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Original Investigation |

Blood Pressure and Progression of Brain Atrophy:  The SMART-MR Study FREE

Hadassa M. Jochemsen, MD1,5; Majon Muller, MD, PhD1,6; Frank L. Visseren, MD, PhD2; Philip Scheltens, MD, PhD5; Koen L. Vincken, PhD3; Willem P. Mali, MD, PhD4; Yolanda van der Graaf, MD, PhD1; Mirjam I. Geerlings, PhD1; for the SMART Study Group
[+] Author Affiliations
1Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
2Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
3Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
4Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
5Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
6Department of Internal Medicine, VU University Medical Center, Amsterdam, the Netherlands
JAMA Neurol. 2013;70(8):1046-1053. doi:10.1001/jamaneurol.2013.217.
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Published online

Importance  Studies have shown that both high and low blood pressure (BP) may play a role in the etiology of brain atrophy. High BP in midlife has been associated with more brain atrophy later in life, whereas studies in older populations have shown a relation between low BP and more brain atrophy. Yet, prospective evidence is limited, and the relation remains unclear in patients with manifest arterial disease.

Objective  To examine the associations of baseline BP and change in BP over time with progression of brain atrophy.

Design  The Secondary Manifestations of ARTerial disease–Magnetic Resonance (SMART-MR) Study is a prospective cohort study with baseline measurements in 2001-2005 and follow-up measurements in 2006-2009. The mean follow-up time was 3.9 years.

Setting  University Medical Center Utrecht, the Netherlands.

Participants  A total of 663 patients (mean [SD] age, 57 [9] years; 81% male) with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysm were included.

Main Outcomes and Measures  Using automated segmentation at baseline and follow-up, change in brain parenchymal fraction, cortical gray matter fraction, and ventricular fraction (%ICV) were quantified as indicators of progression of global, cortical, and subcortical brain atrophy.

Results  Multivariable adjusted regression analysis showed that patients with lower baseline diastolic BP (DBP) or mean arterial pressure had more progression of subcortical atrophy. The mean differences in the change in ventricular fraction between low and high DBP was 0.07% (95% CI, 0.01-0.14) and between low and high mean arterial pressure was 0.05% (95% CI, 0.00-0.10). Furthermore, in patients with higher baseline BP (DBP, mean arterial pressure, or systolic BP), those with declining BP levels over time had less progression of subcortical atrophy compared with those with rising BP levels.

Conclusions and Relevance  In patients with manifest arterial disease, low baseline DBP was associated with more progression of subcortical atrophy, irrespective of the BP course during follow-up. Furthermore, in patients with higher baseline BP, declining BP levels over time were associated with less progression of subcortical atrophy. This could imply that BP lowering is beneficial in patients with higher BP levels, but caution should be taken with further BP lowering in patients who already have a low DBP.

Figures in this Article

It has been well established that high blood pressure (BP) increases the risk for vascular brain lesions,13 and that BP reduction has favorable effects in preventing or slowing down the development of vascular brain lesions.4,5 The evidence for the relation between BP and brain atrophy is less clear, with some studies showing that high midlife BP is related to brain atrophy later in life,68 while others show that in older individuals, especially low BP levels lead to an increased risk for brain atrophy.9,10

The relation between BP and brain atrophy may be different in patients with high vascular risk compared with the general population because they may be subject to early vascular aging. The corresponding increased arterial stiffness, impaired endothelial function, and vasodilatation could lead to impaired cerebral autoregulation, making them more vulnerable to lower BP levels.11,12 This may subsequently lead to progression of brain atrophy.13,14 Yet, to our knowledge, prospective data on the association between BP and the progression of brain atrophy in high vascular risk patients are scarce.15

Here, we examine the prospective associations of baseline BP levels and change in BP levels over time with progression of global, cortical, and subcortical brain atrophy.

Second Manifestations of Arterial Disease–Magnetic Resonance Study

Data were used from the Second Manifestations of ARTerial disease–Magnetic Resonance (SMART-MR) Study, a prospective cohort study on brain changes on magnetic resonance imaging (MRI) in patients with manifest arterial disease.16,17 Between 2001 and 2005, all patients newly referred to the University Medical Center Utrecht with manifest coronary artery disease (CAD), cerebrovascular disease (CVD), peripheral arterial disease (PAD), or an abdominal aortic aneurysm (AAA) and without MR contraindications were invited to participate. Patients with CAD were defined as having myocardial infarction, coronary artery bypass graft surgery, or percutaneous transluminal coronary angioplasty in the past or at inclusion. Patients with a transient ischemic attack or stroke at inclusion and patients who reported stroke in the past were considered to have CVD. Patients with PAD were defined as having surgery or angioplasty of the arteries supplying the lower extremities in history or intermittent claudication or rest pain at inclusion. Those with AAA were defined as having present AAA (distal aortic diameter ≥3 cm) or previous AAA surgery. All patients underwent an MRI of the brain, a physical examination, ultrasonography of the carotid arteries, and blood sampling. Risk factors, medical history, and functioning were assessed with questionnaires. Between 2006 and 2009, follow-up measurements, including a brain MRI, took place. The SMART-MR Study was approved by the ethics committee of our institution, and written informed consent was obtained from all participants.

Of the 1309 patients at baseline, 19 had no MRI and 14 had no fluid-attenuated inversion recovery (FLAIR) sequence. In addition, in 44 patients, brain volume data were missing owing to motion or artifacts. Of the remaining 1232 patients, 718 patients participated at follow-up. Of these, 38 had no MRI, and in 17 patients, brain volume data were missing owing to motion/artifacts. Thus, the prospective analyses were performed in 663 patients (54% of 1232). The patients participating in the follow-up examination (N = 663) were on average younger, had lower BP levels, used more antihypertensive treatment, and had smaller brain volumes on MRI than the drop-outs (N = 569).17

Magnetic Resonance Imaging Protocol

At baseline and follow-up, the MRI investigations were performed on a 1.5-T whole-body system (Gyroscan ACS-NT, Philips Medical Systems). The protocol consisted of transversal T1-weighted (repetition time [TR] = 235 milliseconds, echo time [TE] = 2 milliseconds), T2-weighted (TR = 2200 milliseconds, TE = 11 milliseconds and TR = 2200 milliseconds, TE = 100 milliseconds), FLAIR (TR = 6000 milliseconds, TE = 100 milliseconds, inversion time = 2000 milliseconds), and inversion recovery (TR = 2900 milliseconds, TE = 22 milliseconds, inversion time = 410 milliseconds) sequences. Field of view was 230 × 230 mm and matrix size was 180 × 256 (slice thickness, 4.0 mm; no gap; 38 slices).

Brain Segmentation

We used the T1-weighted gradient-echo inversion recovery sequence and FLAIR sequence for the probabilistic segmentation technique.18,19 It distinguishes cortical gray matter, white matter, sulcal and ventricular cerebrospinal fluid, and white matter lesions (WMLs). The automated segmentation was visually checked and a further distinction was made into WMLs and infarct volumes by manually assigning the lesion volumes to one of these two categories. Total brain volume was calculated by summing the volumes of gray matter, white matter, WMLs, and infarcts. Total intracranial volume (ICV) was calculated by summing the total brain volume and the volumes of the sulcal and ventricular cerebrospinal fluid. Total brain volume, cortical gray matter volume, and ventricular volume were normalized for ICV and expressed as brain parenchymal fraction (BPF), cortical gray matter fraction (GMF) and ventricular fraction (VF) as indicators of global, cortical, and subcortical brain atrophy.

Brain Infarcts and White Matter Lesions

At baseline and follow-up, infarcts were rated visually by an investigator and a neuroradiologist blinded to clinical characteristics and reevaluated in a consensus meeting. Infarcts were defined as focal hyperintensities on T2-weighted images of greater than 3 mm in diameter. T2 hyperintensities located in the white matter also had to be hypointense on T1-weighted and FLAIR images to distinguish them from WMLs. Dilated perivascular spaces were distinguished from infarcts on the basis of their location, form, and absence of gliosis. Volumes of WMLs were normalized for percentage of the ICV (%ICV). Infarcts were categorized as lacunar (3-15 mm) and nonlacunar (cortical infarcts and large supratentorial subcortical infarcts >15 mm).

Blood Pressure

Blood pressure was measured twice in a sitting position with a sphygmomanometer, and the average of the 2 measurements was calculated. Pulse pressure (PP) and mean arterial pressure (MAP) were calculated: systolic BP (SBP) – diastolic BP (DBP) and ([2 × DBP] + SBP) / 3, respectively. Measures of BP were categorized in low, normal, and high, according to the common clinical criteria (SBP: ≤120, 121-140, and >140 mm Hg; DBP: ≤70, 71-90, and >90 mm Hg; PP: ≤50, 51-70, and >70 mm Hg; MAP: ≤95, 96-105, and >105 mm Hg). Changes in SBP and DBP during follow-up were categorized in decline or increase with 0 mm Hg as the cutoff point, and combined categories of baseline BP and change in BP levels over time were created: low-BP decline, low-BP increase, normal-BP decline, normal-BP increase, high-BP decline, and high-BP increase. Antihypertensive drug use at baseline was assessed with questionnaires.

Other Cardiovascular Risk Factors

Height and weight were measured without shoes and heavy clothing, and body mass index was calculated (calculated as weight in kilograms divided by height in meters squared). An overnight fasting venous blood sample was taken to determine glucose and lipid levels. Diabetes mellitus status was defined as a known history of diabetes, a fasting glucose level of greater than or equal to 7.0 mmol/L, or self-reported use of glucose-lowering agents. Hyperlipidemia status was defined as fasting total cholesterol greater than 5.0 mmol/L, fasting low-density lipoprotein cholesterol greater than 3.2 mmol/L, or self-reported use of lipid-lowering drugs. Smoking habits and alcohol intake were assessed with questionnaires and were categorized as never, former, or current. The presence of atherosclerosis in the carotid arteries was assessed at baseline by measuring carotid intima media thickness (CIMT) of the common carotid arteries using ultrasonography and the degree of carotid artery stenosis in the internal carotid arteries using color Doppler–assisted duplex scanning.20 Carotid artery stenosis of 70% or greater was defined as peak systolic velocity greater than 210 cm/s.

Data Analysis

We used multiple imputation (10 data sets) to address missing values in the study sample (N = 663) using the statistical program R (aregImpute) version 2.10.0.21,22 Data were analyzed using SPSS version 20.0 by pooling the 10 imputed data sets.

Analysis of covariance was used to estimate mean changes in BPF, GMF, and VF across baseline categories of SBP, DBP, MAP, and PP. Baseline SBP, DBP, MAP, and PP were included as independent variables and mean change in brain volume fractions during follow-up as dependent variables, adjusted for the baseline brain volume fractions.

Next, we estimated the mean change in brain volume fractions associated with a decline vs an increase in BP over time across the baseline BP categories (low, normal, and high). Adjustments were made for age, sex, baseline brain volume, and follow-up time (model 1); and smoking, alcohol consumption, body mass index, diabetes mellitus, hyperlipidemia, carotid atherosclerosis (CIMT and stenosis), arterial disease categories (CAD, CVD, PAD, and AAA), and antihypertensive treatment (model 2). As the relation between BP and progression of brain atrophy might be mediated or confounded by vascular brain lesions, we additionally adjusted for WML volume and brain infarcts at baseline (model 3) and follow-up.

To examine whether a nonlinear association was present, quadratic terms of BP were added to the regression models. In addition, to investigate whether the relation between BP and progression of brain atrophy was modified by markers of vascular aging (age, PP, and CIMT), interaction terms of BP measures with these markers were included in the regression models (model 2). If significant, stratified analyses were performed. Also, analyses were repeated within the arterial disease categories of CAD, CVD, and PAD (the AAA group was too small for reliable analyses, n = 39).

To investigate whether the observed associations could be explained by arterial disease severity, additional adjustments were made for the presence of arterial disease before inclusion in the study and the number of arterial disease locations.

Finally, the role of antihypertensive treatment on the observed associations was further explored in 3 ways. First, we estimated the association of antihypertensive treatment (yes/no) with change in brain volume fractions (adjusting for demographics, baseline brain volume, follow-up time, cardiovascular risk factors and disease, and baseline BP). Second, we estimated the association of BP with progression of brain atrophy across strata of antihypertensive treatment (yes/no). And third, we adjusted the analysis of the association between change in BP with progression of brain atrophy for increase in the number of antihypertensive drugs during follow-up.

The mean (SD) age of the study population was 57 (9) years (range, 28-79 years). At baseline, patients with higher DBP had higher SBP, PP, and MAP; were more often men; and more often had PAD, carotid atherosclerosis, and brain infarcts on MRI. Patients with lower DBP more often had CAD (Table 1). The mean (SD) total ICV was 1468 (129) mL; mean (SD) total brain, cortical gray matter, and ventricular volumes were 79.3 (2.6) %ICV, 36.3 (3.2) %ICV, and 2.0 (0.8) %ICV, respectively. After a mean follow-up of 3.9 years (range, 3.0-5.8 years), mean (SD) BPF and GMF decreased by 1.0% (1.1%) and 1.7% (2.1%), respectively, and mean (SD) VF increased by 0.2% (0.3%).

Table Graphic Jump LocationTable 1.  Baseline Characteristics of the Total Population and According to Categories of Diastolic Blood Pressure
Baseline Blood Pressure Levels and Progression of Brain Atrophy

In the total population, lower baseline DBP and MAP, as well as higher baseline PP but not SBP, were significantly associated with an increase in VF (more progression of subcortical brain atrophy) (Figure 1), with a mean difference in change in VF between low and high DBP of 0.07% (95% CI, 0.01-0.14), between low and high MAP of 0.05% (95% CI, 0.00-0.10), and between low and high PP of −0.07% (95% CI, −0.13 to −0.01) (model 3). Additional adjustment for WML volume and brain infarcts at follow-up did not change these effect estimates or the results presented in Figure 1. Baseline SBP, DBP, MAP, and PP were not associated with change in BPF or GMF (data not shown).

Place holder to copy figure label and caption
Figure 1.
Baseline Blood Pressure and Progression of Subcortical Brain Atrophy

Baseline systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure levels and mean change (standard error) in ventricular fraction after 3.9 years of follow-up, adjusted for age, sex, baseline ventricular fraction, years of follow-up, alcohol intake, smoking, body mass index, diabetes mellitus, hyperlipidemia, carotid atherosclerosis, history of arterial disease, use of antihypertensives, total white matter lesion volume, and brain infarcts. An increase in ventricular fraction indicates more progression of subcortical atrophy. %ICV indicates percentage of the intracranial volume. * P < .05. The error bars indicate the standard error.

Graphic Jump Location

Stratifying for arterial disease categories showed that the association of lower baseline SBP, DBP, and MAP with increase in VF was particularly present in patients with CAD. In patients with CVD, the opposite was found: higher baseline BP was (nonsignificantly) associated with an increase in VF (Table 2).

Table Graphic Jump LocationTable 2.  Baseline Blood Pressure (Low vs High) and Progression of Subcortical Brain Atrophy for the Different Arterial Disease Categories
Change in Blood Pressure Levels Over Time and Progression of Brain Atrophy

The mean (SD) increases in SBP, DBP, MAP, and PP during follow-up were 2.8 (21) mm Hg, 0.5 (12) mm Hg, 2.2 (14) mm Hg, and 1.3 (14) mm Hg, respectively. The eTable in the Supplement shows the BP characteristics according to combined categories of baseline DBP and change in DBP over time. The mean increase in BP was higher in patients with lower baseline BP levels. Also, the mean decline in BP was higher in patients with higher baseline BP levels. In addition, antihypertensive treatment was intensified in nearly all patients, particularly in those with higher baseline BP and declining BP levels over time (eTable in the Supplement).

Declining DBP levels over time were associated with less progression of subcortical atrophy in patients with normal/high baseline DBP; the mean difference in change in VF between the normal DBP decline and normal DBP increase group was −0.07% (95% CI, −0.11 to −0.02) (Figure 2A). Although not statistically significant, a similar difference in the change in VF was found between the high DBP decline and the high DBP increase group: −0.06% (95% CI, −0.17 to 0.06). In patients with low baseline DBP, change in DBP over time was not associated with change in VF.

Place holder to copy figure label and caption
Figure 2.
Adjusted Change in Blood Pressure and Progression of Subcortical Brain Atrophy

Change in diastolic blood pressure (DBP) (A), systolic BP (SBP) (B), and mean arterial pressure (MAP) (C) over time and mean change (SE) in ventricular fraction after 3.9 years of follow-up. Low, normal, and high categories for SBP are ≤120, 121-140, and >140 mm Hg; ≤70, 71-90, and >90 mm Hg for DBP; and ≤50, 51-70, and >70 mm Hg for MAP. Changes during follow-up were categorized as in decline or increase, with 0 mm Hg as the cutoff point. An increase in ventricular fraction indicates more progression of subcortical atrophy. %ICV indicates percentage of the intracranial volume. * P < .05. The error bars indicate the standard error.

Graphic Jump Location

Findings were comparable with respect to MAP and to a lesser extent SBP (Figure 2B and C), showing that declining BP levels in patients with higher baseline BP were associated with less progression of subcortical atrophy. In contrast, declining SBP levels in patients with low baseline SBP was associated with more progression of subcortical brain atrophy (Figure 2B); however, this group was very small (n = 8). Change in PP was not significantly associated with changes in VF. Adjustment for follow-up WML volume and brain infarcts yielded similar results as presented in Figure 2. Also, adjustments for an increase in the number of antihypertensive drugs during follow-up did not materially change the results. Change in BP levels over time was not associated with change in BPF or GMF (data not shown).

There were no significant interactions between BP measures and age, or PP or CIMT (P >.10 interaction), and there were no clear J-shaped relations present (P >.05 quadratic) (data not shown). Excluding patients with extremely high or low BP levels (>200/110 mm Hg and <100/60 mm Hg, respectively; n = 40) did not materially change the results. Adjustments for measures of arterial disease severity did not materially change the results (data not shown). Finally, although antihypertensive treatment at baseline was borderline significantly associated with a decrease in VF (β = −0.04; 95% CI, −0.08 to 0.02), the association of baseline SBP, DBP, MAP, and PP, as well as change in these BP measures with change in brain volumes, was similar for patients with (n = 453) and without (n = 210) antihypertensive treatment (data not shown).

In this prospective study in patients with manifest arterial disease, the main observations were that (1) low DBP (and MAP) at baseline were associated with more progression of subcortical atrophy, irrespective of the course of the BP levels during follow-up, and (2) declining DBP, MAP, and, to a lesser extent, SBP levels over time in patients with higher baseline BP were associated with less progression of subcortical brain atrophy. These results were independent of important confounders including antihypertensive treatment, cardiovascular risk factors, (severity of) arterial disease, WML volume, or brain infarcts on MRI.

To our knowledge, this is the first study that examined the prospective associations of baseline and changing BP levels over time with progression of brain atrophy in patients with manifest arterial disease. A previous study using data of the SMART-MR cohort related baseline BP to progression of brain atrophy and showed no association, possibly owing to the smaller sample size (N = 331).15 Also, in community-based samples, few prospective studies have been performed, of which most showed no association,2,23,24 while one found that higher midlife BP was associated with more progression of subcortical atrophy later in life.25 Most evidence for the relation between BP and brain atrophy comes from cross-sectional population-based studies. In general, these show that high midlife BP is associated with more brain atrophy later in life,68,26 whereas in late life, low BP is associated with more brain atrophy.9,10,27 Together, these and our data suggest that the effect of BP on the brain in a high-risk population of middle-age individuals is comparable with that of older persons.

Low BP (especially low DBP) in this high-risk population could be a risk indicator of early vascular aging.12 Vascular aging is a well-known age-related stiffening process of the vasculature, and it has been related to an increased risk for ischemic and degenerative brain changes.28 Interestingly, we found that a higher baseline PP was associated with more progression of subcortical brain atrophy, suggesting that arterial stiffness, or early vascular aging, may at least partly explain the low DBP–brain atrophy relation. However, adjusting for PP did not change the effect estimates, and PP did not modify the relation between DBP and the progression of brain atrophy. Another explanation for our findings could be that low DBP (and MAP) are markers of reduced cardiac output, which could be an independent risk factor for brain atrophy.29 This hypothesis is supported by our finding that the association of low DBP and MAP with progression of subcortical atrophy was mainly present in patients with CAD. Although the vascular screening program of this study did not include measures of cardiac output, it is likely that a substantial proportion of the patients with CAD had heart failure and low cardiac output. Interestingly, in patients with CVD, higher SBP, DBP, and PP were borderline significantly related to more progression of subcortical brain atrophy, suggesting that the association depends on vascular disease location. Furthermore, a causal mechanism explaining low DBP and MAP-related brain atrophy should be considered. Patients with manifest arterial disease more likely have impaired cerebral autoregulation, making the brain more vulnerable for lower BP levels, particularly lower DBP and MAP because these are important constituents of cerebral perfusion pressure.11,13 Therefore, lower systemic DBP and MAP levels may be inadequate for healthy cerebral perfusion, which can evolve into a neurodegenerative process,13,14 eventually leading to brain atrophy, specifically subcortical brain atrophy because subcortical areas are very vulnerable for impaired perfusion and ischemic damage.30 Finally, because the brain is involved in BP regulation, it is also possible that low BP is the consequence of brain atrophy.31

Two studies examined change in BP levels over time in relation to brain atrophy, with inconsistent results.24,27 One study showed no association,24 whereas the other found that especially declining DBP levels over time increased the risk for brain atrophy.27 We found that a decline in DBP and MAP over time was associated with less progression of subcortical atrophy, except in patients with a low baseline BP. It is possible that declining BP levels in patients with higher baseline BP indicate adequate treatment for too-high BP levels, reducing the risk for brain atrophy, possibly through the reduction of cerebrovascular lesions. Although adjustment for baseline and follow-up WML volume and infarcts at MRI did not materially attenuate the associations, we previously showed that the presence and progression of periventricular WML volume and lacunar infarcts were associated with progression of brain atrophy.32 It could be hypothesized that increasing BP levels may result in those microvascular changes subsequently causing brain tissue loss,14,33,34 which could be counterbalanced by adequate antihypertensive treatment. Another explanation could be that those with increasing BP levels over time were therapy resistant or noncompliant; although our data show that antihypertensive treatment was intensified in these patients (eTable in the Supplement), we do not have information on dosages or compliance, which limited the possibility to investigate the role of antihypertensive treatment on the observed associations. The increase in BP was most pronounced in those with lower baseline BP levels, possibly owing to regression to the mean, noncompliance, or less-adequate antihypertensive treatment. Similarly, the decline in DBP was largest in the high-DBP decline group, possibly indicating intensified treatment or regression to the mean.

Our finding that in patients with low baseline SBP, DBP, and MAP, those with declining BP levels over time showed similar or even more progression of subcortical atrophy as those with increasing BP levels over time could indicate that further BP lowering in the low baseline BP group might be harmful.

The major strengths of this study were the prospective design that enabled us to investigate change in BP over time with progression of brain atrophy, and the large number of patients included in the study. Furthermore, the segmentation of different brain tissue types and cerebrospinal fluid spaces made it possible to differentiate between GMF and VF. The extensive information on cardiovascular risk factors and markers of vascular brain lesions allowed us to investigate whether the associations of BP measures with change in brain volume were independent of these factors.

A limitation of this study was that individuals who participated in the follow-up examination were somewhat healthier compared with the nonparticipants at follow-up. This may have led to an underestimation of the true associations. Second, our BP measurements were performed on a single day in the clinic and might be influenced by a white-coat effect; therefore, they are less accurate than ambulatory BP monitoring. This may also have led to an underestimation of the observed associations. Finally, because our population consisted of patients with manifest arterial disease, the results might not be applicable to patients without arterial disease and to the general population. Yet, our data might suggest that patients with manifest arterial disease represent a subgroup within the general population in whom low BP might be harmful.

In summary, in this large cohort of patients with manifest arterial disease, low baseline DBP (and MAP) levels were associated with more progression of subcortical brain atrophy, irrespective of the BP course during follow-up. Furthermore, in patients with higher baseline SBP, DBP, and MAP, declining BP levels over time were associated with less progression of subcortical atrophy. This could imply that BP lowering is beneficial in patients with higher BP levels, but one should be cautious with further BP lowering in patients who already have low BP.

Accepted for Publication: November 27, 2012.

Corresponding Author: Mirjam I. Geerlings, PhD, Julius Center for Health Sciences and Primary Care, Stratenum 6.131, PO Box 85500, 3508 GA Utrecht, the Netherlands (m.geerlings@umcutrecht.nl).

Published Online: June 10, 2013. doi:10.1001/jamaneurol.2013.217.

Author Contributions:Study concept and design: Jochemsen, Muller, Scheltens, van der Graaf, and Geerlings.

Acquisition of data: Jochemsen, Muller, Visseren, and Mali.

Analysis and interpretation of data: Jochemsen, Muller, Visseren, Scheltens, Vincken, and Geerlings.

Drafting of the manuscript: Jochemsen, Muller, and Scheltens.

Critical revision of the manuscript for important intellectual content: Muller, Visseren, Scheltens, Vincken, Mali, van der Graaf, and Geerlings.

Statistical analysis: Jochemsen and Muller.

Obtained funding: Scheltens and van der Graaf.

Administrative, technical, and material support: Vincken and Mali.

Study supervision: Muller, Visseren, Scheltens, van der Graaf, and Geerlings.

Secondary Manifestations of ARTerial disease (SMART) Study Investigators: Ale Algra, MD, PhD, Julius Center for Health Sciences and Primary Care and Rudolf Magnus Institute for Neurosciences, Department of Neurology; Peter A. Doevendans, MD, PhD, Department of Cardiology; Yolanda van der Graaf, MD, PhD, Diederick E. Grobbee, MD, PhD, and Guy E. H. M. Rutten, MD, PhD, Julius Center for Health Sciences and Primary Care; L. Jaap Kappelle, MD, PhD, Department of Neurology; Willem P. Th. M. Mali, MD, PhD, Department of Radiology; Frans L. Moll, MD, PhD, Department of Vascular Surgery; and Frank L. J. Visseren, MD, PhD, Department of Vascular Medicine, University Medical Center Utrecht.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by Internationale Stichting Alzheimer Onderzoek (ISAO project No. 09502) and Alzheimer Nederland (WE.15-2011-02).

Role of the Sponsor: The funding sources had no involvement in the writing of this article or in the decision to submit it for publication

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de la Torre  JC.  Critically attained threshold of cerebral hypoperfusion: can it cause Alzheimer’s disease? Ann N Y Acad Sci. 2000;903:424-436.
PubMed   |  Link to Article
Muller  M, van der Graaf  Y, Visseren  FL, Vlek  AL, Mali  WP, Geerlings  MI; SMART Study Group.  Blood pressure, cerebral blood flow, and brain volume: the SMART-MR Study. J Hypertens. 2010;28(7):1498-1505.
PubMed   |  Link to Article
Vlek  AL, Visseren  FL, Kappelle  LJ,  et al; SMART Study Group.  Blood pressure and progression of cerebral atrophy in patients with vascular disease. Am J Hypertens. 2009;22(11):1183-1189.
PubMed   |  Link to Article
Geerlings  MI, Appelman  AP, Vincken  KL,  et al; SMART Study Group.  Brain volumes and cerebrovascular lesions on MRI in patients with atherosclerotic disease: the SMART-MR Study. Atherosclerosis. 2010;210(1):130-136.
PubMed   |  Link to Article
Muller  M, van der Graaf  Y, Algra  A, Hendrikse  J, Mali  WP, Geerlings  MI; SMART Study Group.  Carotid atherosclerosis and progression of brain atrophy: the SMART-MR Study. Ann Neurol. 2011;70(2):237-244.
PubMed   |  Link to Article
Anbeek  P, Vincken  KL, van Osch  MJ, Bisschops  RH, van der Grond  J.  Probabilistic segmentation of white matter lesions in MR imaging. Neuroimage. 2004;21(3):1037-1044.
PubMed   |  Link to Article
Anbeek  P, Vincken  KL, van Bochove  GS, van Osch  MJ, van der Grond  J.  Probabilistic segmentation of brain tissue in MR imaging. Neuroimage. 2005;27(4):795-804.
PubMed   |  Link to Article
Simons  PC, Algra  A, van de Laak  MF, Grobbee  DE, van der Graaf  Y.  Second Manifestations of ARTerial disease (SMART) Study: rationale and design. Eur J Epidemiol. 1999;15(9):773-781.
PubMed   |  Link to Article
Donders  AR, van der Heijden  GJ, Stijnen  T, Moons  KG.  Review: a gentle introduction to imputation of missing values. J Clin Epidemiol. 2006;59(10):1087-1091.
PubMed   |  Link to Article
Rubin  DB, Schenker  N.  Multiple imputation in health-care databases: an overview and some applications. Stat Med. 1991;10(4):585-598.
PubMed   |  Link to Article
Enzinger  C, Fazekas  F, Matthews  PM,  et al.  Risk factors for progression of brain atrophy in aging: six-year follow-up of normal subjects. Neurology. 2005;64(10):1704-1711.
PubMed   |  Link to Article
Goldstein  IB, Bartzokis  G, Guthrie  D, Shapiro  D.  Ambulatory blood pressure and the brain: a 5-year follow-up. Neurology. 2005;64(11):1846-1852.
PubMed   |  Link to Article
Knopman  DS, Penman  AD, Catellier  DJ,  et al.  Vascular risk factors and longitudinal changes on brain MRI: the ARIC Study. Neurology. 2011;76(22):1879-1885.
PubMed   |  Link to Article
Petrovitch  H, White  LR, Izmirilian  G,  et al.  Midlife blood pressure and neuritic plaques, neurofibrillary tangles, and brain weight at death: the HAAS: Honolulu-Asia Aging Study. Neurobiol Aging. 2000;21(1):57-62.
PubMed   |  Link to Article
Heijer  Td, Skoog  I, Oudkerk  M,  et al.  Association between blood pressure levels over time and brain atrophy in the elderly. Neurobiol Aging. 2003;24(2):307-313.
PubMed   |  Link to Article
Mitchell  GF, van Buchem  MA, Sigurdsson  S,  et al.  Arterial stiffness, pressure and flow pulsatility and brain structure and function: the Age, Gene/Environment Susceptibility—Reykjavik Study. Brain. 2011;134(pt 11):3398-3407.
PubMed   |  Link to Article
Jefferson  AL.  Cardiac output as a potential risk factor for abnormal brain aging. J Alzheimers Dis. 2010;20(3):813-821.
PubMed
Iadecola  C, Davisson  RL.  Hypertension and cerebrovascular dysfunction. Cell Metab. 2008;7(6):476-484.
PubMed   |  Link to Article
Burke  WJ, Coronado  PG, Schmitt  CA, Gillespie  KM, Chung  HD.  Blood pressure regulation in Alzheimer’s disease. J Auton Nerv Syst. 1994;48(1):65-71.
PubMed   |  Link to Article
Kloppenborg  RP, Nederkoorn  PJ, Grool  AM,  et al; SMART Study Group.  Cerebral small-vessel disease and progression of brain atrophy: the SMART-MR Study. Neurology. 2012;79(20):2029-2036.
PubMed   |  Link to Article
Appelman  AP, Exalto  LG, van der Graaf  Y, Biessels  GJ, Mali  WP, Geerlings  MI.  White matter lesions and brain atrophy: more than shared risk factors? a systematic review. Cerebrovasc Dis. 2009;28(3):227-242.
PubMed   |  Link to Article
Iadecola  C, Gorelick  PB.  Hypertension, angiotensin, and stroke: beyond blood pressure. Stroke. 2004;35(2):348-350.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Baseline Blood Pressure and Progression of Subcortical Brain Atrophy

Baseline systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure levels and mean change (standard error) in ventricular fraction after 3.9 years of follow-up, adjusted for age, sex, baseline ventricular fraction, years of follow-up, alcohol intake, smoking, body mass index, diabetes mellitus, hyperlipidemia, carotid atherosclerosis, history of arterial disease, use of antihypertensives, total white matter lesion volume, and brain infarcts. An increase in ventricular fraction indicates more progression of subcortical atrophy. %ICV indicates percentage of the intracranial volume. * P < .05. The error bars indicate the standard error.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Adjusted Change in Blood Pressure and Progression of Subcortical Brain Atrophy

Change in diastolic blood pressure (DBP) (A), systolic BP (SBP) (B), and mean arterial pressure (MAP) (C) over time and mean change (SE) in ventricular fraction after 3.9 years of follow-up. Low, normal, and high categories for SBP are ≤120, 121-140, and >140 mm Hg; ≤70, 71-90, and >90 mm Hg for DBP; and ≤50, 51-70, and >70 mm Hg for MAP. Changes during follow-up were categorized as in decline or increase, with 0 mm Hg as the cutoff point. An increase in ventricular fraction indicates more progression of subcortical atrophy. %ICV indicates percentage of the intracranial volume. * P < .05. The error bars indicate the standard error.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Baseline Characteristics of the Total Population and According to Categories of Diastolic Blood Pressure
Table Graphic Jump LocationTable 2.  Baseline Blood Pressure (Low vs High) and Progression of Subcortical Brain Atrophy for the Different Arterial Disease Categories

References

de Leeuw  FE, de Groot  JC, Oudkerk  M,  et al.  Hypertension and cerebral white matter lesions in a prospective cohort study. Brain. 2002;125(pt 4):765-772.
PubMed   |  Link to Article
Debette  S, Seshadri  S, Beiser  A,  et al.  Midlife vascular risk factor exposure accelerates structural brain aging and cognitive decline. Neurology. 2011;77(5):461-468.
PubMed   |  Link to Article
Launer  LJ.  Epidemiology of white matter lesions. Top Magn Reson Imaging. 2004;15(6):365-367.
PubMed   |  Link to Article
Godin  O, Tzourio  C, Maillard  P, Mazoyer  B, Dufouil  C.  Antihypertensive treatment and change in blood pressure are associated with the progression of white matter lesion volumes: the Three-City (3C)-Dijon Magnetic Resonance Imaging Study. Circulation. 2011;123(3):266-273.
PubMed   |  Link to Article
Law  MR, Morris  JK, Wald  NJ.  Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ. 2009;338:b1665. 19454737
Link to Article
DeCarli  C, Miller  BL, Swan  GE,  et al.  Predictors of brain morphology for the men of the NHLBI twin study. Stroke. 1999;30(3):529-536.
PubMed   |  Link to Article
Korf  ES, White  LR, Scheltens  P, Launer  LJ.  Midlife blood pressure and the risk of hippocampal atrophy: the Honolulu Asia Aging Study. Hypertension. 2004;44(1):29-34.
PubMed   |  Link to Article
Swan  GE, DeCarli  C, Miller  BL,  et al.  Association of midlife blood pressure to late-life cognitive decline and brain morphology. Neurology. 1998;51(4):986-993.
PubMed   |  Link to Article
den Heijer  T, Launer  LJ, Prins  ND,  et al.  Association between blood pressure, white matter lesions, and atrophy of the medial temporal lobe. Neurology. 2005;64(2):263-267.
PubMed   |  Link to Article
Skoog  I, Andreasson  LA, Landahl  S, Lernfelt  B.  A population-based study on blood pressure and brain atrophy in 85-year-olds. Hypertension. 1998;32(3):404-409.
PubMed   |  Link to Article
van Beek  AH, Claassen  JA, Rikkert  MG, Jansen  RW.  Cerebral autoregulation: an overview of current concepts and methodology with special focus on the elderly. J Cereb Blood Flow Metab. 2008;28(6):1071-1085.
PubMed   |  Link to Article
Kotsis  V, Stabouli  S, Karafillis  I, Nilsson  P.  Early vascular aging and the role of central blood pressure. J Hypertens. 2011;29(10):1847-1853.
PubMed   |  Link to Article
de la Torre  JC.  Critically attained threshold of cerebral hypoperfusion: can it cause Alzheimer’s disease? Ann N Y Acad Sci. 2000;903:424-436.
PubMed   |  Link to Article
Muller  M, van der Graaf  Y, Visseren  FL, Vlek  AL, Mali  WP, Geerlings  MI; SMART Study Group.  Blood pressure, cerebral blood flow, and brain volume: the SMART-MR Study. J Hypertens. 2010;28(7):1498-1505.
PubMed   |  Link to Article
Vlek  AL, Visseren  FL, Kappelle  LJ,  et al; SMART Study Group.  Blood pressure and progression of cerebral atrophy in patients with vascular disease. Am J Hypertens. 2009;22(11):1183-1189.
PubMed   |  Link to Article
Geerlings  MI, Appelman  AP, Vincken  KL,  et al; SMART Study Group.  Brain volumes and cerebrovascular lesions on MRI in patients with atherosclerotic disease: the SMART-MR Study. Atherosclerosis. 2010;210(1):130-136.
PubMed   |  Link to Article
Muller  M, van der Graaf  Y, Algra  A, Hendrikse  J, Mali  WP, Geerlings  MI; SMART Study Group.  Carotid atherosclerosis and progression of brain atrophy: the SMART-MR Study. Ann Neurol. 2011;70(2):237-244.
PubMed   |  Link to Article
Anbeek  P, Vincken  KL, van Osch  MJ, Bisschops  RH, van der Grond  J.  Probabilistic segmentation of white matter lesions in MR imaging. Neuroimage. 2004;21(3):1037-1044.
PubMed   |  Link to Article
Anbeek  P, Vincken  KL, van Bochove  GS, van Osch  MJ, van der Grond  J.  Probabilistic segmentation of brain tissue in MR imaging. Neuroimage. 2005;27(4):795-804.
PubMed   |  Link to Article
Simons  PC, Algra  A, van de Laak  MF, Grobbee  DE, van der Graaf  Y.  Second Manifestations of ARTerial disease (SMART) Study: rationale and design. Eur J Epidemiol. 1999;15(9):773-781.
PubMed   |  Link to Article
Donders  AR, van der Heijden  GJ, Stijnen  T, Moons  KG.  Review: a gentle introduction to imputation of missing values. J Clin Epidemiol. 2006;59(10):1087-1091.
PubMed   |  Link to Article
Rubin  DB, Schenker  N.  Multiple imputation in health-care databases: an overview and some applications. Stat Med. 1991;10(4):585-598.
PubMed   |  Link to Article
Enzinger  C, Fazekas  F, Matthews  PM,  et al.  Risk factors for progression of brain atrophy in aging: six-year follow-up of normal subjects. Neurology. 2005;64(10):1704-1711.
PubMed   |  Link to Article
Goldstein  IB, Bartzokis  G, Guthrie  D, Shapiro  D.  Ambulatory blood pressure and the brain: a 5-year follow-up. Neurology. 2005;64(11):1846-1852.
PubMed   |  Link to Article
Knopman  DS, Penman  AD, Catellier  DJ,  et al.  Vascular risk factors and longitudinal changes on brain MRI: the ARIC Study. Neurology. 2011;76(22):1879-1885.
PubMed   |  Link to Article
Petrovitch  H, White  LR, Izmirilian  G,  et al.  Midlife blood pressure and neuritic plaques, neurofibrillary tangles, and brain weight at death: the HAAS: Honolulu-Asia Aging Study. Neurobiol Aging. 2000;21(1):57-62.
PubMed   |  Link to Article
Heijer  Td, Skoog  I, Oudkerk  M,  et al.  Association between blood pressure levels over time and brain atrophy in the elderly. Neurobiol Aging. 2003;24(2):307-313.
PubMed   |  Link to Article
Mitchell  GF, van Buchem  MA, Sigurdsson  S,  et al.  Arterial stiffness, pressure and flow pulsatility and brain structure and function: the Age, Gene/Environment Susceptibility—Reykjavik Study. Brain. 2011;134(pt 11):3398-3407.
PubMed   |  Link to Article
Jefferson  AL.  Cardiac output as a potential risk factor for abnormal brain aging. J Alzheimers Dis. 2010;20(3):813-821.
PubMed
Iadecola  C, Davisson  RL.  Hypertension and cerebrovascular dysfunction. Cell Metab. 2008;7(6):476-484.
PubMed   |  Link to Article
Burke  WJ, Coronado  PG, Schmitt  CA, Gillespie  KM, Chung  HD.  Blood pressure regulation in Alzheimer’s disease. J Auton Nerv Syst. 1994;48(1):65-71.
PubMed   |  Link to Article
Kloppenborg  RP, Nederkoorn  PJ, Grool  AM,  et al; SMART Study Group.  Cerebral small-vessel disease and progression of brain atrophy: the SMART-MR Study. Neurology. 2012;79(20):2029-2036.
PubMed   |  Link to Article
Appelman  AP, Exalto  LG, van der Graaf  Y, Biessels  GJ, Mali  WP, Geerlings  MI.  White matter lesions and brain atrophy: more than shared risk factors? a systematic review. Cerebrovasc Dis. 2009;28(3):227-242.
PubMed   |  Link to Article
Iadecola  C, Gorelick  PB.  Hypertension, angiotensin, and stroke: beyond blood pressure. Stroke. 2004;35(2):348-350.
PubMed   |  Link to Article

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