eFigure 1. Study Population
eFigure 2. Cumulative Incidence of Cerebral Microbleeds (CMBs) by Presence of Baseline CMBs
eFigure 3. Cumulative Incidence of Cerebral Microbleeds (CMBs) by Baseline CMB Burden
eTable 1. Baseline Characteristics (2002-2006) of Participants (n=4497) Who Had a Second MRI Assessment and for Those Who Refused or Were Dead/Lost to Follow-up
eTable 2. Incidence of Cerebral Microbleeds (CMBs) by 10-Year Age Group in Strata of the Presence of CMBs on Baseline MRI
eTable 3. Association of Lifestyle and Lipid Factors With Incident Single and Multiple Cerebral Microbleeds (CMBs)
eMethods. Variable Measurement and Sensitivity Analyses
Ding J, Sigurdsson S, Garcia M, Phillips CL, Eiriksdottir G, Gudnason V, van Buchem MA, Launer LJ. Risk Factors Associated With Incident Cerebral Microbleeds According to Location in Older PeopleThe Age, Gene/Environment Susceptibility (AGES)–Reykjavik Study. JAMA Neurol. 2015;72(6):682-688. doi:10.1001/jamaneurol.2015.0174
The spatial distribution of cerebral microbleeds (CMBs), which are asymptomatic precursors of intracerebral hemorrhage, reflects specific underlying microvascular abnormalities of cerebral amyloid angiopathy (lobar structures) and hypertensive vasculopathy (deep brain structures). Relatively little is known about the occurrence of and modifiable risk factors for developing CMBs, especially in a lobar location, in the general population of older people.
To investigate whether lifestyle and lipid factors predict new CMBs in relation to their anatomic location.
Design, Setting, and Participants
We enrolled 2635 individuals aged 66 to 93 years from the population-based Age, Gene/Environment Susceptibility (AGES)–Reykjavik Study in a brain imaging study. Participants underwent a baseline magnetic resonance imaging (MRI) examination of the brain from September 1, 2002, through February 28, 2006, and returned for a second MRI examination from April 1, 2007, through September 30, 2011.
Lifestyle and lipid factors assessed at baseline included smoking, alcohol consumption, body mass index, and serum levels of total cholesterol, high- and low-density lipoprotein cholesterol, and triglycerides.
Main Outcomes and Measures
Incident CMBs detected on MRIs, which were further categorized as exclusively lobar or as deep.
During a mean follow-up of 5.2 years, 486 people (18.4%) developed new CMBs, of whom 308 had lobar CMBs only and 178 had deep CMBs. In the multivariate logarithm-binomial regression model adjusted for baseline cardiovascular risk factors, including blood pressure, antihypertensive use, prevalent CMBs, and markers of cerebral ischemic small-vessel disease, heavy alcohol consumption (vs light to moderate consumption; relative risk [RR], 2.94 [95% CI, 1.23-7.01]) was associated with incident CMBs in a deep location. Baseline underweight (vs normal weight; RR, 2.41 [95% CI, 1.21-4.80]), current smoking (RR, 1.47 [95% CI, 1.11-1.94]), an elevated serum level of high-density lipoprotein cholesterol (RR per 1-SD increase, 1.13 [95% CI, 1.02-1.25]), and a decreased triglyceride level (RR per 1-SD decrease in natural logarithm-transformed triglyceride level, 1.17 [95% CI, 1.03-1.33]) were significantly associated with an increased risk for lobar CMBs exclusively but not for deep CMBs.
Conclusions and Relevance
Lifestyle and lipid risk profiles for CMBs were similar to those for symptomatic intracerebral hemorrhage and differed for lobar and deep CMBs. Modification of these risk factors could have the potential to prevent new-onset CMBs, particularly those occurring in a lobar location.
Cerebral microbleeds (CMBs), visualized as hypointense lesions on T2-weighted gradient-echo magnetic resonance imaging (MRI), frequently occur in healthy older people.1,2 Cerebral microbleeds are an asymptomatic precursor of intracerebral hemorrhage (ICH),3,4 and their presence is associated with an increased risk for (recurrent) ischemic stroke,5 cognitive impairment,6 and mortality.7 In histopathologic studies, CMBs represent hemosiderin deposits from microvascular leakage.8 Similar to ICH, the pathophysiologic features of CMBs may differ according to their location, with lobar (cortical-subcortical) CMBs attributable to cerebral amyloid angiopathy and deep (basal ganglia, thalamus, and brainstem) CMBs attributable to hypertensive vasculopathy.3
Apart from high blood pressure, we know little about potentially modifiable risk factors for the occurrence of new CMBs in the general population, especially in lobar locations.1,9- 11 On the other hand, the modifiable risk factors for ICH have been investigated extensively; establishing an overlap in the risk profiles for CMBs and ICH may pave the way for early detection of people at an increased risk for ICH, which is a devastating condition with no curative treatment options. For example, the adverse effects of lifestyle variables, such as low or high extremes of body mass index (BMI) and excessive alcohol intake, have been reported to be associated with the development of ICH. Whether these factors also predispose to CMBs at a particular location has not yet been well explored.1,12 Furthermore, low serum lipid levels have long been recognized as an important risk factor for ICH13- 15 and also relate to the presence of CMBs in previous studies.9,11,15 However, results are inconsistent with respect to CMB locations, and which serum lipid fractions are most closely associated with CMBs remains unknown. To date, longitudinal data are scarce11 and have been limited by relatively small sample sizes. Therefore, we further examined the incidence and location of CMBs and whether a spectrum of modifiable lifestyle and lipid factors predict new CMBs in relation to their location in the large population-based Age, Gene/Environment Susceptibility (AGES)–Reykjavik Study.
For the present study, we used longitudinal data from the AGES-Reykjavik Study, which originates from the Reykjavik Study, as described fully elsewhere.16 In brief, from September 1, 2002, through February 28, 2006, 5764 surviving men and women in the Reykjavik Study cohort (born January 1, 1907, to December 31, 1935) underwent extensive physical and brain examinations in the AGES-Reykjavik Study. The baseline AGES-Reykjavik examination, completed in 3 clinic visits, and the second clinic visit from April 1, 2007, through September 30, 2011, included MRI of the brain. The study was approved by the Icelandic National Bioethics Committee (VSN 00-063) and by the intramural institutional review board of the National Institute on Aging. All participants gave written informed consent.
Of the 4497 participants who underwent initial MRI of the brain and had no dementia at baseline (eFigure 1 in the Supplement), 547 had died, 154 were unavailable for follow-up (could not be contacted by any means), and 808 declined further participation between baseline and follow-up. Of the 2988 participants in the follow-up examination, MRI data were missing for 353 individuals owing to contraindications (n = 127), refusal or nonattendance (n = 197), or technical reasons (ie, no qualitatively acceptable MRI data available for all necessary sequences) (n = 29). Therefore, 2635 people who had complete and reliable baseline and follow-up MRIs provided data in the analyses. Compared with people who participated in the first examination only, those who participated in both MRI examinations were younger, had higher educational levels, were less often underweight or treated with anticoagulants, and had more favorable profiles of cardiovascular risk factors and disease (eTable 1 in the Supplement).
High-resolution MRIs of the brain were all acquired on the same study-dedicated 1.5-T scanner (Signa Twinspeed; General Electric Medical Systems) following a similar MRI protocol described elsewhere2 at baseline and follow-up. A 2-dimensional T2-weighted gradient-echo echoplanar sequence was used for the detection of CMBs.2Cerebral microbleeds were defined as a focal area of signal void within the brain parenchyma that is visible on the T2-weighted gradient-echo echoplanar sequence and smaller or invisible on T2-weighted fast spin-echo images.2
Two trained radiographers who were blinded to the findings on the baseline images identified CMBs on the follow-up MRIs. If CMBs were identified, the baseline image was examined to determine whether the CMBs were present in the same section. If so, the follow-up CMBs were labeled prevalent; if not, the follow-up CMBs were labeled incident. Each CMB on the follow-up image was evaluated in terms of size and anatomic location. A total count of CMBs per person was generated based on individually labeled CMBs. We counted CMBs in lobar (frontal, parietal, temporal, and occipital) and in deep or infratentorial (basal ganglia and thalamus, corpus callosum, and infratentorium, including the brainstem and cerebellum) regions. People with at least 1 new CMB restricted to lobar regions were considered to have lobar CMBs exclusively; those with CMBs in a deep or infratentorial region with or without concomitant lobar CMBs were considered to have deep CMBs. Intrarater reliability (κ value) was based on 2 ratings within a 6-month interval of 0.75 and 0.73, and the statistic for interrater agreement was 0.70, indicating good reliability.
Information on baseline lifestyle and lipid risk factors was gathered by questionnaire and results of laboratory and physical examinations.16 Cigarette smoking was dichotomized as current vs noncurrent (never or former). Alcohol consumption was categorized into 4 groups based on consumption status and current weekly alcohol consumption as abstinence, former, light to moderate (women, 1-7 drinks/wk; men, 1-14 drinks/wk), and heavy (women, >7 drinks/wk; men, >14 drinks/wk).17 Body mass index was calculated as weight in kilograms divided by height in meters squared and further categorized into the following 4 groups according to the World Health Organization guidelines: underweight (<18.5), normal weight (18.5-24.9), overweight (25.0-29.9), and obese (≥30.0). Fasting levels of total cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglycerides were determined on a chemistry analyzer using comparable enzymatic procedures (Hitachi 912; Roche Diagnostics).18 All measurements fulfilled the criteria of the National Institutes of Health and the National Cholesterol Education Program for precision and accuracy of lipids measurements.19 Low-density lipoprotein (LDL-C) level was calculated using the Friedewald equation.18
All continuous variables were normally distributed except for the triglyceride levels and white matter hyperintensity volume, for which natural logarithmic transformations were used. The cumulative incidence of CMBs was estimated in 10-year baseline age strata and separately in strata of the presence or absence of CMBs on the baseline MRI. To estimate the relative risk (RR), we applied logarithm-binominal regression20 to examine the association of putative risk factors with CMB incidence. The logarithm-binominal model produces an unbiased estimate of the adjusted RR when the incidence of the outcome is greater than 10%.21All analyses were initially adjusted for age and sex (model 1), followed by additional adjustment for the interval between the baseline and follow-up MRIs, head coil, systolic blood pressure, use of antihypertensives, use of anticoagulants or aspirin, prevalent CMBs, subcortical infarcts, and white matter hyperintensity volume (model 2). We additionally adjusted analyses of lipid levels and CMBs for statin use. These analyses were also stratified by incident CMB location. Interactions between putative risk factors and other covariates were assessed in the fully adjusted models. To test the robustness of the results, we performed several sensitivity analyses, details of which are described in the eMethods in the Supplement. The analysis was conducted using commercially available software (Stata, version 12; StataCorp).
Table 1 shows the study population characteristics according to incident CMB categories. The mean age of the study population at baseline was 74.6 years, and 58.9% were women. Overall, 486 of the 2635 participants (18.4%) developed new CMBs on the MRI, and 145 participants (5.5%) had multiple new CMBs during a mean follow-up of 5.2 years (eTable 2 in the Supplement). Among people with new CMBs, 308 (63.4%) had incident lobar CMBs exclusively, and 178 (36.6%) had deep CMBs. Of those people who had incident CMBs located in a deep brain region, 66 also had 1 or more incident lobar CMBs. The 5-year cumulative incidence of any CMBs increased with age at baseline from 16.0% in people aged 65 to 74 years to 28.6% in those older than 85 years (eTable 2 in the Supplement). The similar pattern of incidence by age was also observed for multiple CMBs. Incidence of CMBs was slightly higher for men than for women in all age groups (overall, 21.9% vs 16.1%; eFigure 2 in the Supplement) and higher for participants with CMBs at baseline compared with those without (31.2% vs 15.8%) (eTable 2 in the Supplement). Moreover, participants with multiple CMBs at baseline had the highest incidence (48.4%) (eFigure 3 in the Supplement).
Among participants without baseline CMBs (n = 2186), 346 (15.8%) had completely new-onset CMBs (eTable 2 in the Supplement). Of those with baseline and incident CMBs (n = 140), 78 had a single baseline CMB, and 62 had multiple CMBs at baseline. Furthermore, 66 participants had baseline and incident CMBs occurring in a lobar location exclusively, and 33 had both in a deep location.
In the fully adjusted, multivariate binomial regression model, underweight, current smoking, and heavy current alcohol consumption at baseline were significantly associated with a higher incidence of CMBs (Table 2). When stratified according to CMB location, heavy alcohol consumption (vs light to moderate consumption) predicted incident CMBs in deep (RR, 2.94 [95% CI, 1.23-7.01]) but not in lobar regions. Underweight (vs normal weight; RR, 2.41 [95% CI, 1.21-4.80]) and being a current smoker (RR, 1.47 [95% CI, 1.11-1.94]) were associated with incident lobar CMBs exclusively but not with deep CMBs. No association was observed for other alcohol consumption or BMI categories.
Increasing levels of HDL-C were significantly associated with an increasing risk for any incident CMBs. Triglyceride levels showed an inverse association with the risk for CMBs. These associations were also independent of statin use in the fully adjusted model and were especially strong for incident lobar CMBs exclusively (RR per 1-SD increase in HDL-C level, 1.13 [95% CI, 1.02-1.25]; RR per 1-SD decrease in natural logarithm–transformed triglyceride level, 1.17 [95% CI, 1.03-1.33]), whereas we found no significant association with deep CMBs. Total and LDL-C levels were not associated with CMBs.
When we excluded individuals with both lobar and deep CMBs and analyzed the group with deep CMBs exclusively (n = 112), results were similar to those reported for any deep CMBs. Additional adjustment for APOE ɛ4 (cytogenetic locations, 19q13.32; OMIM 107741) genotype or prevalent stroke generated similar results. In stratified analyses, the associations persisted in participants without baseline CMBs and were found to be in the same direction, although not significant, in the smaller sample of people with baseline CMBs. We also repeated the analyses for subgroups stratified by APOE ɛ4 genotype or statin use. Because we had no a priori hypothesis, we considered interactions significant only if P ≤ .01, and none met this level of significance. We found no significant interactions of putative risk factors with other covariates. In location-specific analyses, exclusion of those with a discordant location between baseline and incident CMBs did not change the findings for incident lobar or deep CMBs. In multinomial logistic regression analyses that categorized the dependent variables of CMBs into no incident CMB, a single CMB, and multiple CMBs, lifestyle factors and increasing levels of HDL-C were significantly associated with an increased risk for developing a single CMB but not multiple CMBs (eTable 3 in the Supplement). Analyses on the imputed data sets yielded results similar to those reported for the main analysis.
The 5-year cumulative incidence of any CMBs in this population-based cohort of older people was 18.4%. Lifestyle and lipid risk profiles for CMBs were similar to those for ICH and differed according to the anatomic location of the CMBs. Heavy current alcohol consumption relative to light to moderate consumption predicted CMBs in a deep region. Baseline underweight (BMI <18.5), current smoking, a high serum HDL-C level, and a low serum triglyceride level were all significantly associated with an increased risk for incident lobar CMBs exclusively but not for deep CMBs. These associations were independent of major cardiovascular risk factors and ischemic cerebral small-vessel disease.
Cerebral microbleeds represent the remnants of small asymptomatic ICHs and are associated with an increased risk for symptomatic ICH.22 The associations with lifestyle factors are all consistent with findings for ICH.23,24 Furthermore, the region-specific associations suggest that these factors have different etiologic roles or are markers of a vulnerable cerebral microvascular system susceptible to specific vascular abnormalities, such as hypertensive arteriopathy or cerebral amyloid angiopathy. For example, heavy alcohol intake increases the risk for arterial hypertension; in our cohort, 7 of 27 heavy drinkers (25.9%) had severe hypertension, which was higher than among those reporting less consumption of alcohol. In particular, a transient increase in blood pressure with cerebral arteriolar vasoconstriction during alcohol exposure might cause the rupture of small cerebral arteries.25 Although the observations with underweight may point to low lipid levels as a potential mechanism, further adjustment for total cholesterol or triglyceride levels in additional analyses did not eliminate the associations. However, few underweight individuals (n = 21) were included, and other studies have shown that low BMI may be a prodromal symptom of dementia.26
Consistent with previous reports,13,15,23,27 we observed an inverse association between triglyceride levels and CMBs. The level of HDL-C was also positively and independently associated with CMBs, which is in accordance with a previous cross-sectional study of HDL-C and the presence of CMBs in patients with neurologic diseases,28 but our finding contrasts with the lack of association in other studies.1,10,15 Cholesterol and triglycerides are essential structural elements of cell membranes. Increased permeability of erythrocyte membranes is seen in vitro and in vivo with reduced lipid levels.29 Lower levels of total cholesterol or triglycerides have been proposed to result in smooth muscle degeneration and endothelial weakness that more readily lead to arterial fragility and microaneurysms, which in turn are prone to leakage and rupture.30,31 In addition, low triglyceride levels might favor a prohemorrhagic state owing to negative correlations with the vitamin K–dependent coagulation factors and with the plasminogen activator inhibitor.32
Increased HDL-C levels have been speculated to have a “dual and opposite effect” on cerebral blood vessels, with vascular protection from ischemia on one hand and increased vulnerability to vascular rupture on the other.32 Although the underlying mechanisms remain unclear, some explanations are possible. Cholesteryl ester transfer protein mediates the transfer of cholesteryl esters from HDL-C to triglyceride-rich lipoproteins.33 This transfer stimulates reverse cholesterol transport from peripheral cells to the liver for excretion. Deficiency or dysfunction of cholesteryl ester transfer protein secondary to genetic or environmental variation (eg, alcohol consumption)34 may cause reduced reverse cholesterol transport; this process is reflected as an increase in HDL-C levels and contributes to the loss of the antiatherogenic properties of HDL-C resulting from its increased cholesterol content and particle size.35 Furthermore, HDL-C is involved in the regulation of reverse cholesterol transport at the blood-brain barrier and in the processing of β-amyloid in the brain. Fagan et al36 found a positive association between plasma HDL-C and HDL-C in the central nervous system; the increased HDL-C levels found in the periphery may reflect increased efflux from the brain.37 Thus, alterations in the metabolism and the actions of HDL-C in the cerebral microvascular subendothelial space may contribute to the vascular deposition of amyloid.38 Serum 24S-hydroxycholesterol has been proposed as a more specific indicator of brain cholesterol than serum HDL-C, and increased levels are observed in patients with Alzheimer disease.39
Our finding that the association with triglycerides was most robust for lobar CMBs exclusively may provide specific etiologic clues and suggest a role through the development of amyloid microangiopathy. The association with HDL-C was also significant for exclusively lobar CMBs. However, the risk estimates were very similar for CMBs in both locations, and we cannot rule out the possibility that the nonsignificant result for deep CMBs was due to a lack of statistical power. In the Rotterdam Scan Study,11 an inverse association between serum total cholesterol level and the incidence of CMBs was found to be strongest for CMBs located in the deep regions. Although not significant, the directions of our findings for LDL-C and total cholesterol levels are consistent with the associations observed for triglycerides. Total cholesterol reflects HDL-C and LDL-C subfractions in varying proportions, which may explain why we could not find associations with total cholesterol level. In addition, a smaller sample, a younger cohort, a higher load of baseline CMBs, and a higher percentage of participants with severe hypertension (19.2% vs 15.0%) in the previous study11 compared with ours may have influenced the findings. Given that the detection of CMBs depends on several MRI variables, different MRI methods may have affected the reported incidence of CMBs and thus limited comparisons between studies.
Major strengths of the present study include the large population-based sample of older individuals, the use of a standard MRI protocol at both points, and the extensive characterization of participants that enabled us to examine a spectrum of modifiable risk factors and to adjust for a series of potential confounders. A possible limitation of the study is that selection bias may have influenced the results. People who were included in the analysis were younger and healthier at baseline than those who were excluded. In particular, people with a worse vascular risk profile or more severe cerebral small-vessel disease (those more likely to develop new CMBs) died or were otherwise unavailable before they could be recruited into the follow-up examination. This attrition may have led us to underestimate the true incidence of CMBs; as such, the findings in relation to the predictors of CMBs may be affected if selection occurred differentially according to the predictor variables (eg, the prevalence of being a current smoker at baseline was higher in those who were excluded; bias would occur if the association between current smoking and CMBs in the excluded sample differed from what we found in the included sample). On the outcome side, if prevalent and incident CMBs were found in different locations (deep vs lobar), then identification of location-specific risk factors might be more difficult. In our sensitivity analyses, we excluded people whose baseline and follow-up CMBs differed in location; results were unaltered for incident lobar CMBs exclusively or for deep CMBs, suggesting that this difference in location is unlikely to affect our findings. The clinical and prognostic significance of these CMBs is another area of great interest, and we are investigating the cognitive consequences of CMBs.
Our study provides essential and new information on the importance of lifestyle and lipid factors for the development of CMBs. Risk profiles for asymptomatic CMBs are similar to those for symptomatic ICH and differ for lobar and deep CMBs. Reducing the prevalence of lifestyle-based risk factors, including current smoking and heavy alcohol consumption, and monitoring lipid levels during intensive therapy to lower them (eg, extremely low triglyceride levels) could have the potential to prevent new-onset CMBs, particularly in lobar locations.
Accepted for Publication: February 10, 2015.
Corresponding Author: Lenore J. Launer, PhD, Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, 7201 Wisconsin Ave, Ste 3C-309, Bethesda, MD 20814 (LaunerL@nia.nih.gov).
Published Online: April 13, 2015. doi:10.1001/jamaneurol.2015.0174.
Author Contributions: Drs Ding and Launer had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Sigurdsson, Gudnason, Launer.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Ding.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Ding, Launer.
Obtained funding: Sigurdsson, Gudnason, Launer.
Administrative, technical, or material support: Garcia, Gudnason, Launer.
Study supervision: Sigurdsson, Gudnason, Launer.
Conflict of Interest Disclosures: None reported.
Funding/Support: The AGES-Reykjavik Study was funded by contract N01-AG-12100 from the National Institutes of Health; by the Intramural Research Program of the National Institute on Aging; and by the Icelandic Heart Association and the Icelandic Parliament.
Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.