology underlying risk for neurodegenerative dementia.

In contrast to findings with plasma total tau, BPV was not associated with change in plasma Aß1–42:Aß1–40 ratio in either treatment group. These findings are interesting when considering recent cross-sectional [17] and longitudinal [16] observational studies reporting links with both Aß and tau AD biomarkers. However, the longitudinal observational study that used cerebrospinal fluid samples [16] also stratified by AD risk gene apolipoprotein e4 allele and found that higher BPV was only associated with tau – and not Aß - in apolipoprotein e4 carriers. Additionally, recent evidence from a postmortem study [37] suggests BPV is related to tau and not Aß pathology. Other more well-studied BP metrics such as mean BP, hypertension status, pulse pressure, and mean arterial pressure are also more consistently associated with tau than Aß [38–40]. Furthermore, cognitive change is more strongly associated with change in tau than Aß [40,41], which may be relevant to a recent finding from the SPRINT trial that higher BPV was associated with cognitive decline only in the standard treatment group [27]. This increasingly appreciated skewness towards tau suggests hemodynamic factors may be particularly relevant to tau. Possible mechanisms linking BPV to tau include hemodynamic stress on the microvasculature induced by large fluctuations in BP that in turn may potentiate tau-mediated neurodegeneration [13]. It is also possible that tau exacerbates microvascular damage [42], which could alter arterial processes critical to maintaining BP levels. Additionally, neurodegenerative effects on autonomic control centers and the locus coeruleus may cause changes in BP levels [43–45]. Apolipoprotein e4 carriers may be particularly susceptible to these changes [36,46,47], given known vascular dysfunction [48,49] and increased risk for AD [50] in this population. Despite the longitudinal and interventional design of the current study, the fact that the SPRINT trial was not specifically designed to study or treat BPV and the post hoc nature of our analyses diminishes our ability to determine directionality or causes. However, the present findings between BPV and tau, and not Aß, in an interventional study targeting vascular mechanisms are intriguing given the recent success of interventions using monoclonal antibodies targeting Aß to reduce cognitive decline [51] (i.e., lecanemab). Importantly, a large percentage of cases with AD have mixed vascular and AD pathology [52], suggesting shared underlying mechanisms and targets for intervention with the possibility of synergetic benefits to both heart and brain health. In the case of interventions using antihypertensive medications, some classes may control both mean BP and BPV better than others [53]. New research also suggests this differential class effect may be related to risk for dementia [54]. We were not able to test for this as it relates to plasma AD biomarkers, but this remains an active area of research with the potential to reduce dementia risk.

It is important to note that mean BP was not associated with plasma total tau or Aß1–42:Aß1–40 ratio in either treatment group. This is consistent with many other studies directly comparing effects of BPV vs mean BP [8] and provides potentially valuable information in the current treatment landscape of BP therapies that overwhelmingly focus on managing mean levels. Fluctuations in BP – regardless of mean levels – may represent different processes that require different treatment approaches. Indeed, several recent post hoc studies to come out of the SPRINT trial have found links between BPV and health outcomes in one or both treatment groups [27,28,55,56], despite strict control of mean BP levels. Some have estimated that improvements in BP control could have a profound effect on rates of dementia worldwide [18,19]. It is also important to note that associations between BP and dementia risk appear to be an inverted U across the lifespan [57], further highlighting the importance of understanding BP dynamics beyond mean levels. Although much more research is needed to translate the growing evidence from BPV studies to the clinic, therapies that also consider BPV may have the potential to improve brain health outcomes perhaps even more.

Findings provide novel evidence that elevated BPV is associated with increased plasma total tau, particularly under standard BP treatment. The current study utilized an interventional cohort with strictly controlled mean BP levels. This enabled us to examine relationships between BPV and AD biomarkers in a more rigorous way than prior BPV studies relying on observational cohorts [16,17]. In doing so, we were able to appreciate for the first time that higher BPV remains a risk for change in plasma levels even in those with rigorously controlled mean BP levels. The study is further strengthened by the longitudinal design and characterization of plasma AD biomarker levels at baseline and follow-up in over 450 participants – an impressive addition to a clinical trial primarily designed to assess cardiovascular risk. Use of blood-based AD biomarkers has skyrocketed in recent years and offers a promising, less invasive, and lower cost alternative to characterize AD process when compared to cerebrospinal fluid, positron emission tomography, and postmortem methods. The current findings with plasma in an interventional cohort are largely consistent with prior observational BPV studies using these other methods and add to growing working linking BPV to AD [8,9]. The SPRINT study recruited from a large geographical area and its participants were racially diverse and had varied levels of education. Additionally, BPV was calculated from BP measurements obtained using methods that are widely used in clinical settings. Together this underscores the feasibility of measuring BPV in various communities and settings and encourages the utility of BPV as an emerging risk factor linked with dementia. SPRINT participants were without history of dementia at study baseline. Consistent with a prior observational study [31], the current findings suggest that BPV elevation may occur before the onset of major neurocognitive dysfunction and is associated with change in plasma AD biomarkers. There are several study limitations. First, the study of BPV is relatively new and standardized methods are not fully established [7,10]. Relatedly, although the concordance between newer plasma and more well-studied cerebrospinal fluid AD biomarkers is remarkably high [58], the SPRINT trial did not also collect cerebrospinal fluid samples and we were not able to verify our findings with plasma. Additionally, although the SPRINT trial did collect plasma Aß and total tau, it did not collect plasma phosphorylated tau, another hallmark AD biomarker [20]. However, prior studies have linked higher BPV to plasma [17], cerebrospinal fluid [16], and positron emission tomography [36] phosphorylated tau markers. The SPRINT participant sample is deeply phenotyped for cardiovascular risk, but AD risk gene apolipoprotein e4 genotype was not available. Future cardiovascular/cerebrovascular studies that do collect apolipoprotein e4 information will help elucidate growing links between genetic risk, cerebrovascular dysfunction, and dementia [48,59]. Finally, our study was a post hoc analysis of a clinical trial aimed at lowering mean BP. Future trials that are explicitly designed to test effects on BPV and mean BP may improve our understanding of how best to control BP to benefit brain health and reduce dementia risk.

CONCLUSIONS

Higher BPV is associated with increased plasma total tau under standard BP treatment. Study findings add new evidence on plasma AD biomarkers in an interventional cohort to a growing literature linking BPV to AD in largely observational cohorts. Despite strict control of mean BP levels, higher BPV remains a risk for pathophysiological change underlying risk for AD.

Supplementary Material

Supp Table 1
Supp Table 2
Supp Table 3

ACKNOWLEDGEMENTS

We would like to thank the participants and their families, investigators, and researchers from the SPRINT and SPRINT MIND trial/study.

SOURCES OF FUNDING

The study data analysis was supported by NIH/NIA grants (R01AG064228, R01AG060049, P30AG066519, P01AG052350) and Alzheimer’s Association grant AARG-17–532905.

Footnotes

CONFLICTS OF INTEREST

Daniel Nation is an Editorial Board Member of this journal, but was not involved in the peer-review process nor had access to any information regarding its peer-review.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp Table 1
NIHMS2063422-supplement-Supp_Table_1.docx (13.8KB, docx)
Supp Table 2
NIHMS2063422-supplement-Supp_Table_2.docx (13.5KB, docx)
Supp Table 3
NIHMS2063422-supplement-Supp_Table_3.docx (13KB, docx)

Data Availability Statement

All data are available through the SPRINT group.

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