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
Abstract
Background—
Blood pressure (BP) is recognized as a major risk factor for white matter lesions (WMLs), but longitudinal data are scarce, and there is insufficient evidence for the benefit of antihypertensive therapy on WML progression. We studied the relationship between BP change and WML volume progression over time in a sample of 1319 elderly individuals who had 2 cerebral magnetic resonance imaging examinations 4 years apart. We also examined the impact of antihypertensive treatment on WML progression.
Methods and Results—
Subjects were participants from the Three-City (3C)–Dijon Magnetic Resonance Imaging Study, a prospective population-based cohort of elderly ≥65 years of age. WML volumes and their progression were estimated with the use of a fully automatic procedure. We performed ANCOVA models first to assess the association between BP change and WML progression and second to estimate the relation between antihypertensive treatment and WML load progression. Baseline and change in BP were significant predictors of higher WML progression over time after controlling for potential confounders. Among subjects with high SBP (≥160 mm Hg) at baseline not treated by antihypertensive medication, antihypertensive treatment started within 2 years was related to a smaller increase in WML volume at a 4-year follow-up (0.24 cm3; SE=0.44 cm3) than no hypertensive treatment (1.60 cm3; SE=0.26 cm3; P=0.0008) on multivariable modeling.
Conclusions—
Our findings reinforce the hypothesis that hypertension is a strong predictor of WML and that adequate treatment may reduce the course of WML progression. Because WMLs are linked to both dementia and stroke risks, these results could have implications for future preventive trials.
White matter lesions (WMLs) are frequently observed on brain magnetic resonance imaging (MRI) of the elderly and are associated with increased risks of developing depression, stroke, and dementia.1,2–5 The exact physiopathology of these lesions is not yet fully understood, but they are considered to reflect ischemic small-vessel disease, and their associations with vascular factors, especially hypertension have been reported.3,6–8
Clinical Perspective on p 273
Overall, cross-sectional studies have provided consistent evidence that systolic (SBP) and diastolic blood pressure (DBP) levels are associated with WML severity.9–12 Most of these studies also reported that among individuals taking antihypertensive treatment, those with controlled BP had less severe WML than those with uncontrolled BP, suggesting that antihypertensive drugs could influence and, more important, slow the progression of WMLs over time.13–15 However, the cross-sectional nature of the data supporting these assertions renders them highly speculative.
Until now, only 1 placebo-controlled trial has shown an effect of antihypertensive treatment on the progression of WMLs.16 However, the sample size was small (192 patients), and the participants included all had a history of stroke. Longitudinal reports on the relationship between BP change, antihypertensive treatment, and WML progression are scarce.17
In the Three-City (3C)–Dijon MRI Study, a large prospective population-based cohort of elderly ≥65 years of age who had 2 MRI examinations, we investigated how BP levels and WML volumes are related cross-sectionally and longitudinally over a 4-year follow-up. We also examined how treatment of hypertension could affect WML volume progression.
Methods
The 3C Study is a multicenter population-based cohort study conducted in 3 French cities (Bordeaux, Dijon, and Montpellier) designed to estimate the risk of dementia and cognitive impairment attributable to vascular factors. The protocol was approved by the ethics committee of the University Hospital of Kremlin-Bicêtre. The study design has been published elsewhere.18 In brief, between March 1999 and March 2001, 9294 noninstitutionalized individuals ≥65 years of age selected from the electoral rolls of the 3 cities agreed to participate in this project. Each participant signed an informed consent and was followed up every 2 years for 4 years. This article reports only on data from Dijon participants who had 2 cerebral MRI examinations 4 years apart.
Data Collected
At each study wave, a trained psychologist collected data at the participant's home during a face-to-face interview using a standardized questionnaire. Information about demographic background, occupation, medical history, and personal habits was collected.
The interviewers recorded all medications used during the preceding month. Participants were asked to show medical prescriptions and drug packages. Drug names were coded according to the Anatomic Therapeutic Chemical classification of the World Health Organization. Cognitive performances were assessed with a battery of neuropsychological tests, including Mini-Mental State Examination,19 Isaac Set Test, Trail Making Test, and Benton Visual Retention Test.18
BP Measurements
Measures of SBP and DBP were performed at each study wave according to a precise protocol: 3 measures on the right arm after 2 minutes of rest in the sitting position. To obtain a more robust measure of BP exposure, baseline BP was considered to be the mean of all BP measurements at inclusion and the 2-year follow-up examination.
High BP was defined as baseline SBP ≥140 mm Hg or baseline DBP ≥90 mm Hg. The presence of hypertension at baseline was defined as high BP or the reported use of antihypertensive medication at baseline.
To take into account the use of antihypertensive drugs and level of BP simultaneously, we considered 4 groups of subjects: (1) those with no hypertension (normotensive), (2) those with high BP taking no antihypertensive drugs (high BP, untreated), (3) those without high BP and taking antihypertensive drugs (normotensive, treated), and (4) those with high BP taking hypertensive drugs (high BP, treated). Change in BP levels was calculated as the BP difference between the 4-year and baseline measurements.
MRI Scans
At baseline and the 4-year follow-up, MRI acquisition was performed according to the same protocol with a 1.5-T Magnetom (Siemens, Erlangen, Germany) as described elsewhere.20 Fully automatic image processing software was developed to detect, measure, and localize WMLs.20,21 Among the various tissue segmentation techniques available, we selected a multispectral approach that uses different MRI sequences. Indeed, because of the heterogeneity of gray matter signals on the T2 images, the white matter mask derived with a 3-class-only segmentation was suboptimal for accurate WML detection. Although such inhomogeneities have negligible impact on calculations of the bias field correction, they could be at the origin of false-positive WMLs on the T2 images. Therefore, T1, T2, and pulsed Doppler bias-corrected volumes were segmented into 7 classes using the same multispectral algorithm: (1) cerebrospinal fluid, (2) gray matter, (3) caudate nucleus, (4) lenticular nucleus, (5) thalamus, (6) white matter, and (7) WML. The MRI analysis contained 3 major steps: preprocessing, including registration, nonbrain tissue removal, and bias field correction; detection of white matter hyperintensities in T2 images, including removal of false positives; and postprocessing, including generation of WML probability maps at the individual and sample levels, morphometry, and localization and classification of WML. Morphological parameters were computed for each detected WML, including center of mass coordinates, Euclidean distance to the ventricular system, and principal axis dimensions. When its distance to the ventricular system was mm, a WML was labeled as periventricular WML; otherwise, it was labeled as deep WML. Periventricular and deep WML volumes were calculated by summing the volumes of all the lesions detected in each area. WML volumes were studied as continuous variables. Progression of WML volumes over time was calculated as the difference in WML volumes between the 4-year and baseline examinations. A neurologist (Y.Z.) assessed the presence of silent brain infarcts (SBIs) visually with a standardized assessment grid. SBIs were defined as focal hyperintensities on T2-weighted images ≥3 mm in size, with corresponding prominent hypointensities on T1-weighted images, with the same density as the cerebrospinal fluid.
Using voxel-based morphometry techniques, we computed total intracranial volume as the sum of the gray matter, white matter, and cerebrospinal fluid volumes. Because WML volumes are highly correlated with brain size, total intracranial volume was systematically adjusted for in all models.
Covariates
Covariates included demographic and health variables collected at study entry. Education level was defined in 4 categories ranging from primary certificate level (low) to baccalaureate or university degree (high). Subjects reporting already-diagnosed diabetes mellitus, having a fasting blood glucose ≥7 mmol/L, or reporting use of diabetes medication were categorized as diabetics. Subjects were classified as having a self-reported history of cardiovascular disease if they reported a history of stroke or myocardial infarction, coronary bypass or angioplasty, or vascular surgery for lower-limb arteritis.
From baseline and 4-year follow-up data, composite cognitive scores were computed for each individual as the sum of each of the 4 cognitive test scores standardized (Mini-Mental State Examination, Trail Making Test B, Isaac Set Test, and Benton Visual Retention Test). Global cognitive change over 4 years was calculated as the difference between composite cognitive scores at the 4-year follow-up and at baseline.
Analytic Sample
Figure 1 illustrates the sample selection for the present analysis. From the original 4931 subjects enrolled in Dijon, a cerebral MRI examination was proposed to those 65 to 80 years of age who enrolled between June 1999 and September 2000 (n=2763). Although 2285 subjects (82.7%) agreed to have a baseline MRI, 1801 examinations were performed and valid for further imaging analysis processing. At the 4-year follow-up, 1332 subjects had a valid follow-up MRI; of these, a further 13 individuals were excluded because of missing BP measurements, leaving an analytical sample of 1319 individuals.

The 482 individuals excluded from the present analyses were, at study entry, on average older, had lower cognitive performances at Mini-Mental State Examination, had higher baseline WML volumes, but did not differ in BP levels (Table 1).
Baseline Characteristics | Valid MRI Follow-Up Scan | ||
---|---|---|---|
No (n=482) | Yes (n=1319) | P* | |
Female gender, % | 56.9 | 61.6 | 0.07 |
Mean (SE) age, y | 73.5 (0.2) | 72.0 (0.1) | <0.0001 |
Low education level, %† | 64.3 | 63.4 | 0.71 |
Mean (SE) SBP, mm Hg | 144.3 (1.0) | 143.7 (0.5) | 0.59 |
Mean (SE) DBP, mm Hg | 82.2 (0.5) | 82.0 (0.3) | 0.70 |
History of cardiovascular disease, %‡ | 8.3 | 5.9 | 0.06 |
Diabetes mellitus, %§ | 8.5 | 8.4 | 0.93 |
Mean (SE) WML volume, cm3 | 6.1 (0.2) | 5.4 (0.1) | 0.004 |
*
Computed from the χ2 test for categorical variables or the Student t test for continuous variables.
†
Education level lower than or equal to primary certificate level.
‡
Self-reported history of stroke or myocardial infarction, coronary bypass or angioplasty, or vascular surgery for lower-limb arteritis.
§
Reporting already-diagnosed diabetes mellitus, having fasting blood glucose ≥7 mmol/L, or reporting use of diabetes medication.
Statistical Analysis
To identify the factors associated cross-sectionally with WML load, we used ANCOVA models adjusted for age, gender, and total intracranial volume. ANCOVA models were performed to assess how baseline WML load and change in WML during follow-up were associated with baseline BP levels, antihypertensive treatment use, and their combination. Specific models by type of WML (periventricular WML versus deep WML volumes) were also computed.
The numbers for each type of antihypertensive medication (diuretics, β-blockers, angiotensin-converting enzyme inhibitors, calcium channel blockers, or others) did not provide enough statistical power to undertake analyses by type of antihypertensive drug. Thus, we chose to provide global findings.
The longitudinal association of change in BP or global cognitive performances with WML progression over 4-year follow-up was assessed with ANCOVA models. To further investigate the potential impact of antihypertensive treatment on WML progression, we restricted the analysis to the subsample of subjects not treated at entry. ANCOVA models were then computed to assess the relationship between antihypertensive treatment initiation after study entry and WML change over time. By adding the cross-product to the model, we assessed the interaction between baseline SBP level and antihypertensive treatment initiation on WML volume progression.
A search for potential interaction with gender or age was performed, but none was significant. All analyses modeling total WML volume progression as the outcome were controlled for age, gender, delay between the 2 MRI examinations, and total intracranial volume. Data analysis was completed with SAS (release 9.1; SAS Statistical Institute, Cary, NC). The type 1 error used for statistical significance was 0.05 for all analyses.
Results
At baseline, the mean age of the analytic sample (n=1319) was 72.4 years (SD=4.1 years), 62% of participants were women, and 75% had hypertension. Mean baseline WML volume was 5.31 cm3 (SD=4.56 cm3): 3.86 cm3 (SD=3.82 cm3) in the periventricular area and 1.45 cm3 (SD=1.23 cm3) in the deep area. Mean Mini-Mental State Examination score was 27.78 (SD=1.72).
Table 2 shows cross-sectional analyses of factors associated with WML volumes. WML load was significantly higher in older subjects. Hypertensive subjects, diabetics, or those with history of cardiovascular disease also had on average significantly higher WML load at baseline.
n | Mean (SE) WML Volume, cm3 | P* | |
---|---|---|---|
Gender | 0.22 | ||
Male | 503 | 5.50 (0.20) | |
Female | 816 | 5.17 (0.16) | |
Age, y | <0.0001 | ||
<70 | 441 | 4.59 (0.22) | |
[70–75] | 489 | 5.34 (0.19) | |
≥75 | 389 | 6.23 (0.26) | |
Education level† | 0.75 | ||
Low | 204 | 5.47 (0.32) | |
Medium-low | 584 | 5.35 (0.19) | |
Medium-high | 250 | 5.09 (0.28) | |
High | 280 | 5.47 (0.27) | |
Hypertension‡ | 0.002 | ||
No | 402 | 4.74 (0.23) | |
Yes | 917 | 5.60 (0.15) | |
Antihypertensive treatment intake and BP§ level | 0.0009 | ||
None treated, normal BP | 402 | 4.72 (0.23) | |
None treated, high BP | 364 | 5.25 (0.23) | |
Treated, normal BP | 187 | 5.38 (0.33) | |
Treated, high BP | 366 | 6.06 (0.23) | |
Diabetes mellitus‖ | 0.004 | ||
No | 1202 | 5.22 (0.13) | |
Yes | 110 | 6.52 (0.42) | |
History of cardiovascular disease¶ | 0.03 | ||
No | 1244 | 5.27 (0.13) | |
Yes | 75 | 6.44 (0.52) |
*
ANCOVA model adjusted for age, gender, and total intracranial volume.
†
Low: primary certificate level; medium-low: technical or professional degree; medium-high: baccalaureate; high: university degree.
‡
SBP ≥140 mm Hg and/or DBP ≥90 mm Hg or antihypertensive treatment.
§
BP is high if SBP is ≥140 mm Hg or DBP is ≥90 mm Hg.
∥
Reporting already-diagnosed diabetes mellitus, having fasting blood glucose ≥7 mmol/L, or reporting use of diabetes medication.
¶
Self-reported history of stroke or myocardial infarction, coronary bypass or angioplasty, or vascular surgery for lower-limb arteritis.
Over the 4 years of follow-up, the mean increase in total WML volume was 1.07 cm3 (SD=2.76 cm3): 1.00 cm3 (SD=2.49 cm3) in the periventricular area and 0.07 cm3 (SD=0.69 cm3) in the deep area.
The cross-sectional analyses of the associations between BP level and WML volumes (Table 3) showed a significant positive linear relationship between WML and DBP only. Hypertensive individuals and those taking antihypertensive treatment also had a significantly higher total WML volume at study entry (Table 3). These associations were consistent regardless of the WML volume type (periventricular or deep).
WML Volume, cm3 | Periventricular WML Volume, cm3 | Deep WML Volume, cm3 | ||||
---|---|---|---|---|---|---|
β (SE) | P* | β (SE) | P* | β (SE) | P* | |
SBP (per 5-mm Hg increase) | 0.06 (0.03) | 0.08 | 0.05 (0.03) | 0.11 | 0.012 (0.009) | 0.16 |
DBP (per 5-mm Hg increase) | 0.16 (0.07) | 0.01 | 0.11 (0.06) | 0.04 | 0.049 (0.017) | 0.004 |
Hypertension (yes vs no) | 0.86 (0.27) | 0.002 | 0.65 (0.23) | 0.005 | 0.21 (0.07) | 0.004 |
Antihypertensive treatment intake (yes vs no) | 0.85 (0.25) | 0.0007 | 0.63 (0.21) | 0.003 | 0.23 (0.07) | 0.0007 |
Antihypertensive treatment intake and BP† level | ||||||
None treated, normal BP | Reference | Reference | Reference | |||
None treated, high BP | 0.49 (0.33) | 0.13 | 0.39 (0.27) | 0.15 | 0.10 (0.09) | 0.27 |
Treated, normal BP | 0.73 (0.33) | 0.03 | 0.48 (0.27) | 0.07 | 0.25 (0.11) | 0.02 |
Treated, high BP | 1.27 (0.31) | <0.001 | 1.00 (0.27) | 0.0002 | 0.28 (0.09) | 0.002 |
P for linear trend | <0.001 | 0.0003 | 0.0003 |
*
ANCOVA model adjusted for age, gender, and total intracranial volume.
†
BP is high if SBP is ≥140 mm Hg or DBP is ≥90 mm Hg.
The relationships between BP level, hypertension, antihypertensive drug intake at baseline, and WML progression over the 4 years of follow-up are presented in Table 4. These multivariable analyses revealed that baseline DBP is a significant predictor of WML progression: The higher the baseline DBP levels are, the higher the WML volumes increase over follow-up. These relationships were seen only in studies of the evolution of total or periventricular WML volumes. A nonsignificant trend between higher baseline SBP and higher WML volume progression (total, periventricular, and deep WMLs) was observed. We also observed a significant association between antihypertensive intake at baseline and WML progression over time (P=0.05).
WML Volume Progression, cm3 | Periventricular WML Volume Progression, cm3 | Deep WML Volume Progression, cm3 | ||||
---|---|---|---|---|---|---|
β (SE) | P* | β (SE) | P* | β (SE) | P* | |
SBP (per 5-mm Hg increase) | 0.04 (0.02) | 0.06 | 0.03 (0.02) | 0.13 | 0.009 (0.005) | 0.07 |
DBP (per 5-mm Hg increase) | 0.09 (0.04) | 0.01 | 0.08 (0.03) | 0.02 | 0.010 (0.009) | 0.27 |
Hypertension (yes vs no) | 0.33 (0.16) | 0.04 | 0.25 (0.15) | 0.08 | 0.08 (0.04) | 0.07 |
Antihypertensive treatment intake (yes vs no) | 0.29 (0.15) | 0.05 | 0.24 (0.13) | 0.07 | 0.005 (0.04) | 0.23 |
Antihypertensive treatment intake and BP level | ||||||
None treated, normal BP | Reference | Reference | Reference | |||
None treated, high BP | 0.31 (0.18) | 0.24 (0.16) | 0.15 | 0.07 (0.05) | 0.14 | |
Treated, normal BP | 0.29 (0.22) | 0.08 | 0.21 (0.20) | 0.29 | 0.08 (0.06) | 0.17 |
Treated, high BP | 0.54 (0.20) | 0.18 | 0.46 (0.19) | 0.01 | 0.08 (0.05) | 0.09 |
P for linear trend | 0.01 | 0.008 | 0.02 | 0.12 |
*
ANCOVA model adjusted for age, gender, and total intracranial volume.
The relationship between change in BP and change in WML is consistent with previous results (Table 5): The higher the BP levels (both SBP and DBP) increase over time, the more severe the WML volume (total and periventricular only) progression is. Similarly, in multivariable models adjusted for age, gender, education level, and follow-up length, we observed a significant correlation between increase in WML volumes over 4 years and worsening of global cognitive performances over the same period (β=−0.26; SE=0.08; P<0.001).
WML Volume, cm3 | Periventricular WML Volume, cm3 | Deep WML Volume, cm3 | ||||
---|---|---|---|---|---|---|
β (SE) | P* | β (SE) | P* | β (SE) | P* | |
SBP change (per 5-mm Hg increase) | 0.05 (0.02) | 0.01 | 0.05 (0.02) | 0.008 | 0.001 (0.005) | 0.80 |
DBP change (per-5 mm Hg increase) | 0.12 (0.04) | 0.002 | 0.11 (0.03) | 0.002 | 0.014 (0.009) | 0.14 |
*
ANCOVA model adjusted for age, gender, and total intracranial volume.
The interaction between baseline high BP level and antihypertensive drug intake in relation to WML load at baseline and WML progression over 4 years is illustrated in Figure 2. This figure shows that treated but uncontrolled subjects are those on average with a higher WML load at baseline (P<0.001) and higher WML progression over time (P<0.01). Subjects not treated but with high BP and those treated but with controlled BP had similar baseline WML load and WML progression; they also had an intermediate WML load level between nonhypertensive and treated but uncontrolled individuals.

Finally, we explored the role of antihypertensive treatment initiation on WML progression (Table 6). In the subsample of subjects not treated at baseline (n=766), those who had a treatment initiated between baseline and the 2-year follow-up (n=103) had a 0.30-cm3 reduction in WML volume progression over the 4-year follow-up compared with those never treated, but the difference was not significant (P=0.21). However, the analysis revealed a significant interaction between baseline SBP levels and antihypertensive treatment initiation on WML volume progression (P=0.03). The stratified analyses displayed in Table 6 show that antihypertensive treatment initiation seems to significantly influence the course of WML evolution only in subjects with the higher baseline SBP level (≥160 mm Hg; n=113); the progression of WML volumes was on average reduced by 85% in subjects who started antihypertensive treatment compared with those who did not (mean WML progression, 0.24 versus 1.60 cm3; P=0.008).
n | WML Volume Progression, cm3 | ||
---|---|---|---|
Mean (SE) | P* | ||
Treatment status at follow-up | 0.21 | ||
Never treated | 663 | 0.90 (0.09) | |
Treated at 2 y | 103 | 0.60 (0.23) | |
SBP at baseline | |||
<140 mm Hg | 0.84 | ||
Never treated | 373 | 0.69 (0.13) | |
Treated at 2 y | 38 | 0.77 (0.38) | |
140–160 mm Hg | 0.52 | ||
Never treated | 206 | 0.97 (0.16) | |
Treated at 2 y | 36 | 0.69 (0.39) | |
≥160 mm Hg | 0.008 | ||
Never treated | 84 | 1.60 (0.26) | |
Treated at 2 y | 29 | 0.24 (0.44) |
*
ANCOVA model adjusted for age, gender, delay between the 2 MRI examinations, and total intracranial volume.
Discussion
In a large population-based cohort of 1319 elderly, we showed that BP level at baseline and changes in BP over a 4-year follow-up are strong predictors of WML volume progression independently of potentials confounders. These relationships were observed mainly for total and periventricular WML.
Data also suggested that appropriate antihypertensive treatment could be efficient to slow WML progression. Indeed, on one hand, treated controlled hypertensive individuals tended to have smaller WML load compared with treated but uncontrolled hypertensive individuals; on the other hand, among subjects not treated at baseline, antihypertensive treatment initiation during follow-up was associated with a reduced WML progression, the more so when subjects had higher SBP level at baseline.
Several cross-sectional studies have reported that BP-controlled treated subjects had decreased risk of WML compared with uncontrolled hypertensive subjects.10,13,22 In the Epidemiology of Vascular Aging MRI cohort, including 845 elderly patients who had an MRI examination 4 years after study entry, the authors found that hypertension was a major risk factor of WMLs and that subjects taking antihypertensive drugs whose BP was controlled had a significantly reduced odds of having severe WMLs.13
Other studies have investigated the relationship between duration of hypertension and WML severity assessed on 1 occasion.10,22 In the Rotterdam Scan Study, which included 1077 subjects 60 to 90 years of age, current hypertension and hypertension established 5 to 20 years before MRI examination were both associated with the presence of WMLs on MRI.10 Similar findings were observed in the Clopidogrel After Surgery for Coronary Artery Disease (CASCADE) study.22 None of the above reports could disentangle the temporality of the relationships. Two studies have made such an attempt.
In the Rotterdam Scan study, 2 MRI examinations 3 years apart in 668 people were performed, and an association between high BP and higher WML progression (categorized as no, minor, or marked) was reported. Given the absences of volumetric estimation of WML change, of repeated measures of BP level over the follow-up, and of consideration of antihypertensive treatment intake effect, the interpretation of these findings remains limited.
The Atherosclerosis Risk in Communities (ARIC) Study investigated the associations between BP measurements assessed at different time points and WML progression over 10 years of follow-up and concluded that cumulative mean SBP was a stronger predictor of WML progression than SBP from individual points. However, it should be noted that volumetric estimation of WML progression was not measured but created from a prediction equation model of baseline WML grade.17
The 3C-Dijon MRI Study is, to the best of our knowledge, the first population-based study in the elderly exploring the relationships between BP evolution, antihypertensive treatment, and WML progression over time. Our results reinforce findings from the MRI substudy of the Perindopril Protection Against Recurrent Stroke Study (PROGRESS).16 Indeed, 192 patients with stroke history had 2 MRI examinations at 3-year intervals to assess the effect of antihypertensive treatment on WML progression. Overall, the risk of incident WML was reduced by 43% in the active treatment arm compared with the placebo arm. The greatest difference was observed in the group of patients with severe WML on the first MRI scan. Results showed, for the first time, that lowering BP could stop or reduce WML progression. Nevertheless, the study had weaknesses in that it included highly selected subjects and results were based on a small sample, limiting the generalization.
The 3C-Dijon Study is the first longitudinal population-based study demonstrating a favorable impact of antihypertensive treatment on WML progression and showing the positive association between BP increase and WML load worsening. These results provide further evidence for a causal link between hypertension and WML.
Several mechanisms have been suggested to explain how hypertension could be linked to WML. A possible explanation is that longstanding hypertension leads to structural changes in the cerebral small vessels such as hyalinization, tortuosity, elongation, and narrowing. These changes lead to a decrease in blood flow and subsequently ischemia.10,23 Another potential mechanism is that hypertension could cause dysfunction in the blood-brain barrier, responsible for vascular permeability, and may cause lesions in white matter by cerebral edema, activation of astrocytes, destructive enzymes, or others toxins that pass through the damaged vessel wall.22,24
The 3C-Dijon MRI Study has some weaknesses. The sample retained for the analyses is selected. Compared with the whole cohort, subjects who did not have MRI examination were on average older and in poorer health. This potential selection bias is likely to be conservative, leading to an underestimation of the strengths of the true relationships. Despite selection, it should noted that the mean WML volumes observed at baseline and follow-up are close to those reported in the literature.25,26 Selection bias in longitudinal analyses could also occur because subjects who did not have repeated MRI had on average higher WML volumes at baseline. To correct for this potential bias, we repeated the analysis on change in WML volumes with inverse probability weights27 in models to account for selective MRI follow-up, and the results were unchanged.
To assess the robustness of our findings, we performed other sensitivity analyses. First, it should be noted that the software used to detect WML does not distinguish SBIs. SBIs were therefore rated visually. We have excluded subjects with SBIs at baseline (n=117) and those with incident SBIs (n=56), and the results were unchanged (results not shown). Second, to be parsimonious in the number of covariates in multivariable analyses, we controlled only for age, gender, and total intracranial volume when modeling BP in relation to WML. However, further adjustments for vascular factors such as diabetes mellitus, history of cardiovascular disease, hypercholesterolemia, and smoking habits did not modify the findings (results not shown). Similarly, in all the analyses of change in WML volumes, adjustment or no adjustment for baseline WML volume led to similar findings. Finally because WML and hypertension are related to dementia and stroke, we excluded prevalent and incident cases of these 2 pathologies (n=49), and the results are unchanged.
In our data, the strengths of the associations are overall stronger with periventricular WML volume progression than with deep WML volume. To the best of our knowledge, there is no underlying physiological mechanism to support this difference. The most likely explanation is a lack of statistical power because progression in WML volumes over the 4-year follow-up is on average much smaller in the deep area than in the periventricular area.
The strengths of our study include the large sample size, the population-based setting, and the repeated assessments of both BP and WML load over follow-up. Another strength of our data is the fully automated longitudinal quantification of WML volume with a validated and reproducible algorithm.28
This is the first population-based study showing a longitudinal relationship between change in BP and change in WML volume over a 4-year follow-up. Antihypertensive treatment seems efficient for slowing the course of WML progression. In parallel, faster progression in WML volumes was associated with a stronger decrease in global cognitive performances over the 4-year follow-up. However, we ought to be cautious when interpreting these findings because of the observational nature of the data reported.
Beyond these results and because WMLs have been associated with stroke and dementia in the elderly,2,4,5 these findings could offer potential possibilities for the prevention of dementia or stroke. Two recent reviews29,30 underline that, in light of current knowledge, WMLs could be used as an intermediate marker for the identification of new risk factors for dementia or stroke and as surrogate markers to assess treatment efficiency. On the basis of the literature and the reported findings, WMLs fulfill the criteria to be considered surrogate markers because WMLs predict the natural course of the disease29 and because therapeutic interventions can delay the progression of WMLs.16
It is now time to test whether reducing the rate of progression of WML by lowering BP may delay the onset of cognitive decline, dementia, or stroke. This needs to be undertaken in large-scale clinical trials.
Clinical Perspective
Our study provides longitudinal population-based data on the relationship between blood pressure (BP) and cerebral white matter lesions (WMLs) in the elderly. WMLs are frequent in older individuals, and there is increasing evidence that they could be a marker of the risk of future stroke or dementia. In cross-sectional studies, elevated BP consistently relates to WMLs, but the relationship of baseline BP and changes in BP to the development of WML over time is less certain. In a longitudinal population-based study including 1319 subjects 65 to 80 years of age, we found that both baseline BP levels and change in BP levels over a 4-year follow-up were significantly associated with higher WML volume progression over 4 years. In addition, our data suggest that antihypertensive therapy was associated with a slowed progression of WML in individuals with high BP and untreated at study entry. Clinical trials are needed to determine whether white matter abnormalities are prevented or progression is slowed by antihypertensive therapy and serve as an early marker of successful treatment. Trials could also determine whether preventing WMLs with antihypertensive treatment can reduce the risk of dementia, which is an important goal in many increasingly older populations.
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Sources of Funding
The 3C Study is conducted under a partnership agreement between the Institut National de la Santé et de la Recherche Médicale (INSERM), the Victor Segalen–Bordeaux II University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” Sponsors are not involved in the design of the study, data analyses, or manuscript elaboration.
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© 2011 American Heart Association, Inc.
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Received: 16 April 2010
Accepted: 2 November 2010
Published online: 10 January 2011
Published in print: 25 January 2011
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