Age-Related Changes in White Matter Lesions, Hippocampal Atrophy, and Cerebral Microbleeds in Healthy Subjects Without Major Cerebrovascular Risk Factors

Age-Related Changes in White Matter Lesions, Hippocampal Atrophy, and Cerebral Microbleeds in Healthy Subjects Without Major Cerebrovascular Risk Factors Monzurul H. Chowdhury, MBBS, MRCP,* Atsushi Nagai, MD, PhD,† Hirokazu Bokura, MD, PhD,* Eisuke Nakamura, MD,* Shotai Kobayashi, MD, PhD,‡ and Shuhei Yamaguchi, MD, PhD*

Although cumulative evidence indicates that risk factors for arteriosclerosis have an impact on age-related changes in brain pathology, the influence of aging without major risk factors on changes in brain structures has not yet been fully elucidated. We used magnetic resonance imaging (MRI) to study how aging affects structural changes in the brain (eg, white matter lesions, hippocampal atrophy [HA], microbleeds) in normal subjects without major risk factors for cerebrovascular diseases. We studied 1108 subjects who underwent voluntary brain screening and had no cerebrovascular risk factors, such as hypertension, diabetes mellitus, or hyperlipidemia. We examined the conventional and T2-weighted MRI to define white matter hyperintensities, HA, and cerebral microbleeds in addition to all physical parameters, blood biochemical data, and neuropsychiatric symptoms. We found that the prevalence of white matter lesions and HA increased significantly with age (P , .001). Logistic analysis showed that periventricular hyperintensity was significantly related to age (P , .0001) and depressive state (P , .01). A linear relation was found between white matter lesions and HA (P ,.05). Cerebral microbleeds also increased with age, and their presence was associated with HA (P ,.001). White matter lesions, HA, and cortical microbleeds were associated with one another in healthy elderly subjects, and these changes were affected by the aging process independent of any cerebrovascular risk factors. Cerebral amyloid angiopathy may underlie these age-related brain changes. Key Words: Periventricular hyperintensity—cerebral amyloid angiopathy—Alzheimer’s disease—deep or subcortical white matter hyperintensity—hippocampal atrophy—cerebral microbleeds. Ó 2011 by National Stroke Association

Deep or subcortical white matter hyperintensity (DSWMH) and periventricular hyperintensity (PVH) are frequently seen on T2-weighted magnetic resonance imagFrom the *Department of Internal Medicine III, †Department of Laboratory Medicine, and ‡University Hospital, Shimane University, Faculty of Medicine, Izumo, Japan. Received September 8, 2009; accepted December 25, 2009. There is no conflict of interest. Address correspondence to Dr. Atsushi Nagai, MD, PhD, Department of Laboratory Medicine, Shimane University Faculty of Medicine, 89-1 Enya-cho, Izumo 693-8501, Japan. E-mail: anagai@med. shimane-u.ac.jp. 1052-3057/$ - see front matter Ó 2011 by National Stroke Association doi:10.1016/j.jstrokecerebrovasdis.2009.12.010

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ing (MRI) in elderly individuals even in clinically asymptomatic conditions.1-3 Arteriosclerosis is suggested as the primary factor in these lesions, resulting from chronic ischemia or transient repeated ischemic damage to the white matter.4,5 Histological findings include lacunar infarctions, gliosis and plaques of demyelination,6,7 loss of myelinated axons, arteriosclerosis, fibrosis, and edema.8,9 Aging and hypertension are suggested to be the major contributing factors in these lesions, due to hyaline sclerosis and ectasia of small arteries and arterioles of brain parenchyma.10,11 Previous studies have suggested that along with age and hypertension, diabetes mellitus and hyperlipidemia are also associated with these lesions, due to chronic hypoxic-ischemic injury

Journal of Stroke and Cerebrovascular Diseases, Vol. 20, No. 4 (July-August), 2011: pp 302-309

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to the brain. Apart from these cerebrovascular risk factors, certain neurodegenerative and ischemic disorders, such as Alzheimer’s disease (AD) and cerebral amyloid angiopathy (CAA), also are related to white matter lesions due to amyloid deposition resulting from cerebral angiopathy in the aging brain.13,14 Cognitive decline and depressive state are the major clinical problems associated with white matter lesions.15-17 In elderly persons, cerebral ischemic injury due to arteriosclerosis may cause neural disconnection, leading to white matter lesions and cognitive decline.18 In AD and CAA, cognitive deficits are related to hippocampal atrophy (HA). Amyloid deposition in arterial walls reduces white matter perfusion through vascular stenosis or vascular dysfunction, resulting in cognitive decline.19,20 Studies analyzing periventricular and subcortical white matter lesions separately in terms of their relationship to cognition and depressive state are limited and inconclusive.15,16,21 More studies are needed to evaluate the precise pathological correlation of white matter lesions with cognitive decline and depressive state in elderly persons. The increasing use of gradient-echo T2-weighted MRI has led to more frequent detection of cerebral microbleeds, especially in stroke patients. The frequency of cerebral microbleeds is 4%-5% in the healthy population,22,23 increasing to up to 50%-70% in patients with cerebrovascular disease.23,24 Among several causative factors of cerebral microbleeds, advanced hypertension and CAA play major roles.25,26 The prevalence of CAA is up to 30%-50% in healthy elderly adults.27,28 Amyloid deposition within the media and adventitia of small to medium-sized cerebral arteries leads to loss of vascular integrity and function. The altered white matter perfusion results in white matter hyperintensities, and increased vascular fragility leads to lobar intracerebral hemorrhage.29 Thus, it may be hypothesized that the association of white matter lesions, HA, and cortical microbleeds reflects a progressive microangiopathy due to CAA. The involvement of amyloid microangiopathy in white matter lesions, HA, and cerebral microbleeds would be better evaluated in the subjects without any cerebrovascular risk factors. In elderly persons, the prevalence of DSWMH, HA, and cerebral microbleeds has been evaluated only in the population-based studies including subjects with cerebrovascular risk factors. However, the underlying pathophysiological correlation of all these age-related changes without the influence of cerebrovascular risk factors has hardly been evaluated. The aim of the present study was to explore the relationship among DSWMH, cerebral microbleeds, and HA and the influence of clinical variables on the MRI findings in healthy individuals without hypertension, hyperlipidemia, or diabetes mellitus. We also sought to explore their common pathophysiological correlations and neuropsychiatric symptoms, such as cognition and depressive state.

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Materials and Methods Subjects and Clinical Data Collection We recruited subjects who enrolled voluntarily at the Shimane Institute of Health Science for health screening over an 11-year period (1995-2006). The screening included medical and neuropsychological examination, head MRI, and blood tests. All subjects were evaluated with same examination procedures throughout the study period by the experienced neurologists. In present study, we excluded subjects with any history of psychiatric or neurologic diseases, including transient ischemic attack, dementia, and abnormal neurologic examination findings; were taking any antiplatelet or anticoagulant medication; and who had hypertension, hyperlipidemia, or diabetes mellitus. Thus, in the present study, we defined aging without 3 major cerebrovascular risk factors, and eventually selected 1120 subjects, age 40-93 years (mean age, 61.7 years) out of 5979 candidates. All physical and biochemical parameters, including age, sex, body mass index, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, weight, and blood levels of total cholesterol, triglyceride, fasting blood sugar (FBS), fibrinogen, and creatinine, were evaluated. Other demographic data were obtained as well, including education level, smoking index (same as the Brinkman index—number of cigarettes smoked per day multiplied by years of smoking),30 and alcohol intake. The study was approved by the Ethics Committee of the Shimane University Faculty of Medicine, and written informed consent was obtained from all the participants. In this study, hypertension was defined as SBP of $140 mm Hg, DBP of $90 mm Hg, or a history of hypertension as reported by the subject or indicated by antihypertensive therapy. Hyperlipidemia was defined as total cholesterol $240 mg/dL or low-density lipoprotein cholesterol $160 mg/dL and/or the use of a cholesterollowering medication. Diabetes mellitus was defined as a FBS of $126 mg/dL (7.0 mmol/L), random blood glucose level of $200 mg/dL (11.1 mmol/L), hemoglobin A1c of $6.5%, or reported treatment for diabetes mellitus. Cognitive function was evaluated using Okabe’s intelligence evaluation test, a shorter version of the Wechsler memory scale consisting of 4 subclasses and a possible total score of 60 points (with a score of 20-29 indicating mild dementia, 10-19 indicating moderate dementia, and ,10 indicating severe dementia),31 and Kohs’ block design test (with a 131-point scale and a normal average score of 90-110).32 The tests were aimed to assess memory function, speed of cognitive function, and global cognitive function. Depressive state or satisfaction with life was evaluated by the Zung’s selfrating depression scale (SDS); the highest possible score on the SDS is 80, and most subjects with depression have a score of 50-69.33,34

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MRI Imaging MRI images of the brain were obtained with a 1.5-T Symphony Ultra Gradient MRI unit (Siemens) during the study period. In 2000, the unit was upgraded to acquire axial T2-weighted echo planar images. The subjects were scanned using pulse sequences of T2-weighted spinecho (repetition time [TR], 4500 ms; echo time [TE], 86 ms) for the transverse plane parallel to the orbitomeatal line, of T1-weighted spin-echo (TR, 2500 ms; TE, 3.9 ms) for coronal slices with a slice thickness of 7 mm, and of fluid-attenuated inversion recovery (FLAIR) images (TR, 8000 ms; TE, 123 ms; inversion time [TI], 2000 ms) for transverse plane. Starting in 2000, we obtained axial T2weighted images (TR, 23,000 ms; TE, 60 ms; flip angle, 25-90 degrees) for 742 of 1108 subjects to better visualize cerebral microbleeds. Independent and experienced radiologists and neurologists who were blinded to the subjects’ clinical data examined the MRI images to characterize brain lesions. Visual rating scales were used to describe the presence, location, and grading of white matter lesions (ie, DSWMH and PVH). White matter lesions were considered as present if they were hyperintense on proton-density and T2weighted images but not hypointense on T1-weighted images. DSWMH were rated according to the Fazekas rating scale (0, absent; 1, punctate foci; 2, beginning confluence of foci; 3, large confluent areas).2 Grade 0-1 was defined as DSWMH (-), and grade 2-3 was defined as DSWMH (1). PVH were graded according to the Fukuda 5-point rating scale (0, absent; 1, caps only on anterior horns of the lateral ventricle; 2, thin lining, smooth halo, or irregular PVH surrounding the body of the lateral ventricle; 3, thick, irregular PVH extending into the outer half area of the white matter at any region around the lateral ventricle; 4, PVH covering the entire white matter).35 Grade 0–2 was defined as PVH (-), and grade 3-4 was defined as PVH (1). HA was rated on a 4-point visual rating scale using T1-weighted MRI images obtained in the coronal planes, based on the width of the choroid fissure and the temporal horn and the height of the hippocampal formation (0, none; 1, mild atrophy; 2, mild to moderate atrophy; 3, severe atrophy).36,37 Grade 0-1 was defined as HA (-), and grade 2-3 was defined as HA (1). Cerebral microbleed was defined as a small hypointense signal (2-5 mm in diameter) with a well-defined margin on T2-weighted images.38,39

Statistical Analysis All data were analyzed using SPSS for Windows version 11.5 (SPSS Inc, Chicago, IL) and StatView version 5 (Abacus Concepts, Inc., Berkeley, CA). Demographic and biochemical data are reported as mean 6 standard deviation. Group comparisons were performed using the Student t test for parametric variables and the Mann-Whitney U test for nonparametric variables. The

variable age was treated as as quintiles in the analysis, and our subjects were divided into 5 groups according to age decade, starting at age 40. The c2 test was used to examine the age effect on MRI findings such as DSWMH, PVH, and HA, and Fisher’s exact test was used to study the relationship between cerebral microbleeds and other MRI findings. Stepwise multiple logistic regression analysis was performed to examine the influence of demographic, physical, and biochemical variables on the MRI findings (DSWMH, PVH, and HA). ANOVA was used to analyze the effects of MRI findings on neuropsychiatric symptoms.

Results Table 1 summarizes demographic and biochemical characteristics of our study population. The prevalence of DSWMH was as follows: grade 0, 77.3% (n 5 856); grade 1, 13.4% (n 5 149); grade 2, 8.7% (n 5 96); grade 3, 0.6% (n 5 7). The prevalence of DSWMH increased gradually and significantly with each decade of life (Fig 1; P , .0001). The degree of DSWMH, as classified by the Fazekas score, showed a linear relationship (r2 5 0.81) with HA (Fig 2A); the prevalence of HA was higher in subjects with DSWMH (1) subjects compared with DSWHM (-) subjects (P , .001). Logistic regression analysis showed no significant relationship between DSWHM and any demographic and biochemical variables except age (Table 2). Cognitive function and depressive state were not affected by DSWMH. The prevalence of PVH was 36.2% (n 5 401) for grade 0, 39.6% (n 5 439) for grade 1, 20.7% (n 5 230) for grade 2, 3.1% (n 5 34) for grade 3, and 0.4% (n 5 4) for grade 4.

Table 1. Demographic data Demographic characteristics Age, years Sex, M/F Body mass index SBP, mm Hg DBP, mm Hg Education, years Smoking index Okabe test Kohs test SDS PVH (3-4) DSWMH (2-3) HA (2-3) Biochemical measures Total cholesterol, mg/dL Triglycerides, mg/dL Fibrinogen, mg/dL FBS, mg/dL Creatinine, mg/dL

61.8 6 9.7 598/510 22.6 6 2.7 123.4 6 16.7 71.21 610.5 12.2 6 2.9 249.4 6 375 45.15 6 8.7 100.7 6 19.4 33.7 6 7.9 38 (3.5%) 103 (9.1%) 40 (3.6%) 199.4 6 30.3 100.4 6 55.4 314.5 6 72.6 86.8 6 34.2 0.73 6 0.16

AGE-RELATED CHANGES IN WHITE MATTER LESIONS

Figure 1. Prevalence of DSWMH, PVH, and HA as function of age. The incidence of each lesion increased significantly with age (P , .001 for all lesion types).

The prevalence of PVH also increased gradually and significantly with each decade (Fig 1). The degree of PVH, as categorized by Fukuda grade, showed a linear increase (r2 5 0.89) with HA (Fig. 2B), the prevalence of HA was significantly higher in PVH (1) subjects compared with PVH (-) subjects (P , .0001). Logistic regression analysis showed that PVH (1) was significantly associated with age and depressive state (P , .0001, , .01), but revealed no significant relationship between PVH (1) and SBP, blood values, education level, or cognitive function (Table 3). The frequency of HA was as follows: grade 0, 77.1% (n 5 854); grade 1, 19.3% (n 5 214); grade 2, 3.2% (n 5 35); grade 3, 0.4% (n 5 5). The prevalence of HA increased significantly with age (Fig 1); interestingly, subjects in the seventh decades of life had a markedly increased prevalence (P , .0001). Logistic regression analysis revealed that only age was significantly associated with HA (P , .0001), with SBP, blood values, cognitive function, and depressive state not related to HA. The frequency of cerebral microbleeds was 2.3% (17/ 742), with cases involving the frontal cortex (n 5 5), temporal cortex (n 5 2), parietal cortex (n 5 1), occipital cortex (n 5 1), thalamus (n 5 6), and basal ganglia (n 5 2). As shown in Fig 3, the prevalence of cerebral microbleeds increased with age, as did other types of brain lesions, but the number of subjects with microbleeds was too small

Figure 2. The age- and sex-adjusted relationships between DSWMH and HA (A) and between PVH and HA (B). HA is expressed as percent incidence according to the rating scale (2-3) for each categorical lesion of DSWMH (A) and PVH (B). The incidence of HA increased significantly with each category of DSWMH and PVH (P , .001 for all lesion types; r2 5 0.81 for DSWMH and r2 5 0.89 for PVH).

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to enable statistical analysis of an aging effect. Table 4 presents the location of the microbleeds detected in our study population, along with demographic data for the affected subjects. Comparing the prevalence of HA in subjects without microbleeds (n 5 725) and those with microbleeds (n 5 17) using Fisher’s exact test showed a higher prevalence in the subjects with microbleeds (P , .0005). When the subjects with cerebral microbleeds were divided into cortical microbleed (n 5 9) and deep microbleed (n 5 8) subgroups, it was apparent that the presence of HA was associated only with the presence of cortical microbleeds (P , .001), not with the presence of deep microbleeds (P 5 .06).

Discussion The critical distinction of the current study from previous reports is the criteria for subject selection, which carefully excluded subjects with any of the 3 major cerebrovascular risk factors of hypertension, diabetes mellitus, and dyslipidemia. Thus, the novel feature of this study is an evaluation of age-related brain changes and their association with neuropsychiatric symptoms, such as cognitive impairment and depressive state, excluding 3 major cerebrovascular risk factors. Another advantage of this study is the inclusion of a large number of subjects (n 5 1108) and coverage of a wide age range (40–93 years). The important finding of this study is that even with the exclusion of the 3 major cerebrovascular risk factors, a robust association between white matter lesions and aging was apparent. This finding suggests the presence of some cumulative factors in the pathogenesis of white matter lesions even after excluding major cerebrovascular risk factors, as reported in the Rotterdam Scan Study and other studies.40,41 Structural changes, such as myelin loss and changes in the composition of connective tissues and muscles of vessel walls, are known to occur in the aging brain, resulting in cerebral hypoperfusion even in the absence of cerebrovascular risk factors.42,43 Another possible mechanism of cerebral hypoperfusion in the aging brain that occurs without major cerebrovascular risk factors is the deposition of amyloid materials in blood vessel walls in the cerebral cortex and leptomeninges.44 Thus, apart from additive deleterious

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Table 2. Association of DSWMH with age, SBP, fibrinogen, total cholesterol, FBS, cognitive function, and depressive state Variable

OR

95% CI

P value

Age SBP DBP Fibrinogen Total cholesterol FBS Okabe test Kohs test SDS

1.108 1.017 1.379 1.004 1.001 1.004 0.991 0.984 1.018

1.060-1.159 0.998-1.037 0.951-1.013 1.000-1.008 0.990-1.012 0.981-1.029 0.950-1.033 0.359-2.700 0.998-1.038

,.0001 .0799 .2403 .0676 .8540 .0720 .6568 .9752 .1867

effects of cerebrovascular risk factors on cerebral perfusion, a combination of age-related structural and functional changes and amyloid deposition in the cerebral vasculature may contribute to the occurrence of white matter lesions in the aging brain.45,46 Regarding the affective symptoms after stroke, the ‘‘vascular depression’’ hypothesis holds that cerebrovascular insult results in white matter lesions, which cause disruption of fronto-striatal connections and lead to a depressive state in elderly persons.47,48 The present study demonstrates that even after the exclusion of major cerebrovascular risk factors, depressive symptoms are associated with PVH. Given the characteristics of the angioarchitecture in periventricular regions, perfusion pressure in the periventricular area is relatively low and sensitive to fluctuations in cerebral blood flow. Thus, an age-related reduction of cerebral blood flow might be associated with extension of PVH and depressive symptoms.49,50 On the other hand, we could find no statistical association between cognitive performance and the presence of PVH or DSWMH. This association has been a matter of dispute in the literature, in which the major cerebrovascular risk factors were included in the study population in most cases.18,51 The high–signal intensity foci on MRI

Table 3. Association of PVH with age, SBP, fibrinogen, total cholesterol, FBS, cognitive function, and depressive state Variable

OR

95% CI

P value

Age SBP DBP Fibrinogen Total cholesterol FBS Okabe test Kohs test SDS

1.174 1.008 1.209 1.003 1.000 1.001 0.959 0.979 1.066

1.104-1.250 0.984-1.033 0.927-1.102 0.998-1.008 0.984-1.017 0.998-1.024 0.919-1.001 0.995-1.003 1.016-1.118

,.0001 .490 .766 .310 .990 .089 .053 .090 .009

Figure 3. Prevalence of cerebral microbleeds as a function of age. A percentage of subjects in each decade suffered from deep (white bar) or cortical (black bar) cerebral microbleeds.

that are correlated with cognitive deficits in subjects with cerebrovascular risk factors may differ in their pathogenesis from those in subjects without these risk factors. White matter lesions associated with cerebrovascular risk factors are usually caused by arteriolosclerosis, which is followed by demyelination,4 whereas white matter lesions in healthy elderly persons are caused by nonischemic demyelination due to different mechanisms, such as subependymal gliosis.52 Thus, exclusion of cerebrovascular risk factors might have led to different results than those reported previously in terms of the relationship between cognitive function and white matter changes. The finding of a significant relationship between HA and the severity of white matter lesions in subcortical and periventricular locations is intriguing, because the incidence of HA in AD has a pathological correlation with white matter lesions, possibly due to microvascular dysfunction.19,40 Microvascular dysfunction caused by CAA could lead to both HA and white matter lesions in AD.14,53 Because CAA is also one of the major features of normal aging,54 our results suggest that simultaneous progression of HA and white matter lesions may reflect the progression of CAA in elderly persons without major cerebrovascular risk factors. Because the evaluation of cortical microbleeds is a sensitive method for detecting CAA in persons with AD and elderly persons in general,26,29 we used T2-weighted gradient echo MRI in this study. Previous studies have found a prevalence of cerebral microbleeds of 3.1% in healthy Asian adults with no neuropsychiatric disorders, including cerebral bleeding, cerebral infarction, cerebral trauma, transient ischemic attack, brain tumor, dementia, or intracranial trauma.22 The overall prevalence of cerebral microbleeds in persons with any cerebrovascular disease is 45% (range, 21%-60%).55,56 In the present study, we found a similar prevalence of cerebral microbleeds (2.3%) in the healthy population after excluding subjects with any of the 3 major cerebrovascular risk factors. Earlier studies have shown an increased prevalence of cortical

AGE-RELATED CHANGES IN WHITE MATTER LESIONS

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Table 4. Demographic data, location, and number of microbleeds and cerebrovascular risk factors in individuals with cerebral microbleeds Age, years/sex

Location

Number

Body mass index

SBP

Total cholesterol

FBS

Smoking index

Alcohol

65/M 66/M 72/F 80/F 85/F 58/M 82/M 72/F 78/M 61/M 57/M 67/M 69/M 76/F 77/M 67/M 79/M

Frontal Frontal Frontal Frontal Frontal Occipital Temporal Temporal Parietal Thalamus Thalamus Thalamus Thalamus Thalamus Thalamus Basal ganglia Basal ganglia

1 2 1 1 1 1 2 1 1 1 1 1 1 1 4 1 1

17.83 23.53 21.84 20.44 18.86 22.34 21.78 24.12 25.00 21.67 27.29 26.41 20.86 22.42 22.37 16.23 26.68

120 130 140 138 120 120 150 110 140 150 156 140 145 130 150 136 130

216 163 203 184 227 225 168 195 181 196 229 195 216 196 211 220 208

93 81 93 87 110 113 100 116 101 107 110 125 95 89 100 99 104

0 0 220 525 0 0 1200 80 150 620 555 0 490 0 0 0 0

0 0 1 1 0 0 2 1 1 3 0 0 1 1 0 0 0

microbleeds with aging,10 although the incidence of deep cerebral microbleeds is positively related with cerebrovascular risk factors, such as hypertension.24,57 In concert with these earlier findings, we found a significant positive correlation between cortical microbleeds and HA in our healthy population, possibly leading to a hypothesis that cortical microbleeds in patients with HA may be linked to CAA. In summary, the present study of healthy adults revealed that white matter lesions can progress with aging in the absence of major cerebrovascular risk factors, and that a depressive state in elderly persons is related to extended PVH. Furthermore, age-related HA is associated with an increase in white matter lesions and cortical microbleeds, both of which may be associated with CAA in persons with no cerebrovascular risk factors. Thus, we conclude that when cerebral cortical microbleeds occur in any healthy elderly individual without major cerebrovascular risk factors, CAA may be considered, and that this consideration may be supported by the additional presence of white matter lesions and/or HA.

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