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High Blood Pressure and Cerebral White Matter Lesion Progression in the General Population

Originally publishedhttps://doi.org/10.1161/HYPERTENSIONAHA.111.00430Hypertension. 2013;61:1354–1359

Abstract

High blood pressure is considered an important risk factor for cerebral white matter lesions (WMLs) in the aging population. In a longitudinal population-based study of 665 nondemented persons, we investigated the longitudinal relationship of systolic blood pressure, diastolic blood pressure, and pulse pressure with annual progression of WMLs. Means of blood pressure were calculated over a 5-year period before longitudinal MRI scanning. WML progression was subsequently measured on 2 scans 3.5 years apart. We performed analyses with linear regression models and evaluated adjustments for age, sex, cardiovascular risk factors, and baseline WML volume. In addition, we evaluated whether treatment of hypertension is related to less WML progression. Both systolic and diastolic blood pressures were significantly associated with annual WML progression (regression coefficient [95% confidence interval], 0.08 [0.03; 0.14] mL/y and 0.09 [0.03; 0.15] mL/y per SD increase in systolic and diastolic blood pressure, respectively). Pulse pressure was also significantly associated with WML progression, but not independent from hypertension. After adjustment for baseline WML volume, only systolic blood pressure remained significantly associated: 0.05 (0.00; 0.09) mL/y per SD increase. People with uncontrolled untreated hypertension had significantly more WML progression than people with uncontrolled treated hypertension (difference [95% confidence interval], 0.12 [0.00; 0.23] mL/y). The present study further establishes high blood pressure to precede WMLs and implies that hypertension treatment could reduce WML progression in the general population.

Introduction

Cerebral white matter lesions (WMLs) are highly prevalent in the elderly population and increase the risk of dementia and stroke.1 Although believed to be vascular in origin, the exact etiology of WMLs is still unknown. On the basis of pathological and epidemiological studies, blood pressure is considered to be one of the most important factors by damaging the cerebral small vessels.2,3 Because blood pressure is modifiable, blood pressure control seems an important candidate for the prevention of WML progression.

The earliest studies demonstrating an association between high blood pressure and WMLs were cross-sectional by design, which limits causal inferences.413 More recently, studies have used longitudinal designs and found similar results.1423 Yet, because WML progression is strongly influenced by the WML load at baseline,15 it is unknown to what extent associations of blood pressure with WML progression are affected by the baseline WML load. Moreover, to provide stronger evidence for a temporal relationship, blood pressure should preferably be measured before the window in which WML progression is determined, instead of during this window. In addition, the use of different MRI scanners or scanning protocols when measuring WML progression can possibly lead to systematic biases. Previous studies have addressed 1 or 2 of these issues, but none of them addressed all.

It is also unknown whether the associations between blood pressure and WML progression are present for systolic, diastolic, and pulse pressure. Moreover, the influence of medication use and control of hypertension on WML progression remains unclear. We hypothesized that blood pressure would relate to WML progression even when taking baseline WML load into account and that medication use and adequate control of hypertension would reduce this progression.

We tested this hypothesis in a population-based longitudinal MRI study in which we measured systolic, diastolic, and pulse pressure before MRI scanning; evaluated the influence of the WML load at baseline; and used exactly the same scanners and scanning protocol at baseline and follow-up.

Methods

Study Population and Design

The study is based on participants from the Rotterdam Study, a population-based cohort study in The Netherlands that investigates determinants of various chronic diseases among the elderly people.24 The original study population consisted of the general population aged 55 years and older within the Ommoord area, a suburb of Rotterdam. In 2000, the cohort was expanded with 3011 people (≥55 years) who were living in the study area and had not been included before.24

For this report, we used data from a random subset of the latter cohort expansion, which underwent 3 visits: visit 1 (in the year 2000), visit 2 (2005–2006), and visit 3 (2008–2010). At visits 1 and 2, blood pressure and cardiovascular determinants were assessed. At visits 2 and 3, MRI scanning was performed.25Figure 1 displays the design used and the timings of the various longitudinal measurements. No blood pressure measurements were available at visit 3.

Figure 1.

Figure 1. Schematic overview of the study design. BP indicates blood pressure; and WML, white matter lesion.

At visit 2, 1073 people were randomly selected for this study from the full cohort expansion (n=3011), because MRI scanning was implemented only from visit 2 onward and could not be performed in the full cohort. Hereto, we used a simple random sampling procedure. After excluding people with previous clinical stroke (n=35), dementia (n=4), or those who had MRI contraindications (n=94), a total of 944 people was eligible. From these, 877 participated and gave written informed consent. Because of physical inabilities, imaging could not be performed in 12 persons, leaving 865 people who underwent MRI scanning. From these, 731 people had a second MRI at visit 3, and of these 699 people had good-quality MRI data of both scans.

After excluding 19 people with MRI-defined cortical infarcts, which hampered the assessment of WMLs, and 15 people with missing information on blood pressure measures, 665 people remained for the current analysis. All measurements were performed at the Rotterdam Study Research Center, which is a single site. The Institutional Review Board (Erasmus MC, Rotterdam, The Netherlands) approved the study.

Blood Pressure, Hypertension, and Antihypertensive Medication

At visits 1 and 2 (5.3 years later; see Figure 1), systolic and diastolic blood pressure were measured twice on the right arm with a random zero sphygmomanometer by a trained research physician after the participant had been sitting quietly for ≥5 minutes. A standard cuff or, if applicable, a large cuff was used. Pulse pressure was defined as systolic blood pressure minus diastolic blood pressure. To gain robust measures of blood pressure, we computed 5-year means of blood pressure measures (mean of blood pressure measure at visit 1 summed with the mean of blood pressure measure at visit 2, and divided by 2). Hypertension was defined as systolic blood pressure ≥140 or diastolic blood pressure ≥90 mm Hg or receiving antihypertensive treatment, at either of the 2 visits. Antihypertensive medication was assessed during a home interview. At the research center, a physician ascertained the indication for which the medication had been prescribed.

MRI and WML Progression

Brain MRI was performed at visits 2 and 3 (3.5 years apart; see Figure 1). At both visits, we used the same MRI scanner and imaging protocol and applied exactly the same image postprocessing steps and segmentation method. We used a 1.5-T scanner (GE Healthcare) with an 8-channel head coil and included T1-weighted, proton density–weighted, and fluid-attenuated inversion recovery sequences.25 Postprocessing steps have been described elsewhere and include a conventional k-nearest-neighbor brain tissue classifier extended with WML segmentation.26,27 Using this classifier, we obtained quantitative measures of WML volume and intracranial volume (in mL). WML progression was assessed by subtracting the WML volume (in mL) at the first measurement from the WML volume (in mL) at the second measurement. This number was subsequently divided by the time between scans (in years) to obtain the annual WML progression (in mL/y). Infarcts were classified as described previously.28

Cardiovascular Risk Factors

Body mass index, total cholesterol, high-density lipoprotein cholesterol, triglycerides (only measured at visit 1), diabetes mellitus, alcohol consumption (only measured at visit 2), and smoking were determined by interview and laboratory and physical examination at visits 1 and 2. Body mass index was calculated by dividing weight (kg) by the square of height (m2). The waist/hip ratio was defined as the ratio between the waist circumference (cm) and the hip circumference (cm). We considered diabetes mellitus present when a person was taking oral antidiabetics or insulin, or if fasting plasma glucose was ≥7 mmol/L (≥126 mg/dL). A physician assessed participants’ smoking habits, and smoking status was further classified as current, former, or never. Alcohol intake was quantified as units per week. Cardiovascular disease (coronary heart disease, heart failure, or atrial fibrillation) was assessed during interview and verified by reviewing medical records and through automated linkage of the study database with files from general practioners.29 For the analyses, we computed means for the continuous covariates at visits 1 and 2 and determined the ever presence of a condition between visits 1 and 2 for dichotomous variables. Apolipoprotein E (ApoE)-ε4 genotyping was performed as previously described.30

Statistical Analyses

We investigated how systolic blood pressure, diastolic blood pressure, and pulse pressure were related to WML volume cross-sectionally and annual WML progression longitudinally, using linear regression models, adjusted for age, sex, and intracranial volume in model I, and additionally for cardiovascular risk factors (antihypertensive medication, total cholesterol, high-density lipoprotein cholesterol, triglycerides, body mass index, alcohol consumption, smoking, and diabetes mellitus) in model II. For the analyses regarding WML progression, we also applied a model III with adjustments for baseline WML volume, to assess whether possible associations were explained by WML accumulated before the first scan.

Additionally, the following exploratory analyses were conducted. We evaluated additional adjustments for cardiovascular disease and ApoE-ε4 carriership and tested for interaction of ApoE-ε4 carriership with systolic blood pressure, diastolic blood pressure, or pulse pressure. In addition, we adjusted pulse pressure for the presence of hypertension to see whether pulse pressure had additional value beyond hypertension. We evaluated the addition of quadratic terms of systolic blood pressure, diastolic blood pressure, and pulse pressure to explore whether J-shaped relationships were present. We repeated all analyses with waist/hip ratio as covariate instead of body mass index.

Finally, we evaluated the relationship between hypertension treatment and WML progression by constructing 4 mutually exclusive groups of people: normotensives, controlled treated hypertensives, uncontrolled treated hypertensives, and uncontrolled untreated hypertensives. These 4 groups were defined as follows based on the mean blood pressure of visits 1 and 2, and the use of antihypertensive medication during this 5-year period: (1) normotensives: study participants with normal mean blood pressure and receiving no antihypertensive treatment during this period; (2) controlled treated hypertensives: study participants with normal mean blood pressure and receiving antihypertensive treatment during this period; (3) uncontrolled treated hypertensives: study participants with hypertensive mean blood pressure and receiving antihypertensive treatment during this period; and (4) uncontrolled untreated hypertensives: study participants with hypertensive mean blood pressure and not receiving antihypertensive treatment during this period. We compared WML progression of the groups using linear regression models, adjusted for age, sex, intracranial volume, and baseline WML volume. In addition, we tested for a trend in increasing WML progression across groups.

Results

Characteristics of the study population are represented in Table 1. The mean (SD) age of the population was 61.6 (5.0) years at visit 1, 66.9 (5.0) years at visit 2, and 70.4 (5.0) years at visit 3. The age range was 55 to 82 years at visit 1, 60 to 87 years at visit 2, and 64 to 91 years at visit 3. In Table S1 (online-only Data Supplement), the associations between blood pressure measures and cross-sectionally assessed WML volume are represented.

Table 1. Characteristics of the Study Population

VariableVisit 1Visit 2Visit 3P Value for Difference
Age, y61.6 (5.0)66.9 (5.0)70.4 (5.0)NA
Female52%52%52%NA
Systolic blood pressure, mm Hg138 (19)143 (18)<0.01
Diastolic blood pressure, mm Hg78 (10)81 (10)<0.01
Pulse pressure, mm Hg60 (14)62 (15)<0.01
Anithypertensive medication22%34%<0.01
Total cholesterol, mmol/L5.84 (0.95)5.73 (0.93)<0.01
High-density lipoprotein, mmol/L1.39 (0.37)1.44 (0.38)<0.01
Triglycerides, mmol/L1.33 [0.80]NA
Body mass index26.8 (3.5)27.5 (3.6)<0.01
Alcohol, units/wk6 [14]NA
Current smoker16%11%<0.01
Diabetes mellitus*8%9%<0.01
Cardiovascular disease6%7%0.03

Values are means (SD), percentages, or median [interquartile range]. NA indicates not applicable.

*Fasting glucose ≥7.0 mmol/L (≥126 mg/dL) or receiving glucose-lowering drugs.

The presence of coronary heart disease, heart failure, or atrial fibrillation.

Table 2 shows the relationship of systolic blood pressure, diastolic blood pressure, and pulse pressure with annual WML progression. All values mentioned below represent regression coefficients. Both systolic and diastolic blood pressures were significantly associated with WML progression, even after adjustment for age, sex, intracranial volume, and cardiovascular risk factors for WML progression (95% confidence interval [CI]) per SD increase in systolic blood pressure: 0.08 (0.03; 0.14) mL/y and 0.09 (0.03; 0.15) mL/y per SD increase in diastolic blood pressure. After adjustment for baseline WML volume only, the association between systolic blood pressure and WML progression remained statistically significant: 0.05 (95% CI, 0.00; 0.09) mL/y per SD increase in systolic blood pressure (P<0.05). Pulse pressure was also significantly associated with WML progression (0.06 [95% CI, 0.00; 0.11] mL/y per SD increase in pulse pressure; P<0.05), although this value attenuated and lost statistical significance after adjustment for the presence of hypertension (−0.02 [95% CI, −0.05; 0.09] mL/y per SD increase in pulse pressure; P=0.58), or adjustment for baseline WML volume (0.04 [95% CI, 0.00; 0.08] mL/y per SD increase in pulse pressure; P=0.09). Addition of quadratic terms of systolic blood pressure, diastolic blood pressure, or pulse pressure to any of the models was not significant. After additional adjustments for the presence of cardiovascular disease, the effect estimates remained unchanged. Adjustment for ApoE-ε4 carriership did not change the effect estimates either. No interaction between ApoE-ε4 and systolic blood pressure, diastolic blood pressure, and pulse pressure was observed (all P>0.20). No differences were observed when body mass index was replaced by the waist/hip ratio as covariate in the analyses.

Table 2. Annual White Matter Lesion Progression per SD Increase in Blood Pressure Measure

VariableModel I*Model IIModel III
Systolic blood pressure0.07 (0.02; 0.12)0.08 (0.03; 0.14)0.05 (0.00; 0.09)
Diastolic blood pressure0.07 (0.02; 0.12)0.09 (0.03; 0.15)0.02 (−0.02; 0.07)
Pulse pressure0.05 (0.00; 0.10)0.06 (0.00; 0.11)0.04 (0.00; 0.08)

Values are white matter lesion progression in mL/y (95% CI) per SD increase of blood pressure (mean of the measures at visit 1 and 2), derived from linear regression models. CI indicates confidence interval; HDL, high-density lipoprotein; and WML, white matter lesion.

*Model I: adjustments for age, sex, and intracranial volume.

Model II: adjustments for age, sex, intracranial volume, antihypertensive medication, total cholesterol, HDL-cholesterol, triglycerides, body mass index, alcohol consumption, smoking, and diabetes mellitus.

Model III: as model II, but additional adjustment for WML volume on scan 1.

Figure 2 displays the WML progression on top of the baseline WML volume for (1) nomotensives (n=255), (2) controlled treated hypertensives (n=83), (3) uncontrolled treated hypertensives (n=155), and (4) uncontrolled untreated hypertensives (n=172). We found that the largest amount of WML progression was observed in the uncontrolled untreated hypertensives group. When taking into account the baseline WML load, the WML progression in this group was statistically significantly higher than in the uncontrolled treated hypertensives group with a difference (0.12 [0.00; 0.23] mL/y; P<0.05). Furthermore, we observed that across people with persistent normal blood pressure, controlled treated hypertension, uncontrolled treated hypertension, and uncontrolled untreated hypertension, there was a trend of increasing annual WML progression (P=0.01).

Figure 2.

Figure 2. Hypertension treatment and white matter lesion (WML) progression. This figure shows the mean WML progression in mL (95% confidence interval [CI]; black bars) on top of the baseline WML volume (grey bars) for 4 blood pressure categories. Categories were defined as follows based on their mean blood pressure and medication use in the 5 years before the first scan: (1) normotensives: study participants with normal mean blood pressure and receiving no antihypertensive medication during this period (n=255); (2) controlled treated hypertensives: study participants with normal mean blood pressure and receiving antihypertensive medication during this period (n=83); (3) uncontrolled treated hypertensives: study participants with hypertensive mean blood pressure and receiving antihypertensive medication during this period (n=155); and (4) uncontrolled untreated hypertensives: study participants with hypertensive mean blood pressure and receiving no antihypertensive medication during this period (n=172). Hypertensive mean blood pressure was defined as diastolic blood pressure ≥90 mm Hg or systolic blood pressure ≥140 mm Hg. A statistically significant difference in WML progression was observed between the uncontrolled untreated hypertensives group and the uncontrolled treated hypertensives group, after adjustment for age, sex, intracranial volume, time between scans, and the baseline WML load (P<0.05).

Discussion

In this longitudinal MRI study, we found that high systolic blood pressure and high diastolic blood pressure were associated with cerebral WML progression in the general population. Furthermore, we found that only the association with systolic blood pressure remained significant after taking into account the baseline WML load. Finally, we found that WML progression was less in controlled treated hypertensives compared with uncontrolled untreated hypertensives, despite a higher baseline WML load.

Major strengths of this study are the measurement of blood pressure before longitudinal MRI scanning, the quantitatively assessed WML progression, and the adjustment for baseline WML volume. This enabled us to address temporality of the relationships, assess WML volume more precisely, and evaluate whether any longitudinal associations could be explained by cross-sectional associations between blood pressure and WMLs. Previous studies have addressed 1 or 2 of these issues, but none of them addressed all. Another strength is that our population-based setting allows generalizability to a general community-dwelling setting.

A possible limitation of this study is that although the response rate was high, selective dropout could have occurred during the follow-up period. Nevertheless, we believe that if present, this would have led to an underestimation of the results found. Another consideration is that adjustment for baseline WML load is a form of overadjustment because the baseline WML load may be part of the causal chain. However, because the baseline WML load could also act as a confounder, the true effect estimate of the association between blood pressure and WML progression probably lies between the adjusted and unadjusted effect estimates. Another consideration is that we investigated the 5-year mean blood pressure and not the change in blood pressure over 5 years in relation to WML progression. However, blood pressure is highly variable over time and shows considerable regression to the mean.31 In our study, we therefore decided to use the average over 5 years instead of the change over 5 years. We also note that our study only had 2 measurements of WML volume, preventing us to assess nonlinear trends over time.

High blood pressure has consistently been associated with cross-sectionally measured WML burden413 and with longitudinally measured WML progression.14,15,1721 With respect to differences in the associations for systolic blood pressure versus diastolic blood pressure, studies have been inconsistent both for cross-sectionally measured WML burden and longitudinally measured WML progression. Some studies found associations for 1 of the 2, others for both. We found both systolic and diastolic blood pressures to be related to WML progression, but only systolic blood pressure to be related to WML progression after taking into account the already present WML load. Yet, this does not per se imply that systolic blood pressure is more important than diastolic blood pressure in WML progression because the distribution of systolic blood pressure is possibly more favorable to find associations. We also investigated whether pulse pressure would give additional information beyond the presence of hypertension. Pulse pressure has been associated with cross-sectionally measured WML load in several studies.6,32,33 However, we found that the association of pulse pressure with WML progression attenuated and lost statistical significance after taking into account the presence of hypertension. Perhaps the use of pulse wave velocity or other better indirect measures of arterial stiffness would be more sensitive to pick up an association with WML progression in future studies.

We found that per SD increase in systolic blood pressure, WML volume increased with 0.08 mL/y. For diastolic blood pressure, this was 0.09 mL/y. This corresponds to 23% and 25% of the mean annual WML progression in our population, respectively. Several studies found WML progression associated with cognitive decline.18,23,34,35 This implies that high blood pressure could affect cognition via WMLs.

Our finding that people with uncontrolled treated hypertension have significantly less WML progression than people with uncontrolled untreated hypertension implies that treatment of hypertension is important in slowing down WML progression. These results are in-line with a recent observational study that found treatment of people with high systolic blood pressure to be related to less WML progression.21 Recently, also randomized controlled trials have been investigating the effect of extra blood pressure–lowering treatment compared with standard treatment on WML progression in stroke patients.36,37 One trial found a protective effect of extra treatment, whereas the other did not find a difference. Yet, as participants in these trials were stroke patients, the question remains whether the WMLs in these patients are etiologically similar to the WML disease in the general population.

In conclusion, in this longitudinal MRI study, we found that high blood pressure precedes WML progression. Furthermore, we found that hypertension treatment is associated with less WML progression. Our study therefore further establishes high blood pressure as a strong risk factor for WMLs and implies that treatment of hypertension could lead to less WML progression in the general population. Further studies are needed to assess whether preventing WML development is also relevant to prevent cognitive decline and clinical disease.

Perspectives

The results of our study suggest that antihypertensive treatment would be beneficial in preventing WML progression in the general population. To further elucidate the relationship between blood pressure and WML, additional studies with >2 longitudinal measures of blood pressure and WMLs are desirable. Examination of interactions between blood pressure and other risk factors could possibly detect deleterious risk profiles. Including change in cognition as an outcome measure could throw light on the clinical implications of change in blood pressure and WML volume. Still, clinical trials are the best way to establish that blood pressure control is beneficial in the slowing or prevention of WML progression.

Footnotes

Continuing medical education (CME) credit is available for this article. Go to http://cme.ahajournals.org to take the quiz.

The online-only Data Supplement is available with this article at http://hyper.ahajournals.org/lookup/suppl/doi:10.1161/HYPERTENSIONAHA.111.00430/-/DC1.

Correspondence to M. Arfan Ikram, Department of Epidemiology, Erasmus MC University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands. E-mail

References

  • 1. Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis.BMJ. 2010; 341:c3666.CrossrefMedlineGoogle Scholar
  • 2. Xiong YY, Mok V. Age-related white matter changes.J Aging Res. 2011; 2011:617927.CrossrefMedlineGoogle Scholar
  • 3. Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review.Stroke. 1997; 28:652–659.LinkGoogle Scholar
  • 4. Fukuda H, Kitani M. Differences between treated and untreated hypertensive subjects in the extent of periventricular hyperintensities observed on brain MRI.Stroke. 1995; 26:1593–1597.LinkGoogle Scholar
  • 5. Longstreth WT, Manolio TA, Arnold A, Burke GL, Bryan N, Jungreis CA, Enright PL, O’Leary D, Fried L. Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: the Cardiovascular Health Study.Stroke. 1996; 27:1274–1282.LinkGoogle Scholar
  • 6. Liao D, Cooper L, Cai J, Toole J, Bryan N, Burke G, Shahar E, Nieto J, Mosley T, Heiss G. The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: the ARIC Study.Neuroepidemiology. 1997; 16:149–162.CrossrefMedlineGoogle Scholar
  • 7. Swan GE, DeCarli C, Miller BL, Reed T, Wolf PA, Jack LM, Carmelli D. Association of midlife blood pressure to late-life cognitive decline and brain morphology.Neurology. 1998; 51:986–993.CrossrefMedlineGoogle Scholar
  • 8. de Leeuw FE, de Groot JC, Oudkerk M, Witteman JC, Hofman A, van Gijn J, Breteler MM. A follow-up study of blood pressure and cerebral white matter lesions.Ann Neurol. 1999; 46:827–833.CrossrefMedlineGoogle Scholar
  • 9. Dufouil C, de Kersaint-Gilly A, Besançon V, Levy C, Auffray E, Brunnereau L, Alpérovitch A, Tzourio C. Longitudinal study of blood pressure and white matter hyperintensities: the EVA MRI Cohort.Neurology. 2001; 56:921–926.CrossrefMedlineGoogle Scholar
  • 10. van Dijk EJ, Breteler MM, Schmidt R, Berger K, Nilsson LG, Oudkerk M, Pajak A, Sans S, de Ridder M, Dufouil C, Fuhrer R, Giampaoli S, Launer LJ, Hofman A; CASCADE Consortium. The association between blood pressure, hypertension, and cerebral white matter lesions: cardiovascular determinants of dementia study.Hypertension. 2004; 44:625–630.LinkGoogle Scholar
  • 11. Shrestha I, Takahashi T, Nomura E, Ohtsuki T, Ohshita T, Ueno H, Kohriyama T, Matsumoto M. Association between central systolic blood pressure, white matter lesions in cerebral MRI and carotid atherosclerosis.Hypertens Res. 2009; 32:869–874.CrossrefMedlineGoogle Scholar
  • 12. Vuorinen M, Solomon A, Rovio S, Nieminen L, Kåreholt I, Tuomilehto J, Soininen H, Kivipelto M. Changes in vascular risk factors from midlife to late life and white matter lesions: a 20-year follow-up study.Dement Geriatr Cogn Disord. 2011; 31:119–125.CrossrefMedlineGoogle Scholar
  • 13. Carmelli D, Swan GE, Reed T, Wolf PA, Miller BL, DeCarli C. Midlife cardiovascular risk factors and brain morphology in identical older male twins.Neurology. 1999; 52:1119–1124.CrossrefMedlineGoogle Scholar
  • 14. Veldink JH, Scheltens P, Jonker C, Launer LJ. Progression of cerebral white matter hyperintensities on MRI is related to diastolic blood pressure.Neurology. 1998; 51:319–320.CrossrefMedlineGoogle Scholar
  • 15. Schmidt R, Enzinger C, Ropele S, Schmidt H, Fazekas F; Austrian Stroke Prevention Study. Progression of cerebral white matter lesions: 6-year results of the Austrian Stroke Prevention Study.Lancet. 2003; 361:2046–2048.CrossrefMedlineGoogle Scholar
  • 16. Sachdev P, Wen W, Chen X, Brodaty H. Progression of white matter hyperintensities in elderly individuals over 3 years.Neurology. 2007; 68:214–222.CrossrefMedlineGoogle Scholar
  • 17. Firbank MJ, Wiseman RM, Burton EJ, Saxby BK, O’Brien JT, Ford GA. Brain atrophy and white matter hyperintensity change in older adults and relationship to blood pressure. Brain atrophy, WMH change and blood pressure.J Neurol. 2007; 254:713–721.CrossrefMedlineGoogle Scholar
  • 18. van Dijk EJ, Prins ND, Vrooman HA, Hofman A, Koudstaal PJ, Breteler MM. Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study.Stroke. 2008; 39:2712–2719.LinkGoogle Scholar
  • 19. Gottesman RF, Coresh J, Catellier DJ, Sharrett AR, Rose KM, Coker LH, Shibata DK, Knopman DS, Jack CR, Mosley TH. Blood pressure and white-matter disease progression in a biethnic cohort: Atherosclerosis Risk in Communities (ARIC) study.Stroke. 2010; 41:3–8.LinkGoogle Scholar
  • 20. Debette S, Seshadri S, Beiser A, Au R, Himali JJ, Palumbo C, Wolf PA, DeCarli C. Midlife vascular risk factor exposure accelerates structural brain aging and cognitive decline.Neurology. 2011; 77:461–468.CrossrefMedlineGoogle Scholar
  • 21. 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; 123:266–273.LinkGoogle Scholar
  • 22. Gouw AA, van der Flier WM, Fazekas F, van Straaten EC, Pantoni L, Poggesi A, Inzitari D, Erkinjuntti T, Wahlund LO, Waldemar G, Schmidt R, Scheltens P, Barkhof F; LADIS Study Group. Progression of white matter hyperintensities and incidence of new lacunes over a 3-year period: the Leukoaraiosis and Disability study.Stroke. 2008; 39:1414–1420.LinkGoogle Scholar
  • 23. White WB, Wolfson L, Wakefield DB, Hall CB, Campbell P, Moscufo N, Schmidt J, Kaplan RF, Pearlson G, Guttmann CR. Average daily blood pressure, not office blood pressure, is associated with progression of cerebrovascular disease and cognitive decline in older people.Circulation. 2011; 124:2312–2319.LinkGoogle Scholar
  • 24. Hofman A, van Duijn CM, Franco OH, Ikram MA, Janssen HL, Klaver CC, Kuipers EJ, Nijsten TE, Stricker BH, Tiemeier H, Uitterlinden AG, Vernooij MW, Witteman JC. The Rotterdam Study: 2012 objectives and design update.Eur J Epidemiol. 2011; 26:657–686.CrossrefMedlineGoogle Scholar
  • 25. Ikram MA, van der Lugt A, Niessen WJ, Krestin GP, Koudstaal PJ, Hofman A, Breteler MM, Vernooij MW. The Rotterdam Scan Study: design and update up to 2012.Eur J Epidemiol. 2011; 26:811–824.CrossrefMedlineGoogle Scholar
  • 26. Vrooman HA, Cocosco CA, van der Lijn F, Stokking R, Ikram MA, Vernooij MW, Breteler MM, Niessen WJ. Multi-spectral brain tissue segmentation using automatically trained k-nearest-neighbor classification.Neuroimage. 2007; 37:71–81.CrossrefMedlineGoogle Scholar
  • 27. de Boer R, Vrooman HA, van der Lijn F, Vernooij MW, Ikram MA, van der Lugt A, Breteler MM, Niessen WJ. White matter lesion extension to automatic brain tissue segmentation on MRI.Neuroimage. 2009; 45:1151–1161.CrossrefMedlineGoogle Scholar
  • 28. Vernooij MW, Ikram MA, Tanghe HL, Vincent AJ, Hofman A, Krestin GP, Niessen WJ, Breteler MM, van der Lugt A. Incidental findings on brain MRI in the general population.N Engl J Med. 2007; 357:1821–1828.CrossrefMedlineGoogle Scholar
  • 29. Leening MJ, Kavousi M, Heeringa J, van Rooij FJ, Verkroost-van Heemst J, Deckers JW, Mattace-Raso FU, Ziere G, Hofman A, Stricker BH, Witteman JC. Methods of data collection and definitions of cardiac outcomes in the Rotterdam Study.Eur J Epidemiol. 2012; 27:173–185.CrossrefMedlineGoogle Scholar
  • 30. Slooter AJ, Cruts M, Kalmijn S, Hofman A, Breteler MM, Van Broeckhoven C, van Duijn CM. Risk estimates of dementia by apolipoprotein E genotypes from a population-based incidence study: the Rotterdam Study.Arch Neurol. 1998; 55:964–968.CrossrefMedlineGoogle Scholar
  • 31. Gordon T, Sorlie P, Kannel WB. Problems in the assessment of blood pressure: the Framingham Study.Int J Epidemiol. 1976; 5:327–334.CrossrefMedlineGoogle Scholar
  • 32. Kim CK, Lee SH, Kim BJ, Ryu WS, Yoon BW. Age-independent association of pulse pressure with cerebral white matter lesions in asymptomatic elderly individuals.J Hypertens. 2011; 29:325–329.CrossrefMedlineGoogle Scholar
  • 33. Henskens LH, Kroon AA, van Oostenbrugge RJ, Gronenschild EH, Fuss-Lejeune MM, Hofman PA, Lodder J, de Leeuw PW. Increased aortic pulse wave velocity is associated with silent cerebral small-vessel disease in hypertensive patients.Hypertension. 2008; 52:1120–1126.LinkGoogle Scholar
  • 34. Schmidt R, Ropele S, Enzinger C, Petrovic K, Smith S, Schmidt H, Matthews PM, Fazekas F. White matter lesion progression, brain atrophy, and cognitive decline: the Austrian Stroke Prevention Study.Ann Neurol. 2005; 58:610–616.CrossrefMedlineGoogle Scholar
  • 35. Longstreth WT, Arnold AM, Beauchamp NJ, Manolio TA, Lefkowitz D, Jungreis C, Hirsch CH, O’Leary DH, Furberg CD. Incidence, manifestations, and predictors of worsening white matter on serial cranial magnetic resonance imaging in the elderly: the Cardiovascular Health Study.Stroke. 2005; 36:56–61.LinkGoogle Scholar
  • 36. Dufouil C, Chalmers J, Coskun O, Besançon V, Bousser MG, Guillon P, MacMahon S, Mazoyer B, Neal B, Woodward M, Tzourio-Mazoyer N, Tzourio C; PROGRESS MRI Substudy Investigators. Effects of blood pressure lowering on cerebral white matter hyperintensities in patients with stroke: the PROGRESS (Perindopril Protection Against Recurrent Stroke Study) Magnetic Resonance Imaging Substudy.Circulation. 2005; 112:1644–1650.LinkGoogle Scholar
  • 37. Weber R, Weimar C, Blatchford J, Hermansson K, Wanke I, Möller-Hartmann C, Gizewski ER, Forsting M, Demchuk AM, Sacco RL, Saver JL, Warach S, Diener HC, Diehl A; PRoFESS Imaging Substudy Group. Telmisartan on top of antihypertensive treatment does not prevent progression of cerebral white matter lesions in the prevention regimen for effectively avoiding second strokes (PRoFESS) MRI substudy.Stroke. 2012; 43:2336–2342.LinkGoogle Scholar

Novelty and Significance

What Is New?

  • Our study provides strong and much needed confirmatory evidence that high blood pressure is a risk factor for progression of cerebral white matter lesion in the aging general population.

What Is Relevant?

  • Our study further adds to the evidence, suggesting that treatment of hypertension may decrease the risk of white matter lesions.

Summary

In this longitudinal MRI study, we found that high blood pressure precedes cerebral white matter lesion progression and that treatment of hypertension is associated with less progression.

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