Interaction Between Hypertension, apoE, and Cerebral White Matter Lesions
Background and Purpose— Cerebral white matter lesions (WMLs) are frequently found on magnetic resonance imaging scans in both cognitively intact and demented elderly persons. Vascular risk factors, especially hypertension, are related to their presence. However, not every person with vascular risk factors has WMLs, which suggests interaction with other determinants, eg, genetic factors. The ε4 allele of the apolipoprotein E gene (apoE) may be a candidate because this allele is associated with both the vascular risk factors and the consequences (cognitive impairment, dementia) of WMLs.
Methods— We investigated apoE genotype, blood pressure levels, and their interaction in relation to subcortical and periventricular WMLs in 971 participants in the Rotterdam Scan Study.
Results— ApoE ε4 carriers had a significantly higher subcortical WML volume than did apoE ε3ε3 carriers (adjusted mean difference, 0.5; 95% confidence interval, 0.2 to 0.8), irrespective of hypertension. This was not found for periventricular WMLs. Participants with both hypertension and at least 1 apoE ε4 allele had the highest degree of both types of WML; the interaction was statistically significant for subcortical WMLs (P=0.016).
Conclusions— apoE ε4 carriers are at increased risk for WMLs if they suffer from hypertension as well. This may reflect a diminished capacity for neuronal repair in apoE ε4 carriers.
Cerebral white matter lesions (WMLs) are frequently found on magnetic resonance imaging (MRI) scans in both cognitively intact1 and demented2 elderly persons. WMLs are related to both cognitive impairment3 and dementia.2 Pathologically, WMLs are characterized by arteriolosclerosis, myelin loss, and gliosis.4 Vascular risk factors, especially hypertension, are related to the presence of these lesions.5 That not every person with vascular risk factors has cerebral WMLs suggests that the occurrence of WMLs is dependent on the interaction between vascular risk factors and other factors, eg, genotype. Support for genetic involvement in the development of WMLs comes from a twin study, in which the volume of WMLs was more strongly correlated for monozygotic than for dizygotic twins.6
A possible candidate for such a genetic factor might be the apolipoprotein E (apoE) ε4 allele, 1 of the 3 polymorphic forms of the apoE gene, because this allele is associated not only with the vascular risk factors for WMLs7 but also with its consequences, particularly cognitive impairment and dementia.8 The apoE gene encodes apoE, which has important functions in lipid metabolism and neuronal repair.9 Initially, it was hypothesized that the ε4 allele was related to cognitive impairment, mainly because of the presence of WMLs.10 However, previous studies found no relation between an ε4 allele and WMLs, neither in patients with Alzheimer’s disease or vascular dementia10 nor in population-based studies.11 On the other hand, a twin study showed that the presence of an ε4 allele in combination with unspecified cardiovascular or cerebrovascular disease did increase the risk for WMLs.12 Because hypertension is the primary risk factor for vascular disease and WMLs,5 we hypothesized that the destructive effect of vascular risk factors, in particular hypertension, on the white matter might be enhanced by the presence of an ε4 allele. We investigated this in the population-based Rotterdam Scan Study.
The Rotterdam Scan Study investigated the determinants and cognitive consequences of age-related brain abnormalities in the elderly. In 1995 to 1996, 1904 subjects aged between 60 and 90 years were randomly selected by strata of age (5 years) and sex from 2 large ongoing, prospective, follow-up studies, the Zoetermeer Study and the Rotterdam Study. Both studies have been described in detail elsewhere.13,14 In brief, the Zoetermeer Study is a prospective, population-based study of 10 361 subjects aged 5 to 91 years at baseline; its aim is to study the determinants of chronic disease. The Rotterdam Study is a prospective, population-based cohort study of 7983 subjects aged 55 years and older that investigates the determinants of neurologic, cardiovascular, endocrine, and ophthalmologic diseases in the elderly. The populations in both studies are almost completely white and of Dutch origin.
For the Rotterdam Scan Study, subjects were invited to participate by letter and subsequently contacted by telephone. Upon agreement to participate, a list of contraindications was reviewed to assess eligibility: dementia, blindness, or the presence of MRI contraindications, such as prosthetic valves, pacemakers, cerebral aneurysm clips, a history of intraocular metal fragments, cochlear implants, and claustrophobia. Of 1904 invited subjects, 1717 were eligible. The total response rate was 63%. The Rotterdam Study had 563 respondents, and the Zoetermeer Study had 514 respondents. For the 1077 individuals, blood pressure measurements and a cerebral MRI scan were available; for 971, apoE genotype data were also available; this article reports on these 971 participants. Those without apoE genotype data did not significantly differ from our study population, except for a higher body mass index (BMI). Each participant signed an informed consent form. The study was approved by the medical ethics committee of the Erasmus University, Rotterdam, The Netherlands.
Hypertension was defined as systolic blood pressure ≥160 mm Hg, diastolic blood pressure ≥95 mm Hg, self-reported use of blood pressure–lowering medication, or any combination of these parameters. Information on blood pressure–lowering medication was obtained from a computerized, structured questionnaire, which was checked by a physician.
ApoE genotyping was performed as described previously15 on coded genomic DNA samples, without knowledge of the WML rating. The results were read by 3 independent raters; in cases of discrepancies, the apoE genotyping was repeated.
MRI Scanning Protocol
For all participants, an axial T1-, T2-, and proton density–weighted cerebral MRI scan was performed on a 1.5-T MRI device. Subjects recruited from the Zoetermeer Study were scanned with a 1.5-T MR gyroscan (Philips), and participants from the Rotterdam Study were scanned with a 1.5-T MR Vision device (Siemens). Slice thickness was 6 mm and 5 mm, respectively, with an interslice gap of 20.0%. The images were printed on hard copy with a reduction factor of 2.7.
WML Rating Scale
WMLs were considered present if they appeared hyperintense on both the proton density- and T2-weighted images without hypointensity on the T1-weighted images. WMLs were rated separately for subcortical and periventricular regions. WMLs in the basal ganglia or infratentorial regions were not taken into account. When there was asymmetry between left- and right-sided periventricular WMLs, the score of the more severely affected side was used in the analysis. The number and size of subcortical WMLs were rated in both hemispheres on hard copy according to the largest diameter of a lesion in any of the slices in which the lesion could be observed in categories of small (<3 mm; diameter, 1 mm), medium (3 to 10 mm; diameter, 6 mm), or large (>10 mm; diameter, 12 mm) lesions. Confluent lesions were considered to be large, subcortical WMLs. To calculate the volume of subcortical WMLs on hard copy, they were considered to be spherical with a predefined diameter per size category.
Periventricular WMLs were rated semiquantitatively per region: adjacent to the frontal horns, to the lateral wall of lateral ventricles, and to the occipital horns, on a scale ranging from 0 to 3. The overall degree of periventricular WMLs was calculated by adding the scores for the 3 separate categories (range, 0 to 9). All MRI scans were examined by 2 individuals from a pool of experienced raters. Interrater and intrarater weighted kappa values for periventricular WMLs were 0.73 and 0.88, respectively. The weighted kappa was obtained by giving weights to the frequencies in each cell of the table according to the distance from the diagonal that indicates agreement. Thus, we give cells on the diagonal a weight of 1. For the periventricular WML score of 0 to 3, weights for discrepancies of 0, 1, 2, and 3 are thus 1, 2/3, 1/3, and 0, respectively. For total subcortical WML volume, the interrater and intrarater intraclass correlation coefficients were 0.88 and 0.95, respectively.
Measurement of Other Covariates
Height and weight of participants were measured without shoes in light clothing. The BMI was calculated as weight (kilograms) divided by height squared (meters, squared). Blood pressure was measured twice on the right arm with a random-zero sphygmomanometer with the participant in a sitting position. The average of these 2 measurements was used. As an indicator of atherosclerosis, the ankle-brachial index was calculated by the measurement of blood pressure of the tibial artery with an 8-MHz continuous-wave Doppler probe (Huntleigh 500D, Huntleigh Technology). For the brachial artery, the blood pressure was measured with a random-zero sphygmomanometer with the participant in a supine position. The ankle-brachial index was defined by the averaged systolic blood pressure at the left and right posterior tibial artery divided by the systolic pressure of the right arm. Subjects with an ankle-brachial index <0.9 were considered to have peripheral arterial disease.16 Diabetes mellitus was considered present if the participant was taking oral antidiabetic medication, insulin, or if the random or postload glucose level was >11.1 mmol/L.
The mean volume of subcortical WMLs and the mean grade of periventricular WMLs were calculated by ANCOVA for participants with or without hypertension, irrespective of the apoE genotype. This was also done for apoE ε4 carriers (apoE ε3ε4 and apoE ε4ε4) compared with apoE ε3ε3 homozygotes as the reference group, irrespective of hypertension. apoE ε2ε4 (n=22), apoE ε2ε3 (n=116), and apoE ε2ε2 (n=4) genotypes were excluded from these analyses.
To investigate the interaction between hypertension and apoE with respect to WMLs, the severity of WMLs was compared across 4 groups through linear regression analysis: (1) no hypertension and apoE ε3ε3 genotype (reference group); (2) hypertension and apoE ε3ε3 genotype; (3) no hypertension and apoE ε4 carrier; and (4) hypertension and apoE ε4 carrier. Interaction between hypertension and apoE was also tested by adding the interaction term to a model that contained variables for hypertension (yes/no) and apoE ε4 carrier status (yes/no).
In all analyses, adjustments were made for possible confounding factors, including age, sex, and intermediate vascular risk factors, such as BMI, peripheral arterial disease, diabetes mellitus, and study site (Zoetermeer or Rotterdam).
Genetic data on the apoE polymorphism were available for 971 subjects. The ε2, ε3, and ε4 allele frequencies were 0.075, 0.767, and 0.158, respectively. The distribution of the apoE genotypes was in Hardy-Weinberg equilibrium.
For all subjects, the mean degree of periventricular WMLs was 2.4 (SD, 2.2; range, 0 to 9), and the mean volume of subcortical WMLs was 1.3 mL (SD, 2.8 mL; range, 0 to 29.5 mL). There were no significant differences between the 2 groups except for age (Table 1). Subjects with an apoE ε4 allele were slightly younger than apoE ε3ε3 genotypes (71.1 vs 72.6 years of age; P=0.0056). About one half of all participants had hypertension. Of all participants, ≈20% and 10% were without periventricular or subcortical WMLs, respectively, whereas 5% had no WMLs at all.
Independent of their apoE genotype, subjects with hypertension had a significantly higher volume of subcortical WMLs than did subjects without hypertension (adjusted mean difference, 1.0; 95% confidence interval [CI], 0.8 to 1.2). The same was found for periventricular WMLs (adjusted mean difference, 0.9; 95% CI, 0.7 to 1.1). Exclusion of apoE ε2 carriers did not consistently change the results.
apoE ε4 carriers (n=261) had a higher mean subcortical WML volume compared with the reference group (n=568; adjusted mean difference, 0.5; 95%, CI 0.2 to 0.8). This was not found for periventricular WMLs (adjusted mean difference, 0.1; 95% CI, −0.2 to 0.5).
Participants with both hypertension and at least 1 apoE ε4 allele had the highest subcortical WML volumes and the highest degree of periventricular WMLs (Table 2). We detected a statistically significant interaction between hypertension and the presence of at least 1 apoE ε4 allele for subcortical WMLs (interaction term apoE ε4 allele×hypertension, P=0.016). This interaction was not found for periventricular WMLs.
We found that participants with hypertension had a significantly higher degree of WMLs in both subcortical and periventricular regions than did normotensives, irrespective of their apoE genotype. ApoE ε4 carriers had a higher subcortical WML volume than did subjects with the ε3ε3 genotype, but this was not found for periventricular WMLs. There was a significant interaction between hypertension and the apoE ε4 allele with regard to subcortical but not periventricular WMLs.
A strength of this study is its large number of elderly subjects from the general population, including institutionalized persons. Although our study was population-based, some selection bias may have occurred by selective nonresponse. Probably the participation rate was lowest among subjects with the highest degree of WMLs, because they are the most likely to forget appointments at the study center because of memory problems8 or to have difficulties in reaching the study center because of gait disturbances related to WMLs.17 Another form of selection bias may be underrepresentation of ε4 carriers by exclusion of demented patients, who have the highest odds of having an ε4 allele. A third potential source of error is survival bias by reduced survival in ε4 carriers compared with non-ε4 carriers, although findings from the Rotterdam Study suggested that survival was not different across apoE genotypes.18 In addition, the distribution of apoE genotypes was in Hardy-Weinberg equilibrium in our population. Therefore, we consider it unlikely that either selection bias or survival bias influenced our findings.
Our definition of hypertension was chosen to increase the contrast between hypertensives and nonhypertensives. By the application of current guidelines of hypertension, more people would qualify as hypertensive than according to our definition. Consequently, the hypertensive group would encompass more people with a relatively mild degree of WMLs. This would lead to a “dilution” of the difference in the degree of WMLs between the normotensive and hypertensive groups.
Like other smaller studies, we found an association only between the apoE ε4 allele and subcortical WMLs, irrespective of the presence of hypertension.19 A possible explanation for this observation may be a difference in the vascularization between subcortical and periventricular white matter, the latter being an arterial border zone that is more susceptible to a decrease in cerebral blood flow than the subcortical white matter.20 Compatible with this view is the presence of severe periventricular WMLs in patients with reduced cerebral blood flow associated with longstanding hypertension.21 In this marginally perfused periventricular area, WMLs may readily emerge, especially in the presence of chronic hypertension, whereas other vascular risk factors also predominantly seem to affect the periventricular white matter in contrast to the subcortical white matter.22 The joint effect of vascular risk factors and specific local anatomy in the periventricular white matter may be so predominant that the presence of an apoE ε4 allele is not necessary for the emergence of WMLs. However, the subcortical white matter may be more resistant against the influence of vascular risk factors, and it may be that only the combination of a disease-modifying factor, eg, an apoE ε4 allele and a vascular risk factor, is a sufficient cause for the emergence of WMLs in the subcortical area.
The explanation for the genetic factor is incompletely understood but is in keeping with the notion that the apoE ε4 allele is associated with an impaired response to cerebral damage.9 Neuronal repair, including dendrite formation and synaptogenesis, is an important process in restoring the integrity of the brain in response to injury,9 eg, after a period of ischemia. It is known that longstanding hypertension ultimately leads to ischemia in areas with an already marginal blood supply under physiologic conditions, such as the periventricular and subcortical white matter,20 eventually resulting in WMLs.5 Pathologically these areas are characterized by tissue injury with neuronal loss, arteriolosclerosis, and membrane damage such as demyelination.4 It is therefore plausible that the brain injury caused by hypertension in apoE ε4 carriers is more severe than in others. If the brain does not have the correct proteins to repair itself after lifelong vascular risk factor exposure, subsequent deterioration of brain function is to be expected, reflected in cognitive impairment or dementia. Indeed, a recent study confirmed that apoE ε4 carriers with hypertension are most severely affected with respect to cognitive impairment.23
Previous large studies, both in demented patients and in participants from the general population, failed to show an association between the apoE ε4 allele and WMLs.10,11 An explanation for the difference with previous studies may be that those investigated the relation between the apoE ε4 allele and WMLs, irrespective of the presence of concomitant vascular disease. There is gradually increasing evidence that it is the interaction between the apoE ε4 allele and vascular risk factors that results in vascular disease.24 WML volume may be up to 3 times higher in individuals with an apoE ε4 allele and unspecified vascular disease than in those with an apoE ε4 allele alone.12 However, in that study, it remained to be elucidated which vascular disease or risk factor was responsible for this interaction. In our study, we studied a well-defined vascular risk factor in detail and found that an interaction between hypertension and the apoE ε4 allele resulted in a significantly higher WML volume than in individuals with hypertension or the apoE ε4 allele alone.
In conclusion, our results suggest that apoE ε4 carriers are at increased risk for WMLs if they suffer from hypertension as well. Intervention studies are needed to investigate whether the interaction of hypertension with the apoE ε4 allele indeed is a causal link in the development of WMLs and the attendant cognitive impairment.
This research was made possible by financial support from the Netherlands Organization for Scientific Research and the Health Research Development Council.
- Received November 3, 2003.
- Revision received January 16, 2004.
- Accepted January 29, 2004.
Longstreth WT Jr, 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.
Scheltens P, Barkhof F, Valk J, Algra PR, van der Hoop RG, Nauta J, Wolters EC. WML on magnetic resonance imaging in clinically diagnosed Alzheimer’s disease: evidence for heterogeneity. Brain. 1992; 115: 735–748.
Van Swieten JC, van den Hout JH, van Ketel BA, Hijdra A, Wokke JH, van Gijn J. Periventricular lesions in the white matter on magnetic resonance imaging in the elderly: a morphometric correlation with arteriolosclerosis and dilated perivascular spaces. Brain. 1991; 114: 761–774.
De Leeuw FE, de Groot JC, Oudkerk M, Witteman JC, Hofman A, van Gijn J, Breteler MMB. Hypertension and cerebral WML in a prospective cohort study. Brain. 2002; 125: 765–772.
Carmelli D, DeCarli C, Swan GE, Jack LM, Reed T, Wolf PA, Miller BL. Evidence for genetic variance in white matter hyperintensity volume in normal elderly male twins. Stroke. 1998; 29: 1177–1181.
Dik MG, Jonker C, Comijs HC, Bouter LM, Twisk JW, van Kamp GJ, Deeg DJ. Memory complaints and apoE-ε4 accelerate cognitive decline in cognitively normal elderly. Neurology. 2001; 57: 2217–2222.
Hirono N, Yasuda M, Tanimukai S, Kitagaki H, Mori E. Effect of the apolipoprotein E ε4 allele on white matter hyperintensities in dementia. Stroke. 2000; 31: 1263–1268.
Kuller LH, Shemanski L, Manolio T, Haan M, Fried L, Bryan N, Burke GL, Tracy R, Bhadelia R. Relationship between apoE, MRI findings, and cognitive function in the Cardiovascular Health Study. Stroke. 1998; 29: 388–398.
DeCarli C, Reed T, Miller BL, Wolf PA, Swan GE, Carmelli D. Impact of apolipoprotein E ε4 and vascular disease on brain morphology in men from the NHLBI twin study. Stroke. 1999; 30: 1548–1553.
Hofman A, Boomsma F, Schalekamp MA, Valkenburg HA. Raised blood pressure and plasma noradrenaline concentrations in teenagers and young adults selected from an open population. BMJ. 1979; 1: 1536–1538.
Fowkes FG, Housley E, Cawood EH, Macintyre CC, Ruckley CV, Prescott RJ. Edinburgh Artery Study: prevalence of asymptomatic and symptomatic peripheral arterial disease in the general population. Int J Epidemiol. 1991; 20: 384–392.
Benson RR, Guttmann CR, Wei X, Warfield SK, Hall C, Schmidt JA, Kikinis R, Wolfson LI. Older people with impaired mobility have specific loci of periventricular abnormality on MRI. Neurology. 2002; 58: 48–55.
Nebes RD, Vora IJ, Meltzer CC, Fukui MB, Williams RL, Kamboh MI, Saxton J, Houck PR, DeKosky ST, Reynolds CF III. Relationship of deep white matter hyperintensities and apolipoprotein E genotype to depressive symptoms in older adults without clinical depression. Am J Psychiatry. 2001; 158: 878–884.
Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke. 1997; 28: 652–659.
Matsushita K, Kuriyama Y, Nagatsuka K, Nakamura M, Sawada T, Omae T. Periventricular white matter lucency and cerebral blood flow autoregulation in hypertensive patients. Hypertension. 1994; 23: 565–568.
Lindgren A, Roijer A, Rudling O, Norrving B, Larsson EM, Eskilsson J, Wallin L, Olsson B, Johansson BB. Cerebral lesions on magnetic resonance imaging, heart disease, and vascular risk factors in subjects without stroke: a population-based study. Stroke. 1994; 25: 929–934.
Peila R, White LR, Petrovich H, Masaki K, Ross GW, Havlik RJ, Launer LJ. Joint effect of the apoE gene and midlife systolic blood pressure on late-life cognitive impairment: the Honolulu-Asia aging study. Stroke. 2001; 32: 2882–2889.
Tiret L, de Knijff P, Menzel HJ, Ehnholm C, Nicaud V, Havekes LM. ApoE polymorphism and predisposition to coronary heart disease in youths of different European populations: the EARS Study: European Atherosclerosis Research Study. Arterioscler Thromb. 1994; 14: 1617–1624.